755:), when the optimization goal changes because designers introduce improvements and extensions to the protein design model, such as improvements to the structural flexibility allowed (e.g., protein backbone flexibility) or including sophisticated energy terms, many of the extensions on protein design that improve modeling are built atop these algorithms. For example, Rosetta Design incorporates sophisticated energy terms, and backbone flexibility using Monte Carlo as the underlying optimizing algorithm. OSPREY's algorithms build on the dead-end elimination algorithm and A* to incorporate continuous backbone and side-chain movements. Thus, these algorithms provide a good perspective on the different kinds of algorithms available for protein design.
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resurfacing was the design of the RSC3 probe to select broadly neutralizing HIV antibodies at the NIH Vaccine
Research Center. First, residues outside of the binding interface between the gp120 HIV envelope protein and the formerly discovered b12-antibody were selected to be designed. Then, the sequence spaced was selected based on evolutionary information, solubility, similarity with the wild-type, and other considerations. Then the RosettaDesign software was used to find optimal sequences in the selected sequence space. RSC3 was later used to discover the broadly neutralizing antibody VRC01 in the serum of a long-term HIV-infected non-progressor individual.
423:
conformations of many sequences. Thus, molecular mechanics force-fields must be tailored for protein design. In practice, protein design energy functions often incorporate both statistical terms and physics-based terms. For example, the
Rosetta energy function, one of the most-used energy functions, incorporates physics-based energy terms originating in the CHARMM energy function, and statistical energy terms, such as rotamer probability and knowledge-based electrostatics. Typically, energy functions are highly customized between laboratories, and specifically tailored for every design.
2961:-binding peptides by Amy Keating and coworkers for 19 out of the 20 bZIP families; 8 of these peptides were specific for their intended partner over competing peptides. Further, positive and negative design was also used by Anderson and coworkers to predict mutations in the active site of a drug target that conferred resistance to a new drug; positive design was used to maintain wild-type activity, while negative design was used to disrupt binding of the drug. Recent computational redesign by Costas Maranas and coworkers was also capable of experimentally switching the
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challenges is that, in general, the interfaces between proteins are more polar than protein cores, and binding involves a tradeoff between desolvation and hydrogen bond formation. To overcome this challenge, Bruce Tidor and coworkers developed a method to improve the affinity of antibodies by focusing on electrostatic contributions. They found that, for the antibodies designed in the study, reducing the desolvation costs of the residues in the interface increased the affinity of the binding pair.
394:, are typically derived from quantum mechanical simulations, and experimental data from thermodynamics, crystallography, and spectroscopy. These energy functions typically simplify physical energy function and make them pairwise decomposable, meaning that the total energy of a protein conformation can be calculated by adding the pairwise energy between each atom pair, which makes them attractive for optimization algorithms. Physics-based energy functions typically model an attractive-repulsive
345:
protein redesign because sequence mutations often result in small changes to the backbone structure. Moreover, backbone flexibility can be essential for more advanced applications of protein design, such as binding prediction and enzyme design. Some models of protein design backbone flexibility include small and continuous global backbone movements, discrete backbone samples around the target fold, backrub motions, and protein loop flexibility.
406:
1063:. A* computes a lower-bound score on each partial tree path that lower bounds (with guarantees) the energy of each of the expanded rotamers. Each partial conformation is added to a priority queue and at each iteration the partial path with the lowest lower bound is popped from the queue and expanded. The algorithm stops once a full conformation has been enumerated and guarantees that the conformation is the optimal.
469:
can be formulated as a sum of individual and pairwise terms between residue positions. If a designer is interested only in the best sequence, the protein design algorithm only requires the lowest-energy conformation of the lowest-energy sequence. In these cases, the amino acid identity of each rotamer can be ignored and all rotamers belonging to different amino acids can be treated the same. Let
246:
341:, in contrast, describe the rotamers as how likely they are to appear depending on the protein backbone arrangement around the side chain. Most protein design programs use one conformation (e.g., the modal value for rotamer dihedrals in space) or several points in the region described by the rotamer; the OSPREY protein design program, in contrast, models the entire continuous region.
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156:'s laboratory designed a full protein to a fold never seen before in nature. Later, in 2008, Baker's group computationally designed enzymes for two different reactions. In 2010, one of the most powerful broadly neutralizing antibodies was isolated from patient serum using a computationally designed protein probe. Due to these and other successes (e.g., see
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medical needs. Although this method has high requirements for information and technology and is relatively difficult to implement, with the development of computing technology and bioinformatics, the application prospects of semi-rational design in protein engineering are becoming more and more broad.
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The methodology of semi-rational design emphasizes the in-depth understanding of enzymes and the control of the evolutionary process. It allows researchers to use known information to guide the evolutionary process, thereby improving efficiency and success rate. This method plays an important role in
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The dead-end elimination (DEE) algorithm reduces the search space of the problem iteratively by removing rotamers that can be provably shown to be not part of the global lowest energy conformation (GMEC). On each iteration, the dead-end elimination algorithm compares all possible pairs of rotamers at
452:
have 4 rotamers each in the rotamer library, while Asn and His have 7 and 8 rotamers, respectively, in the rotamer library (from the
Richardson's penultimate rotamer library). The animation loops through all (4 + 4) x (7 + 8) = 120 possibilities. The structure shown is that of myoglobin, PDB id: 1mbn.
422:
Protein design, however, has requirements that can sometimes be limited in molecular mechanics force-fields. Molecular mechanics force-fields, which have been used mostly in molecular dynamics simulations, are optimized for the simulation of single sequences, but protein design searches through many
314:
on the target structure in order to increase the number of sequences that can be designed for that structure and to minimize the chance of a sequence folding to a different structure. For example, in a protein redesign of one small amino acid (such as alanine) in the tightly packed core of a protein,
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Semi-rational design has a wide range of applications, including but not limited to enzyme optimization, modification of drug targets, evolution of biocatalysts, etc. Through this method, researchers can more effectively improve the functional properties of proteins to meet specific biotechnology or
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The most common energy functions can be decomposed into pairwise terms between rotamers and amino acid types, which casts the problem as a combinatorial one, and powerful optimization algorithms can be used to solve it. In those cases, the total energy of each conformation belonging to each sequence
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Individual water molecules can sometimes have a crucial structural role in the core of proteins, and in protein–protein or protein–ligand interactions. Failing to model such waters can result in mispredictions of the optimal sequence of a protein–protein interface. As an alternative, water molecules
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When the first proteins were rationally designed during the 1970s and 1980s, the sequence for these was optimized manually based on analyses of other known proteins, the sequence composition, amino acid charges, and the geometry of the desired structure. The first designed proteins are attributed to
745:
algorithms, such as Monte Carlo, that are faster than exact algorithms but have no guarantees on the optimality of the results. Exact algorithms guarantee that the optimization process produced the optimal according to the protein design model. Thus, if the predictions of exact algorithms fail when
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Thus, an essential parameter of any design process is the amount of flexibility allowed for both the side-chains and the backbone. In the simplest models, the protein backbone is kept rigid while some of the protein side-chains are allowed to change conformations. However, side-chains can have many
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Most often, the target structure is based on a known structure of another protein. However, novel folds not seen in nature have been made increasingly possible. Peter S. Kim and coworkers designed trimers and tetramers of unnatural coiled coils, which had not been seen before in nature. The protein
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This animation illustrates the complexity of a protein design search, which typically compares all the rotamer-conformations from all possible mutations at all residues. In this example, the residues Phe36 and His 106 are allowed to mutate to, respectively, the amino acids Tyr and Asn. Phe and Tyr
211:
Protein function is heavily dependent on protein structure, and rational protein design uses this relationship to design function by designing proteins that have a target structure or fold. Thus, by definition, in rational protein design the target structure or ensemble of structures must be known
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Although the Dead-end elimination algorithm runs in polynomial time on each iteration, it cannot guarantee convergence. If, after a certain number of iterations, the dead-end elimination algorithm does not prune any more rotamers, then either rotamers have to be merged or another search algorithm
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determined by the protein design energy function. Thus, a typical input to the protein design algorithm is the target fold, the sequence space, the structural flexibility, and the energy function, while the output is one or more sequences that are predicted to fold stably to the target structure.
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Water makes up most of the molecules surrounding proteins and is the main driver of protein structure. Thus, modeling the interaction between water and protein is vital in protein design. The number of water molecules that interact with a protein at any given time is huge and each one has a large
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instances of the integer programming, but in order to maintain guarantees on optimality, they are most useful when used to approximate the dual of the protein design problem, because approximating the dual guarantees that no solutions are missed. Message-passing based approximations include the
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Comparison of various potential energy functions. The most accurate energy are those that use quantum mechanical calculations, but these are too slow for protein design. On the other extreme, heuristic energy functions are based on statistical terms and are very fast. In the middle are molecular
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Wang, Jue; Lisanza, Sidney; Juergens, David; Tischer, Doug; Watson, Joseph L.; Castro, Karla M.; Ragotte, Robert; Saragovi, Amijai; Milles, Lukas F.; Baek, Minkyung; Anishchenko, Ivan; Yang, Wei; Hicks, Derrick R.; Expòsit, Marc; Schlichthaerle, Thomas; Chun, Jung-Ho; Dauparas, Justas; Bennett,
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designs of globular proteins. Five more protein structures were designed, synthesized, and verified in 2012 by the Baker group. These new proteins serve no biotic function, but the structures are intended to act as building-blocks that can be expanded to incorporate functional active sites. The
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Semi-rational design is a purposeful modification method based on a certain understanding of the sequence, structure, and catalytic mechanism of enzymes. This method is between irrational design and rational design. It uses known information and means to perform evolutionary modification on the
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Although rational protein design must preserve the general backbone fold a protein, allowing some backbone flexibility can significantly increase the number of sequences that fold to the structure while maintaining the general fold of the protein. Backbone flexibility is especially important in
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Protein–protein interactions can be designed using protein design algorithms because the principles that rule protein stability also rule protein–protein binding. Protein–protein interaction design, however, presents challenges not commonly present in protein design. One of the most important
2619:) infection involve protein–protein interactions. Thus, to treat such diseases, it is desirable to design protein or protein-like therapeutics that bind one of the partners of the interaction and, thus, disrupt the disease-causing interaction. This requires designing protein-therapeutics for
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The goal of protein design is to find a protein sequence that will fold to a target structure. A protein design algorithm must, thus, search all the conformations of each sequence, with respect to the target fold, and rank sequences according to the lowest-energy conformation of each one, as
190:
environments. In order to make the problem tractable, these forces are simplified by protein design models. Although protein design programs vary greatly, they have to address four main modeling questions: What is the target structure of the design, what flexibility is allowed on the target
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Protein resurfacing consists of designing a protein's surface while preserving the overall fold, core, and boundary regions of the protein intact. Protein resurfacing is especially useful to alter the binding of a protein to other proteins. One of the most important applications of protein
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must be used to search the remaining search space. In such cases, the dead-end elimination acts as a pre-filtering algorithm to reduce the search space, while other algorithms, such as A*, Monte Carlo, Linear
Programming, or FASTER are used to search the remaining search space.
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Sander, Chris; Vriend, Gerrit; Bazan, Fernando; Horovitz, Amnon; Nakamura, Haruki; Ribas, Luis; Finkelstein, Alexei V.; Lockhart, Andrew; Merkl, Rainer; et al. (1992). "Protein Design on computers. Five new proteins: Shpilka, Grendel, Fingerclasp, Leather and Aida".
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simulations enabled the development of structure-based computational protein design tools. Following the development of these computational tools, great success has been achieved over the last 30 years in protein design. The first protein successfully designed completely
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Russ, William P.; Figliuzzi, Matteo; Stocker, Christian; Barrat-Charlaix, Pierre; Socolich, Michael; Kast, Peter; Hilvert, Donald; Monasson, Remi; Cocco, Simona; Weigt, Martin; Ranganathan, Rama (2020). "An evolution-based model for designing chorismatemutase enzymes".
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Several transmembrane proteins have been successfully designed, along with many other membrane-associated peptides and proteins. Recently, Costas
Maranas and his coworkers developed an automated tool to redesign the pore size of Outer Membrane Porin Type-F (OmpF) from
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The FASTER algorithm uses a combination of deterministic and stochastic criteria to optimize amino acid sequences. FASTER first uses DEE to eliminate rotamers that are not part of the optimal solution. Then, a series of iterative steps optimize the rotamer assignment.
1491:(ILP). One of the most powerful formulations uses binary variables to represent the presence of a rotamer and edges in the final solution, and constraints the solution to have exactly one rotamer for each residue and one pairwise interaction for each pair of residues:
66:
Rational protein design dates back to the mid-1970s. Recently, however, there were numerous examples of successful rational design of water-soluble and even transmembrane peptides and proteins, in part due to a better understanding of different factors contributing to
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specific functions of the target enzyme. The characteristic of semi-rational design is that it does not rely solely on random mutation and screening, but combines the concept of directed evolution. It creates a library of random mutants with diverse sequences through
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that each residue has about the probability of each rotamer in neighboring residues. The algorithm updates messages on every iteration and iterates until convergence or until a fixed number of iterations. Convergence is not guaranteed in protein design. The message
465:), this results in an exponential number of conformations for each sequence. Thus, in our 100 residue protein, and assuming that each amino acid has exactly 10 rotamers, a search algorithm that searches this space will have to search over 200 protein conformations.
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The most accurate energy functions are those based on quantum mechanical simulations. However, such simulations are too slow and typically impractical for protein design. Instead, many protein design algorithms use either physics-based energy functions adapted from
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Water-mediated hydrogen bonds play a key role in protein–protein binding. One such interaction is shown between residues D457, S365 in the heavy chain of the HIV-broadly-neutralizing antibody VRC01 (green) and residues N58 and Y59 in the HIV envelope protein GP120
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Monte Carlo is one of the most widely used algorithms for protein design. In its simplest form, a Monte Carlo algorithm selects a residue at random, and in that residue a randomly chosen rotamer (of any amino acid) is evaluated. The new energy of the protein,
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The number of candidate protein sequences, however, grows exponentially with the number of protein residues; for example, there are 20 protein sequences of length 100. Furthermore, even if amino acid side-chain conformations are limited to a few rotamers (see
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The design of protein–protein interactions must be highly specific because proteins can interact with a large number of proteins; successful design requires selective binders. Thus, protein design algorithms must be able to distinguish between on-target (or
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The K* algorithm approximates the binding constant of the algorithm by including conformational entropy into the free energy calculation. The K* algorithm considers only the lowest-energy conformations of the free and bound complexes (denoted by the sets
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Statistical potentials, in contrast to physics-based potentials, have the advantage of being fast to compute, of accounting implicitly of complex effects and being less sensitive to small changes in the protein structure. These energy functions are
253:
computational design of a full protein. The target fold was that of the zinc finger in residues 33–60 of the structure of protein Zif268 (shown in red, PDB id: 1ZAA). The designed sequence had very little sequence identity with any known protein
305:
Common protein design programs use rotamer libraries to simplify the conformational space of protein side chains. This animation loops through all the rotamers of the isoleucine amino acid based on the
Penultimate Rotamer Library (total of 7
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is a use of protein design with huge bioengineering and biomedical applications. In general, designing a protein structure can be different from designing an enzyme, because the design of enzymes must consider many states involved in the
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Wu, X; Yang, ZY; Li, Y; Hogerkorp, CM; Schief, WR; Seaman, MS; Zhou, T; Schmidt, SD; Wu, L; Xu, L; Longo, NS; McKee, K; O'Dell, S; Louder, MK; Wycuff, DL; Feng, Y; Nason, M; Doria-Rose, N; Connors, M; Kwong, PD; Roederer, M; Wyatt, RT;
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that bridge between secondary structure prediction and tertiary structures. These principles, which build on both protein structure prediction and protein design, were used to design five different novel protein topologies.
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Rational protein design techniques must be able to discriminate sequences that will be stable under the target fold from those that would prefer other low-energy competing states. Thus, protein design requires accurate
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Pokala, Navin & Handel, Tracy M. (2005). "Energy
Functions for Protein Design: Adjustment with Protein–Protein Complex Affinities, Models for the Unfolded State, and Negative Design of Solubility and Specificity".
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to a specific protein structure. Although the number of possible protein sequences is vast, growing exponentially with the size of the protein chain, only a subset of them will fold reliably and quickly to one
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these are experimentally validated, then the source of error can be attributed to the energy function, the allowed flexibility, the sequence space or the target structure (e.g., if it cannot be designed for).
1497:
2755:
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Zhou, T; Georgiev, I; Wu, X; Yang, ZY; Dai, K; Finzi, A; Kwon, YD; Scheid, JF; Shi, W; Xu, L; Yang, Y; Zhu, J; Nussenzweig, MC; Sodroski, J; Shapiro, L; Nabel, GJ; Mascola, JR; Kwong, PD (August 13, 2010).
293:-based designed proteins, for example, are often composed of Gly-Pro-X repeating patterns. The advent of computational techniques allows designing proteins with no human intervention in sequence selection.
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number of degrees of freedom and interaction partners. Instead, protein design programs model most of such water molecules as a continuum, modeling both the hydrophobic effect and solvation polarization.
2046:-based methods to perform the LP relaxation at each branch. These LP algorithms were developed as general-purpose optimization methods and are not optimized for the protein design problem (Equation (
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127:
peptides based on rules on sequence composition. Richardson and coworkers designed a 79-residue protein with no sequence homology to a known protein. In the 1990s, the advent of powerful computers,
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protein function modification because it can combine the advantages of irrational design and rational design, and can explore unknown space and use known knowledge for targeted modification.
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to select HIV-broadly neutralizing antibodies was restricted based on evolutionary data and charge balancing. Many of the earliest attempts on protein design were heavily based on empiric
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algorithm to search only a small portion of the conformation space for the optimal solution. ILP solvers have been shown to solve many instances of the side-chain placement problem.
1999:
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Röthlisberger, Daniela; Khersonsky, Olga; Wollacott, Andrew M.; Jiang, Lin; Dechancie, Jason; Betker, Jamie; Gallaher, Jasmine L.; Althoff, Eric A.; Zanghellini, Alexandre (2008).
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Jiang, Lin; Althoff, Eric A.; Clemente, Fernando R.; Doyle, Lindsey; Rothlisberger, Daniela; Zanghellini, Alexandre; Gallaher, Jasmine L.; Betker, Jamie L.; Tanaka, Fujie (2008).
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problem. Even though the class of problems is NP-hard, in practice many instances of protein design can be solved exactly or optimized satisfactorily through heuristic methods.
228:'s lab, was designed completely using protein design algorithms, to a completely novel fold. More recently, Baker and coworkers developed a series of principles to design ideal
115:
Bernd Gutte, who designed a reduced version of a known catalyst, bovine ribonuclease, and tertiary structures consisting of beta-sheets and alpha-helices, including a binder of
5510:
Chowdhury, Ratul; Kumar, Manish; Maranas, Costas D.; Golbeck, John H.; Baker, Carol; Prabhakar, Jeevan; Grisewood, Matthew; Decker, Karl; Shankla, Manish (September 10, 2018).
2539:. Furthermore, Stephen Mayo and coworkers developed an iterative method to design the most efficient known enzyme for the Kemp-elimination reaction. Also, in the laboratory of
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Siegel, JB; Zanghellini, A; Lovick, HM; Kiss, G; Lambert, AR; St Clair, JL; Gallaher, JL; Hilvert, D; Gelb, MH; Stoddard, BL; Houk, KN; Michael, FE; Baker, D (July 16, 2010).
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behind protein design. One of the most challenging requirements for successful design is an energy function that is both accurate and simple for computational calculations.
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Desmet, J; Spriet, J; Lasters, I (July 1, 2002). "Fast and accurate side-chain topology and energy refinement (FASTER) as a new method for protein structure optimization".
3013:, which makes globular proteins more attractive for protein design than the other types of proteins. Most successful protein designs have involved globular proteins. Both
51:
approaches make protein-sequence predictions that will fold to specific structures. These predicted sequences can then be validated experimentally through methods such as
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structures were found computationally by using new heuristics based on analyzing the connecting loops between parts of the sequence that specify secondary structures.
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Several algorithms have been developed specifically for the protein design problem. These algorithms can be divided into two broad classes: exact algorithms, such as
367:
that can rank and score sequences by how well they fold to the target structure. At the same time, however, these energy functions must consider the computational
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315:
very few mutants would be predicted by a rational design approach to fold to the target structure, if the surrounding side-chains are not allowed to be repacked.
99:
minimum for the chain. Thus, protein design is the search for sequences that have the chosen structure as a free energy minimum. In a sense, it is the reverse of
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Looger, Loren L.; Dwyer, Mary A.; Smith, James J. & Hellinga, Homme W. (2003). "Computational design of receptor and sensor proteins with novel functions".
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Kuhlman, B; Dantas, G; Ireton, GC; Varani, G; Stoddard, BL; Baker, D (November 21, 2003). "Design of a novel globular protein fold with atomic-level accuracy".
2484:{\displaystyle m_{i\to j}(r_{j})=\max _{r_{i}}{\Big (}e^{\frac {-E_{i}(r_{i})-E_{ij}(r_{i},r_{j})}{T}}{\Big )}\prod _{k\in N(i)\backslash j}m_{k\to i(r_{i})}}
262:
protein design. In protein redesign, most of the residues in the sequence are maintained as their wild-type amino-acid while a few are allowed to mutate. In
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Some protein design algorithms are listed below. Although these algorithms address only the most basic formulation of the protein design problem, Equation (
3051:, proteins that will sense the presence of specific compounds. Some attempts in the design of biosensors include sensors for unnatural molecules including
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4021:
Voigt, CA; Gordon, DB; Mayo, SL (June 9, 2000). "Trading accuracy for speed: A quantitative comparison of search algorithms in protein sequence design".
39:
molecules to design novel activity, behavior, or purpose, and to advance basic understanding of protein function. Proteins can be designed from scratch (
111:. Protein design is then an optimization problem: using some scoring criteria, an optimized sequence that will fold to the desired structure is chosen.
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Leach, AR; Lemon, AP (November 1, 1998). "Exploring the conformational space of protein side chains using dead-end elimination and the A* algorithm".
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337:
Rotamer libraries are derived from the statistical analysis of many protein structures. Backbone-independent rotamer libraries describe all rotamers.
1807:
7535:
2052:)). In consequence, the LP relaxation becomes the bottleneck of ILP solvers when the problem size is large. Recently, several alternatives based on
326:. To simplify this space, protein design methods use rotamer libraries that assume ideal values for bond lengths and bond angles, while restricting
2056:
have been designed specifically for the optimization of the LP relaxation of the protein design problem. These algorithms can approximate both the
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Wainwright, Martin J; Tommi S. Jaakkola; Alan S. Willsky (2005). "MAP estimation via agreement on trees: message-passing and linear programming".
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2584:. At the same time, it uses the understanding of enzymes and design principles to purposefully screen out mutants with desired characteristics.
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to identify design-rules. In 2022, a study reported deep learning software that can design proteins that contain prespecified functional sites.
1004:{\displaystyle E(r_{i}^{\prime })+\sum _{j\neq i}\min _{r_{j}}E(r_{i}^{\prime },r_{j})>E(r_{i})+\sum _{j\neq i}\max _{r_{j}}E(r_{i},r_{j})}
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In protein design, the target structure (or structures) of the protein are known. However, a rational protein design approach must model some
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4999:
3085:
448:
6321:
5914:
5809:
1710:{\displaystyle \ \min \sum _{i}\sum _{r_{i}}E_{i}(r_{i})q_{i}(r_{i})+\sum _{j\neq i}\sum _{r_{j}}E_{ij}(r_{i},r_{j})q_{ij}(r_{i},r_{j})\,}
2933:{\displaystyle K^{*}={\frac {\sum \limits _{x\in PL}e^{-E(x)/RT}}{\sum \limits _{x\in P}e^{-E(x)/RT}\sum \limits _{x\in L}e^{-E(x)/RT}}}}
258:
In rational protein design, proteins can be redesigned from the sequence and structure of a known protein, or completely from scratch in
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enzyme design because, at the very least, the design of catalysts requires a scaffold in which the catalytic mechanism can be inserted.
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Protein design energy functions must be adapted to score binding predictions because binding involves a trade-off between the lowest-
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to other noncognate substrates including charged amino acids; the redesigned enzymes had activities close to those of the wild-type.
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5919:
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3001:, which have multiple conformations. The three-dimensional structure of globular proteins is typically easier to determine through
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Nathaniel; Wicky, Basile I. M.; Muenks, Andrew; DiMaio, Frank; Correia, Bruno; Ovchinnikov, Sergey; Baker, David (July 22, 2022).
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are proteins that contain a hydrophobic core and a hydrophilic surface. Globular proteins often assume a stable structure, unlike
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5899:
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Harbury, PB; Plecs, JJ; Tidor, B; Alber, T; Kim, PS (November 20, 1998). "High-resolution protein design with backbone freedom".
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enzyme design, and redesign, was made in the first decade of the 21st century. In three major studies, David Baker and coworkers
277:: the specific amino acids that are allowed at each mutable residue position. For example, the composition of the surface of the
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mechanics energy functions that are physically based but are not as computationally expensive as quantum mechanical simulations.
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5802:
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Globerson, Amir; Tommi S. Jaakkola (2007). "Fixing max-product: Convergent message passing algorithms for MAP LP-relaxations".
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Yanover, Chen; Talya
Meltzer; Yair Weiss (2006). "Linear Programming Relaxations and Belief Propagation – An Empirical Study".
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6847:
95:. Protein design involves identifying novel sequences within this subset. The native state of a protein is the conformational
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191:
structure, which sequences are included in the search, and which force field will be used to score sequences and structures.
3584:"A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions"
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7113:
6636:
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2009:
1044:, where the protein residues are ordered in an arbitrary way, and the tree branches at each of the rotamers in a residue.
5732:"De Novo Design of Foldable Proteins with Smooth Folding Funnel: Automated Negative Design and Experimental Verification"
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Privett, HK; Kiss, G; Lee, TM; Blomberg, R; Chica, RA; Thomas, LM; Hilvert, D; Houk, KN; Mayo, SL (March 6, 2012).
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is a lower bound on the energy of the rotamers that have not yet been assigned. Each is designed as follows, where
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83:
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Allen, BD; Mayo, SL (July 30, 2006). "Dramatic performance enhancements for the FASTER optimization algorithm".
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Samish, I; MacDermaid, CM; Perez-Aguilar, JM; Saven, JG (2011). "Theoretical and computational protein design".
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Kolmogorov, Vladimir (October 28, 2006). "Convergent tree-reweighted message passing for energy minimization".
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331:
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2008:, can compute the exact optimal solution for large instances of protein design problems. These solvers use a
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Lovell, SC; Word, JM; Richardson, JS; Richardson, DC (August 15, 2000). "The penultimate rotamer library".
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6274:
5886:
5876:
5825:
5630:"Redesign of the PAK1 autoinhibitory domain for enhanced stability and affinity in biosensor applications"
4551:
4448:
4332:
4030:
3538:
3192:
2581:
2061:
2057:
1488:
763:
383:, or a hybrid mix of both. The trend has been toward using more physics-based potential energy functions.
3039:
to any desired sub-nm size and assembled them in membranes to perform precise angstrom scale separation.
1226:
7858:
7642:
7525:
7339:
7145:
7118:
7108:
7076:
7066:
7031:
6946:
6891:
6886:
6869:
6815:
6653:
6606:
6467:
6331:
6252:
6108:
5894:
4844:
4212:
3922:
3002:
1041:
380:
3183:
Dahiyat, BI; Mayo, SL (October 3, 1997). "De novo protein design: fully automated sequence selection".
3685:
7812:
7667:
7627:
7381:
7334:
7155:
7103:
7026:
7016:
6916:
6879:
6859:
6790:
6780:
6188:
6178:
6135:
6113:
6068:
6011:
5586:
5523:
5412:
5308:
5251:
4936:
4877:
4806:
4757:
4700:
4227:
4150:
3884:
3643:
3480:
3423:
3318:
3056:
2548:
2536:
1019:
1015:
784:
734:
4556:
4337:
4035:
3543:
7607:
7530:
7439:
7324:
7172:
7150:
7056:
7036:
6901:
6760:
6745:
6658:
6425:
6378:
6159:
5955:
5924:
4795:"Computational design of an enzyme catalyst for a stereoselective bimolecular Diels-Alder reaction"
4453:
3197:
3080:
2195:
1469:
1060:
376:
207:
protein was one of the first proteins designed for a fold that had never been seen before in nature
161:
20:
3412:"Rational design of envelope identifies broadly neutralizing human monoclonal antibodies to HIV-1"
216:, where a variety of methods are used to find proteins that achieve a specific function, and with
7844:
7720:
7672:
7647:
7086:
6921:
6906:
6765:
6581:
6452:
6398:
6130:
5718:
5610:
5512:"PoreDesigner for tuning solute selectivity in a robust and highly permeable outer membrane pore"
5436:
5122:
4620:
4577:
4509:
4466:
4358:
4174:
3564:
3506:
3342:
2216:
2187:
2053:
1465:
1078:
is the exact energy of the rotamers that have already been assigned in the partial conformation.
539:. Then, we define the optimization problem as one of finding the conformation of minimum energy (
213:
132:
7872:
1022:. This algorithm has also been extended to handle continuous rotamers with provable guarantees.
2494:
Both max-product and sum-product belief propagation have been used to optimize protein design.
43:
design) or by making calculated variants of a known protein structure and its sequence (termed
7827:
7797:
7602:
7555:
7411:
7401:
7222:
7217:
7212:
7182:
7021:
7006:
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6931:
6864:
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6358:
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5385:
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3708:
3659:
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3210:
3160:
2039:
52:
6842:
7802:
7767:
7742:
7455:
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7391:
7197:
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7081:
6986:
6976:
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6703:
6673:
6648:
6616:
6576:
6516:
6447:
6286:
5980:
5775:
5743:
5702:
5649:
5641:
5594:
5577:
5547:
5531:
5455:
5420:
5375:
5367:
5356:"Computational design of Candida boidinii xylose reductase for altered cofactor specificity"
5326:
5316:
5267:
5259:
5210:
5202:
5161:
5153:
5106:
5069:
5061:
5013:
4987:
4954:
4944:
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4885:
4822:
4814:
4765:
4716:
4708:
4659:
4651:
4604:
4561:
4493:
4458:
4392:
4381:"Solving and analyzing side-chain positioning problems using linear and integer programming"
4342:
4292:
4251:
4235:
4158:
4087:
4079:
4040:
3990:
3951:
3900:
3892:
3844:
3809:
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3700:
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3595:
3548:
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3240:
3202:
3152:
3010:
2994:
2513:
2043:
1045:
1035:
229:
19:
This article is about rational protein design. For the broader engineering of proteins, see
4068:"Rotamer optimization for protein design through MAP estimation and problem-size reduction"
3655:
7792:
7772:
7752:
7747:
7737:
7632:
7267:
7257:
7242:
7202:
7167:
7160:
7091:
7051:
6820:
6693:
6683:
6591:
6548:
6528:
6257:
6208:
6004:
5730:
Jin, Wenzhen; Kambara, Ohki; Sasakawa, Hiroaki; Tamura, Atsuo & Takada, Shoji (2003).
5354:
Khoury, GA; Fazelinia, H; Chin, JW; Pantazes, RJ; Cirino, PC; Maranas, CD (October 2009).
3835:
Vizcarra, CL; Mayo, SL (December 2005). "Electrostatics in computational protein design".
3758:
Boas, F. E. & Harbury, P. B. (2007). "Potential energy functions for protein design".
3407:
2998:
2957:). One of the most prominent examples of design for specificity is the design of specific
2577:
164:. There is great hope that the design of new proteins, small and large, will have uses in
124:
107:
is specified, and a sequence that will fold to it is identified. Hence, it is also termed
87:
68:
32:
3231:
Gordon, DB; Marshall, SA; Mayo, SL (August 1999). "Energy functions for protein design".
1048:
algorithms use this representation to efficiently explore the conformation tree: At each
5628:
Jha, RK; Wu, YI; Zawistowski, JS; MacNevin, C; Hahn, KM; Kuhlman, B (October 21, 2011).
5590:
5527:
5416:
5312:
5255:
4940:
4881:
4810:
4761:
4704:
4231:
4154:
3942:
Mendes, J; Guerois, R; Serrano, L (August 2002). "Energy estimation in protein design".
3888:
3647:
3484:
3427:
3322:
3143:
Richardson, JS; Richardson, DC (July 1989). "The de novo design of protein structures".
405:
7817:
7762:
7715:
7697:
7499:
7247:
7237:
7232:
7207:
7001:
6981:
6854:
6825:
6775:
6708:
6668:
6631:
6553:
6511:
6506:
6388:
6383:
6373:
6291:
6269:
6103:
6093:
5950:
5654:
5629:
5552:
5511:
5380:
5355:
5331:
5296:
5272:
5239:
5215:
5190:
5166:
5141:
5074:
5049:
5018:
4959:
4924:
4900:
4865:
4827:
4794:
4721:
4688:
4664:
4639:
4256:
4092:
4067:
3905:
3872:
3681:
3608:
3583:
3444:
3411:
3063:
2544:
2532:
2027:
399:
320:
233:
181:
169:
5748:
5731:
4297:
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2603:
are involved in most biotic processes. Many of the hardest-to-treat diseases, such as
7896:
7822:
7807:
7787:
7710:
7612:
7444:
7434:
7262:
7252:
7227:
7192:
6755:
6688:
6611:
6586:
6538:
6523:
6230:
6150:
5440:
5403:
Burton, DR; Weiss, RA (August 13, 2010). "AIDS/HIV. A boost for HIV vaccine design".
4178:
3800:
Boas, FE; Harbury, PB (April 2007). "Potential energy functions for protein design".
3156:
2556:
767:
395:
5722:
4624:
4470:
4397:
4380:
4362:
7705:
7682:
7652:
7637:
6926:
6543:
6484:
6296:
6247:
6198:
6173:
6125:
6118:
5965:
5680:
5614:
5498:
5483:
5126:
4513:
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3568:
3510:
3378:
3361:
3346:
2552:
2540:
447:
145:
141:
92:
4581:
3282:
5240:"Design of protein-interaction specificity gives selective bZIP-binding peptides"
5142:"Computational design of antibody-affinity improvement beyond in vivo maturation"
4281:"Branch-and-terminate: a combinatorial optimization algorithm for protein design"
3873:"Structural basis for broad and potent neutralization of HIV-1 by antibody VRC01"
3704:
7782:
7777:
7757:
7677:
7597:
7406:
7311:
6621:
6596:
6568:
6497:
6442:
6420:
6168:
6145:
6140:
6083:
6078:
5050:"Computational design of affinity and specificity at protein–protein interfaces"
4991:
4986:. Methods in Molecular Biology (Clifton, N.J.). Vol. 1685. pp. 15–23.
3995:
3978:
3206:
2958:
2569:
2543:, computational protein design was used to switch the specificity of one of the
165:
160:
below), protein design has become one of the most important tools available for
149:
148:
and coworkers designed dimers, trimers, and tetramers of unnatural right-handed
5535:
5479:
5301:
Proceedings of the
National Academy of Sciences of the United States of America
4929:
Proceedings of the
National Academy of Sciences of the United States of America
4870:
Proceedings of the National Academy of Sciences of the United States of America
3848:
1930:{\displaystyle \sum _{r_{j}}q_{ij}(r_{i},r_{j})=q_{i}(r_{i}),\forall i,r_{i},j}
245:
7879:
7396:
6991:
6770:
6492:
6472:
6326:
6164:
5960:
5779:
5645:
5206:
5065:
3813:
3771:
3599:
3403:
80:
5543:
5009:
4247:
330:
dihedral angles to a few frequently observed low-energy conformations termed
7865:
7851:
7662:
7386:
7371:
7329:
6941:
6501:
6341:
5424:
5321:
4949:
4890:
4818:
4712:
4462:
4239:
4162:
3896:
3435:
3330:
3048:
2604:
1014:
Other powerful extensions to the dead-end elimination algorithm include the
353:
212:
beforehand. This contrasts with other forms of protein engineering, such as
5787:
5757:
5706:
5663:
5606:
5561:
5432:
5389:
5340:
5281:
5224:
5175:
5118:
5083:
5027:
4968:
4909:
4836:
4779:
4730:
4673:
4616:
4573:
4505:
4497:
4406:
4347:
10.1002/(sici)1097-0134(19981101)33:2<227::aid-prot7>3.0.co;2-f
4306:
4265:
4170:
4101:
4052:
4044:
4004:
3963:
3914:
3856:
3821:
3779:
3712:
3663:
3617:
3560:
3502:
3453:
3387:
3338:
3252:
1213:{\displaystyle g=\sum _{i=1}^{d}(E(r_{i})+\sum _{j=i+1}^{d}E(r_{i},r_{j}))}
5714:
4354:
3290:
3214:
3164:
2194:
can be chosen such that in the initial rounds it is high and it is slowly
266:
design, the entire sequence is designed anew, based on no prior sequence.
6996:
6043:
5794:
5494:
5110:
4982:
Korendovych, Ivan V. (2018). "Rational and Semirational Protein Design".
758:
In 2020 scientists reported the development of an AI-based process using
290:
5598:
5263:
4770:
4745:
4640:"An exciting but challenging road ahead for computational enzyme design"
301:
7617:
7545:
6155:
5945:
4608:
2219:
for protein design, the algorithm exchanges messages that describe the
1086:
is the index of the last assigned residue in the partial conformation.
722:
186:
120:
36:
4565:
4083:
3553:
10.1002/1097-0134(20000815)40:3<389::AID-PROT50>3.0.CO;2-2
2038:
ILP solvers depend on linear programming (LP) algorithms, such as the
7376:
6027:
2608:
2508:
797:
that can be shown to always be of higher energy than another rotamer
391:
5371:
5157:
4655:
3493:
3468:
495:
the potential energy between the internal atoms of the rotamer. Let
3055:. More recently, Kuhlman and coworkers designed a biosensor of the
2034:
Message-passing based approximations to the linear programming dual
157:
6088:
5295:
Frey, KM; Georgiev, I; Donald, BR; Anderson, AC (August 3, 2010).
4923:
Chen, CY; Georgiev, I; Anderson, AC; Donald, BR (March 10, 2009).
4116:"Machine learning reveals recipe for building artificial proteins"
4066:
Hong, EJ; Lippow, SM; Tidor, B; Lozano-PĂ©rez, T (September 2009).
2005:
404:
387:
352:
300:
244:
198:
5297:"Predicting resistance mutations using protein design algorithms"
7128:
2612:
1056:
the conformation space and explore only the promising branches.
1040:
The protein design conformational space can be represented as a
204:
7581:
7284:
6729:
6056:
6000:
5798:
199:
5975:
5970:
4486:
IEEE Transactions on Pattern Analysis and Machine Intelligence
3052:
2616:
2172:{\displaystyle p=e^{-\beta (E_{\text{new}}-E_{\text{old}}))},}
116:
2026:
are allowed to take continuous values, in combination with a
2441:
890:
830:
4925:"Computational structure-based redesign of enzyme activity"
4746:"Kemp elimination catalysts by computational enzyme design"
2653:) and the lowest-energy conformation of the bound complex (
319:
degrees of freedom in their bond lengths, bond angles, and
220:
where the sequence is known, but the structure is unknown.
4213:"Scaffolding protein functional sites using deep learning"
2749:) to approximate the partition functions of each complex:
741:
guarantees but guarantee the quality of the solution; and
5996:
3047:
One of the most desirable uses for protein design is for
273:
designs and protein redesigns can establish rules on the
5238:
Grigoryan, G; Reinke, AW; Keating, AE (April 16, 2009).
4193:"Biologists train AI to generate medicines and vaccines"
3091:
Comparison of software for molecular mechanics modeling
1794:{\displaystyle \sum _{r_{i}}q_{i}(r_{i})=1,\ \forall i}
419:
from frequency of appearance on a structural database.
4379:
Kingsford, CL; Chazelle, B; Singh, M (April 1, 2005).
3686:"Backbone flexibility in computational protein design"
5097:
Shoichet, BK (October 2007). "No free energy lunch".
4689:"De Novo Computational Design of Retro-Aldol Enzymes"
2758:
2669:
2263:
2114:
1946:
1810:
1729:
1500:
1229:
1095:
1059:
A popular search algorithm for protein design is the
813:
559:
3111:"Minimalist design of peptide and protein catalysts"
289:
usually follows strict rules on the sequence space.
7518:
7477:
7420:
7310:
6562:
6481:
6397:
6305:
6187:
6067:
5938:
5885:
5832:
4866:"Iterative approach to computational enzyme design"
176:
Underlying models of protein structure and function
144:and coworkers in 1997, and, shortly after, in 1999
5495:Designed membrane-associated peptides and proteins
5140:Lippow, SM; Wittrup, KD; Tidor, B (October 2007).
4197:University of Washington-Harborview Medical Center
3469:"Structural biology: A toolbox for protein design"
2932:
2724:
2483:
2171:
1993:
1929:
1793:
1709:
1448:
1212:
1003:
690:
249:FSD-1 (shown in blue, PDB id: 1FSV) was the first
79:The goal in rational protein design is to predict
5695:Proteins: Structure, Function, and Bioinformatics
4529:Advances in Neural Information Processing Systems
2413:
2318:
682:
588:
71:and development of better computational methods.
5191:"Protein binding specificity versus promiscuity"
3582:Shapovalov, MV; Dunbrack RL, Jr (June 8, 2011).
3226:
3224:
3138:
3136:
3134:
3132:
3130:
3128:
2300:
1504:
1392:
1267:
953:
858:
790:each residue position, and removes each rotamer
560:
427:Challenges for effective design energy functions
368:
286:
184:of the molecular forces that drive proteins in
5043:
5041:
5039:
5037:
4374:
4372:
3360:Sterner, R; Merkl, R; Raushel, FM (May 2008).
2725:{\displaystyle \Delta _{G}=E_{PL}-E_{P}-E_{L}}
2516:. However protein design is a prerequisite of
2498:Applications and examples of designed proteins
6012:
5810:
5480:Designed transmembrane alpha-hairpin proteins
3675:
3673:
3524:
3522:
3520:
3178:
3176:
3174:
691:{\displaystyle \min E_{T}=\sum _{i}{\Big }\,}
8:
4849:: CS1 maint: multiple names: authors list (
3927:: CS1 maint: multiple names: authors list (
1988:
1976:
5189:Schreiber, G; Keating, AE (February 2011).
4279:Gordon, DB; Mayo, SL (September 15, 1999).
3795:
3793:
3791:
3789:
3732:
3730:
3728:
3726:
3724:
3722:
3629:
3627:
3304:
3302:
3300:
3264:
3262:
2535:, a Kemp-elimination reaction, and for the
2067:tree reweighted max-product message passing
7578:
7307:
7281:
6726:
6064:
6053:
6019:
6005:
5997:
5817:
5803:
5795:
5685:Algorithms in Structural Molecular Biology
5048:Karanicolas, J; Kuhlman, B (August 2009).
4318:
4316:
4016:
4014:
3742:Algorithms in Structural Molecular Biology
3062:In a sense, protein design is a subset of
2077:Optimization algorithms without guarantees
1466:Linear programming § Integer unknowns
1020:generalized dead-end elimination criterion
5747:
5653:
5551:
5379:
5330:
5320:
5271:
5214:
5165:
5073:
5017:
4958:
4948:
4899:
4889:
4826:
4769:
4720:
4663:
4555:
4452:
4396:
4336:
4296:
4255:
4091:
4034:
3994:
3904:
3607:
3542:
3492:
3443:
3377:
3196:
2914:
2898:
2882:
2865:
2849:
2833:
2814:
2798:
2779:
2772:
2763:
2757:
2716:
2703:
2687:
2674:
2668:
2470:
2453:
2422:
2412:
2411:
2395:
2382:
2366:
2350:
2337:
2327:
2317:
2316:
2308:
2303:
2287:
2268:
2262:
2152:
2139:
2125:
2113:
1964:
1951:
1945:
1915:
1890:
1877:
1861:
1848:
1832:
1820:
1815:
1809:
1764:
1751:
1739:
1734:
1728:
1706:
1697:
1684:
1668:
1655:
1642:
1626:
1614:
1609:
1593:
1577:
1564:
1551:
1538:
1526:
1521:
1511:
1499:
1431:
1418:
1400:
1395:
1385:
1368:
1352:
1339:
1323:
1312:
1296:
1275:
1270:
1257:
1240:
1228:
1198:
1185:
1169:
1152:
1136:
1117:
1106:
1094:
1070:in protein design consists of two parts,
992:
979:
961:
956:
940:
924:
902:
889:
884:
866:
861:
845:
829:
824:
812:
687:
681:
680:
671:
658:
642:
626:
610:
597:
587:
586:
580:
567:
558:
402:coulombic term between non-bonded atoms.
7536:Good Design Award (Museum of Modern Art)
446:
386:Physics-based energy functions, such as
278:
131:, and force fields developed mainly for
16:Rational design of new protein molecules
4441:IEEE Transactions on Information Theory
3977:Pierce, NA; Winfree, E (October 2002).
3753:
3751:
3101:
1994:{\displaystyle q_{i},q_{ij}\in \{0,1\}}
766:designing of novel proteins. They used
4842:
3920:
3656:10.1146/annurev-physchem-032210-103509
7541:Good Design Award (Chicago Athenaeum)
5454:Jessica Marshall (November 7, 2012).
5195:Current Opinion in Structural Biology
5054:Current Opinion in Structural Biology
3944:Current Opinion in Structural Biology
3802:Current Opinion in Structural Biology
3760:Current Opinion in Structural Biology
3233:Current Opinion in Structural Biology
3086:Protein structure prediction software
3018:
2615:), and human immunodeficiency virus (
285:on the sequence space. Moreover, the
129:libraries of amino acid conformations
119:. Urry and colleagues later designed
7:
4422:Journal of Machine Learning Research
3109:Korendovych, Ivan (March 19, 2018).
2639:conformations of the free proteins (
550:
339:Backbone-dependent rotamer libraries
3837:Current Opinion in Chemical Biology
3636:Annual Review of Physical Chemistry
3014:
2879:
2830:
2776:
2094:is compared against the old energy
2082:Monte Carlo and simulated annealing
1449:{\displaystyle h=\sum _{j=d+1}^{n}}
7485:American Institute of Graphic Arts
4544:Journal of Computational Chemistry
4072:Journal of Computational Chemistry
2671:
2071:message passing linear programming
1902:
1785:
1487:)) can be easily formulated as an
804:and is thus not part of the GMEC:
517:) be the potential energy between
398:term between atoms and a pairwise
14:
7495:Design and Industries Association
3362:"Computational design of enzymes"
478:be a rotamer at residue position
3693:Current Opinion in Biotechnology
381:knowledge based energy-functions
3009:than both fibrous proteins and
2549:nonribosomal peptide synthetase
2531:designed enzymes for the retro-
417:based on deriving energy values
7490:Chartered Society of Designers
3467:Höcker, B (November 8, 2012).
3379:10.1016/j.chembiol.2008.04.007
3145:Trends in Biochemical Sciences
2911:
2905:
2862:
2856:
2811:
2805:
2476:
2463:
2457:
2438:
2432:
2401:
2375:
2356:
2343:
2293:
2280:
2272:
2161:
2158:
2132:
1896:
1883:
1867:
1841:
1770:
1757:
1703:
1677:
1661:
1635:
1583:
1570:
1557:
1544:
1443:
1440:
1437:
1411:
1358:
1332:
1302:
1289:
1283:
1263:
1207:
1204:
1178:
1142:
1129:
1123:
1052:, branch and bound algorithms
998:
972:
930:
917:
908:
877:
835:
817:
677:
651:
616:
603:
1:
7561:Prince Philip Designers Prize
6204:Architectural lighting design
5749:10.1016/S0969-2126(03)00075-3
4398:10.1093/bioinformatics/bti144
4298:10.1016/s0969-2126(99)80176-2
3956:10.1016/s0959-440x(02)00345-7
3283:10.1126/science.282.5393.1462
3245:10.1016/s0959-440x(99)80072-4
2953:) and off-target binding (or
2555:, from its natural substrate
2010:linear programming relaxation
7367:Electronic design automation
7350:Virtual home design software
6322:Automotive suspension design
5768:Journal of Molecular Biology
5634:Journal of Molecular Biology
4023:Journal of Molecular Biology
3705:10.1016/j.copbio.2009.07.006
3157:10.1016/0968-0004(89)90070-4
2601:Protein–protein interactions
774:With mathematical guarantees
218:protein structure prediction
180:Protein design programs use
101:protein structure prediction
6226:Environmental impact design
5687:. Cambridge, MA: MIT Press.
4992:10.1007/978-1-4939-7366-8_2
3979:"Protein design is NP-hard"
3744:. Cambridge, MA: MIT Press.
3207:10.1126/science.278.5335.82
3113:. American Chemical Society
3030:Design of membrane proteins
2990:Design of globular proteins
2631:Scoring binding predictions
2582:site-saturation mutagenesis
2048:
1483:
1016:pairs elimination criterion
751:
69:protein structure stability
7924:
7505:International Forum Design
6875:Engineering design process
5536:10.1038/s41467-018-06097-1
3849:10.1016/j.cbpa.2005.10.014
3007:nuclear magnetic resonance
2198:to overcome local minima.
2054:message-passing algorithms
1474:The problem of optimizing
1463:
1460:Integer linear programming
1033:
782:
714:The problem of minimizing
482:in the protein chain, and
443:As an optimization problem
436:can be added to rotamers.
287:design of fibrous proteins
18:
7840:
7588:
7577:
7306:
7280:
6736:
6725:
6627:Integrated circuit design
6549:Stage/set lighting design
6438:Hardware interface design
6354:Hardware interface design
6063:
6052:
6034:
5986:Nucleic acid double helix
5780:10.1016/j.jmb.2004.12.019
5646:10.1016/j.jmb.2011.08.022
5207:10.1016/j.sbi.2010.10.002
5066:10.1016/j.sbi.2009.07.005
4638:Baker, D (October 2010).
3996:10.1093/protein/15.10.779
3814:10.1016/j.sbi.2007.03.006
3772:10.1016/j.sbi.2007.03.006
3600:10.1016/j.str.2011.03.019
3076:Molecular design software
61:artificial gene synthesis
57:site-directed mutagenesis
7462:Industrial design rights
7450:Fashion design copyright
7362:Design quality indicator
6811:Creative problem-solving
6602:Electrical system design
6458:Sonic interaction design
6369:Photographic lens design
6243:Healthy community design
5456:"Proteins made to order"
7658:New product development
7623:Enterprise architecture
7551:IF Product Design Award
7510:Design Research Society
7062:Reliability engineering
5425:10.1126/science.1194693
5322:10.1073/pnas.1002162107
4950:10.1073/pnas.0900266106
4891:10.1073/pnas.1118082108
4819:10.1126/science.1190239
4713:10.1126/science.1152692
4463:10.1109/tit.2005.856938
4240:10.1126/science.abn2100
4163:10.1126/science.aba3304
3897:10.1126/science.1192819
3436:10.1126/science.1187659
3366:Chemistry & Biology
3331:10.1126/science.1089427
2250:at neighboring residue
2243:sends to every rotamer
2105:with a probability of:
2101:and the new rotamer is
234:protein folding funnels
49:Rational protein design
7114:Top-down and bottom-up
6463:User experience design
6364:Packaging and labeling
6337:Electric guitar design
6275:Landscape architecture
5887:Nucleic acid structure
5826:Biomolecular structure
5707:10.1002/prot.340120203
4498:10.1109/TPAMI.2006.200
4045:10.1006/jmbi.2000.3758
2969:xylose reductase from
2944:Design for specificity
2934:
2726:
2485:
2173:
2012:of the problem, where
1995:
1931:
1795:
1711:
1489:integer linear program
1450:
1390:
1328:
1262:
1214:
1174:
1122:
1005:
692:
463:Structural flexibility
453:
411:
359:
307:
297:Structural flexibility
255:
208:
7643:Innovation management
7526:European Design Award
7292:Intellectual property
7109:Theory of constraints
7072:Responsibility-driven
6912:For manufacturability
6816:Creativity techniques
6654:Nuclear weapon design
6468:User interface design
6332:Corrugated box design
6253:Interior architecture
5516:Nature Communications
3003:X-ray crystallography
2935:
2727:
2486:
2174:
2004:ILP solvers, such as
1996:
1932:
1796:
1712:
1464:Further information:
1451:
1364:
1308:
1236:
1215:
1148:
1102:
1006:
693:
450:
408:
379:simulation programs,
356:
304:
248:
202:
7688:Unintelligent design
7668:Philosophy of design
7382:Design specification
7335:Comprehensive layout
6907:For behaviour change
6880:Probabilistic design
6642:Power network design
6179:Visual merchandising
6136:Instructional design
6114:Postage stamp design
5146:Nature Biotechnology
5111:10.1038/nbt1007-1109
5099:Nature Biotechnology
2756:
2667:
2623:toward its partner.
2563:Semi-rational design
2537:Diels-Alder reaction
2261:
2190:and the temperature
2112:
1944:
1808:
1727:
1498:
1227:
1093:
811:
785:Dead-end elimination
779:Dead-end elimination
735:dead-end elimination
557:
535:at residue position
232:structures based on
75:Overview and history
7908:Protein engineering
7608:Creative industries
7531:German Design Award
7440:Design infringement
7325:Architectural model
6664:Organization design
6659:Nucleic acid design
6607:Experimental design
6160:Traffic sign design
5956:Protein engineering
5599:10.1038/nature01556
5591:2003Natur.423..185L
5528:2018NatCo...9.3661C
5417:2010Sci...329..770B
5313:2010PNAS..10713707F
5264:10.1038/nature07885
5256:2009Natur.458..859G
4984:Protein Engineering
4941:2009PNAS..106.3764C
4882:2012PNAS..109.3790P
4811:2010Sci...329..309S
4771:10.1038/nature06879
4762:2008Natur.453..190R
4705:2008Sci...319.1387J
4232:2022Sci...377..387W
4155:2020Sci...369..440R
3983:Protein Engineering
3889:2010Sci...329..811Z
3648:2011ARPC...62..129S
3485:2012Natur.491..204H
3428:2010Sci...329..856W
3410:(August 13, 2010).
3323:2003Sci...302.1364K
3081:Protein engineering
2981:Protein resurfacing
2596:Design for affinity
2514:catalytic mechanism
2069:algorithm, and the
1470:Integer programming
1061:A* search algorithm
894:
834:
377:molecular mechanics
224:Top7, developed in
162:protein engineering
21:Protein engineering
7673:Process simulation
7648:Intelligent design
6972:Intelligence-based
6967:Integrated topside
6897:Framework-oriented
6582:Behavioural design
6453:Information design
6131:Information design
4609:10.1002/prot.10131
3043:Other applications
2930:
2893:
2844:
2793:
2722:
2607:'s, many forms of
2523:Great progress in
2507:The design of new
2481:
2448:
2315:
2217:belief propagation
2211:Belief propagation
2188:Boltzmann constant
2169:
1991:
1927:
1827:
1791:
1746:
1707:
1621:
1604:
1533:
1516:
1446:
1407:
1282:
1210:
1001:
968:
951:
880:
873:
856:
820:
688:
637:
585:
454:
412:
360:
308:
256:
214:directed evolution
209:
133:molecular dynamics
105:tertiary structure
7903:Protein structure
7890:
7889:
7836:
7835:
7603:Conceptual design
7573:
7572:
7569:
7568:
7556:James Dyson Award
7412:Website wireframe
7402:Technical drawing
7276:
7275:
7124:Transgenerational
6865:Ecological design
6741:Activity-centered
6721:
6720:
6717:
6716:
6699:Spacecraft design
6493:Public art design
6431:Video game design
6409:Experience design
6379:Production design
6359:Motorcycle design
6317:Automotive design
6221:Ecological design
6099:Film title design
5994:
5993:
5834:Protein structure
5585:(6936): 185–190.
5001:978-1-4939-7364-4
4699:(5868): 1387–91.
4566:10.1002/jcc.20420
4492:(10): 1568–1583.
4447:(11): 3697–3717.
4226:(6604): 387–394.
4149:(6502): 440–445.
4084:10.1002/jcc.21188
3011:membrane proteins
2995:Globular proteins
2928:
2878:
2829:
2775:
2578:DNA recombination
2418:
2408:
2299:
2155:
2142:
1811:
1784:
1730:
1605:
1589:
1517:
1507:
1503:
1391:
1266:
952:
936:
857:
841:
712:
711:
622:
576:
53:peptide synthesis
7915:
7882:
7875:
7868:
7861:
7854:
7847:
7579:
7456:Geschmacksmuster
7430:Community design
7308:
7282:
7042:Process-centered
6838:Design–bid–build
6806:Cradle-to-cradle
6786:Concept-oriented
6727:
6704:Strategic design
6674:Processor design
6649:Mechanism design
6617:Geometric design
6577:Algorithm design
6517:Jewellery design
6448:Immersive design
6342:Furniture design
6287:Landscape design
6065:
6054:
6021:
6014:
6007:
5998:
5981:Structural motif
5819:
5812:
5805:
5796:
5791:
5761:
5751:
5726:
5688:
5681:Donald, Bruce R.
5668:
5667:
5657:
5625:
5619:
5618:
5572:
5566:
5565:
5555:
5507:
5501:
5492:
5486:
5477:
5471:
5470:
5468:
5466:
5451:
5445:
5444:
5400:
5394:
5393:
5383:
5351:
5345:
5344:
5334:
5324:
5307:(31): 13707–12.
5292:
5286:
5285:
5275:
5250:(7240): 859–64.
5235:
5229:
5228:
5218:
5186:
5180:
5179:
5169:
5137:
5131:
5130:
5094:
5088:
5087:
5077:
5045:
5032:
5031:
5021:
4979:
4973:
4972:
4962:
4952:
4920:
4914:
4913:
4903:
4893:
4861:
4855:
4854:
4848:
4840:
4830:
4805:(5989): 309–13.
4790:
4784:
4783:
4773:
4741:
4735:
4734:
4724:
4684:
4678:
4677:
4667:
4635:
4629:
4628:
4592:
4586:
4585:
4559:
4539:
4533:
4532:
4524:
4518:
4517:
4481:
4475:
4474:
4456:
4436:
4430:
4429:
4417:
4411:
4410:
4400:
4376:
4367:
4366:
4340:
4320:
4311:
4310:
4300:
4276:
4270:
4269:
4259:
4217:
4207:
4201:
4200:
4189:
4183:
4182:
4137:
4131:
4130:
4128:
4126:
4112:
4106:
4105:
4095:
4063:
4057:
4056:
4038:
4018:
4009:
4008:
3998:
3974:
3968:
3967:
3939:
3933:
3932:
3926:
3918:
3908:
3867:
3861:
3860:
3832:
3826:
3825:
3797:
3784:
3783:
3755:
3746:
3745:
3738:Donald, Bruce R.
3734:
3717:
3716:
3690:
3677:
3668:
3667:
3631:
3622:
3621:
3611:
3579:
3573:
3572:
3546:
3526:
3515:
3514:
3496:
3464:
3458:
3457:
3447:
3422:(5993): 856–61.
3398:
3392:
3391:
3381:
3357:
3351:
3350:
3317:(5649): 1364–8.
3306:
3295:
3294:
3277:(5393): 1462–7.
3266:
3257:
3256:
3228:
3219:
3218:
3200:
3180:
3169:
3168:
3140:
3123:
3122:
3120:
3118:
3106:
2999:fibrous proteins
2967:Candida boidinii
2939:
2937:
2936:
2931:
2929:
2927:
2926:
2925:
2918:
2892:
2877:
2876:
2869:
2843:
2827:
2826:
2825:
2818:
2792:
2773:
2768:
2767:
2731:
2729:
2728:
2723:
2721:
2720:
2708:
2707:
2695:
2694:
2679:
2678:
2490:
2488:
2487:
2482:
2480:
2479:
2475:
2474:
2447:
2417:
2416:
2410:
2409:
2404:
2400:
2399:
2387:
2386:
2374:
2373:
2355:
2354:
2342:
2341:
2328:
2322:
2321:
2314:
2313:
2312:
2292:
2291:
2279:
2278:
2178:
2176:
2175:
2170:
2165:
2164:
2157:
2156:
2153:
2144:
2143:
2140:
2000:
1998:
1997:
1992:
1972:
1971:
1956:
1955:
1936:
1934:
1933:
1928:
1920:
1919:
1895:
1894:
1882:
1881:
1866:
1865:
1853:
1852:
1840:
1839:
1826:
1825:
1824:
1800:
1798:
1797:
1792:
1782:
1769:
1768:
1756:
1755:
1745:
1744:
1743:
1716:
1714:
1713:
1708:
1702:
1701:
1689:
1688:
1676:
1675:
1660:
1659:
1647:
1646:
1634:
1633:
1620:
1619:
1618:
1603:
1582:
1581:
1569:
1568:
1556:
1555:
1543:
1542:
1532:
1531:
1530:
1515:
1501:
1455:
1453:
1452:
1447:
1436:
1435:
1423:
1422:
1406:
1405:
1404:
1389:
1384:
1357:
1356:
1344:
1343:
1327:
1322:
1301:
1300:
1281:
1280:
1279:
1261:
1256:
1219:
1217:
1216:
1211:
1203:
1202:
1190:
1189:
1173:
1168:
1141:
1140:
1121:
1116:
1046:Branch and bound
1036:Branch and bound
1030:Branch and bound
1010:
1008:
1007:
1002:
997:
996:
984:
983:
967:
966:
965:
950:
929:
928:
907:
906:
893:
888:
872:
871:
870:
855:
833:
828:
760:genome databases
706:
697:
695:
694:
689:
686:
685:
676:
675:
663:
662:
650:
649:
636:
615:
614:
602:
601:
592:
591:
584:
572:
571:
551:
365:energy functions
230:globular-protein
195:Target structure
45:protein redesign
7923:
7922:
7918:
7917:
7916:
7914:
7913:
7912:
7893:
7892:
7891:
7886:
7880:
7873:
7866:
7859:
7852:
7845:
7832:
7633:Futures studies
7584:
7565:
7514:
7473:
7422:
7416:
7302:
7301:
7272:
7178:Value sensitive
7168:User innovation
7047:Public interest
7012:Object-oriented
6732:
6713:
6694:Software design
6684:Research design
6637:Physical design
6592:Database design
6566:
6564:
6558:
6534:Property design
6529:Game art design
6483:
6477:
6400:
6393:
6308:
6301:
6258:Interior design
6209:Building design
6190:
6183:
6070:
6059:
6048:
6030:
6025:
5995:
5990:
5934:
5881:
5828:
5823:
5764:
5729:
5691:
5679:
5676:
5674:Further reading
5671:
5627:
5626:
5622:
5574:
5573:
5569:
5509:
5508:
5504:
5493:
5489:
5478:
5474:
5464:
5462:
5453:
5452:
5448:
5411:(5993): 770–3.
5402:
5401:
5397:
5372:10.1002/pro.227
5366:(10): 2125–38.
5360:Protein Science
5353:
5352:
5348:
5294:
5293:
5289:
5237:
5236:
5232:
5188:
5187:
5183:
5158:10.1038/nbt1336
5139:
5138:
5134:
5105:(10): 1109–10.
5096:
5095:
5091:
5047:
5046:
5035:
5002:
4981:
4980:
4976:
4922:
4921:
4917:
4863:
4862:
4858:
4841:
4792:
4791:
4787:
4756:(7192): 190–5.
4743:
4742:
4738:
4686:
4685:
4681:
4656:10.1002/pro.481
4644:Protein Science
4637:
4636:
4632:
4594:
4593:
4589:
4557:10.1.1.425.5418
4541:
4540:
4536:
4526:
4525:
4521:
4483:
4482:
4478:
4438:
4437:
4433:
4419:
4418:
4414:
4378:
4377:
4370:
4338:10.1.1.133.7986
4322:
4321:
4314:
4278:
4277:
4273:
4215:
4209:
4208:
4204:
4191:
4190:
4186:
4139:
4138:
4134:
4124:
4122:
4114:
4113:
4109:
4078:(12): 1923–45.
4065:
4064:
4060:
4036:10.1.1.138.2023
4020:
4019:
4012:
3976:
3975:
3971:
3941:
3940:
3936:
3919:
3883:(5993): 811–7.
3869:
3868:
3864:
3834:
3833:
3829:
3799:
3798:
3787:
3757:
3756:
3749:
3736:
3735:
3720:
3688:
3684:(August 2009).
3679:
3678:
3671:
3633:
3632:
3625:
3581:
3580:
3576:
3544:10.1.1.555.4071
3528:
3527:
3518:
3494:10.1038/491204a
3479:(7423): 204–5.
3466:
3465:
3461:
3400:
3399:
3395:
3359:
3358:
3354:
3308:
3307:
3298:
3268:
3267:
3260:
3230:
3229:
3222:
3182:
3181:
3172:
3142:
3141:
3126:
3116:
3114:
3108:
3107:
3103:
3099:
3072:
3045:
3032:
2992:
2983:
2965:specificity of
2955:negative design
2951:positive design
2946:
2894:
2845:
2828:
2794:
2774:
2759:
2754:
2753:
2748:
2744:
2740:
2712:
2699:
2683:
2670:
2665:
2664:
2659:
2658:
2652:
2651:
2645:
2644:
2633:
2598:
2574:error-prone RCR
2565:
2545:protein domains
2505:
2500:
2466:
2449:
2391:
2378:
2362:
2346:
2333:
2329:
2323:
2304:
2283:
2264:
2259:
2258:
2254:is defined as:
2253:
2249:
2248:
2242:
2239:that a residue
2238:
2237:
2232:
2231:
2227:
2213:
2204:
2193:
2185:
2148:
2135:
2121:
2110:
2109:
2100:
2097:
2093:
2090:
2084:
2079:
2036:
2025:
2024:
2018:
2017:
1960:
1947:
1942:
1941:
1911:
1886:
1873:
1857:
1844:
1828:
1816:
1806:
1805:
1760:
1747:
1735:
1725:
1724:
1693:
1680:
1664:
1651:
1638:
1622:
1610:
1573:
1560:
1547:
1534:
1522:
1496:
1495:
1480:
1479:
1472:
1462:
1427:
1414:
1396:
1348:
1335:
1292:
1271:
1225:
1224:
1194:
1181:
1132:
1091:
1090:
1085:
1081:
1077:
1073:
1069:
1038:
1032:
988:
975:
957:
920:
898:
862:
809:
808:
803:
802:
796:
795:
787:
781:
776:
764:evolution-based
731:
720:
719:
704:
667:
654:
638:
606:
593:
563:
555:
554:
547:
546:
542:
538:
534:
533:
529:
525:
524:
520:
516:
515:
511:
507:
506:
502:
498:
494:
492:
491:
487:
481:
477:
476:
472:
445:
439:
429:
351:
349:Energy function
329:
324:dihedral angles
323:
299:
243:
197:
182:computer models
178:
109:inverse folding
103:. In design, a
77:
33:rational design
24:
17:
12:
11:
5:
7921:
7919:
7911:
7910:
7905:
7895:
7894:
7888:
7887:
7885:
7884:
7877:
7870:
7863:
7856:
7849:
7841:
7838:
7837:
7834:
7833:
7831:
7830:
7825:
7820:
7815:
7810:
7805:
7800:
7795:
7790:
7785:
7780:
7775:
7770:
7765:
7760:
7755:
7750:
7745:
7740:
7735:
7734:
7733:
7728:
7718:
7713:
7708:
7701:
7700:
7698:Wicked problem
7695:
7690:
7685:
7680:
7675:
7670:
7665:
7660:
7655:
7650:
7645:
7640:
7635:
7630:
7625:
7620:
7615:
7610:
7605:
7600:
7595:
7589:
7586:
7585:
7583:Related topics
7582:
7575:
7574:
7571:
7570:
7567:
7566:
7564:
7563:
7558:
7553:
7548:
7543:
7538:
7533:
7528:
7522:
7520:
7516:
7515:
7513:
7512:
7507:
7502:
7500:Design Council
7497:
7492:
7487:
7481:
7479:
7475:
7474:
7472:
7471:
7470:
7469:
7467:European Union
7459:
7452:
7447:
7442:
7437:
7432:
7426:
7424:
7418:
7417:
7415:
7414:
7409:
7404:
7399:
7394:
7389:
7384:
7379:
7374:
7369:
7364:
7359:
7354:
7353:
7352:
7347:
7337:
7332:
7327:
7322:
7316:
7314:
7304:
7303:
7300:
7299:
7296:
7293:
7290:
7286:
7285:
7278:
7277:
7274:
7273:
7271:
7270:
7265:
7260:
7255:
7250:
7245:
7240:
7235:
7230:
7225:
7220:
7215:
7210:
7205:
7200:
7195:
7188:
7187:
7186:
7185:
7175:
7170:
7165:
7164:
7163:
7153:
7148:
7146:Usage-centered
7143:
7142:
7141:
7139:Design for All
7131:
7126:
7121:
7119:Transformation
7116:
7111:
7106:
7101:
7100:
7099:
7089:
7084:
7079:
7074:
7069:
7067:Research-based
7064:
7059:
7054:
7049:
7044:
7039:
7034:
7032:Platform-based
7029:
7024:
7019:
7014:
7009:
7004:
6999:
6994:
6989:
6984:
6982:KISS principle
6979:
6974:
6969:
6964:
6959:
6954:
6949:
6944:
6939:
6934:
6929:
6924:
6919:
6914:
6909:
6904:
6899:
6894:
6892:Fault-tolerant
6889:
6887:Error-tolerant
6884:
6883:
6882:
6872:
6870:Energy neutral
6867:
6862:
6857:
6852:
6851:
6850:
6840:
6835:
6830:
6829:
6828:
6826:Design fiction
6818:
6813:
6808:
6803:
6798:
6793:
6788:
6783:
6778:
6773:
6768:
6763:
6758:
6753:
6748:
6743:
6737:
6734:
6733:
6730:
6723:
6722:
6719:
6718:
6715:
6714:
6712:
6711:
6709:Systems design
6706:
6701:
6696:
6691:
6686:
6681:
6679:Protein design
6676:
6671:
6669:Process design
6666:
6661:
6656:
6651:
6646:
6645:
6644:
6639:
6634:
6632:Circuit design
6624:
6619:
6614:
6609:
6604:
6599:
6594:
6589:
6584:
6579:
6573:
6571:
6560:
6559:
6557:
6556:
6554:Textile design
6551:
6546:
6541:
6536:
6531:
6526:
6521:
6520:
6519:
6514:
6512:Costume design
6507:Fashion design
6504:
6495:
6489:
6487:
6479:
6478:
6476:
6475:
6470:
6465:
6460:
6455:
6450:
6445:
6440:
6435:
6434:
6433:
6428:
6418:
6417:
6416:
6405:
6403:
6395:
6394:
6392:
6391:
6389:Service design
6386:
6384:Sensory design
6381:
6376:
6374:Product design
6371:
6366:
6361:
6356:
6351:
6350:
6349:
6339:
6334:
6329:
6324:
6319:
6313:
6311:
6303:
6302:
6300:
6299:
6294:
6292:Spatial design
6289:
6284:
6283:
6282:
6272:
6270:Keyline design
6267:
6266:
6265:
6255:
6250:
6245:
6240:
6239:
6238:
6236:Computer-aided
6228:
6223:
6218:
6217:
6216:
6206:
6201:
6195:
6193:
6185:
6184:
6182:
6181:
6176:
6171:
6162:
6153:
6148:
6143:
6138:
6133:
6128:
6123:
6122:
6121:
6116:
6111:
6104:Graphic design
6101:
6096:
6094:Exhibit design
6091:
6086:
6081:
6075:
6073:
6061:
6060:
6057:
6050:
6049:
6047:
6046:
6041:
6035:
6032:
6031:
6026:
6024:
6023:
6016:
6009:
6001:
5992:
5991:
5989:
5988:
5983:
5978:
5973:
5968:
5963:
5958:
5953:
5951:Protein domain
5948:
5942:
5940:
5936:
5935:
5933:
5932:
5930:Thermodynamics
5927:
5922:
5917:
5912:
5907:
5902:
5897:
5891:
5889:
5883:
5882:
5880:
5879:
5877:Thermodynamics
5874:
5869:
5864:
5859:
5854:
5849:
5844:
5838:
5836:
5830:
5829:
5824:
5822:
5821:
5814:
5807:
5799:
5793:
5792:
5774:(1): 203–227.
5762:
5742:(5): 581–590.
5727:
5701:(2): 105–110.
5689:
5675:
5672:
5670:
5669:
5620:
5567:
5502:
5487:
5472:
5446:
5395:
5346:
5287:
5230:
5181:
5152:(10): 1171–6.
5132:
5089:
5033:
5000:
4974:
4935:(10): 3764–9.
4915:
4876:(10): 3790–5.
4856:
4785:
4736:
4679:
4650:(10): 1817–9.
4630:
4587:
4550:(10): 1071–5.
4534:
4519:
4476:
4454:10.1.1.71.9565
4431:
4412:
4391:(7): 1028–36.
4385:Bioinformatics
4368:
4312:
4291:(9): 1089–98.
4271:
4202:
4184:
4132:
4107:
4058:
4029:(3): 789–803.
4010:
3989:(10): 779–82.
3969:
3934:
3862:
3827:
3808:(2): 199–204.
3785:
3766:(2): 199–204.
3747:
3718:
3669:
3623:
3574:
3537:(3): 389–408.
3516:
3459:
3393:
3352:
3296:
3258:
3220:
3198:10.1.1.72.7304
3191:(5335): 82–7.
3170:
3124:
3100:
3098:
3095:
3094:
3093:
3088:
3083:
3078:
3071:
3068:
3064:battery design
3044:
3041:
3031:
3028:
2991:
2988:
2982:
2979:
2945:
2942:
2941:
2940:
2924:
2921:
2917:
2913:
2910:
2907:
2904:
2901:
2897:
2891:
2888:
2885:
2881:
2875:
2872:
2868:
2864:
2861:
2858:
2855:
2852:
2848:
2842:
2839:
2836:
2832:
2824:
2821:
2817:
2813:
2810:
2807:
2804:
2801:
2797:
2791:
2788:
2785:
2782:
2778:
2771:
2766:
2762:
2746:
2742:
2738:
2734:
2733:
2719:
2715:
2711:
2706:
2702:
2698:
2693:
2690:
2686:
2682:
2677:
2673:
2656:
2654:
2649:
2647:
2642:
2640:
2632:
2629:
2597:
2594:
2564:
2561:
2551:that produces
2533:aldol reaction
2504:
2501:
2499:
2496:
2492:
2491:
2478:
2473:
2469:
2465:
2462:
2459:
2456:
2452:
2446:
2443:
2440:
2437:
2434:
2431:
2428:
2425:
2421:
2415:
2407:
2403:
2398:
2394:
2390:
2385:
2381:
2377:
2372:
2369:
2365:
2361:
2358:
2353:
2349:
2345:
2340:
2336:
2332:
2326:
2320:
2311:
2307:
2302:
2298:
2295:
2290:
2286:
2282:
2277:
2274:
2271:
2267:
2251:
2246:
2244:
2240:
2235:
2233:
2229:
2228:
2225:
2212:
2209:
2203:
2200:
2191:
2183:
2180:
2179:
2168:
2163:
2160:
2151:
2147:
2138:
2134:
2131:
2128:
2124:
2120:
2117:
2098:
2095:
2091:
2088:
2083:
2080:
2078:
2075:
2035:
2032:
2028:branch and cut
2022:
2020:
2015:
2013:
2002:
2001:
1990:
1987:
1984:
1981:
1978:
1975:
1970:
1967:
1963:
1959:
1954:
1950:
1938:
1937:
1926:
1923:
1918:
1914:
1910:
1907:
1904:
1901:
1898:
1893:
1889:
1885:
1880:
1876:
1872:
1869:
1864:
1860:
1856:
1851:
1847:
1843:
1838:
1835:
1831:
1823:
1819:
1814:
1802:
1801:
1790:
1787:
1781:
1778:
1775:
1772:
1767:
1763:
1759:
1754:
1750:
1742:
1738:
1733:
1718:
1717:
1705:
1700:
1696:
1692:
1687:
1683:
1679:
1674:
1671:
1667:
1663:
1658:
1654:
1650:
1645:
1641:
1637:
1632:
1629:
1625:
1617:
1613:
1608:
1602:
1599:
1596:
1592:
1588:
1585:
1580:
1576:
1572:
1567:
1563:
1559:
1554:
1550:
1546:
1541:
1537:
1529:
1525:
1520:
1514:
1510:
1506:
1477:
1475:
1461:
1458:
1457:
1456:
1445:
1442:
1439:
1434:
1430:
1426:
1421:
1417:
1413:
1410:
1403:
1399:
1394:
1388:
1383:
1380:
1377:
1374:
1371:
1367:
1363:
1360:
1355:
1351:
1347:
1342:
1338:
1334:
1331:
1326:
1321:
1318:
1315:
1311:
1307:
1304:
1299:
1295:
1291:
1288:
1285:
1278:
1274:
1269:
1265:
1260:
1255:
1252:
1249:
1246:
1243:
1239:
1235:
1232:
1221:
1220:
1209:
1206:
1201:
1197:
1193:
1188:
1184:
1180:
1177:
1172:
1167:
1164:
1161:
1158:
1155:
1151:
1147:
1144:
1139:
1135:
1131:
1128:
1125:
1120:
1115:
1112:
1109:
1105:
1101:
1098:
1083:
1079:
1075:
1071:
1067:
1034:Main article:
1031:
1028:
1012:
1011:
1000:
995:
991:
987:
982:
978:
974:
971:
964:
960:
955:
949:
946:
943:
939:
935:
932:
927:
923:
919:
916:
913:
910:
905:
901:
897:
892:
887:
883:
879:
876:
869:
865:
860:
854:
851:
848:
844:
840:
837:
832:
827:
823:
819:
816:
800:
798:
793:
791:
783:Main article:
780:
777:
775:
772:
730:
727:
717:
715:
710:
709:
700:
698:
684:
679:
674:
670:
666:
661:
657:
653:
648:
645:
641:
635:
632:
629:
625:
621:
618:
613:
609:
605:
600:
596:
590:
583:
579:
575:
570:
566:
562:
544:
543:
540:
536:
531:
530:
527:
522:
521:
518:
513:
512:
509:
504:
503:
500:
496:
489:
488:
485:
483:
479:
474:
473:
470:
444:
441:
428:
425:
400:electrostatics
350:
347:
327:
321:
298:
295:
275:sequence space
242:
241:Sequence space
239:
196:
193:
177:
174:
170:bioengineering
76:
73:
29:Protein design
15:
13:
10:
9:
6:
4:
3:
2:
7920:
7909:
7906:
7904:
7901:
7900:
7898:
7883:
7878:
7876:
7871:
7869:
7864:
7862:
7857:
7855:
7850:
7848:
7843:
7842:
7839:
7829:
7826:
7824:
7821:
7819:
7816:
7814:
7813:specification
7811:
7809:
7806:
7804:
7801:
7799:
7796:
7794:
7791:
7789:
7786:
7784:
7781:
7779:
7776:
7774:
7771:
7769:
7766:
7764:
7761:
7759:
7756:
7754:
7751:
7749:
7746:
7744:
7741:
7739:
7736:
7732:
7729:
7727:
7726:architectural
7724:
7723:
7722:
7719:
7717:
7714:
7712:
7709:
7707:
7703:
7702:
7699:
7696:
7694:
7693:Visualization
7691:
7689:
7686:
7684:
7681:
7679:
7676:
7674:
7671:
7669:
7666:
7664:
7661:
7659:
7656:
7654:
7651:
7649:
7646:
7644:
7641:
7639:
7636:
7634:
7631:
7629:
7626:
7624:
7621:
7619:
7616:
7614:
7613:Cultural icon
7611:
7609:
7606:
7604:
7601:
7599:
7596:
7594:
7591:
7590:
7587:
7580:
7576:
7562:
7559:
7557:
7554:
7552:
7549:
7547:
7544:
7542:
7539:
7537:
7534:
7532:
7529:
7527:
7524:
7523:
7521:
7517:
7511:
7508:
7506:
7503:
7501:
7498:
7496:
7493:
7491:
7488:
7486:
7483:
7482:
7480:
7478:Organizations
7476:
7468:
7465:
7464:
7463:
7460:
7458:
7457:
7453:
7451:
7448:
7446:
7445:Design patent
7443:
7441:
7438:
7436:
7435:Design around
7433:
7431:
7428:
7427:
7425:
7419:
7413:
7410:
7408:
7405:
7403:
7400:
7398:
7395:
7393:
7390:
7388:
7385:
7383:
7380:
7378:
7375:
7373:
7370:
7368:
7365:
7363:
7360:
7358:
7355:
7351:
7348:
7346:
7343:
7342:
7341:
7338:
7336:
7333:
7331:
7328:
7326:
7323:
7321:
7318:
7317:
7315:
7313:
7309:
7305:
7297:
7295:Organizations
7294:
7291:
7288:
7287:
7283:
7279:
7269:
7266:
7264:
7261:
7259:
7256:
7254:
7251:
7249:
7246:
7244:
7241:
7239:
7236:
7234:
7231:
7229:
7226:
7224:
7221:
7219:
7216:
7214:
7211:
7209:
7206:
7204:
7201:
7199:
7196:
7194:
7190:
7189:
7184:
7181:
7180:
7179:
7176:
7174:
7171:
7169:
7166:
7162:
7159:
7158:
7157:
7156:User-centered
7154:
7152:
7149:
7147:
7144:
7140:
7137:
7136:
7135:
7132:
7130:
7127:
7125:
7122:
7120:
7117:
7115:
7112:
7110:
7107:
7105:
7104:Tableless web
7102:
7098:
7095:
7094:
7093:
7090:
7088:
7085:
7083:
7080:
7078:
7075:
7073:
7070:
7068:
7065:
7063:
7060:
7058:
7055:
7053:
7050:
7048:
7045:
7043:
7040:
7038:
7035:
7033:
7030:
7028:
7027:Participatory
7025:
7023:
7020:
7018:
7015:
7013:
7010:
7008:
7005:
7003:
7000:
6998:
6995:
6993:
6990:
6988:
6985:
6983:
6980:
6978:
6975:
6973:
6970:
6968:
6965:
6963:
6960:
6958:
6955:
6953:
6950:
6948:
6945:
6943:
6940:
6938:
6935:
6933:
6930:
6928:
6925:
6923:
6920:
6918:
6917:For Six Sigma
6915:
6913:
6910:
6908:
6905:
6903:
6900:
6898:
6895:
6893:
6890:
6888:
6885:
6881:
6878:
6877:
6876:
6873:
6871:
6868:
6866:
6863:
6861:
6860:Domain-driven
6858:
6856:
6853:
6849:
6848:architect-led
6846:
6845:
6844:
6841:
6839:
6836:
6834:
6831:
6827:
6824:
6823:
6822:
6819:
6817:
6814:
6812:
6809:
6807:
6804:
6802:
6799:
6797:
6794:
6792:
6791:Configuration
6789:
6787:
6784:
6782:
6779:
6777:
6774:
6772:
6769:
6767:
6764:
6762:
6759:
6757:
6756:Brainstorming
6754:
6752:
6749:
6747:
6744:
6742:
6739:
6738:
6735:
6728:
6724:
6710:
6707:
6705:
6702:
6700:
6697:
6695:
6692:
6690:
6689:Social design
6687:
6685:
6682:
6680:
6677:
6675:
6672:
6670:
6667:
6665:
6662:
6660:
6657:
6655:
6652:
6650:
6647:
6643:
6640:
6638:
6635:
6633:
6630:
6629:
6628:
6625:
6623:
6620:
6618:
6615:
6613:
6612:Filter design
6610:
6608:
6605:
6603:
6600:
6598:
6595:
6593:
6590:
6588:
6587:Boiler design
6585:
6583:
6580:
6578:
6575:
6574:
6572:
6570:
6561:
6555:
6552:
6550:
6547:
6545:
6542:
6540:
6539:Scenic design
6537:
6535:
6532:
6530:
6527:
6525:
6524:Floral design
6522:
6518:
6515:
6513:
6510:
6509:
6508:
6505:
6503:
6499:
6496:
6494:
6491:
6490:
6488:
6486:
6480:
6474:
6471:
6469:
6466:
6464:
6461:
6459:
6456:
6454:
6451:
6449:
6446:
6444:
6441:
6439:
6436:
6432:
6429:
6427:
6424:
6423:
6422:
6419:
6415:
6412:
6411:
6410:
6407:
6406:
6404:
6402:
6396:
6390:
6387:
6385:
6382:
6380:
6377:
6375:
6372:
6370:
6367:
6365:
6362:
6360:
6357:
6355:
6352:
6348:
6345:
6344:
6343:
6340:
6338:
6335:
6333:
6330:
6328:
6325:
6323:
6320:
6318:
6315:
6314:
6312:
6310:
6304:
6298:
6295:
6293:
6290:
6288:
6285:
6281:
6278:
6277:
6276:
6273:
6271:
6268:
6264:
6261:
6260:
6259:
6256:
6254:
6251:
6249:
6246:
6244:
6241:
6237:
6234:
6233:
6232:
6231:Garden design
6229:
6227:
6224:
6222:
6219:
6215:
6214:Passive solar
6212:
6211:
6210:
6207:
6205:
6202:
6200:
6197:
6196:
6194:
6192:
6189:Environmental
6186:
6180:
6177:
6175:
6172:
6170:
6166:
6163:
6161:
6157:
6154:
6152:
6151:Retail design
6149:
6147:
6144:
6142:
6139:
6137:
6134:
6132:
6129:
6127:
6124:
6120:
6117:
6115:
6112:
6110:
6107:
6106:
6105:
6102:
6100:
6097:
6095:
6092:
6090:
6087:
6085:
6082:
6080:
6077:
6076:
6074:
6072:
6069:Communication
6066:
6062:
6055:
6051:
6045:
6042:
6040:
6037:
6036:
6033:
6029:
6022:
6017:
6015:
6010:
6008:
6003:
6002:
5999:
5987:
5984:
5982:
5979:
5977:
5974:
5972:
5969:
5967:
5964:
5962:
5959:
5957:
5954:
5952:
5949:
5947:
5944:
5943:
5941:
5937:
5931:
5928:
5926:
5923:
5921:
5918:
5916:
5915:Determination
5913:
5911:
5908:
5906:
5903:
5901:
5898:
5896:
5893:
5892:
5890:
5888:
5884:
5878:
5875:
5873:
5870:
5868:
5865:
5863:
5862:Determination
5860:
5858:
5855:
5853:
5850:
5848:
5845:
5843:
5840:
5839:
5837:
5835:
5831:
5827:
5820:
5815:
5813:
5808:
5806:
5801:
5800:
5797:
5789:
5785:
5781:
5777:
5773:
5769:
5763:
5759:
5755:
5750:
5745:
5741:
5737:
5733:
5728:
5724:
5720:
5716:
5712:
5708:
5704:
5700:
5696:
5690:
5686:
5682:
5678:
5677:
5673:
5665:
5661:
5656:
5651:
5647:
5643:
5640:(2): 513–22.
5639:
5635:
5631:
5624:
5621:
5616:
5612:
5608:
5604:
5600:
5596:
5592:
5588:
5584:
5580:
5579:
5571:
5568:
5563:
5559:
5554:
5549:
5545:
5541:
5537:
5533:
5529:
5525:
5521:
5517:
5513:
5506:
5503:
5500:
5496:
5491:
5488:
5485:
5481:
5476:
5473:
5461:
5457:
5450:
5447:
5442:
5438:
5434:
5430:
5426:
5422:
5418:
5414:
5410:
5406:
5399:
5396:
5391:
5387:
5382:
5377:
5373:
5369:
5365:
5361:
5357:
5350:
5347:
5342:
5338:
5333:
5328:
5323:
5318:
5314:
5310:
5306:
5302:
5298:
5291:
5288:
5283:
5279:
5274:
5269:
5265:
5261:
5257:
5253:
5249:
5245:
5241:
5234:
5231:
5226:
5222:
5217:
5212:
5208:
5204:
5200:
5196:
5192:
5185:
5182:
5177:
5173:
5168:
5163:
5159:
5155:
5151:
5147:
5143:
5136:
5133:
5128:
5124:
5120:
5116:
5112:
5108:
5104:
5100:
5093:
5090:
5085:
5081:
5076:
5071:
5067:
5063:
5060:(4): 458–63.
5059:
5055:
5051:
5044:
5042:
5040:
5038:
5034:
5029:
5025:
5020:
5015:
5011:
5007:
5003:
4997:
4993:
4989:
4985:
4978:
4975:
4970:
4966:
4961:
4956:
4951:
4946:
4942:
4938:
4934:
4930:
4926:
4919:
4916:
4911:
4907:
4902:
4897:
4892:
4887:
4883:
4879:
4875:
4871:
4867:
4860:
4857:
4852:
4846:
4838:
4834:
4829:
4824:
4820:
4816:
4812:
4808:
4804:
4800:
4796:
4789:
4786:
4781:
4777:
4772:
4767:
4763:
4759:
4755:
4751:
4747:
4740:
4737:
4732:
4728:
4723:
4718:
4714:
4710:
4706:
4702:
4698:
4694:
4690:
4683:
4680:
4675:
4671:
4666:
4661:
4657:
4653:
4649:
4645:
4641:
4634:
4631:
4626:
4622:
4618:
4614:
4610:
4606:
4602:
4598:
4591:
4588:
4583:
4579:
4575:
4571:
4567:
4563:
4558:
4553:
4549:
4545:
4538:
4535:
4530:
4523:
4520:
4515:
4511:
4507:
4503:
4499:
4495:
4491:
4487:
4480:
4477:
4472:
4468:
4464:
4460:
4455:
4450:
4446:
4442:
4435:
4432:
4427:
4423:
4416:
4413:
4408:
4404:
4399:
4394:
4390:
4386:
4382:
4375:
4373:
4369:
4364:
4360:
4356:
4352:
4348:
4344:
4339:
4334:
4331:(2): 227–39.
4330:
4326:
4319:
4317:
4313:
4308:
4304:
4299:
4294:
4290:
4286:
4282:
4275:
4272:
4267:
4263:
4258:
4253:
4249:
4245:
4241:
4237:
4233:
4229:
4225:
4221:
4214:
4206:
4203:
4198:
4194:
4188:
4185:
4180:
4176:
4172:
4168:
4164:
4160:
4156:
4152:
4148:
4144:
4136:
4133:
4121:
4117:
4111:
4108:
4103:
4099:
4094:
4089:
4085:
4081:
4077:
4073:
4069:
4062:
4059:
4054:
4050:
4046:
4042:
4037:
4032:
4028:
4024:
4017:
4015:
4011:
4006:
4002:
3997:
3992:
3988:
3984:
3980:
3973:
3970:
3965:
3961:
3957:
3953:
3949:
3945:
3938:
3935:
3930:
3924:
3916:
3912:
3907:
3902:
3898:
3894:
3890:
3886:
3882:
3878:
3874:
3866:
3863:
3858:
3854:
3850:
3846:
3842:
3838:
3831:
3828:
3823:
3819:
3815:
3811:
3807:
3803:
3796:
3794:
3792:
3790:
3786:
3781:
3777:
3773:
3769:
3765:
3761:
3754:
3752:
3748:
3743:
3739:
3733:
3731:
3729:
3727:
3725:
3723:
3719:
3714:
3710:
3706:
3702:
3698:
3694:
3687:
3683:
3680:Mandell, DJ;
3676:
3674:
3670:
3665:
3661:
3657:
3653:
3649:
3645:
3641:
3637:
3630:
3628:
3624:
3619:
3615:
3610:
3605:
3601:
3597:
3594:(6): 844–58.
3593:
3589:
3585:
3578:
3575:
3570:
3566:
3562:
3558:
3554:
3550:
3545:
3540:
3536:
3532:
3525:
3523:
3521:
3517:
3512:
3508:
3504:
3500:
3495:
3490:
3486:
3482:
3478:
3474:
3470:
3463:
3460:
3455:
3451:
3446:
3441:
3437:
3433:
3429:
3425:
3421:
3417:
3413:
3409:
3405:
3397:
3394:
3389:
3385:
3380:
3375:
3371:
3367:
3363:
3356:
3353:
3348:
3344:
3340:
3336:
3332:
3328:
3324:
3320:
3316:
3312:
3305:
3303:
3301:
3297:
3292:
3288:
3284:
3280:
3276:
3272:
3265:
3263:
3259:
3254:
3250:
3246:
3242:
3239:(4): 509–13.
3238:
3234:
3227:
3225:
3221:
3216:
3212:
3208:
3204:
3199:
3194:
3190:
3186:
3179:
3177:
3175:
3171:
3166:
3162:
3158:
3154:
3150:
3146:
3139:
3137:
3135:
3133:
3131:
3129:
3125:
3112:
3105:
3102:
3096:
3092:
3089:
3087:
3084:
3082:
3079:
3077:
3074:
3073:
3069:
3067:
3065:
3060:
3058:
3054:
3050:
3042:
3040:
3038:
3029:
3027:
3024:
3020:
3016:
3012:
3008:
3004:
3000:
2996:
2989:
2987:
2980:
2978:
2976:
2972:
2968:
2964:
2960:
2956:
2952:
2943:
2922:
2919:
2915:
2908:
2902:
2899:
2895:
2889:
2886:
2883:
2873:
2870:
2866:
2859:
2853:
2850:
2846:
2840:
2837:
2834:
2822:
2819:
2815:
2808:
2802:
2799:
2795:
2789:
2786:
2783:
2780:
2769:
2764:
2760:
2752:
2751:
2750:
2717:
2713:
2709:
2704:
2700:
2696:
2691:
2688:
2684:
2680:
2675:
2663:
2662:
2661:
2638:
2630:
2628:
2624:
2622:
2618:
2614:
2610:
2606:
2602:
2595:
2593:
2589:
2585:
2583:
2579:
2575:
2571:
2562:
2560:
2558:
2557:phenylalanine
2554:
2550:
2546:
2542:
2538:
2534:
2530:
2526:
2521:
2519:
2515:
2510:
2503:Enzyme design
2502:
2497:
2495:
2471:
2467:
2460:
2454:
2450:
2444:
2435:
2429:
2426:
2423:
2419:
2405:
2396:
2392:
2388:
2383:
2379:
2370:
2367:
2363:
2359:
2351:
2347:
2338:
2334:
2330:
2324:
2309:
2305:
2296:
2288:
2284:
2275:
2269:
2265:
2257:
2256:
2255:
2222:
2218:
2210:
2208:
2201:
2199:
2197:
2189:
2166:
2149:
2145:
2136:
2129:
2126:
2122:
2118:
2115:
2108:
2107:
2106:
2104:
2081:
2076:
2074:
2072:
2068:
2063:
2059:
2055:
2051:
2050:
2045:
2041:
2033:
2031:
2029:
2011:
2007:
1985:
1982:
1979:
1973:
1968:
1965:
1961:
1957:
1952:
1948:
1940:
1939:
1924:
1921:
1916:
1912:
1908:
1905:
1899:
1891:
1887:
1878:
1874:
1870:
1862:
1858:
1854:
1849:
1845:
1836:
1833:
1829:
1821:
1817:
1812:
1804:
1803:
1788:
1779:
1776:
1773:
1765:
1761:
1752:
1748:
1740:
1736:
1731:
1723:
1722:
1721:
1698:
1694:
1690:
1685:
1681:
1672:
1669:
1665:
1656:
1652:
1648:
1643:
1639:
1630:
1627:
1623:
1615:
1611:
1606:
1600:
1597:
1594:
1590:
1586:
1578:
1574:
1565:
1561:
1552:
1548:
1539:
1535:
1527:
1523:
1518:
1512:
1508:
1494:
1493:
1492:
1490:
1486:
1485:
1471:
1467:
1459:
1432:
1428:
1424:
1419:
1415:
1408:
1401:
1397:
1386:
1381:
1378:
1375:
1372:
1369:
1365:
1361:
1353:
1349:
1345:
1340:
1336:
1329:
1324:
1319:
1316:
1313:
1309:
1305:
1297:
1293:
1286:
1276:
1272:
1258:
1253:
1250:
1247:
1244:
1241:
1237:
1233:
1230:
1223:
1222:
1199:
1195:
1191:
1186:
1182:
1175:
1170:
1165:
1162:
1159:
1156:
1153:
1149:
1145:
1137:
1133:
1126:
1118:
1113:
1110:
1107:
1103:
1099:
1096:
1089:
1088:
1087:
1066:The A* score
1064:
1062:
1057:
1055:
1051:
1047:
1043:
1037:
1029:
1027:
1023:
1021:
1017:
993:
989:
985:
980:
976:
969:
962:
958:
947:
944:
941:
937:
933:
925:
921:
914:
911:
903:
899:
895:
885:
881:
874:
867:
863:
852:
849:
846:
842:
838:
825:
821:
814:
807:
806:
805:
786:
778:
773:
771:
769:
768:deep learning
765:
761:
756:
754:
753:
747:
744:
740:
736:
728:
726:
724:
708:
701:
699:
672:
668:
664:
659:
655:
646:
643:
639:
633:
630:
627:
623:
619:
611:
607:
598:
594:
581:
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7653:Lean startup
7638:Indie design
7454:
7421:Intellectual
7173:Value-driven
7151:Use-centered
7057:Regenerative
7037:Policy-based
6997:Mind mapping
6902:For assembly
6843:Design–build
6761:By committee
6746:Adaptive web
6678:
6544:Sound design
6502:glass design
6500: /
6485:applied arts
6426:Level design
6297:Urban design
6248:Hotel design
6199:Architecture
6174:Video design
6167: /
6158: /
6126:Illustration
6119:Print design
6089:Brand design
5966:Nucleic acid
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150:coiled coils
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142:Stephen Mayo
140:was done by
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7628:Form factor
7598:Concept art
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7087:Sustainable
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6766:By contract
6622:Work design
6597:Drug design
6569:engineering
6443:Icon design
6421:Game design
6399:Interaction
6347:Sustainable
6280:Sustainable
6169:Type design
6146:Photography
6141:News design
6084:Book design
6079:Advertising
6058:Disciplines
5522:(1): 3661.
5460:Nature News
3682:Kortemme, T
3408:Mascola, JR
2570:mutagenesis
2073:algorithm.
1481:(Equation (
312:flexibility
226:David Baker
166:biomedicine
154:David Baker
152:. In 2003,
97:free energy
7897:Categories
7881:Wiktionary
7874:Wikisource
7828:technology
7798:principles
7397:Storyboard
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7218:leadership
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6992:Metadesign
6962:Integrated
6952:High-level
6937:Generative
6932:Functional
6801:Continuous
6796:Contextual
6771:C-K theory
6731:Approaches
6473:Web design
6327:CMF design
6307:Industrial
6165:Typography
5961:Proteasome
5920:Prediction
5910:Quaternary
5867:Prediction
5857:Quaternary
4125:August 17,
3642:: 129–49.
3097:References
3049:biosensors
2230:i→ j
1018:, and the
729:Algorithms
369:challenges
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7867:Wikiquote
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7768:knowledge
7743:education
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7387:Prototype
7372:Flowchart
7330:Blueprint
7198:computing
7134:Universal
7082:Safe-life
6987:Low-level
6977:Iterative
6957:Inclusive
6942:Geodesign
6833:Defensive
6781:Co-design
6751:Affective
5900:Secondary
5847:Secondary
5736:Structure
5544:2041-1723
5441:206528638
5010:1064-3745
4552:CiteSeerX
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4333:CiteSeerX
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1050:branching
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631:≠
624:∑
578:∑
410:(purple).
254:sequence.
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7860:Wikinews
7793:paradigm
7773:language
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7748:elements
7738:director
7423:property
7268:thinking
7258:strategy
7243:research
7203:controls
7161:Empathic
7092:Systemic
7052:Rational
7007:New Wave
6821:Critical
6044:Designer
5939:See also
5905:Tertiary
5852:Tertiary
5788:15733929
5758:12737823
5723:38986245
5683:(2011).
5664:21888918
5607:12736688
5562:30202038
5433:20705840
5390:19693930
5341:20643959
5282:19370028
5225:21071205
5176:17891135
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4910:22357762
4837:20647463
4780:18354394
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4674:20717908
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4617:12012335
4597:Proteins
4574:16685715
4506:16986540
4471:10007532
4407:15546935
4363:12872539
4325:Proteins
4307:10508778
4266:35862514
4171:32703877
4120:phys.org
4102:19123203
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3822:17387014
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3713:19709874
3664:21128762
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3531:Proteins
3503:23135466
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3388:18482694
3339:14631033
3253:10449371
3070:See also
2963:cofactor
2621:affinity
2196:annealed
2103:accepted
792:r′
332:rotamers
291:Collagen
158:examples
7846:Commons
7818:studies
7763:history
7731:student
7716:classic
7704:Design
7618:.design
7546:Graphex
7248:science
7238:pattern
7233:methods
7208:culture
7191:Design
7002:Modular
6855:Diffuse
6776:Closure
6498:Ceramic
6156:Signage
6039:Outline
5946:Protein
5895:Primary
5842:Primary
5715:1603799
5655:3202338
5615:4387641
5587:Bibcode
5553:6131167
5524:Bibcode
5413:Bibcode
5405:Science
5381:2786976
5332:2922245
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5273:2748673
5252:Bibcode
5216:3053118
5167:2803018
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4693:Science
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4228:Bibcode
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4143:Science
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3877:Science
3644:Bibcode
3609:3118414
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3445:2965066
3424:Bibcode
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3347:1939390
3319:Bibcode
3311:Science
3291:9822371
3271:Science
3215:9311930
3185:Science
3165:2672455
3023:de novo
2611:(e.g.,
2547:of the
2529:de novo
2525:de novo
2518:de novo
2509:enzymes
2186:is the
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2040:Simplex
739:runtime
723:NP-hard
271:de novo
264:de novo
260:de novo
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187:in vivo
138:de novo
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4175:S2CID
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3507:S2CID
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1072:f=g+h
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283:rules
269:Both
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5429:PMID
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