354:), until a certain number of steps have been tried. The assumption is that convergence to the best structure should occur from a large class of initial configurations, only one of which needs to be considered. Initial configurations may be sampled coarsely, and much computation time can be saved. Because of the difficulty of finding a scoring function which is both highly discriminating for the correct configuration and also converges to the correct configuration from a distance, the use of two levels of refinement, with different scoring functions, has been proposed. Torsion can be introduced naturally to Monte Carlo as an additional property of each random move.
232:, the focus moved towards developing generalized techniques which could be applied to an arbitrary set of complexes at acceptable computational cost. The new methods were envisaged to apply even in the absence of phylogenetic or experimental clues; any specific prior knowledge could still be introduced at the stage of choosing between the highest ranking output models, or be framed as input if the algorithm catered for it. 1992 saw the publication of the correlation method, an algorithm which used the
514:
assessed. They are significant in most of the complexes, and large movements or disorder-to-order transitions are frequently observed. The set may be used to benchmark biophysical models aiming to relate affinity to structure in protein–protein interactions, taking into account the reactants and the conformation changes that accompany the association reaction, instead of just the final product.
267:. A subject of speculation is whether or not rigid-body docking is sufficiently good for most docking. When substantial conformational change occurs within the components at the time of complex formation, rigid-body docking is inadequate. However, scoring all possible conformational changes is prohibitively expensive in computer time. Docking procedures which permit conformational change, or
451:(R ~ 0). It was also observed that some components of the scoring algorithms may display better correlation to the experimental binding energies than the full score, suggesting that a significantly better performance might be obtained by combining the appropriate contributions from different scoring algorithms. Experimental methods for the determination of binding affinities are:
317:
clash, the remaining space of possible complexed structures must be sampled exhaustively, evenly and with a sufficient coverage to guarantee a near hit. Each configuration must be scored with a measure that is capable of ranking a nearly correct structure above at least 100,000 alternatives. This is
540:
CAPRI attracts a high level of participation (37 groups participated worldwide in round seven) and a high level of interest from the biological community in general. Although CAPRI results are of little statistical significance owing to the small number of targets in each round, the role of CAPRI in
513:
ranging between 10 and 10 M. Nine pairs of entries represent closely related complexes that have a similar structure, but a very different affinity, each pair comprising a cognate and a noncognate assembly. The unbound structures of the component proteins being available, conformation changes can be
508:
This
Benchmark was post-peer reviewed and significantly expanded. The new set is diverse in terms of the biological functions it represents, with complexes that involve G-proteins and receptor extracellular domains, as well as antigen/antibody, enzyme/inhibitor, and enzyme/substrate complexes. It is
377:
To find a score which forms a consistent basis for selecting the best configuration, studies are carried out on a standard benchmark (see below) of protein–protein interaction cases. Scoring functions are assessed on the rank they assign to the best structure (ideally the best structure should be
216:
complex. Computers discriminated between good and bad models using a scoring function which rewarded large interface area, and pairs of molecules in contact but not occupying the same space. The computer used a simplified representation of the interacting proteins, with one interaction centre for
827:
Strynadka NC, Eisenstein M, Katchalski-Katzir E, Shoichet BK, Kuntz ID, Abagyan R, Totrov M, Janin J, Cherfils J, Zimmerman F, Olson A, Duncan B, Rao M, Jackson R, Sternberg M, James MN (1996). "Molecular
Docking Programs Successfully Predict the Binding of a Beta-lactamase Inhibitory Protein to
337:
Reciprocal space methods have been used extensively for their ability to evaluate enormous numbers of configurations. They lose their speed advantage if torsional changes are introduced. Another drawback is that it is impossible to make efficient use of prior knowledge. The question also remains
68:
but keeping their relative orientations fixed. Later, the relative orientations of the interacting partners in the modelling was allowed to vary, but the internal geometry of each of the partners was held fixed. This type of modelling is sometimes referred to as "rigid docking". With further
479:
A benchmark of 84 protein–protein interactions with known complexed structures has been developed for testing docking methods. The set is chosen to cover a wide range of interaction types, and to avoid repeated features, such as the profile of interactors' structural families according to the
112:
proteins, and there is a desire to understand what, if any, anomalous protein–protein interactions a given mutation can cause. In the distant future, proteins may be designed to perform biological functions, and a determination of the potential interactions of such proteins will be essential.
199:
In the 1970s, complex modelling revolved around manually identifying features on the surfaces of the interactors, and interpreting the consequences for binding, function and activity; any computer programmes were typically used at the end of the modelling process, to discriminate between the
504:
A binding affinity benchmark has been based on the protein–protein docking benchmark. 81 protein–protein complexes with known experimental affinities are included; these complexes span over 11 orders of magnitude in terms of affinity. Each entry of the benchmark includes several biochemical
427:
It is usual to create hybrid scores by combining one or more categories above in a weighted sum whose weights are optimized on cases from the benchmark. To avoid bias, the benchmark cases used to optimize the weights must not overlap with the cases used to make the final test of the score.
528:
The
Critical Assessment of PRediction of Interactions is an ongoing series of events in which researchers throughout the community try to dock the same proteins, as provided by the assessors. Rounds take place approximately every 6 months. Each round contains between one and six target
56:
The ultimate goal of docking is the prediction of the three-dimensional structure of the macromolecular complex of interest as it would occur in a living organism. Docking itself only produces plausible candidate structures. These candidates must be ranked using methods such as
484:
database. Benchmark elements are classified into three levels of difficulty (the most difficult containing the largest change in backbone conformation). The protein–protein docking benchmark contains examples of enzyme-inhibitor, antigen-antibody and homomultimeric complexes.
447:). Several scoring functions have been proposed for binding affinity / free energy prediction. However the correlation between experimentally determined binding affinities and the predictions of nine commonly used scoring functions have been found to be nearly
488:
The latest version of protein-protein docking benchmark consists of 230 complexes. A protein-DNA docking benchmark consists of 47 test cases. A protein-RNA docking benchmark was curated as a dataset of 45 non-redundant test cases with complexes solved by
357:
Monte Carlo methods are not guaranteed to search exhaustively, so that the best configuration may be missed even using a scoring function which would in theory identify it. How severe a problem this is for docking has not been firmly established.
247:(BLIP). The exercise brought into focus the necessity of accommodating conformational change and the difficulty of discriminating between conformers. It also served as the prototype for the CAPRI assessment series, which debuted in 2001.
505:
parameters associated with the experimental data, along with the method used to determine the affinity. This benchmark was used to assess the extent to which scoring functions could also predict affinities of macromolecular complexes.
69:
increases in computational power, it became possible to model changes in internal geometry of the interacting partners that may occur when a complex is formed. This type of modelling is referred to as "flexible docking".
431:
The ultimate goal in protein–protein docking is to select the ideal ranking solution according to a scoring scheme that would also give an insight into the affinity of the complex. Such a development would drive
874:
Gray JJ, Moughon S, Wang C, Schueler-Furman O, Kuhlman B, Rohl CA, Baker D (2003). "Protein–protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations".
64:
The term "docking" originated in the late 1970s, with a more restricted meaning; then, "docking" meant refining a model of a complex structure by optimizing the separation between the
1747:
529:
protein–protein complexes whose structures have been recently determined experimentally. The coordinates and are held privately by the assessors, with the cooperation of the
523:
1100:
Kastritis PL, Bonvin AM (May 2010). "Are scoring functions in protein–protein docking ready to predict interactomes? Clues from a novel binding affinity benchmark".
1380:
PĂ©rez-Cano L, JimĂ©nez-GarcĂa B, Fernández-Recio J (July 2012). "A protein-RNA docking benchmark (II): extended set from experimental and homology modeling data".
236:
to give a vastly improved scalability for evaluating coarse shape complementarity on rigid-body models. This was extended in 1997 to cover coarse electrostatics.
1239:
Vreven T, Moal IH, Vangone A, Pierce BG, Kastritis PL, Torchala M, Chaleil R, JimĂ©nez-GarcĂa B, Bates PA, Fernandez-Recio J, Bonvin AM, Weng Z (September 2015).
579:
Yousif, Ragheed Hussam, et al. "Exploring the
Molecular Interactions between Neoculin and the Human Sweet Taste Receptors through Computational Approaches."
1800:
792:
Gabb HA, Jackson RM, Sternberg MJ (September 1997). "Modelling protein docking using shape complementarity, electrostatics and biochemical information".
471:(MST) or spectroscopic measurements and other fluorescence techniques. Textual information from scientific articles can provide useful cues for scoring.
334:. It is possible to construct reasonable, if approximate, convolution-like scoring functions representing both stereochemical and electrostatic fitness.
330:, configurations related to each other by translation of one protein by an exact lattice vector can all be scored almost simultaneously by applying the
378:
ranked 1), and on their coverage (the proportion of the benchmark cases for which they achieve an acceptable result). Types of scores studied include:
228:
In the early 1990s, more structures of complexes were determined, and available computational power had increased substantially. With the emergence of
1639:
1887:
1569:
Janin J, Henrick K, Moult J, Eyck LT, Sternberg MJ, Vajda S, Vakser I, Wodak SJ (2003). "CAPRI: a
Critical Assessment of PRedicted Interactions".
350:, an initial configuration is refined by taking random steps which are accepted or rejected based on their induced improvement in score (see the
200:
relatively few configurations which remained after all the heuristic constraints had been imposed. The first use of computers was in a study on
157:
principles, even proteins of unknown function (or which have been studied relatively little) may be docked. The only prerequisite is that their
1882:
191:
they interact with is composed of nucleic acids. Modeling protein–nucleic acid complexes presents some unique challenges, as described below.
481:
1011:
Zhang C, Liu S, Zhu Q, Zhou Y (2005). "A knowledge-based energy function for protein–ligand, protein–protein, and protein–DNA complexes".
456:
239:
In 1996 the results of the first blind trial were published, in which six research groups attempted to predict the complexed structure of
153:
Protein–protein docking is ultimately envisaged to address all these issues. Furthermore, since docking methods can be based on purely
116:
For any given set of proteins, the following questions may be of interest, from the point of view of technology or natural history:
1737:
1717:
464:
1241:"Updates to the Integrated Protein-Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2"
1196:
Mintseris J, Wiehe K, Pierce B, Anderson R, Chen R, Janin J, Weng Z (2005). "Protein-Protein
Docking Benchmark 2.0: an update".
82:
1698:
735:"Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques"
1727:
1632:
372:
351:
58:
1923:
1775:
654:
162:
34:
1874:
1780:
1708:
1466:
Nithin, Chandran; Ghosh, Pritha; Bujnicki, Janusz; Nithin, Chandran; Ghosh, Pritha; Bujnicki, Janusz M. (2018-08-25).
1468:"Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes"
326:
Each of the proteins may be represented as a simple cubic lattice. Then, for the class of scores which are discrete
1918:
1908:
440:
290:
For many interactions, the binding site is known on one or more of the proteins to be docked. This is the case for
1732:
1722:
1712:
1674:
468:
452:
1423:
Nithin C, Mukherjee S, Bahadur RP (November 2016). "A non-redundant protein-RNA docking benchmark version 2.0".
1752:
1625:
1913:
403:
393:
1823:
1578:
962:"In silico screening of mutational effects on enzyme-proteic inhibitor affinity: a docking-based approach"
233:
271:
procedures, must intelligently select small subset of possible conformational changes for consideration.
1742:
498:
490:
338:
whether convolutions are too limited a class of scoring function to identify the best complex reliably.
295:
169:
1337:
Barik A, C N, P M, Bahadur RP (July 2012). "A protein-RNA docking benchmark (I): nonredundant cases".
1790:
1669:
746:
606:
554:
1583:
595:"Hemoglobin Interactions in Sickle Cell Fibers: I. Theoretical Approaches to the Molecular Contacts"
1757:
1703:
1694:
560:
436:
400:
331:
158:
38:
49:–protein complexes are the most commonly attempted targets of such modelling, followed by protein–
1689:
1604:
1448:
1405:
1362:
1221:
853:
530:
347:
260:
94:
86:
501:
and now it consists of 126 test cases. The benchmarks have a combined dataset of 209 complexes.
1844:
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1319:
1270:
1213:
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993:
942:
891:
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809:
774:
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671:
634:
494:
244:
1859:
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1346:
1309:
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1260:
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1117:
1109:
1069:
1059:
1020:
983:
973:
932:
922:
883:
837:
801:
764:
754:
702:
663:
624:
614:
188:
283:
Generating a set of configurations which reliably includes at least one nearly correct one.
1828:
1652:
314:
306:
evidence. Configurations where the proteins interpenetrate severely may also be ruled out
184:
173:
105:
101:
1147:"Natural language processing in text mining for structural modeling of protein complexes"
497:
as well. The protein-RNA benchmark has been updated to include more structures solved by
85:, are known at best incompletely. Even those proteins that participate in a well-studied
750:
610:
1767:
1684:
1546:
1521:
1494:
1467:
1314:
1289:
1265:
1240:
1173:
1146:
1074:
1047:
988:
961:
240:
229:
222:
17:
887:
629:
594:
557:– any biological complex of protein, RNA, DNA (sometimes has lipids and carbohydrates)
263:
of the components are not modified at any stage of complex generation, it is known as
1902:
1864:
1854:
1795:
937:
910:
769:
734:
733:
Katchalski-Katzir E, Shariv I, Eisenstein M, Friesem AA, Aflalo C, Vakser IA (1992).
707:
690:
667:
218:
42:
1608:
1452:
1409:
1225:
857:
1849:
1818:
1679:
1520:
Kastritis PL, Moal IH, Hwang H, Weng Z, Bates PA, Bonvin AM, Janin J (March 2011).
534:
318:
a computationally intensive task, and a variety of strategies have been developed.
50:
1366:
493:
only as well as an extended dataset of 71 test cases with structures derived from
1617:
545:
assessment is a similar exercise in the field of protein structure prediction).
460:
444:
327:
299:
205:
135:
90:
652:
Wodak SJ, Janin J (1978). "Computer
Analysis of Protein-Protein Interactions".
443:
and/or high-throughput annotation of which proteins bind or not (annotation of
1661:
1256:
1163:
448:
386:
201:
177:
65:
1064:
382:
303:
181:
1600:
1555:
1503:
1444:
1401:
1358:
1323:
1274:
1217:
1182:
1131:
1083:
1032:
997:
978:
946:
927:
895:
805:
759:
619:
849:
813:
778:
716:
638:
168:
Protein–nucleic acid interactions feature prominently in the living cell.
1484:
1305:
675:
291:
109:
841:
1648:
1592:
1436:
1393:
1350:
1209:
1122:
209:
154:
122:
100:
In cases of known protein–protein interactions, other questions arise.
78:
46:
1113:
1024:
509:
also diverse in terms of the partners' affinity for each other, with K
286:
Reliably distinguishing nearly correct configurations from the others.
407:
1537:
161:
has been either determined experimentally, or can be estimated by a
1810:
1522:"A structure-based benchmark for protein-protein binding affinity"
1048:"Scoring docking conformations using predicted protein interfaces"
411:
542:
213:
61:
to identify structures that are most likely to occur in nature.
1621:
298:. In other cases, a binding site may be strongly suggested by
134:
What is the spatial configuration which they adopt in their
691:"Computer Studies of Interactions between Macromolecules"
81:
roles of most proteins, as characterized by which other
533:
who determined them. The assessment of submissions is
593:
Levinthal C, Wodak SJ, Kahn P, Dadivanian AK (1975).
417:
Phylogenetic desirability of the interacting regions.
313:
After making exclusions based on prior knowledge or
1873:
1837:
1809:
1766:
1660:
911:"Protein docking along smooth association pathways"
524:Critical Assessment of PRediction of Interactions
208:fibres. This was followed in 1978 by work on the
149:Can they be made to bind by inducing a mutation?
1515:
1513:
1095:
1093:
915:Proceedings of the National Academy of Sciences
599:Proceedings of the National Academy of Sciences
399:Free energies, estimated using parameters from
27:Computational modeling of molecular interaction
869:
867:
93:) may have unexpected interaction partners or
1633:
1145:Badal, VD, Kundrotas, PJ, Vakser, IA (2018).
728:
726:
8:
695:Progress in Biophysics and Molecular Biology
689:Wodak SJ, De Crombrugghe M, Janin J (1987).
261:bond angles, bond lengths and torsion angles
541:stimulating discourse is significant. (The
1640:
1626:
1618:
279:Successful docking requires two criteria:
1582:
1545:
1493:
1483:
1313:
1264:
1172:
1162:
1121:
1073:
1063:
987:
977:
936:
926:
830:Nature Structural & Molecular Biology
768:
758:
706:
628:
618:
108:) are known to be caused by misfolded or
141:How strong or weak is their interaction?
572:
1883:Photoactivated localization microscopy
1801:Protein–protein interaction prediction
33:is the computational modelling of the
1288:van Dijk M, Bonvin AM (August 2008).
97:which are unrelated to that process.
7:
563:– small molecule docking to proteins
187:, are composed of proteins, and the
1758:Freeze-fracture electron microscopy
41:formed by two or more interacting
25:
1290:"A protein-DNA docking benchmark"
1046:Esmaielbeiki R, Nebel JC (2014).
457:Förster resonance energy transfer
83:macromolecules they interact with
1738:Isothermal titration calorimetry
1718:Dual-polarization interferometry
465:isothermal titration calorimetry
1013:Journal of Medicinal Chemistry
1:
1728:Chromatin immunoprecipitation
888:10.1016/S0022-2836(03)00670-3
373:Scoring functions for docking
1791:Protein structural alignment
1776:Protein structure prediction
1245:Journal of Molecular Biology
960:Camacho CJ, Vajda S (2007).
909:Camacho CJ, Vajda S (2008).
739:Proc. Natl. Acad. Sci. U.S.A
708:10.1016/0079-6107(87)90008-3
668:10.1016/0022-2836(78)90302-9
655:Journal of Molecular Biology
163:protein structure prediction
1875:Super-resolution microscopy
1781:Protein function prediction
1709:Peptide mass fingerprinting
1704:Protein immunoprecipitation
225:, were identified by hand.
1940:
521:
441:computer-aided drug design
370:
1733:Surface plasmon resonance
1723:Microscale thermophoresis
1713:Protein mass spectrometry
1675:Green fluorescent protein
1257:10.1016/j.jmb.2015.07.016
1164:10.1186/s12859-018-2079-4
469:microscale thermophoresis
453:surface plasmon resonance
392:Shape complementarity of
43:biological macromolecules
1753:Cryo-electron microscopy
1065:10.1186/1471-2105-15-171
420:Clustering coefficients.
322:Reciprocal space methods
221:interactions, including
217:each residue. Favorable
1786:Protein–protein docking
1699:Protein electrophoresis
828:TEM-1 Beta-Lactamase".
423:Information based cues.
120:Do these proteins bind
18:Protein–protein docking
1685:Protein immunostaining
1294:Nucleic Acids Research
979:10.1186/1472-6807-7-37
966:BMC Structural Biology
928:10.1073/pnas.181147798
806:10.1006/jmbi.1997.1203
760:10.1073/pnas.89.6.2195
620:10.1073/pnas.72.4.1330
296:competitive inhibitors
234:fast Fourier transform
31:Macromolecular docking
1743:X-ray crystallography
583:49.3 (2020): 517-525.
531:structural biologists
499:X-ray crystallography
491:X-ray crystallography
170:Transcription factors
145:If they do not bind,
1670:Protein purification
1485:10.3390/genes9090432
555:Biomolecular complex
518:The CAPRI assessment
396:("stereochemistry").
352:Metropolis criterion
243:with Beta-lactamase
241:TEM-1 Beta-lactamase
35:quaternary structure
1924:Molecular modelling
1695:Gel electrophoresis
921:(19): 10636–10641.
842:10.1038/nsb0396-233
751:1992PNAS...89.2195K
611:1975PNAS...72.1330L
561:Docking (molecular)
463:-based techniques,
437:protein engineering
401:molecular mechanics
342:Monte Carlo methods
332:convolution theorem
251:Rigid-body docking
159:molecular structure
1838:Display techniques
1690:Protein sequencing
1593:10.1002/prot.10381
1437:10.1002/prot.25211
1394:10.1002/prot.24075
1351:10.1002/prot.24083
1306:10.1093/nar/gkn386
1210:10.1002/prot.20560
1151:BMC Bioinformatics
1052:BMC Bioinformatics
495:homology modelling
394:molecular surfaces
265:rigid body docking
255:. flexible docking
87:biological process
1919:Molecular physics
1909:Protein structure
1896:
1895:
1845:Bacterial display
1114:10.1021/pr9009854
1025:10.1021/jm049314d
367:Scoring functions
245:inhibitor protein
172:, which regulate
130:If they do bind,
59:scoring functions
16:(Redirected from
1931:
1860:Ribosome display
1796:Protein ontology
1642:
1635:
1628:
1619:
1613:
1612:
1586:
1566:
1560:
1559:
1549:
1517:
1508:
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1420:
1414:
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1370:
1334:
1328:
1327:
1317:
1285:
1279:
1278:
1268:
1236:
1230:
1229:
1193:
1187:
1186:
1176:
1166:
1142:
1136:
1135:
1125:
1108:(5): 2216–2225.
1097:
1088:
1087:
1077:
1067:
1043:
1037:
1036:
1019:(7): 2325–2335.
1008:
1002:
1001:
991:
981:
957:
951:
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930:
906:
900:
899:
871:
862:
861:
824:
818:
817:
789:
783:
782:
772:
762:
745:(6): 2195–2199.
730:
721:
720:
710:
686:
680:
679:
649:
643:
642:
632:
622:
605:(4): 1330–1334.
590:
584:
581:Sains Malaysiana
577:
385:scores based on
269:flexible docking
189:genetic material
102:Genetic diseases
21:
1939:
1938:
1934:
1933:
1932:
1930:
1929:
1928:
1899:
1898:
1897:
1892:
1869:
1833:
1829:Secretion assay
1805:
1762:
1656:
1646:
1616:
1584:10.1.1.461.3355
1568:
1567:
1563:
1538:10.1002/pro.580
1526:Protein Science
1519:
1518:
1511:
1465:
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1422:
1421:
1417:
1379:
1378:
1374:
1336:
1335:
1331:
1287:
1286:
1282:
1251:(19): 3031–41.
1238:
1237:
1233:
1195:
1194:
1190:
1144:
1143:
1139:
1102:J. Proteome Res
1099:
1098:
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1045:
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724:
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551:
526:
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477:
375:
369:
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344:
324:
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204:interaction in
197:
174:gene expression
106:cystic fibrosis
75:
28:
23:
22:
15:
12:
11:
5:
1937:
1935:
1927:
1926:
1921:
1916:
1914:Bioinformatics
1911:
1901:
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1768:Bioinformatics
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1760:
1755:
1750:
1745:
1740:
1735:
1730:
1725:
1720:
1715:
1706:
1701:
1692:
1687:
1682:
1677:
1672:
1666:
1664:
1658:
1657:
1647:
1645:
1644:
1637:
1630:
1622:
1615:
1614:
1561:
1532:(3): 482–491.
1509:
1458:
1431:(2): 256–267.
1415:
1388:(7): 1872–82.
1372:
1345:(7): 1866–71.
1329:
1280:
1231:
1204:(2): 214–216.
1188:
1137:
1089:
1038:
1003:
952:
901:
882:(1): 281–299.
863:
836:(3): 233–239.
819:
800:(1): 106–120.
784:
722:
681:
662:(2): 323–342.
644:
585:
571:
569:
566:
565:
564:
558:
550:
547:
522:Main article:
519:
516:
510:
476:
473:
425:
424:
421:
418:
415:
397:
390:
371:Main article:
368:
365:
363:
360:
343:
340:
323:
320:
315:stereochemical
288:
287:
284:
276:
273:
256:
249:
230:bioinformatics
223:hydrogen bonds
196:
193:
151:
150:
143:
142:
139:
128:
127:
74:
71:
26:
24:
14:
13:
10:
9:
6:
4:
3:
2:
1936:
1925:
1922:
1920:
1917:
1915:
1912:
1910:
1907:
1906:
1904:
1889:
1886:
1884:
1881:
1880:
1878:
1876:
1872:
1866:
1865:Yeast display
1863:
1861:
1858:
1856:
1855:Phage display
1853:
1851:
1848:
1846:
1843:
1842:
1840:
1836:
1830:
1827:
1825:
1824:Protein assay
1822:
1820:
1817:
1816:
1814:
1812:
1808:
1802:
1799:
1797:
1794:
1792:
1789:
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1779:
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1696:
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1678:
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1668:
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1598:
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1576:
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1565:
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1505:
1501:
1496:
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1477:
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1459:
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1426:
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1411:
1407:
1403:
1399:
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1391:
1387:
1383:
1376:
1373:
1368:
1364:
1360:
1356:
1352:
1348:
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1333:
1330:
1325:
1321:
1316:
1311:
1307:
1303:
1299:
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1291:
1284:
1281:
1276:
1272:
1267:
1262:
1258:
1254:
1250:
1246:
1242:
1235:
1232:
1227:
1223:
1219:
1215:
1211:
1207:
1203:
1199:
1192:
1189:
1184:
1180:
1175:
1170:
1165:
1160:
1156:
1152:
1148:
1141:
1138:
1133:
1129:
1124:
1119:
1115:
1111:
1107:
1103:
1096:
1094:
1090:
1085:
1081:
1076:
1071:
1066:
1061:
1057:
1053:
1049:
1042:
1039:
1034:
1030:
1026:
1022:
1018:
1014:
1007:
1004:
999:
995:
990:
985:
980:
975:
971:
967:
963:
956:
953:
948:
944:
939:
934:
929:
924:
920:
916:
912:
905:
902:
897:
893:
889:
885:
881:
877:
870:
868:
864:
859:
855:
851:
847:
843:
839:
835:
831:
823:
820:
815:
811:
807:
803:
799:
795:
788:
785:
780:
776:
771:
766:
761:
756:
752:
748:
744:
740:
736:
729:
727:
723:
718:
714:
709:
704:
700:
696:
692:
685:
682:
677:
673:
669:
665:
661:
657:
656:
648:
645:
640:
636:
631:
626:
621:
616:
612:
608:
604:
600:
596:
589:
586:
582:
576:
573:
567:
562:
559:
556:
553:
552:
548:
546:
544:
538:
536:
532:
525:
517:
515:
506:
502:
500:
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492:
486:
483:
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472:
470:
466:
462:
458:
454:
450:
446:
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438:
435:
429:
422:
419:
416:
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405:
402:
398:
395:
391:
388:
384:
381:
380:
379:
374:
366:
361:
359:
355:
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349:
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329:
321:
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316:
311:
309:
305:
301:
297:
293:
285:
282:
281:
280:
274:
272:
270:
266:
262:
254:
250:
248:
246:
242:
237:
235:
231:
226:
224:
220:
219:electrostatic
215:
211:
207:
203:
194:
192:
190:
186:
183:
179:
175:
171:
166:
164:
160:
156:
148:
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140:
137:
133:
132:
131:
125:
124:
119:
118:
117:
114:
111:
107:
103:
98:
96:
92:
88:
84:
80:
72:
70:
67:
62:
60:
54:
52:
48:
44:
40:
36:
32:
19:
1850:mRNA display
1819:Enzyme assay
1785:
1680:Western blot
1662:Experimental
1574:
1570:
1564:
1529:
1525:
1475:
1471:
1461:
1428:
1424:
1418:
1385:
1381:
1375:
1342:
1338:
1332:
1297:
1293:
1283:
1248:
1244:
1234:
1201:
1197:
1191:
1154:
1150:
1140:
1105:
1101:
1055:
1051:
1041:
1016:
1012:
1006:
969:
965:
955:
918:
914:
904:
879:
876:J. Mol. Biol
875:
833:
829:
822:
797:
794:J. Mol. Biol
793:
787:
742:
738:
701:(1): 29–63.
698:
694:
684:
659:
653:
647:
602:
598:
588:
580:
575:
539:
535:double blind
527:
507:
503:
487:
478:
433:
430:
426:
404:force fields
376:
356:
345:
336:
328:convolutions
325:
312:
307:
304:phylogenetic
289:
278:
268:
264:
258:
252:
238:
227:
198:
167:
152:
144:
129:
121:
115:
99:
76:
63:
55:
51:nucleic acid
30:
29:
1888:Vertico SMI
1748:Protein NMR
1300:(14): e88.
1123:1874/202590
461:radioligand
445:interactome
348:Monte Carlo
206:sickle-cell
185:replication
178:polymerases
165:technique.
136:bound state
91:Krebs cycle
89:(e.g., the
66:interactors
53:complexes.
1903:Categories
1577:(1): 2–9.
1478:(9): 432.
568:References
475:Benchmarks
449:orthogonal
362:Evaluation
292:antibodies
202:hemoglobin
79:biological
73:Background
1579:CiteSeerX
1157:(1): 84.
434:in silico
389:contacts.
383:Heuristic
300:mutagenic
95:functions
39:complexes
1655:of study
1649:Proteins
1609:31489448
1601:12784359
1571:Proteins
1556:21213247
1504:30149645
1453:26814049
1445:27862282
1425:Proteins
1410:20322388
1402:22488990
1382:Proteins
1359:22488669
1339:Proteins
1324:18583363
1275:26231283
1226:24049376
1218:15981264
1198:Proteins
1183:29506465
1132:20329755
1084:24906633
1033:15801826
998:17559675
947:11517309
896:12875852
858:40212654
549:See also
455:(SPR),
406:such as
308:a priori
294:and for
182:catalyse
180:, which
155:physical
1653:methods
1547:3064828
1495:6162694
1315:2504314
1266:4677049
1174:5838950
1075:4057934
1058:: 171.
989:1913526
850:8605624
814:9299341
779:1549581
747:Bibcode
717:3310103
639:1055409
607:Bibcode
467:(ITC),
387:residue
275:Methods
259:If the
210:trypsin
195:History
123:in vivo
110:mutated
104:(e.g.,
47:Protein
1651:: key
1607:
1599:
1581:
1554:
1544:
1502:
1492:
1451:
1443:
1408:
1400:
1367:437472
1365:
1357:
1322:
1312:
1273:
1263:
1224:
1216:
1181:
1171:
1130:
1082:
1072:
1031:
996:
986:
972:: 37.
945:
935:
894:
856:
848:
812:
777:
767:
715:
676:712840
674:
637:
630:432527
627:
408:CHARMM
176:, and
1811:Assay
1605:S2CID
1472:Genes
1449:S2CID
1406:S2CID
1363:S2CID
1222:S2CID
938:58518
854:S2CID
770:48623
412:AMBER
1597:PMID
1552:PMID
1500:PMID
1441:PMID
1398:PMID
1355:PMID
1320:PMID
1271:PMID
1214:PMID
1179:PMID
1128:PMID
1080:PMID
1029:PMID
994:PMID
943:PMID
892:PMID
846:PMID
810:PMID
775:PMID
713:PMID
672:PMID
635:PMID
543:CASP
482:SCOP
214:BPTI
77:The
1589:doi
1542:PMC
1534:doi
1490:PMC
1480:doi
1433:doi
1390:doi
1347:doi
1310:PMC
1302:doi
1261:PMC
1253:doi
1249:427
1206:doi
1169:PMC
1159:doi
1118:hdl
1110:doi
1070:PMC
1060:doi
1021:doi
984:PMC
974:doi
933:PMC
923:doi
884:doi
880:331
838:doi
802:doi
798:272
765:PMC
755:doi
703:doi
664:doi
660:124
625:PMC
615:doi
410:or
346:In
302:or
37:of
1905::
1603:.
1595:.
1587:.
1575:52
1573:.
1550:.
1540:.
1530:20
1528:.
1524:.
1512:^
1498:.
1488:.
1474:.
1470:.
1447:.
1439:.
1429:85
1427:.
1404:.
1396:.
1386:80
1384:.
1361:.
1353:.
1343:80
1341:.
1318:.
1308:.
1298:36
1296:.
1292:.
1269:.
1259:.
1247:.
1243:.
1220:.
1212:.
1202:60
1200:.
1177:.
1167:.
1155:19
1153:.
1149:.
1126:.
1116:.
1104:.
1092:^
1078:.
1068:.
1056:15
1054:.
1050:.
1027:.
1017:48
1015:.
992:.
982:.
968:.
964:.
941:.
931:.
919:98
917:.
913:.
890:.
878:.
866:^
852:.
844:.
832:.
808:.
796:.
773:.
763:.
753:.
743:89
741:.
737:.
725:^
711:.
699:49
697:.
693:.
670:.
658:.
633:.
623:.
613:.
603:72
601:.
597:.
537:.
459:,
439:,
310:.
253:vs
45:.
1711:/
1697:/
1641:e
1634:t
1627:v
1611:.
1591::
1558:.
1536::
1506:.
1482::
1476:9
1455:.
1435::
1412:.
1392::
1369:.
1349::
1326:.
1304::
1277:.
1255::
1228:.
1208::
1185:.
1161::
1134:.
1120::
1112::
1106:9
1086:.
1062::
1035:.
1023::
1000:.
976::
970:7
949:.
925::
898:.
886::
860:.
840::
834:3
816:.
804::
781:.
757::
749::
719:.
705::
678:.
666::
641:.
617::
609::
511:d
414:.
212:-
138:?
126:?
20:)
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