A Structure-Centric View of Protein Evolution, Design and Adaptation

Eric J. Deeds; Eugene I. Shakhnovich

REVIEW

A Structure-Centric View of Protein Evolution, Design and Adaptation

Eric J. Deeds, Eugene I. Shakhnovich

Biomolecules · Submitted 22 Mar 2006 · 120 references

Pith's verdict: A useful review whose central anti-convergence claim overreaches: the oPDUG test only rejects uniform random subgraphs, not all state-independent convergent models.

T0 · AI review

How this review was made: An AI referee (deepseek-v4-flash) read the paper on August 28, 2026 and answered a fixed list of questions about it. T0 is the starting level every paper gets. The levels describe how deeply Pith has checked the paper, never the authors.

T0 AI review An AI read the paper and answered a fixed list of questions.
T1 Audit Automatic checks that the references and files the paper relies on exist and match.
T2 Compute The paper's code or calculations re-run with the same results.
T3 Formal statement The claims written out in a formal math language a computer can read.
T4 Proof Those claims proved, and the proof checked by computer.

How Pith checks papers →

· 2 major objections · 4 minor · Ask about this paper · The compiled record · Read the full review →

Challenge this review Comment (0) Read on arXiv ↗

Cite ▾

arXiv IDq-bio/0603028 (version 1)

Pith IDWPI24N3M, Pith's permanent record of this paper and its review

CitationEric J. Deeds, Eugene I. Shakhnovich. "A Structure-Centric View of Protein Evolution, Design and Adaptation." arXiv:q-bio/0603028 (2006). https://pith.science/paper/WPI24N3M

Cite this reviewBibTeX for Pith's review of this paper

Claim paper

Why Pith says this

Highlight any text to comment on it.

Editor's note

read the letter

Dear colleague,

Here is my read on arXiv:q-bio/0603028. The paper is a review of the structure-centric view of protein evolution, and the main thing you should know is that it is a good, honest review, but its central claim against "equilibrium convergence" is broader than the test that supports it.

What it does well: the authors lay out the PDUG and oPDUG framework clearly, summarize the lattice-model results accurately, and are refreshingly candid about weaknesses in the literature. They explicitly flag the Tiana et al. designability-over-time claim as impossible to judge, and they emphasize repeatedly that cluster-size distributions cannot discriminate between models. The graph-theoretic material is well explained, and the review gives a balanced treatment of the convergent point of view where it deserves it.

The soft spot is in the section on structural proteomes. The authors define equilibrium convergence as a class of models in which the state of the organismal graph at time t0 cannot influence the sampling of domains at later times. They then test a null hypothesis that treats organismal subgraphs as uniform random subgraphs of the PDUG, and they reject that null. From that, they conclude that the entire class of equilibrium-convergent models is unlikely. That inference does not follow. A state-independent sampler could use fixed probabilities that favor more designable or more connected domains. Under the definition given, such a sampler is still equilibrium-convergent, but its resulting subgraphs need not look like uniform random subgraphs. The paper anticipates this objection in the paragraph beginning "Although the null convergent model is fully consistent with the convergent picture..." and dismisses it by saying that the required bias to raise kmax would create unrealistic degree distributions. But no such biased sampler is constructed or tested, and no argument is given that every state-independent biased sampler must distort degree distributions. So the P-values in Figure 8 only quantify departure from uniform random sampling.

The heavy self-citation is a minor issue in a review written by the group that produced most of the original results. The parameter fitting in the lattice models is acknowledged, and the authors are careful not to overstate their own models' predictions.

This paper is for someone entering the field who wants a critical map of the lattice and graph-theoretic approaches. It is a useful review, but I would not cite it as evidence against equilibrium convergence.

It deserves a serious referee because it is a field synthesis by leading researchers; a good referee should push on the oPDUG null model.

Referee report

Significance

If the equilibrium-convergence claim were established, it would be a quantitative argument against a broad class of convergent scenarios and would strengthen the divergent paradigm. The review has genuine strengths: it presents random controls clearly, explicitly discusses nontrivial limitations (e.g., the Tiana et al. designability-over-time inference is called 'impossible to judge', and the raw CD-family-size correlation is only R2=0.09), and it explains why cluster-size distributions alone cannot distinguish models. The coherent presentation of the PDUG/BB/LSG modeling sequence and the candid assessment of orphan-count deficiencies in divergent models are valuable. However, the structural-proteome section's central inference is broader than the test that supports it, which is a load-bearing issue for the paper's main claim.

Major objections (2)

[Results from Structural Proteomes] The test described in this section compares oPDUGs with uniform random subgraphs of the PDUG of equal node count, and the P-values in Figure 8A measure departure from that null. The later definition of 'equilibrium convergence' is broader: it includes any model in which the state at time t0 cannot influence later sampling. A model that samples each domain family independently with fixed probabilities proportional to designability, functional category, or PDUG degree would be equilibrium-convergent by that definition but would not produce uniform random subgraphs, and its kmax would differ accordingly. The conclusion that 'a whole class of convergent models ... is unlikely' therefore goes beyond what the test establishes; strictly, the test establishes that uniform random sampling is unlikely.
[Results from Structural Proteomes] The paragraph beginning 'Although the null convergent model is fully consistent with the convergent picture' anticipates the biased-sampler objection but dismisses it by asserting that the bias needed to raise kmax must create unrealistic oPDUG degree distributions. No such biased sampler is constructed or tested, and no argument is given that every state-independent biased sampler must distort degree distributions. Since the class-level rejection depends on this dismissal, this is a load-bearing gap. The authors should either narrow the claim to uniform random subgraphs or analyze a family of state-independent biased samplers (e.g., designability- or degree-weighted) and show that they cannot reproduce oPDUG kmax without unrealistic degree distributions.

Minor objections (4)

[Structural Evolution on the Lattice] The displayed equations for the F-score (Eq. 1) and the England-Shakhnovich designability measure (Eq. 2) are missing from the manuscript text; please insert the expressions.
[Results from Structural Proteomes] The method used to compute the random-subgraph P-values in Figure 8 is not described in the review; a sentence pointing to the exact statistic and null model in reference 74 would help readers evaluate the central claim.
[Influence of Designability on Structural Evolution] The review is appropriately candid that the Tiana et al. designability-over-time claim is 'impossible to judge' without more careful phylogenetic analysis; given that, the later statement that the simulation result 'implies' migration toward more designable structures should be phrased as a model prediction rather than an established conclusion.
[Designability and Protein Evolution] The contrast between the binned correlation (R2=0.9) and raw correlation (R2=0.09) in Figure 10 is clear, but the text should state explicitly that the raw correlation is the relevant predictive accuracy for individual families.

How Pith checks papers → · Full audit of this paper →

The paper

The paper claims

Protein structures betray shared ancestry, not convergent sampling

The reading

This review argues that the protein structures found in living organisms are best read as records of divergence from shared ancestors, not as repeated convergent rediscovery of a few favorable shapes. Its central evidence is a graph-theoretic test: each organism's set of protein domains, called an organismal Protein Domain Universe Graph (oPDUG), is compared against random subgraphs of the full protein-structure similarity graph (PDUG). More than two-thirds of the prokaryotic genomes examined have a probability below $10^{-6}$ of being random subgraphs, because their most highly connected domains are far more connected than random sampling would produce. The authors conclude that a whole class of convergent models, which they call "equilibrium convergence," cannot explain structural proteomes, while duplication-and-divergence models reproduce the non-randomness naturally. This matters because it shifts how we interpret fold abundance, which data can test evolutionary models, and whether protein structures can serve as reliable phylogenetic characters.

What carries the argument

The load-bearing object is the Protein Domain Universe Graph (PDUG), whose nodes are protein domain families and whose edges connect domains whose structural similarity, measured by DALI Z-scores, exceeds a cutoff chosen at the critical point of the graph's giant-component transition. Each organism's structural proteome induces a subgraph called an oPDUG. The argument turns on comparing two observables: cluster-size distributions, which cannot distinguish evolved graphs from randomized ones, and degree distributions, especially the maximum degree $k_{\max}$, which can. Under the convergent null hypothesis an oPDUG should resemble a random subgraph of the PDUG; the paper shows it does not, and that a duplication-and-divergence model can reproduce the observed non-randomness.

Extended reading notes

Core claim

The paper's central claim is that protein structural evolution is dominated by divergence: new domain families arise from duplication and divergence of existing ones, and the observed network of structural similarity is the trace of that process rather than independent convergence on the same folds. The decisive observation is that organismal structural proteomes are highly non-random subgraphs of the Protein Domain Universe Graph. Comparing each oPDUG to random subgraphs of the PDUG with the same number of nodes, the authors found that the maximal connectivity ($k_{\max}$) in real proteomes is far larger than in random controls; for over two-thirds of the prokaryotic genomes considered, the probability that the oPDUG is a random subgraph falls below $10^{-6}$. This rules out "equilibrium convergence," meaning models in which the state of an organismal graph at time $t_0$ cannot influence which domains are sampled from the underlying graph at any later time $t$. A divergent Big Bang speciation model, by contrast, produces oPDUGs with the same low probabilities of being random subgraphs, and the authors show that no simple history-independent bias can rescue the convergent picture without producing unrealistic degree distributions.

Load-bearing premise

The case against convergence assumes that a convergent world would leave each organism with a random, history-independent sample of the protein-structure universe; if convergent evolution were instead biased by function or ecology, the random-subgraph test would not rule it out.

Editorial extensions

If this is right

If the central claim is right, the scale-free degree distribution of the PDUG is a genuine evolutionary signal, not a trivial consequence of compact-polymer geometry.
Fold-size distributions alone cannot arbitrate between evolutionary models, since randomized graphs reproduce them; topological observables such as degree distributions are required.
Structural proteomes shaped by divergence provide legitimate phylogenetic characters, with Dollo parsimony as the tree-building method most consistent with the models.
Designability and evolutionary history jointly determine family size: a structure's contact density sets its potential, while duplication and divergence determine how much of that potential is realized.
Lateral transfer of whole structural domains should be rare enough that domain presence and absence track lineage history, which explains why domain-content phylogenies succeed.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

One extension the authors do not develop is applying the same random-subgraph test to other conserved genomic characters, such as functional modules or domain combinations, to ask whether the non-randomness is specific to structure or generic to descent.
A testable extension would run the identical $k_{\max}$ and P-value calculation on eukaryotic oPDUGs as structural coverage improves; the paper's decisive dataset is mostly prokaryotic, and it is not obvious the conclusion carries over unchanged.
The oPDUG argument leaves open convergence at the scale of local structural elements, such as active-site residue arrangements within globally divergent domains; that kind of convergence would not register as randomness in the graph.

Original abstract

Proteins, by virtue of their central role in most biological processes, represent one of the key subjects of the study of molecular evolution. Inherent to the indispensability of proteins for living cells is the fact that a given protein can adopt a specific three-dimensional shape that is specified solely by the proteins sequence of amino acids. Over the past several decades, structural biologists have demonstrated that the array of structures that proteins may adopt is quite astounding, and this has lead to a strong interest in understanding how protein structures change and evolve over time. In this review we consider a large body of recent work that attempts to illuminate this structure-centric picture of protein evolution. Much of this work has focused on the question of how completely new protein structures (i.e. new folds or topologies) are discovered by protein sequences as they evolve. Pursuant to this question of structural innovation has been a desire to describe and understand the observation that certain types of protein structures are far more abundant than others and how this uneven distribution of proteins implicates on the process through which new shapes are discovered. We consider a number of theoretical models that have been successful at explaining this heterogeneity in protein populations and discuss the increasing amount of evidence that indicates that the process of structural evolution involves the divergence of protein sequences and structures from one another.

The compiled record

The paper's own sentences, arranged, kept beside the review and separate from it. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 5,755 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.05 · human participants 0.03 · controlled comparison 0.02 · randomized assignment 0.01 · states quantitative result 0.03 · compares with prior results 0.06 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; show every role.

Proteins, by virtue of their central role in most biological processes, represent one of the key subjects of the study of molecular evolution. Inherent to the indispensability of proteins for living cells is the fact that a given protein can adopt a specific three-dimensional shape that is specified solely by the proteins sequence of amino acids. Over the past several decades, structural biologists have demonstrated that the array of structures that proteins may adopt is quite astounding, and this has lead to a strong interest in understanding how protein structures change and evolve over time. In this review we consider a large body of recent work that attempts to illuminate this structure-centric picture of protein evolution. Much of this work has focused on the question of how completely new protein structures (i.e. new folds or topologies) are discovered by protein sequences as they evolve. Pursuant to this question of structural innovation has been a desire to describe and understand the observation that certain types of protein structures are far more abundant than others and how this uneven distribution of proteins implicates on the process through which new shapes are discovered. We consider a number of theoretical models that have been successful at explaining this heterogeneity in protein populations and discuss the increasing amount of evidence that indicates that the process of structural evolution involves the divergence of protein sequences and structures from one another.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#	sentence	role	the authors' own work	states the main conclusion	strength
s0	Proteins, by virtue of their central role in most biological processes, represent one of the key subjects of the study of molecular evolution.	background 1.00	0.04	0.03	asserted 1.00
s1	Inherent to the indispensability of proteins for living cells is the fact that a given protein can adopt a specific three-dimensional shape that is specified solely by the proteins sequence of amino acids.	background 1.00	0.04	0.03	asserted 1.00
s2	Over the past several decades, structural biologists have demonstrated that the array of structures that proteins may adopt is quite astounding, and this has lead to a strong interest in understanding how protein structures change and evolve over time.	background 1.00	0.03	0.03	asserted 0.99
s3	In this review we consider a large body of recent work that attempts to illuminate this structure-centric picture of protein evolution.	contribution 0.94	0.25	0.05	asserted 0.79
s4	Much of this work has focused on the question of how completely new protein structures (i.e. new folds or topologies) are discovered by protein sequences as they evolve.	background 0.63	0.05	0.05	asserted 0.94
s5	Pursuant to this question of structural innovation has been a desire to describe and understand the observation that certain types of protein structures are far more abundant than others and how this uneven distribution of proteins implicates on the process through which new shapes are discovered.	background 0.92	0.07	0.08	asserted 0.91
s6	We consider a number of theoretical models that have been successful at explaining this heterogeneity in protein populations and discuss the increasing amount of evidence that indicates that the process of structural evolution involves the divergence of protein sequences and structures from one another.	contribution 0.81	0.15	0.29	hedged possibility 0.85

What kind of paper the classifier reports this is: review 1.00 · evidence from literature 1.00.

What was examined, and what was not

sources read

arXiv listing abstract v1

not examined

full text
figures and tables
references and citing sentences
relations to other papers

levels run

P abstract

not run

S sections
T body sentences
C citations
R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

Figures

**Figure 4.** Degree distributions, taken from (33). (A) Degree distribution of the PDUG at a Z

**Figure 5.** The distribution of sequence occupancy in

**Figure 9.** Success of the ES designability measure for

Showing 3 of the paper's 10 figures. See all figures in the PDF ↗ Figures reproduced from arXiv:q-bio/0603028 by the authors.

References

Works cited (120)

[1]

Anfinsen, C. B., Principles that govern the folding of protein chains, Science, 181, 223 (1973)

View on Pith 1973
[2]

Chothia, C., Proteins. One thousand families for the molecular biologist, Nature, 357, 543 (1992)

View on Pith 1992
[3]

Murzin, A. G., Brenner, S. E., Hubbard, T., and Chothia, C., SCOP: a structural classification of proteins database for the investigation of sequences and structures, J Mol Biol, 247, 536 (1995)

View on Pith 1995
[4]

Orengo, C. A., Todd, A. E., and Thornt on, J. M., From protein structure to function, Curr Opin Struct Biol, 9, 374 (1999)

View on Pith 1999
[5]

Thornton, J. M., Orengo, C. A., Todd, A. E., and Pearl, F. M., Protein folds, functions and evolution, J Mol Biol, 293, 333 (1999)

View on Pith 1999
[6]

Koonin, E. V., Wolf, Y. I., and Karev, G. P., The structure of the protein universe and genome evolution, Nature, 420, 218 (2002)

View on Pith 2002
[7]

Orengo, C. A., Bray, J. E., Buchan, D. W., Harrison, A., Lee, D., Pearl, F. M., Sillitoe, I., Todd, A. E., and Thornton, J. M., The CATH protein family database: a resource for structural and functional annotation of genomes, Proteomics, 2, 11 (2002)

View on Pith 2002
[8]

Dietmann, S., and Holm, L., Identifica tion of homology in protein structure classification, Nat Struct Biol, 8, 953 (2001)

View on Pith 2001
[9]

Holm, L., and Sander, C., The FSSP da tabase: fold classification based on structure-structure alignment of proteins, Nucleic Acids Res, 24, 206 (1996)

View on Pith 1996
[10]

Holm, L., and Sander, C., Protein stru cture comparison by alignment of distance matrices, J Mol Biol, 233, 123 (1993)

View on Pith 1993
[11]

Wilson, C. A., Kreychman, J., and Gerste in, M., Assessing annotation transfer for genomics: quantifying the relations between protein sequence, structure and function through traditional and probabilistic scores, J Mol Biol, 297, 233 (2000)

View on Pith 2000
[12]

Altschul, S. F., Gish, W., Miller, W., Myer s, E. W., and Lipman, D. J., Basic local alignment search tool, J Mol Biol, 215, 403 (1990)

View on Pith 1990
[13]

Altschul, S. F., Madden, T. L., Schaffer , A. A., Zhang, J., Zhang, Z., Miller, W., and Lipman, D. J., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic Acids Res, 25, 3389 (1997)

View on Pith 1997
[14]

Getz, G., Vendruscolo, M., Sachs, D., and Domany, E., Automated assignment of SCOP and CATH protein structure classifications from FSSP scores, Proteins, 46, 405 (2002)

View on Pith 2002
[15]

Shakhnovich, B. E., and Max Harvey, J., Quantifying structure-function uncertainty: a graph theoretical exploration into the origins and limitations of protein annotation, J Mol Biol, 337, 933 (2004)

View on Pith 2004
[16]

Finkelstein, A. V., Gutun, A. M., and Ba dretdinov, A., Why are the same protein folds used to perform different functions?, FEBS Lett, 325, 23 (1993)

View on Pith 1993
[17]

Finkelstein, A. V., Badretdinov, A., and Gutin, A. M., Why do protein architectures have Boltzmann-like statistics?, Proteins, 23, 142 (1995)

View on Pith 1995
[18]

Finkelstein, A. V., Gutin, A. M., and Badr etdinov, A., Boltzmann-like statistics of protein architectures. Origins and consequences, Subcell Biochem, 24, 1 (1995). 74

View on Pith 1995
[19]

Orengo, C. A., Jones, D. T., and Thornton, J. M., Protein superfamilies and domain superfolds, Nature, 372, 631 (1994)

View on Pith 1994
[20]

Zhang, C. T., Relations of the numbers of protein sequences, families and folds, Protein Eng, 10, 757 (1997)

View on Pith 1997
[21]

Zhang, C., and DeLisi, C., Estima ting the number of protein folds, J Mol Biol, 284, 1301 (1998)

View on Pith 1998
[22]

Wang, Z. X., A re-estimation for the total numbers of protein folds and superfamilies, Protein Eng, 11, 621 (1998)

View on Pith 1998
[23]

Govindarajan, S., Recabarren, R., and Goldstein, R. A., Estimating the total number of protein folds, Proteins, 35, 408 (1999)

View on Pith 1999
[24]

Wolf, Y. I., Grishin, N. V., and Kooni n, E. V., Estimating the number of protein folds and families from complete genome data, J Mol Biol, 299, 897 (2000)

View on Pith 2000
[25]

Lesk, A. M., Lo Conte, L., and Hubbard, T. J., Assessment of novel fold targets in CASP4: predictions of three-dimensional structures, secondary structures, and interresidue contacts, Proteins, Suppl 5, 98 (2001)

View on Pith 2001
[26]

Qian, J., Luscombe, N. M., and Gerstei n, M., Protein family and fold occurrence in genomes: power-law behaviour and evolutionary model, J Mol Biol, 313, 673 (2001)

View on Pith 2001
[27]

Luscombe, N. M., Qian, J., Zhang, Z., Johnson, T., and Gerstein, M., The dominance of the population by a selected few: power-law behaviour applies to a wide variety of genomic properties, Genome Biol, 3, RESEARCH0040 (2002)

View on Pith 2002
[28]

Karev, G. P., Wolf, Y. I., Rzhetsky, A. Y., Berezovskaya, F. S., and Koonin, E. V., Birth and death of protein domains: A simple model of evolution explains power law behavior, BMC Evol Biol, 2, 18 (2002)

View on Pith 2002
[29]

Rzhetsky, A., and Gomez, S. M., Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome, Bioinformatics, 17, 988 (2001)

View on Pith 2001
[30]

Dokholyan, N. V., and Shakhnovich, E. I ., Understanding hierarchical protein evolution from first principles, J Mol Biol, 312, 289 (2001)

View on Pith 2001
[31]

Mirny, L. A., and Shakhnovich, E. I., Un iversally conserved positions in protein folds: reading evolutionary signals about stability, folding kinetics and function, J Mol Biol, 291, 177 (1999)

View on Pith 1999
[32]

Li, H., Helling, R., Tang, C., and Wingreen, N., Emergence of preferred structures in a simple model of protein folding, Science, 273, 666 (1996)

View on Pith 1996
[33]

Dokholyan, N. V., Shakhnovich, B., and Shakhnovich, E. I., Expanding protein universe and its origin from the biological Big Bang, Proc Natl Acad Sci U S A, 99, 14132 (2002)

View on Pith 2002
[34]

Albert, R., and Barabasi, A.-L., Statis tical mechanics of complex networks, Rev Mod Phys, 74, 47 (2002)

View on Pith 2002
[35]

Barabasi, A. L., and Albert, R., Emer gence of scaling in random networks, Science, 286, 509 (1999)

View on Pith 1999
[36]

Jeong, H., Mason, S. P., Barabasi, A. L., and Oltvai, Z. N., Lethality and centrality in protein networks, Nature, 411, 41 (2001)

View on Pith 2001
[37]

Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N., and Barabasi, A. L., The large- scale organization of metabolic networks, Nature, 407, 651 (2000). 75

View on Pith 2000
[38]

Ravasz, E., Somera, A. L., Mongru, D. A ., Oltvai, Z. N., and Barabasi, A. L., Hierarchical organization of modularity in metabolic networks, Science, 297, 1551 (2002)

View on Pith 2002
[39]

Yook, S. H., Oltvai, Z. N., and Bara basi, A. L., Functional and topological characterization of protein interaction networks, Proteomics, 4, 928 (2004)

View on Pith 2004
[40]

Krapivsky, P. L., Rodgers, G. J., and Re dner, S., Degree distributions of growing networks, Phys Rev Lett, 86, 5401 (2001)

View on Pith 2001
[41]

Shakhnovich, E. I., and Gutin, A., Enumer ation of all compact conformations of copolymers with random sequence links, J Chem Phys, 93, 5967 (1990)

View on Pith 1990
[42]

Mirny, L., and Shakhnovich, E., Protein fold ing theory: from lattice to all-atom models, Annu Rev Biophys Biomol Struct, 30, 361 (2001)

View on Pith 2001
[43]

Shakhnovich, E. I., and Gutin, A. M., Imp lications of thermodynamics of protein folding for evolution of primary sequences, Nature, 346, 773 (1990)

View on Pith 1990
[44]

Gutin, A. M., Abkevich, V. I., and Shakhnovi ch, E. I., Evolution-like selection of fast-folding model proteins, Proc Natl Acad Sci U S A, 92, 1282 (1995)

View on Pith 1995
[45]

Goldstein, R. A., Luthey-Schulten, Z. A ., and Wolynes, P. G., Optimal protein- folding codes from spin-glass theory, Proc Natl Acad Sci U S A, 89, 4918 (1992)

View on Pith 1992
[46]

Chan, H. S., and Bornberg-Bauer, E., Perspectives on protein evolution from simple exact models, Appl Bioinformatics, 1, 121 (2002)

View on Pith 2002
[47]

Xia, Y., and Levitt, M., Simulating prot ein evolution in sequence and structure space, Curr Opin Struct Biol, 14, 202 (2004)

View on Pith 2004
[48]

Dinner, A. R., Abkevich, V., Shakhnovic h, E., and Karplus, M., Factors that affect the folding ability of proteins, Proteins, 35, 34 (1999)

View on Pith 1999
[49]

Bryngelson, J. D., and Wolynes, P. G., Sp in glasses and the statistical mechanics of protein folding, Proc Natl Acad Sci U S A, 84, 7524 (1987)

View on Pith 1987
[50]

Bryngelson, J. D., and Wolynes, P. G., Intermediates and Barrier Crossing in a Random Energy-Model (With Applications to Protein Folding), J Phys Chem, 93, 6902 (1989)

View on Pith 1989
[51]

Shakhnovich, E. I., and Gutin, A. M., Formation of unique structure in polypeptide chains. Theoretical investigation with the aid of a replica approach, Biophys Chem, 34, 187 (1989)

View on Pith 1989
[52]

Bornberg-Bauer, E., How are model prot ein structures distributed in sequence space?, Biophys J, 73, 2393 (1997)

View on Pith 1997
[53]

Bornberg-Bauer, E., and Chan, H. S., Modeling evolutionary landscapes: mutational stability, topology, and superfunnels in sequence space, Proc Natl Acad Sci U S A, 96, 10689 (1999)

View on Pith 1999
[54]

Xia, Y., and Levitt, M., Funnel-like or ganization in sequence space determines the distributions of protein stability and folding rate preferred by evolution, Proteins, 55, 107 (2004)

View on Pith 2004
[55]

Fontana, W., Modelling 'evo-devo' with RNA, Bioessays, 24, 1164 (2002)

View on Pith 2002
[56]

Fontana, W., and Schuster, P., Conti nuity in evolution: on the nature of transitions, Science, 280, 1451 (1998)

View on Pith 1998
[57]

Bornberg-Bauer, E., Randomness, struct ural uniqueness, modularity, and neutral evolution in sequence space of mpdel proteins, Z Phys Chem, 216, 139 (2002). 76

View on Pith 2002
[58]

Cui, Y., Wong, W. H., Bornberg-Bauer, E., and Chan, H. S., Recombinatoric exploration of novel folded structures: a heteropolymer-based model of protein evolutionary landscapes, Proc Natl Acad Sci U S A, 99, 809 (2002)

View on Pith 2002
[59]

Taverna, D. M., and Goldstein, R. A., Th e distribution of structures in evolving protein populations, Biopolymers, 53, 1 (2000)

View on Pith 2000
[60]

Taverna, D. M., and Goldstein, R. A., Why are proteins so robust to site mutations?, J Mol Biol, 315, 479 (2002)

View on Pith 2002
[61]

Taverna, D. M., and Goldstein, R. A., Why are proteins marginally stable?, Proteins, 46, 105 (2002)

View on Pith 2002
[62]

Blackburne, B. P., and Hirst, J. D., Evolution of functional model proteins, J Chem Phys, 115, 1935 (2001)

View on Pith 2001
[63]

Blackburne, B. P., and Hirst, J. D., Thr ee-dimensional functional model proteins: structure, function and evolution, J Chem Phys, 119, 3453 (2003)

View on Pith 2003
[64]

Hirst, J. D., The evolutionary la ndscape of functional model proteins, Protein Eng, 12, 721 (1999)

View on Pith 1999
[65]

Holm, L., and Sander, C., Mapping the protein universe, Science, 273, 595 (1996)

View on Pith 1996
[66]

Deeds, E. J., Dokholyan, N. V., and Sha khnovich, E. I., Protein evolution within a structural space, Biophys J, 85, 2962 (2003)

View on Pith 2003
[67]

England, J. L., and Shakhnovich, E. I ., Structural determinant of protein designability, Phys Rev Lett, 90, 218101 (2003)

View on Pith 2003
[68]

Deeds, E. J., and Shakhnovich, E. I., The Emergence of Scaling in Sequence- based Physical Models of Protein Evolution, Biophys J (2005)

View on Pith 2005
[69]

Mirny, L. A., and Shakhnovich, E. I., How to derive a protein folding potential? A new approach to an old problem, J Mol Biol, 264, 1164 (1996)

View on Pith 1996
[70]

Miyazawa, S., and Jernigan, R. L., Resi due-residue potentials with a favorable contact pair term and an unfavorable high packing density term, for simulation and threading, J Mol Biol, 256, 623 (1996)

View on Pith 1996
[71]

Miyazawa, S., and Jernigan, R. L., Estim ation of effective interresidue contact energies from protein crystal structures: quasi-chemical approximation., Macromolecules, 18, 534 (1985)

View on Pith 1985
[72]

Tiana, G., Broglia, R. A., and Shakhnovi ch, E. I., Hiking in the energy landscape in sequence space: a bumpy road to good folders, Proteins, 39, 244 (2000)

View on Pith 2000
[73]

Kim, J., Krapivsky, P. L., Kahng, B., and Redner, S., Infinite-order percolation and giant fluctuations in a protein interaction network, Phys Rev E Stat Nonlin Soft Matter Phys, 66, 055101 (2002)

View on Pith 2002
[74]

Deeds, E. J., Shakhnovich, B., and Shakhnovich, E. I., Proteomic Traces of Speciation, J Mol Biol, 336, 695 (2004)

View on Pith 2004
[75]

Doolittle, W. F., Phylogenetic clas sification and the universal tree, Science, 284, 2124 (1999)

View on Pith 1999
[76]

Doolittle, W. F., Lateral genomics, Trends Cell Biol, 9, M5 (1999)

View on Pith 1999
[77]

Gogarten, J. P., Doolittle, W. F., and La wrence, J. G., Prokaryotic evolution in light of gene transfer, Mol Biol Evol, 19, 2226 (2002)

View on Pith 2002
[78]

Aravind, L., Tatusov, R. L., Wolf, Y. I., Walker, D. R., and Koonin, E. V., Evidence for massive gene exchange between archaeal and bacterial hyperthermophiles, Trends Genet, 14, 442 (1998). 77

View on Pith 1998
[79]

Wolf, Y. I., Brenner, S. E., Bash, P. A ., and Koonin, E. V., Distribution of protein folds in the three superkingdoms of life, Genome Res, 9, 17 (1999)

View on Pith 1999
[80]

Chothia, C., Gough, J., Vogel, C., and Teic hmann, S. A., Evolution of the protein repertoire, Science, 300, 1701 (2003)

View on Pith 2003
[81]

Shakhnovich, B. E., Harvey, J. M., Co meau, S., Lorenz, D., DeLisi, C., and Shakhnovich, E., ELISA: structure-function inferences based on statistically significant and evolutionarily inspired observations, BMC Bioinformatics, 4, 34 (2003)

View on Pith 2003
[82]

Lupas, A. N., Ponting, C. P., and Russell, R. B., On the evolution of protein folds: are similar motifs in different protein folds the result of convergence, insertion, or relics of an ancient peptide world?, J Struct Biol, 134, 191 (2001)

View on Pith 2001
[83]

Ponting, C. P., and Russell, R. R., The natural history of protein domains, Annu Rev Biophys Biomol Struct, 31, 45 (2002)

View on Pith 2002
[84]

Sali, A., Target practice, Nat Struct Biol, 8, 482 (2001)

View on Pith 2001
[85]

Vitkup, D., Melamud, E., Moult, J., and Sander, C., Completeness in structural genomics, Nat Struct Biol, 8, 559 (2001)

View on Pith 2001
[86]

Galperin, M. Y., Walker, D. R., and Koonin, E. V., Analogous enzymes: independent inventions in enzyme evolution, Genome Res, 8, 779 (1998)

View on Pith 1998
[87]

Wolynes, P. G., Symmetry and the energy landscapes of biomolecules, Proc Natl Acad Sci U S A, 93, 14249 (1996)

View on Pith 1996
[88]

Kussell, E. L., and Shakhnovich, E. I., An alytical approach to the protein design problem, Phys Rev Lett, 83, 4437 (1999)

View on Pith 1999
[89]

England, J. L., Shakhnovich, B. E., and Shakhnovich, E. I., Natural selection of more designable folds: a mechanism for thermophilic adaptation, Proc Natl Acad Sci U S A, 100, 8727 (2003)

View on Pith 2003
[90]

Tiana, G., Shakhnovich, B. E., Dokholya n, N. V., and Shakhnovich, E. I., Imprint of evolution on protein structures, Proc Natl Acad Sci U S A, 101, 2846 (2004)

View on Pith 2004
[91]

Shakhnovich, B. E., Deeds, E., Delisi, C., and Shakhnovich, E., Protein structure and evolutionary history determine sequence space topology, Genome Res, 15, 385 (2005)

View on Pith 2005
[92]

Giribet, G., Current advances in th e phylogenetic reconstruction of metazoan evolution. A new paradigm for the Cambrian explosion?, Mol Phylogenet Evol, 24, 345 (2002)

View on Pith 2002
[93]

Woese, C. R., and Fox, G. E., Phylogene tic structure of the prokaryotic domain: the primary kingdoms, Proc Natl Acad Sci U S A, 74, 5088 (1977)

View on Pith 1977
[94]

Woese, C. R., Kandler, O., and Wheelis , M. L., Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya, Proc Natl Acad Sci U S A, 87, 4576 (1990)

View on Pith 1990
[95]

Doolittle, W. F., and Brown, J. R., Tem po, mode, the progenote, and the universal root, Proc Natl Acad Sci U S A, 91, 6721 (1994)

View on Pith 1994
[96]

Baldauf, S. L., The deep roots of eukaryotes, Science, 300, 1703 (2003)

View on Pith 2003
[97]

Wolf, Y. I., Rogozin, I. B., Grishin, N. V., and Koonin, E. V., Genome trees and the tree of life, Trends Genet, 18, 472 (2002)

View on Pith 2002
[98]

Cole, J. R., Chai, B., Marsh, T. L., Farris, R. J., Wang, Q., Kulam, S. A., Chandra, S., McGarrell, D. M., Schmidt, T. M., Garrity, G. M., and Tiedje, J. M., The Ribosomal Database Project (RDP-II): previewing a new autoaligner that allows 78 regular updates and the new prokaryotic taxonomy, Nucleic Acids Res, 31, 442 (2003)

View on Pith 2003
[99]

Tatusov, R. L., Natale, D. A., Garkavtse v, I. V., Tatusova, T. A., Shankavaram, U. T., Rao, B. S., Kiryutin, B., Galperin, M. Y., Fedorova, N. D., and Koonin, E. V., The COG database: new developments in phylogenetic classification of proteins from complete genomes, Nucleic Acids Res, 29, 22 (2001)

View on Pith 2001
[100]

Brown, J. R., Douady, C. J ., Italia, M. J., Marshall, W. E., and Stanhope, M. J., Universal trees based on large combined protein sequence data sets, Nat Genet, 28, 281 (2001)

View on Pith 2001
[101]

Wolf, Y. I., Rogozin, I. B., Grishin, N. V., Tatusov, R. L., and Koonin, E. V., Genome trees constructed using five different approaches suggest new major bacterial clades, BMC Evol Biol, 1, 8 (2001)

View on Pith 2001
[102]

Nesbo, C. L., L'Haridon, S., Stetter, K. O., and Doolittle, W. F., Phylogenetic analyses of two "archaeal" genes in thermotoga maritima reveal multiple transfers between archaea and bacteria, Mol Biol Evol, 18, 362 (2001)

View on Pith 2001
[103]

Jain, R., Rivera, M. C., and Lake, J. A ., Horizontal gene transfer among genomes: the complexity hypothesis, Proc Natl Acad Sci U S A, 96, 3801 (1999)

View on Pith 1999
[104]

Lawrence, J. G., Gene transfer, spec iation, and the evolution of bacterial genomes, Curr Opin Microbiol, 2, 519 (1999)

View on Pith 1999
[105]

Korbel, J. O., Snel, B., Huynen, M. A., and Bork, P., SHOT: a web server for the construction of genome phylogenies, Trends Genet, 18, 158 (2002)

View on Pith 2002
[106]

Fitz-Gibbon, S. T., and House, C. H., Whole genome-based phylogenetic analysis of free-living microorganisms, Nucleic Acids Res, 27, 4218 (1999)

View on Pith 1999
[107]

House, C. H., and Fitz-Gibbon, S. T., Using homolog groups to create a whole- genomic tree of free-living organisms: an update, J Mol Evol, 54, 539 (2002)

View on Pith 2002
[108]

Brown, J. R., and Doolittle, W. F., Archaea and the prokaryote-to-eukaryote transition, Microbiol Mol Biol Rev, 61, 456 (1997)

View on Pith 1997
[109]

Dutilh, B. E., Huynen, M. A., Bruno, W. J., and Snel, B., The consistent phylogenetic signal in genome trees revealed by reducing the impact of noise, J Mol Evol, 58, 527 (2004)

View on Pith 2004
[110]

Clarke, G. D., Beiko, R. G., Ragan, M. A., and Charlebois, R. L., Inferring genome trees by using a filter to eliminate phylogenetically discordant sequences and a distance matrix based on mean normalized BLASTP scores, J Bacteriol, 184, 2072 (2002)

View on Pith 2002
[111]

Nesbo, C. L., Boucher, Y., and Doolittle, W. F., Defining the core of nontransferable prokaryotic genes: the euryarchaeal core, J Mol Evol, 53, 340 (2001)

View on Pith 2001
[112]

Lin, J., and Gerstein, M., Whole-genome trees based on the occurrence of folds and orthologs: implications for comparing genomes on different levels, Genome Res, 10, 808 (2000)

View on Pith 2000
[113]

Caetano-Anolles, G., and Caetano-Anolle s, D., An evolutionarily structured universe of protein architecture, Genome Res, 13, 1563 (2003)

View on Pith 2003
[114]

Deeds, E. J., Hennessey, H., and Sha khnovich, E. I., Prokaryotic phylogenies inferred from protein structural domains, Genome Res, 15, 393 (2005)

View on Pith 2005
[115]

Farris, J. S., Phylogenetic analysis under Dollo's Law, Syst Zool, 26, 77 (1977). 79

View on Pith 1977
[116]

Swofford, D. L., Paup*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4, Sinauer Associates, Sunderland, Massachusetts (2003)

View on Pith 2003
[117]

Mirkin, B. G., Fenner, T. I., Galperi n, M. Y., and Koonin, E. V., Algorithms for computing parsimonious evolutionary scenarios for genome evolution, the last universal common ancestor and dominance of horizontal gene transfer in the evolution of prokaryotes, BMC Evol Biol, 3, 2 (2003)

View on Pith 2003
[118]

Saitou, N., and Nei, M., The nei ghbor-joining method: a new method for reconstructing phylogenetic trees, Mol Biol Evol, 4, 406 (1987)

View on Pith 1987
[119]

Yang, S., Doolittle, R. F., and Bourne, P. E., Phylogeny determined by protein domain content, Proc Natl Acad Sci U S A, 102, 373 (2005)

View on Pith 2005
[120]

Gough, J., Karplus, K., Hughey, R., and C hothia, C., Assignment of homology to genome sequences using a library of hidden Markov models that represent all proteins of known structure, J Mol Biol, 313, 903 (2001)

View on Pith 2001

Discussion

Disagree with the review, or know something it missed? Leave a comment, highlight any passage above to comment on it, or challenge this review formally.

[1] [1]

Anfinsen, C. B., Principles that govern the folding of protein chains, Science, 181, 223 (1973)

View on Pith 1973

[2] [2]

Chothia, C., Proteins. One thousand families for the molecular biologist, Nature, 357, 543 (1992)

View on Pith 1992

[3] [3]

Murzin, A. G., Brenner, S. E., Hubbard, T., and Chothia, C., SCOP: a structural classification of proteins database for the investigation of sequences and structures, J Mol Biol, 247, 536 (1995)

View on Pith 1995

[4] [4]

Orengo, C. A., Todd, A. E., and Thornt on, J. M., From protein structure to function, Curr Opin Struct Biol, 9, 374 (1999)

View on Pith 1999

[5] [5]

Thornton, J. M., Orengo, C. A., Todd, A. E., and Pearl, F. M., Protein folds, functions and evolution, J Mol Biol, 293, 333 (1999)

View on Pith 1999

[6] [6]

Koonin, E. V., Wolf, Y. I., and Karev, G. P., The structure of the protein universe and genome evolution, Nature, 420, 218 (2002)

View on Pith 2002

[7] [7]

Orengo, C. A., Bray, J. E., Buchan, D. W., Harrison, A., Lee, D., Pearl, F. M., Sillitoe, I., Todd, A. E., and Thornton, J. M., The CATH protein family database: a resource for structural and functional annotation of genomes, Proteomics, 2, 11 (2002)

View on Pith 2002

[8] [8]

Dietmann, S., and Holm, L., Identifica tion of homology in protein structure classification, Nat Struct Biol, 8, 953 (2001)

View on Pith 2001

[9] [9]

Holm, L., and Sander, C., The FSSP da tabase: fold classification based on structure-structure alignment of proteins, Nucleic Acids Res, 24, 206 (1996)

View on Pith 1996

[10] [10]

Holm, L., and Sander, C., Protein stru cture comparison by alignment of distance matrices, J Mol Biol, 233, 123 (1993)

View on Pith 1993

[11] [11]

Wilson, C. A., Kreychman, J., and Gerste in, M., Assessing annotation transfer for genomics: quantifying the relations between protein sequence, structure and function through traditional and probabilistic scores, J Mol Biol, 297, 233 (2000)

View on Pith 2000

[12] [12]

Altschul, S. F., Gish, W., Miller, W., Myer s, E. W., and Lipman, D. J., Basic local alignment search tool, J Mol Biol, 215, 403 (1990)

View on Pith 1990

[13] [13]

Altschul, S. F., Madden, T. L., Schaffer , A. A., Zhang, J., Zhang, Z., Miller, W., and Lipman, D. J., Gapped BLAST and PSI-BLAST: a new generation of protein database search programs, Nucleic Acids Res, 25, 3389 (1997)

View on Pith 1997

[14] [14]

Getz, G., Vendruscolo, M., Sachs, D., and Domany, E., Automated assignment of SCOP and CATH protein structure classifications from FSSP scores, Proteins, 46, 405 (2002)

View on Pith 2002

[15] [15]

Shakhnovich, B. E., and Max Harvey, J., Quantifying structure-function uncertainty: a graph theoretical exploration into the origins and limitations of protein annotation, J Mol Biol, 337, 933 (2004)

View on Pith 2004

[16] [16]

Finkelstein, A. V., Gutun, A. M., and Ba dretdinov, A., Why are the same protein folds used to perform different functions?, FEBS Lett, 325, 23 (1993)

View on Pith 1993

[17] [17]

Finkelstein, A. V., Badretdinov, A., and Gutin, A. M., Why do protein architectures have Boltzmann-like statistics?, Proteins, 23, 142 (1995)

View on Pith 1995

[18] [18]

Finkelstein, A. V., Gutin, A. M., and Badr etdinov, A., Boltzmann-like statistics of protein architectures. Origins and consequences, Subcell Biochem, 24, 1 (1995). 74

View on Pith 1995

[19] [19]

Orengo, C. A., Jones, D. T., and Thornton, J. M., Protein superfamilies and domain superfolds, Nature, 372, 631 (1994)

View on Pith 1994

[20] [20]

Zhang, C. T., Relations of the numbers of protein sequences, families and folds, Protein Eng, 10, 757 (1997)

View on Pith 1997

[21] [21]

Zhang, C., and DeLisi, C., Estima ting the number of protein folds, J Mol Biol, 284, 1301 (1998)

View on Pith 1998

[22] [22]

Wang, Z. X., A re-estimation for the total numbers of protein folds and superfamilies, Protein Eng, 11, 621 (1998)

View on Pith 1998

[23] [23]

Govindarajan, S., Recabarren, R., and Goldstein, R. A., Estimating the total number of protein folds, Proteins, 35, 408 (1999)

View on Pith 1999

[24] [24]

Wolf, Y. I., Grishin, N. V., and Kooni n, E. V., Estimating the number of protein folds and families from complete genome data, J Mol Biol, 299, 897 (2000)

View on Pith 2000

[25] [25]

Lesk, A. M., Lo Conte, L., and Hubbard, T. J., Assessment of novel fold targets in CASP4: predictions of three-dimensional structures, secondary structures, and interresidue contacts, Proteins, Suppl 5, 98 (2001)

View on Pith 2001

[26] [26]

Qian, J., Luscombe, N. M., and Gerstei n, M., Protein family and fold occurrence in genomes: power-law behaviour and evolutionary model, J Mol Biol, 313, 673 (2001)

View on Pith 2001

[27] [27]

Luscombe, N. M., Qian, J., Zhang, Z., Johnson, T., and Gerstein, M., The dominance of the population by a selected few: power-law behaviour applies to a wide variety of genomic properties, Genome Biol, 3, RESEARCH0040 (2002)

View on Pith 2002

[28] [28]

Karev, G. P., Wolf, Y. I., Rzhetsky, A. Y., Berezovskaya, F. S., and Koonin, E. V., Birth and death of protein domains: A simple model of evolution explains power law behavior, BMC Evol Biol, 2, 18 (2002)

View on Pith 2002

[29] [29]

Rzhetsky, A., and Gomez, S. M., Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome, Bioinformatics, 17, 988 (2001)

View on Pith 2001

[30] [30]

Dokholyan, N. V., and Shakhnovich, E. I ., Understanding hierarchical protein evolution from first principles, J Mol Biol, 312, 289 (2001)

View on Pith 2001

[31] [31]

Mirny, L. A., and Shakhnovich, E. I., Un iversally conserved positions in protein folds: reading evolutionary signals about stability, folding kinetics and function, J Mol Biol, 291, 177 (1999)

View on Pith 1999

[32] [32]

Li, H., Helling, R., Tang, C., and Wingreen, N., Emergence of preferred structures in a simple model of protein folding, Science, 273, 666 (1996)

View on Pith 1996

[33] [33]

Dokholyan, N. V., Shakhnovich, B., and Shakhnovich, E. I., Expanding protein universe and its origin from the biological Big Bang, Proc Natl Acad Sci U S A, 99, 14132 (2002)

View on Pith 2002

[34] [34]

Albert, R., and Barabasi, A.-L., Statis tical mechanics of complex networks, Rev Mod Phys, 74, 47 (2002)

View on Pith 2002

[35] [35]

Barabasi, A. L., and Albert, R., Emer gence of scaling in random networks, Science, 286, 509 (1999)

View on Pith 1999

[36] [36]

Jeong, H., Mason, S. P., Barabasi, A. L., and Oltvai, Z. N., Lethality and centrality in protein networks, Nature, 411, 41 (2001)

View on Pith 2001

[37] [37]

Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N., and Barabasi, A. L., The large- scale organization of metabolic networks, Nature, 407, 651 (2000). 75

View on Pith 2000

[38] [38]

Ravasz, E., Somera, A. L., Mongru, D. A ., Oltvai, Z. N., and Barabasi, A. L., Hierarchical organization of modularity in metabolic networks, Science, 297, 1551 (2002)

View on Pith 2002

[39] [39]

Yook, S. H., Oltvai, Z. N., and Bara basi, A. L., Functional and topological characterization of protein interaction networks, Proteomics, 4, 928 (2004)

View on Pith 2004

[40] [40]

Krapivsky, P. L., Rodgers, G. J., and Re dner, S., Degree distributions of growing networks, Phys Rev Lett, 86, 5401 (2001)

View on Pith 2001

[41] [41]

Shakhnovich, E. I., and Gutin, A., Enumer ation of all compact conformations of copolymers with random sequence links, J Chem Phys, 93, 5967 (1990)

View on Pith 1990

[42] [42]

Mirny, L., and Shakhnovich, E., Protein fold ing theory: from lattice to all-atom models, Annu Rev Biophys Biomol Struct, 30, 361 (2001)

View on Pith 2001

[43] [43]

Shakhnovich, E. I., and Gutin, A. M., Imp lications of thermodynamics of protein folding for evolution of primary sequences, Nature, 346, 773 (1990)

View on Pith 1990

[44] [44]

Gutin, A. M., Abkevich, V. I., and Shakhnovi ch, E. I., Evolution-like selection of fast-folding model proteins, Proc Natl Acad Sci U S A, 92, 1282 (1995)

View on Pith 1995

[45] [45]

Goldstein, R. A., Luthey-Schulten, Z. A ., and Wolynes, P. G., Optimal protein- folding codes from spin-glass theory, Proc Natl Acad Sci U S A, 89, 4918 (1992)

View on Pith 1992

[46] [46]

Chan, H. S., and Bornberg-Bauer, E., Perspectives on protein evolution from simple exact models, Appl Bioinformatics, 1, 121 (2002)

View on Pith 2002

[47] [47]

Xia, Y., and Levitt, M., Simulating prot ein evolution in sequence and structure space, Curr Opin Struct Biol, 14, 202 (2004)

View on Pith 2004

[48] [48]

Dinner, A. R., Abkevich, V., Shakhnovic h, E., and Karplus, M., Factors that affect the folding ability of proteins, Proteins, 35, 34 (1999)

View on Pith 1999

[49] [49]

Bryngelson, J. D., and Wolynes, P. G., Sp in glasses and the statistical mechanics of protein folding, Proc Natl Acad Sci U S A, 84, 7524 (1987)

View on Pith 1987

[50] [50]

Bryngelson, J. D., and Wolynes, P. G., Intermediates and Barrier Crossing in a Random Energy-Model (With Applications to Protein Folding), J Phys Chem, 93, 6902 (1989)

View on Pith 1989

[51] [51]

Shakhnovich, E. I., and Gutin, A. M., Formation of unique structure in polypeptide chains. Theoretical investigation with the aid of a replica approach, Biophys Chem, 34, 187 (1989)

View on Pith 1989

[52] [52]

Bornberg-Bauer, E., How are model prot ein structures distributed in sequence space?, Biophys J, 73, 2393 (1997)

View on Pith 1997

[53] [53]

Bornberg-Bauer, E., and Chan, H. S., Modeling evolutionary landscapes: mutational stability, topology, and superfunnels in sequence space, Proc Natl Acad Sci U S A, 96, 10689 (1999)

View on Pith 1999

[54] [54]

Xia, Y., and Levitt, M., Funnel-like or ganization in sequence space determines the distributions of protein stability and folding rate preferred by evolution, Proteins, 55, 107 (2004)

View on Pith 2004

[55] [55]

Fontana, W., Modelling 'evo-devo' with RNA, Bioessays, 24, 1164 (2002)

View on Pith 2002

[56] [56]

Fontana, W., and Schuster, P., Conti nuity in evolution: on the nature of transitions, Science, 280, 1451 (1998)

View on Pith 1998

[57] [57]

Bornberg-Bauer, E., Randomness, struct ural uniqueness, modularity, and neutral evolution in sequence space of mpdel proteins, Z Phys Chem, 216, 139 (2002). 76

View on Pith 2002

[58] [58]

Cui, Y., Wong, W. H., Bornberg-Bauer, E., and Chan, H. S., Recombinatoric exploration of novel folded structures: a heteropolymer-based model of protein evolutionary landscapes, Proc Natl Acad Sci U S A, 99, 809 (2002)

View on Pith 2002

[59] [59]

Taverna, D. M., and Goldstein, R. A., Th e distribution of structures in evolving protein populations, Biopolymers, 53, 1 (2000)

View on Pith 2000

[60] [60]

Taverna, D. M., and Goldstein, R. A., Why are proteins so robust to site mutations?, J Mol Biol, 315, 479 (2002)

View on Pith 2002

[61] [61]

Taverna, D. M., and Goldstein, R. A., Why are proteins marginally stable?, Proteins, 46, 105 (2002)

View on Pith 2002

[62] [62]

Blackburne, B. P., and Hirst, J. D., Evolution of functional model proteins, J Chem Phys, 115, 1935 (2001)

View on Pith 2001

[63] [63]

Blackburne, B. P., and Hirst, J. D., Thr ee-dimensional functional model proteins: structure, function and evolution, J Chem Phys, 119, 3453 (2003)

View on Pith 2003

[64] [64]

Hirst, J. D., The evolutionary la ndscape of functional model proteins, Protein Eng, 12, 721 (1999)

View on Pith 1999

[65] [65]

Holm, L., and Sander, C., Mapping the protein universe, Science, 273, 595 (1996)

View on Pith 1996

[66] [66]

Deeds, E. J., Dokholyan, N. V., and Sha khnovich, E. I., Protein evolution within a structural space, Biophys J, 85, 2962 (2003)

View on Pith 2003

[67] [67]

England, J. L., and Shakhnovich, E. I ., Structural determinant of protein designability, Phys Rev Lett, 90, 218101 (2003)

View on Pith 2003

[68] [68]

Deeds, E. J., and Shakhnovich, E. I., The Emergence of Scaling in Sequence- based Physical Models of Protein Evolution, Biophys J (2005)

View on Pith 2005

[69] [69]

Mirny, L. A., and Shakhnovich, E. I., How to derive a protein folding potential? A new approach to an old problem, J Mol Biol, 264, 1164 (1996)

View on Pith 1996

[70] [70]

Miyazawa, S., and Jernigan, R. L., Resi due-residue potentials with a favorable contact pair term and an unfavorable high packing density term, for simulation and threading, J Mol Biol, 256, 623 (1996)

View on Pith 1996

[71] [71]

Miyazawa, S., and Jernigan, R. L., Estim ation of effective interresidue contact energies from protein crystal structures: quasi-chemical approximation., Macromolecules, 18, 534 (1985)

View on Pith 1985

[72] [72]

Tiana, G., Broglia, R. A., and Shakhnovi ch, E. I., Hiking in the energy landscape in sequence space: a bumpy road to good folders, Proteins, 39, 244 (2000)

View on Pith 2000

[73] [73]

Kim, J., Krapivsky, P. L., Kahng, B., and Redner, S., Infinite-order percolation and giant fluctuations in a protein interaction network, Phys Rev E Stat Nonlin Soft Matter Phys, 66, 055101 (2002)

View on Pith 2002

[74] [74]

Deeds, E. J., Shakhnovich, B., and Shakhnovich, E. I., Proteomic Traces of Speciation, J Mol Biol, 336, 695 (2004)

View on Pith 2004

[75] [75]

Doolittle, W. F., Phylogenetic clas sification and the universal tree, Science, 284, 2124 (1999)

View on Pith 1999

[76] [76]

Doolittle, W. F., Lateral genomics, Trends Cell Biol, 9, M5 (1999)

View on Pith 1999

[77] [77]

Gogarten, J. P., Doolittle, W. F., and La wrence, J. G., Prokaryotic evolution in light of gene transfer, Mol Biol Evol, 19, 2226 (2002)

View on Pith 2002

[78] [78]

Aravind, L., Tatusov, R. L., Wolf, Y. I., Walker, D. R., and Koonin, E. V., Evidence for massive gene exchange between archaeal and bacterial hyperthermophiles, Trends Genet, 14, 442 (1998). 77

View on Pith 1998

[79] [79]

Wolf, Y. I., Brenner, S. E., Bash, P. A ., and Koonin, E. V., Distribution of protein folds in the three superkingdoms of life, Genome Res, 9, 17 (1999)

View on Pith 1999

[80] [80]

Chothia, C., Gough, J., Vogel, C., and Teic hmann, S. A., Evolution of the protein repertoire, Science, 300, 1701 (2003)

View on Pith 2003

[81] [81]

Shakhnovich, B. E., Harvey, J. M., Co meau, S., Lorenz, D., DeLisi, C., and Shakhnovich, E., ELISA: structure-function inferences based on statistically significant and evolutionarily inspired observations, BMC Bioinformatics, 4, 34 (2003)

View on Pith 2003

[82] [82]

Lupas, A. N., Ponting, C. P., and Russell, R. B., On the evolution of protein folds: are similar motifs in different protein folds the result of convergence, insertion, or relics of an ancient peptide world?, J Struct Biol, 134, 191 (2001)

View on Pith 2001

[83] [83]

Ponting, C. P., and Russell, R. R., The natural history of protein domains, Annu Rev Biophys Biomol Struct, 31, 45 (2002)

View on Pith 2002

[84] [84]

Sali, A., Target practice, Nat Struct Biol, 8, 482 (2001)

View on Pith 2001

[85] [85]

Vitkup, D., Melamud, E., Moult, J., and Sander, C., Completeness in structural genomics, Nat Struct Biol, 8, 559 (2001)

View on Pith 2001

[86] [86]

Galperin, M. Y., Walker, D. R., and Koonin, E. V., Analogous enzymes: independent inventions in enzyme evolution, Genome Res, 8, 779 (1998)

View on Pith 1998

[87] [87]

Wolynes, P. G., Symmetry and the energy landscapes of biomolecules, Proc Natl Acad Sci U S A, 93, 14249 (1996)

View on Pith 1996

[88] [88]

Kussell, E. L., and Shakhnovich, E. I., An alytical approach to the protein design problem, Phys Rev Lett, 83, 4437 (1999)

View on Pith 1999

[89] [89]

England, J. L., Shakhnovich, B. E., and Shakhnovich, E. I., Natural selection of more designable folds: a mechanism for thermophilic adaptation, Proc Natl Acad Sci U S A, 100, 8727 (2003)

View on Pith 2003

[90] [90]

Tiana, G., Shakhnovich, B. E., Dokholya n, N. V., and Shakhnovich, E. I., Imprint of evolution on protein structures, Proc Natl Acad Sci U S A, 101, 2846 (2004)

View on Pith 2004

[91] [91]

Shakhnovich, B. E., Deeds, E., Delisi, C., and Shakhnovich, E., Protein structure and evolutionary history determine sequence space topology, Genome Res, 15, 385 (2005)

View on Pith 2005

[92] [92]

Giribet, G., Current advances in th e phylogenetic reconstruction of metazoan evolution. A new paradigm for the Cambrian explosion?, Mol Phylogenet Evol, 24, 345 (2002)

View on Pith 2002

[93] [93]

Woese, C. R., and Fox, G. E., Phylogene tic structure of the prokaryotic domain: the primary kingdoms, Proc Natl Acad Sci U S A, 74, 5088 (1977)

View on Pith 1977

[94] [94]

Woese, C. R., Kandler, O., and Wheelis , M. L., Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya, Proc Natl Acad Sci U S A, 87, 4576 (1990)

View on Pith 1990

[95] [95]

Doolittle, W. F., and Brown, J. R., Tem po, mode, the progenote, and the universal root, Proc Natl Acad Sci U S A, 91, 6721 (1994)

View on Pith 1994

[96] [96]

Baldauf, S. L., The deep roots of eukaryotes, Science, 300, 1703 (2003)

View on Pith 2003

[97] [97]

Wolf, Y. I., Rogozin, I. B., Grishin, N. V., and Koonin, E. V., Genome trees and the tree of life, Trends Genet, 18, 472 (2002)

View on Pith 2002

[98] [98]

Cole, J. R., Chai, B., Marsh, T. L., Farris, R. J., Wang, Q., Kulam, S. A., Chandra, S., McGarrell, D. M., Schmidt, T. M., Garrity, G. M., and Tiedje, J. M., The Ribosomal Database Project (RDP-II): previewing a new autoaligner that allows 78 regular updates and the new prokaryotic taxonomy, Nucleic Acids Res, 31, 442 (2003)

View on Pith 2003

[99] [99]

Tatusov, R. L., Natale, D. A., Garkavtse v, I. V., Tatusova, T. A., Shankavaram, U. T., Rao, B. S., Kiryutin, B., Galperin, M. Y., Fedorova, N. D., and Koonin, E. V., The COG database: new developments in phylogenetic classification of proteins from complete genomes, Nucleic Acids Res, 29, 22 (2001)

View on Pith 2001

[100] [100]

Brown, J. R., Douady, C. J ., Italia, M. J., Marshall, W. E., and Stanhope, M. J., Universal trees based on large combined protein sequence data sets, Nat Genet, 28, 281 (2001)

View on Pith 2001

[101] [101]

Wolf, Y. I., Rogozin, I. B., Grishin, N. V., Tatusov, R. L., and Koonin, E. V., Genome trees constructed using five different approaches suggest new major bacterial clades, BMC Evol Biol, 1, 8 (2001)

View on Pith 2001

[102] [102]

Nesbo, C. L., L'Haridon, S., Stetter, K. O., and Doolittle, W. F., Phylogenetic analyses of two "archaeal" genes in thermotoga maritima reveal multiple transfers between archaea and bacteria, Mol Biol Evol, 18, 362 (2001)

View on Pith 2001

[103] [103]

Jain, R., Rivera, M. C., and Lake, J. A ., Horizontal gene transfer among genomes: the complexity hypothesis, Proc Natl Acad Sci U S A, 96, 3801 (1999)

View on Pith 1999

[104] [104]

Lawrence, J. G., Gene transfer, spec iation, and the evolution of bacterial genomes, Curr Opin Microbiol, 2, 519 (1999)

View on Pith 1999

[105] [105]

Korbel, J. O., Snel, B., Huynen, M. A., and Bork, P., SHOT: a web server for the construction of genome phylogenies, Trends Genet, 18, 158 (2002)

View on Pith 2002

[106] [106]

Fitz-Gibbon, S. T., and House, C. H., Whole genome-based phylogenetic analysis of free-living microorganisms, Nucleic Acids Res, 27, 4218 (1999)

View on Pith 1999

[107] [107]

House, C. H., and Fitz-Gibbon, S. T., Using homolog groups to create a whole- genomic tree of free-living organisms: an update, J Mol Evol, 54, 539 (2002)

View on Pith 2002

[108] [108]

Brown, J. R., and Doolittle, W. F., Archaea and the prokaryote-to-eukaryote transition, Microbiol Mol Biol Rev, 61, 456 (1997)

View on Pith 1997

[109] [109]

Dutilh, B. E., Huynen, M. A., Bruno, W. J., and Snel, B., The consistent phylogenetic signal in genome trees revealed by reducing the impact of noise, J Mol Evol, 58, 527 (2004)

View on Pith 2004

[110] [110]

Clarke, G. D., Beiko, R. G., Ragan, M. A., and Charlebois, R. L., Inferring genome trees by using a filter to eliminate phylogenetically discordant sequences and a distance matrix based on mean normalized BLASTP scores, J Bacteriol, 184, 2072 (2002)

View on Pith 2002

[111] [111]

Nesbo, C. L., Boucher, Y., and Doolittle, W. F., Defining the core of nontransferable prokaryotic genes: the euryarchaeal core, J Mol Evol, 53, 340 (2001)

View on Pith 2001

[112] [112]

Lin, J., and Gerstein, M., Whole-genome trees based on the occurrence of folds and orthologs: implications for comparing genomes on different levels, Genome Res, 10, 808 (2000)

View on Pith 2000

[113] [113]

Caetano-Anolles, G., and Caetano-Anolle s, D., An evolutionarily structured universe of protein architecture, Genome Res, 13, 1563 (2003)

View on Pith 2003

[114] [114]

Deeds, E. J., Hennessey, H., and Sha khnovich, E. I., Prokaryotic phylogenies inferred from protein structural domains, Genome Res, 15, 393 (2005)

View on Pith 2005

[115] [115]

Farris, J. S., Phylogenetic analysis under Dollo's Law, Syst Zool, 26, 77 (1977). 79

View on Pith 1977

[116] [116]

Swofford, D. L., Paup*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4, Sinauer Associates, Sunderland, Massachusetts (2003)

View on Pith 2003

[117] [117]

Mirkin, B. G., Fenner, T. I., Galperi n, M. Y., and Koonin, E. V., Algorithms for computing parsimonious evolutionary scenarios for genome evolution, the last universal common ancestor and dominance of horizontal gene transfer in the evolution of prokaryotes, BMC Evol Biol, 3, 2 (2003)

View on Pith 2003

[118] [118]

Saitou, N., and Nei, M., The nei ghbor-joining method: a new method for reconstructing phylogenetic trees, Mol Biol Evol, 4, 406 (1987)

View on Pith 1987

[119] [119]

Yang, S., Doolittle, R. F., and Bourne, P. E., Phylogeny determined by protein domain content, Proc Natl Acad Sci U S A, 102, 373 (2005)

View on Pith 2005

[120] [120]

Gough, J., Karplus, K., Hughey, R., and C hothia, C., Assignment of homology to genome sequences using a library of hidden Markov models that represent all proteins of known structure, J Mol Biol, 313, 903 (2001)

View on Pith 2001