234:
same as in
Precambrian biology, resulting in skewed sequence inference. Several studies have attempted to construct ancient scoring matrices via various methodologies and have compared the resultant sequences and their protein's biophysical properties. While these modified sequences result in somewhat different ASR sequences, the observed biophysical properties did not seem to vary outside from experimental error. Because of the 'holistic' nature of ASR and the intense complexity that arises when one considers all the possible sources of experimental error β the experimental community considers the ultimate measurement of ASR reliability to be the comparison of several alternate ASR reconstructions of the same node and the identification of similar biophysical properties. While this method does not offer a robust statistical, mathematical measure of reliability it does build off of the fundamental idea used in ASR that individual amino acid substitutions do not cause significant biophysical property changes in a protein β a tenant that must be held true in order to be able to overcome the effect of inference ambiguity.
202:' model of protein evolution, whereby at evolutionary junctions (nodes) a population of genotypically different but phenotypically similar protein sequences existed in the extant organismal population. Hence, it is possible that ASR would generate one of the sequences of a node's neutral network and while it may not represent the genotype of the last common ancestor of the modern day sequences, it does likely represent the phenotype. This is supported by the modern day observation that many mutations in a protein's non-catalytic/functional site cause minor changes in biophysical properties. Hence, ASR allows one to probe the biophysical properties of past proteins and is indicative of ancient genetics.
230:
predicted β often in these cases, several ASR sequences are produced, encompassing most of the ambiguities and compared to one-another. ML ASR often needs complementing experiments to indicate that the derived sequences are more than just consensuses of the input sequences. This is particularly necessary in the observation of 'Ancestral
Superiority'. In the trend of increasing thermostability, one explanation is that ML ASR creates a consensus sequence of several different, parallel mechanisms evolved to confer minor protein thermostability throughout the phylogeny β leading to an additive effect resulting in 'superior' ancestral thermostability.
328:) and while these clocks offer the only method of inferring a very ancient protein's age, they have sweeping error margins and are difficult to defend against contrary data. To this end, ASR 'age' should really be only used as an indicative feature and is often surpassed altogether for a measurement of the number of substitutions between the ancestral and the modern sequences (the fundament on which the clock is calculated). That being said, the use of a clock allows one to compare observed biophysical data of an ASR protein to the geological or ecological environment at the time. For example, ASR studies on bacterial
141:, and have revealed ancestral protein properties that seem to be evolutionarily desirable traits β such as increased thermostability, catalytic activity and catalytic promiscuity. These data have been accredited to artifacts of the ASR algorithms, as well as indicative illustrations of ancient Earth's environment β often, ASR research must be complemented with extensive controls (usually alternate ASR experiments) to mitigate algorithmic error. Not all studied ASR proteins exhibit this so-called 'ancestral superiority'. The nascent field of '
198:
bacteria are basal or derivative in bacterial evolution β many ASR papers construct several phylogenies with differing topologies and hence differing ASR sequences. These sequences are then compared and often several (~10) are expressed and studied per phylogenetic node. ASR does not claim to recreate the actual sequence of the ancient protein/DNA, but rather a sequence that is likely to be similar to the one that was indeed at the node. This is not considered a shortcoming of ASR as it fits into the '
90:
243:
changes between '5' and '2' may illustrate the precise biophysical explanation for this difference. As ASR experiments can extract ancestors that are likely billions of years old, there are often tens if not hundreds of sequence changes between ancestors themselves and ancestors and extant sequences β because of this, such sequence-function evolutionary studies can take a lot of work and rational direction.
73:, showing the potential of this technique. Thanks to the improvement of algorithms and of better sequencing and synthesis techniques, the method was developed further in the early 2000s to allow the resurrection of a greater variety of and much more ancient genes. Over the last decade, ancestral protein resurrection has developed as a strategy to reveal the mechanisms and dynamics of protein evolution.
82:
189:' is constructed with statistically inferred sequences at the nodes of the branches. It is these sequences that are the so-called 'ancestors' β the process of synthesizing the corresponding DNA, transforming it into a cell and producing a protein is the so-called 'reconstruction'. Ancestral sequences are typically calculated by
376:
enzymes from up to 4 billion year old organisms. Whereas the chemical activity of these reconstructed enzymes were remarkably similar to modern enzymes, their physical properties showed significantly elevated thermal and acidic stability. These results were interpreted as suggesting that ancient life
431:
who often desire these traits (producing effects sometimes greater than current, rationally lead tools). ASR also promises to 'resurrect' phenotypically similar 'ancient organisms' which in turn would allow evolutionary biochemists to probe the story of life. Proponents of ASR such as Benner state
242:
a protein family, ASR can be used to probe the specific sequence changes that conferred the observed biophysical effect β such as stabilising interactions. Consider in the diagram, if sequence 'A' encoded a protein that was optimally functional at neutral pHs and 'D' in acidic conditions, sequence
197:
methods are also implemented. Because the ancestors are inferred from a phylogeny, the topology and composition of the phylogeny plays a major role in the output ASR sequences. Given that there is much discourse and debate over how to construct phylogenies β for example whether or not thermophilic
93:
Algorithm to reconstruct ancestral sequences 1,2, and 3 (referring to figure above). The ancestral sequence of sequence 1 can be reconstructed from B and C, as long as at least one outgroup is available, e.g. D or E. For example, sequences B and C are different in position 4, but since sequences D
233:
The expression of consensus sequences and parallel ASR via non-ML methods are often required to disband this theory per experiment. One other concern raised by ML methods is that the scoring matrices are derived from modern sequences and particular amino acid frequencies seen today may not be the
229:
Another method involves the consideration of residue uncertainty β so-called
Bayesian methods β this form of ASR is sometimes used to complement ML methods but typically produces more ambiguous sequences. In ASR, the term 'ambiguity' refers to residue positions where no clear substitution can be
423:
shows that at the level of interaction between single amino acid residues and chemical groups of the hormones arise by very small but specific changes. Knowledge about these changes may for example lead to the synthesis of hormonal equivalents capable of mimicking or inhibiting the action of a
149:. Due to inherent limitations in these sorts of studies β primarily being the lack of suitably ancient genomes to fit these ancestors in to, the small repertoire of well categorized laboratory model systems, and the inability to mimic ancient cellular environments; very few ASR studies
418:
and made the changes to the receptor irreversible. These different experiments on receptors show that, during their evolution, proteins are greatly differentiated and this explains how complexity may evolve. A closer look at the different ancestral hormone receptors and the various
237:
Candidates used for ASR are often selected based on the particular property of interest being studied β e.g. thermostability. By selecting sequences from either end of a property's range (e.g., psychrophilic proteins and thermophilic proteins) but
126:, ASR has also been used to study the development of a protein's thermodynamic and kinetic landscapes over evolutionary time as well as protein folding pathways by combining many modern day analytical techniques such as
205:
Maximum likelihood (ML) methods work by generating a sequence where the residue at each position is predicted to be the most likely to occupy said position by the method of inference used β typically this is a
409:
plays a major role in protein evolution β an observation that in combination with the observations of several examples of parallel evolution, support the neutral network model mentioned above. Other earlier
432:
that through these and other experiments, the end of the current century will see a level of understanding in biology analogous to the one that arose in classical chemistry in the last century.
114:
manner (see diagram, right). This approach gives access to protein properties that may have transiently arisen over evolutionary time and has recently been used as a way to infer the potential
94:
and E have a C in that position, sequence 1 most likely had a C as well. Sequence 3 cannot be completely reconstructed without an additional outgroup sequence (uncertainty indicated by an "X").
887:
Hobbs JK, Prentice EJ, Groussin M, Arcus VL (October 2015). "Reconstructed
Ancestral Enzymes Impose a Fitness Cost upon Modern Bacteria Despite Exhibiting Favorable Biochemical Properties".
226:
is the most likely. MP is often considered the least reliable method for reconstruction as it arguably oversimplifies evolution to a degree that is not applicable on the billion year scale.
145:' has been bolstered by the recent increase in ASR studies using the ancestors as ways to probe organismal fitness within certain cellular contexts β effectively testing ancestral proteins
1457:
Risso VA, Gavira JA, Mejia-Carmona DF, Gaucher EA, Sanchez-Ruiz JM (February 2013). "Hyperstability and substrate promiscuity in laboratory resurrections of
Precambrian Ξ²-lactamases".
251:
There are many examples of ancestral proteins that have been computationally reconstructed, expressed in living cell lines, and β in many cases β purified and biochemically studied.
153:
have been conducted. Despite the above mentioned obstacles, preliminary insights into this avenue of research from a 2015 paper, have revealed that observed 'ancestral superiority'
122:
after duplication by first determining that said mutation was located between ancestors '5' and '4' on the diagram (illustratively) using functional assays. In the field of protein
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occurred before the earliest molecular fossils indicate (>4.1Ga), but given the debatable reliability of molecular clocks, such observations should be taken with caution.
401:. Thus very small changes at the molecular level may have enormous consequences. The Thornton lab has also been able to show that evolution is irreversible studying the
397:
in the amino acid sequence of hormone receptors determine an important change in their preferences for hormones. These changes mean huge steps in the evolution of the
130:. These sort of insights are typically inferred from several ancestors reconstructed along a phylogeny β referring to the previous analogy, by studying nodes
405:. This receptor was changed by seven mutations in a cortisol receptor, but reversing these mutations didn't give the original receptor back. Indicating that
344:~2C greater than Tenv) indicate a hotter Precambrian Earth which fits very closely with geological data on ancient earth ocean temperatures based on
324:
model, and often several are employed. This dating technique is often calibrated using geological time-points (such as ancient ocean constituents or
519:
Jermann TM, Opitz JG, Stackhouse J, Benner SA (March 1995). "Reconstructing the evolutionary history of the artiodactyl ribonuclease superfamily".
1058:
1068:
222:β usually the idea that the minimum number of nucleotidal sequence changes represents the most efficient route for evolution to take and by
999:
Gaucher EA, Govindarajan S, Ganesh OK (February 2008). "Palaeotemperature trend for
Precambrian life inferred from resurrected proteins".
1408:"Reconstruction of ancestral metabolic enzymes reveals molecular mechanisms underlying evolutionary innovation through gene duplication"
390:
1566:"A genomic timescale of prokaryote evolution: insights into the origin of methanogenesis, phototrophy, and the colonization of land"
573:
Thornton JW, Need E, Crews D (September 2003). "Resurrecting the ancestral steroid receptor: ancient origin of estrogen signaling".
215:
427:
Given that ASR has revealed a tendency towards ancient thermostability and enzymatic promiscuity, ASR poses as a valuable tool for
173:'; indeed Zuckerkandl and Pauling originally intended ASR to be the starting point of a field they termed 'Paleobiochemistry'.
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1802:
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that resulted in present-day sequences. ASR has been used to probe the causative mutation that resulted in a protein's
341:
199:
182:
51:
1797:
1680:
Perez-Jimenez R, InglΓ©s-Prieto A, Zhao ZM, Sanchez-Romero I, Alegre-Cebollada J, Kosuri P, et al. (May 2011).
668:
Anderson DP, Whitney DS, Hanson-Smith V, Woznica A, Campodonico-Burnett W, Volkman BF, et al. (January 2016).
352:
Adhs for ethanol metabolism (not just waste excretion) arose at a time similar to the dawn of fleshy fruit in the
127:
1083:
337:
402:
219:
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69:(British: palaeoenzymology). Some early efforts were made in the 1980s and 1990s, led by the laboratory of
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107:
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333:
325:
302:
294:
211:
115:
951:
Risso VA, Gavira JA, Sanchez-Ruiz JM (June 2014). "Thermostable and promiscuous
Precambrian proteins".
89:
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194:
119:
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Unlike conventional evolutionary and biochemical approaches to studying proteins, i.e. the so-called
428:
47:
452:
Thornton JW (May 2004). "Resurrecting ancient genes: experimental analysis of extinct molecules".
1492:
1190:"Biophysical mechanisms for large-effect mutations in the evolution of steroid hormone receptors"
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930:
606:
552:
477:
190:
85:
An illustration of a phylogenetic tree and how it plays in conceptualising how ASR is conducted.
1090:"Evolutionary biochemistry: revealing the historical and physical causes of protein properties"
782:"Evolutionary biochemistry: revealing the historical and physical causes of protein properties"
110:; ASR probes the statistically inferred ancestral proteins within the nodes of the tree β in a
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Period and that before this emergence, Adh served to excrete ethanol as a byproduct of excess
298:
274:
lab has recently published several studies concerning the evolutionary biophysical history of
256:
186:
103:
62:
1406:
Voordeckers K, Brown CA, Vanneste K, van der Zande E, Voet A, Maere S, Verstrepen KJ (2012).
1758:
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1701:
1693:
1649:
1639:
1587:
1577:
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1523:
1512:"Improving the efficiency of Rubisco by resurrecting its ancestors in the family Solanaceae"
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670:"Evolution of an ancient protein function involved in organized multicellularity in animals"
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223:
70:
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Harms MJ, Eick GN, Goswami D, Colucci JK, Griffin PR, Ortlund EA, Thornton JW (July 2013).
1349:"Molecular analysis of the evolutionary significance of ultraviolet vision in vertebrates"
321:
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532:
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Lin, Myat T.; Salihovic, Heidi; Clark, Frances K.; Hanson, Maureen R. (15 April 2022).
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of a given protein. ASR presents one of a few mechanisms to study biochemistry of the
57:
The method can be used to 'resurrect' ancestral proteins and was suggested in 1963 by
1786:
1496:
481:
170:
58:
1731:"An epistatic ratchet constrains the direction of glucocorticoid receptor evolution"
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610:
385:
These experiments address various important questions in evolutionary biology: does
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Several related homologues of the protein of interest are selected and aligned in a
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838:"Evolutionary trend toward kinetic stability in the folding trajectory of RNases H"
556:
357:
306:
142:
1424:
1314:
1155:
1296:
Hart KM, Harms MJ, Schmidt BH, Elya C, Thornton JW, Marqusee S (November 2014).
497:"Chemical paleogenetics: molecular restoration studies of extinct forms of life"
373:
361:
162:
1624:
Proceedings of the
National Academy of Sciences of the United States of America
1353:
Proceedings of the
National Academy of Sciences of the United States of America
1194:
Proceedings of the
National Academy of Sciences of the United States of America
1139:"Evolution of minimal specificity and promiscuity in steroid hormone receptors"
842:
Proceedings of the National Academy of Sciences of the United States of America
17:
908:
741:
314:
259:(from about 500Ma) and collaborated with the Stevens lab to resurrect ancient
123:
50:. The method uses related sequences to reconstruct an "ancestral" gene from a
1682:"Single-molecule paleoenzymology probes the chemistry of resurrected enzymes"
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may have evolved in oceans that were much hotter and more acidic than today.
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proceed in small steps or in large leaps; is evolution reversible; how does
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134:(further and further back in evolutionary time) within the tree of life.
1754:
1620:"Potentially biogenic carbon preserved in a 4.1 billion-year-old zircon"
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1020:
686:
348:
isotopic levels. ASR studies of yeast Adhs reveal that the emergence of
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420:
310:
286:
1697:
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Finnigan GC, Hanson-Smith V, Stevens TH, Thornton JW (January 2012).
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or MSAs) calculated from extant sequences. Alternate methods include
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797:
642:
625:
568:
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Some other examples are ancestral visual pigments in vertebrates,
264:
88:
1137:
Eick GN, Colucci JK, Harms MJ, Ortlund EA, Thornton JW (2012).
271:
320:
The 'age' of a reconstructed sequence is determined using a
424:
hormone, which might open possibilities for new therapies.
1241:"Evolution of increased complexity in a molecular machine"
301:); the ribonucleases involved in ruminant digestion; the
726:"The thermostability and specificity of ancient proteins"
65:. In the case of enzymes, this approach has been called
1729:
Bridgham JT, Ortlund EA, Thornton JW (September 2009).
836:
Lim SA, Hart KM, Harms MJ, Marqusee S (November 2016).
255:
The Thornton lab notably resurrected several ancestral
724:
Wheeler LC, Lim SA, Marqusee S, Harms MJ (June 2016).
1564:
Battistuzzi FU, Feijao A, Hedges SB (November 2004).
360:. The use of a clock also perhaps indicates that the
289:
in yeast that break down sugars (800Ma); enzymes in
1618:, Boehnke P, Harrison TM, Mao WL (November 2015).
1675:
1673:
1298:"Thermodynamic system drift in protein evolution"
1063:. Oxford, New York: Oxford University Press.
8:
447:
445:
218:(MP) that construct a sequence based on a
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1686:Nature Structural & Molecular Biology
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685:
641:
1459:Journal of the American Chemical Society
626:"Prehistoric proteins: Raising the dead"
80:
441:
393:evolve? It has been shown that slight
46:β is a technique used in the study of
1559:
1557:
1088:Harms MJ, Thornton JW (August 2013).
1052:
1050:
1048:
1046:
994:
992:
946:
944:
780:Harms MJ, Thornton JW (August 2013).
730:Current Opinion in Structural Biology
372:One example is the reconstruction of
7:
831:
829:
827:
825:
775:
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771:
769:
719:
717:
715:
663:
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336:, that are likely rarely subject to
106:from different branch ends of the
25:
1060:Ancestral Sequence Reconstruction
495:Pauling L, Zuckerkandl E (1963).
28:Ancestral sequence reconstruction
1347:Shi Y, Yokoyama S (July 2003).
1057:Liberles DA, ed. (2007-07-26).
137:Most ASR studies are conducted
889:Journal of Molecular Evolution
169:) and is hence often used in '
102:comparison of related protein
1:
1425:10.1371/journal.pbio.1001446
1315:10.1371/journal.pbio.1001994
1156:10.1371/journal.pgen.1003072
220:model of sequence evolution
183:multiple sequence alignment
52:multiple sequence alignment
1824:
953:Environmental Microbiology
210:(similar to those used in
909:10.1007/s00239-015-9697-5
742:10.1016/j.sbi.2016.05.015
501:Acta Chemica Scandinavica
305:(Adhs) involved in yeast
143:evolutionary biochemistry
1570:BMC Evolutionary Biology
1094:Nature Reviews. Genetics
786:Nature Reviews. Genetics
624:Pearson H (March 2012).
454:Nature Reviews. Genetics
1645:10.1073/pnas.1517557112
1374:10.1073/pnas.1532535100
1207:10.1073/pnas.1303930110
965:10.1111/1462-2920.12319
855:10.1073/pnas.1611781113
636:(7390). London: 390β3.
595:10.1126/science.1086185
403:glucocorticoid receptor
157:were not recapitulated
40:sequence reconstruction
1583:10.1186/1471-2148-4-44
1529:10.1126/sciadv.abm6871
340:and typically exhibit
332:(proteins involved in
303:alcohol dehydrogenases
95:
86:
297:to antibiotics (2 β 3
92:
84:
1793:Evolutionary biology
247:Resurrected proteins
165:era of life (>541
120:neofunctionalization
1803:Molecular evolution
1755:10.1038/nature08249
1747:2009Natur.461..515B
1636:2015PNAS..11214518B
1630:(47): 14518β14521.
1365:2003PNAS..100.8308S
1265:10.1038/nature10724
1257:2012Natur.481..360F
1021:10.1038/nature06510
1013:2008Natur.451..704G
901:2015JMolE..81..110H
848:(46): 13045β13050.
687:10.7554/eLife.10147
587:2003Sci...301.1714T
581:(5640): 1714β1717.
533:1995Natur.374...57J
116:selection pressures
48:molecular evolution
191:maximum likelihood
96:
87:
34:) β also known as
1798:Molecular biology
1741:(7263): 515β519.
1698:10.1038/nsmb.2020
1471:10.1021/ja311630a
1359:(14): 8308β8313.
1251:(7381): 360β364.
1070:978-0-19-929918-8
1007:(7179): 704β707.
429:protein engineers
412:neutral mutations
350:subfunctionalized
257:hormone receptors
216:maximum parsimony
187:phylogenetic tree
132:higher and higher
63:Emile Zuckerkandl
16:(Redirected from
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1522:(15): eabm6871.
1516:Science Advances
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1465:(8): 2899β2902.
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1418:(12): e1001446.
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1308:(11): e1001994.
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1209:
1200:(28): 11475β80.
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1149:(11): e1003072.
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1041:
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996:
987:
986:
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959:(6): 1485β1489.
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920:
895:(3β4): 110β120.
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541:10.1038/374057a0
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71:Steven A. Benner
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643:10.1038/483390a
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527:(6517): 57β59.
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466:10.1038/nrg1324
451:
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322:molecular clock
279:Ribonuclease H1
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200:neutral network
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67:paleoenzymology
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18:Paleoenzymology
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1692:(5): 592β596.
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414:acted as a
374:thioredoxin
368:Thioredoxin
334:translation
177:Methodology
163:Precambrian
1787:Categories
680:: e10147.
436:References
391:complexity
315:Solanaceae
295:resistance
193:, however
185:(MSA), a '
124:biophysics
104:homologues
100:horizontal
77:Principles
1497:207092445
736:: 37β43.
507:: S9βS16.
482:205482979
407:epistasis
395:mutations
387:evolution
346:Oxygen-18
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1602:15535883
1548:35427154
1489:23394108
1444:23239941
1393:12824471
1334:25386647
1283:22230956
1226:23798447
1175:23166518
1124:23864121
1084:Figure 1
1029:18256669
983:25009840
935:18833850
927:26349578
874:27799545
816:23864121
760:27288744
706:26740169
652:22437590
611:37628350
603:14500980
474:15143319
421:hormones
358:pyruvate
354:Cambrian
291:bacteria
272:Marqusee
267:(800Ma).
261:V-ATPase
195:Bayesian
155:in vitro
139:in vitro
112:vertical
1764:6141187
1743:Bibcode
1707:3087858
1655:4664351
1632:Bibcode
1616:Bell EA
1539:9012466
1435:3519909
1361:Bibcode
1325:4227636
1274:3979732
1253:Bibcode
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1166:3499368
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1009:Bibcode
897:Bibcode
865:5135364
807:4418793
751:5010474
697:4718807
583:Bibcode
575:Science
557:4315312
549:7532788
529:Bibcode
416:ratchet
311:RuBisCO
287:enzymes
276:E. coli
159:in vivo
151:in vivo
147:in vivo
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330:EF-Tus
240:within
212:BLASTs
1493:S2CID
1033:S2CID
931:S2CID
674:eLife
607:S2CID
553:S2CID
478:S2CID
265:yeast
128:HX/MS
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1065:ISBN
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756:PMID
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648:PMID
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326:BIFs
270:The
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1751:doi
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1534:PMC
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1475:hdl
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1261:doi
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1212:PMC
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342:Tms
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