title: Intermediate divergence levels maximize the strength of structure-sequence correlations in enzymes and viral proteins.
abstract: Structural properties such as solvent accessibility and contact number predict site-specific sequence variability in many proteins. However, the strength and significance of these structure-sequence relationships vary widely among different proteins, with absolute correlation strengths ranging from 0 to 0.8. In particular, two recent works have made contradictory observations. Yeh et al. (Mol. Biol. Evol. 31:135-139, 2014) found that both relative solvent accessibility (RSA) and weighted contact number (WCN) are good predictors of sitewise evolutionary rate in enzymes, with WCN clearly out-performing RSA. Shahmoradi et al. (J. Mol. Evol. 79:130-142, 2014) considered these same predictors (as well as others) in viral proteins and found much weaker correlations and no clear advantage of WCN over RSA. Because these two studies had substantial methodological differences, however, a direct comparison of their results is not possible. Here, we reanalyze the datasets of the two studies with one uniform analysis pipeline, and we find that many apparent discrepancies between the two analyses can be attributed to the extent of sequence divergence in individual alignments. Specifically, the alignments of the enzyme dataset are much more diverged than those of the virus dataset, and proteins with higher divergence exhibit, on average, stronger structure-sequence correlations. However, the highest structure-sequence correlations are observed at intermediate divergence levels, where both highly conserved and highly variable sites are present in the same alignment.
authors.affiliation: Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, 78712.|Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, 78712.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, 78712.
authors.forename: Eleisha L
authors.initials: EL
authors.lastname: Jackson
authors.affiliation: Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, 78712.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, 78712.|Department of Physics, The University of Texas at Austin, Austin, Texas, 78712.
authors.forename: Amir
authors.initials: A
authors.lastname: Shahmoradi
authors.affiliation: Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, 78712.|Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, 78712.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, 78712.
authors.forename: Stephanie J
authors.initials: SJ
authors.lastname: Spielman
authors.affiliation: Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, 78712.|Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, 78712.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, 78712.
authors.forename: Benjamin R
authors.initials: BR
authors.lastname: Jack
authors.affiliation: Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, 78712.|Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, 78712.|Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, 78712.
authors.forename: Claus O
authors.initials: CO
authors.lastname: Wilke
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods; D004798:Enzymes / Q000737:chemistry* / Q000235:genetics; D019143:Evolution, Molecular; D008958:Models, Molecular; D011487:Protein Conformation; D016415:Sequence Alignment; D012997:Solvents / Q000737:chemistry; D014764:Viral Proteins / Q000737:chemistry* / Q000235:genetics
chemical_list: D004798:Enzymes; D012997:Solvents; D014764:Viral Proteins
keywords: packing density; protein design; protein evolution; relative solvent accessibility; site variability