ArticlePeerJ2015
Too packed to change: side-chain packing and site-specific substitution rates in protein evolution.
Article in PeerJ, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- CONSTRUCT: an algorithmic tool for identifying functional or structurally important regions in protein tertiary structure.Bioinformatics (Oxford, England) · 2025Article
- Improved prediction of site-rates from structure with averaging across homologs.Protein science : a publication of the Protein Society · 2024Article
- Toxic Determination of Cry11 Mutated Proteins Obtained Using Rational Design and Its Computational Analysis.International journal of molecular sciences · 2023Article
- ZINC40099027 promotes monolayer circular defect closure by a novel pathway involving cytosolic activation of focal adhesion kinase and downstream paxillin and ERK1/2.Cell and tissue research · 2022Article
- Evolution of Amino Acid Propensities under Stability-Mediated Epistasis.Molecular biology and evolution · 2022Article
- Evolutionary coupling range varies widely among enzymes depending on selection pressure.Biophysical journal · 2021Article
- Quantifying evolutionary importance of protein sites: A Tale of two measures.PLoS genetics · 2021Article
- Computational reconstruction of atomistic protein structures from coarse-grained models.Computational and structural biotechnology journal · 2020Review
- Fitness Effects of Single Amino Acid Insertions and Deletions in TEM-1 β-Lactamase.Journal of molecular biology · 2019Article
- The Site-Specific Amino Acid Preferences of Homologous Proteins Depend on Sequence Divergence.Genome biology and evolution · 2019Article
- Using Pseudoenzymes to Probe Evolutionary Design Principles of Enzymes.Evolutionary bioinformatics online · 2019Article
- Article
- Beyond Thermodynamic Constraints: Evolutionary Sampling Generates Realistic Protein Sequence Variation.Genetics · 2018Article
- Biophysical Models of Protein Evolution: Understanding the Patterns of Evolutionary Sequence Divergence.Annual review of biophysics · 2017Review
- Computational prediction of the tolerance to amino-acid deletion in green-fluorescent protein.PloS one · 2017Article
- Measuring evolutionary rates of proteins in a structural context.F1000Research · 2017Article
- Alpha Helices Are More Robust to Mutations than Beta Strands.PLoS computational biology · 2016Article
- Quantifying side-chain conformational variations in protein structure.Scientific reports · 2016Article
- Intermediate divergence levels maximize the strength of structure-sequence correlations in enzymes and viral proteins.Protein science : a publication of the Protein Society · 2016Article
- Dissecting the roles of local packing density and longer-range effects in protein sequence evolution.Proteins · 2016Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In protein evolution, due to functional and biophysical constraints, the rates of amino acid substitution differ from site to site. Among the best predictors of site-specific rates are solvent accessibility and packing density. The packing density measure that best correlates with rates is the weighted contact number (WCN), the sum of inverse square distances between a site's C α and the C α of the other sites. According to a mechanistic stress model proposed recently, rates are determined by packing because mutating packed sites stresses and destabilizes the protein's active conformation. While WCN is a measure of C α packing, mutations replace side chains. Here, we consider whether a site's evolutionary divergence is constrained by main-chain packing or side-chain packing. To address this issue, we extended the stress theory to model side chains explicitly. The theory predicts that rates should depend solely on side-chain contact density. We tested this prediction on a data set of structurally and functionally diverse monomeric enzymes. We compared side-chain contact density with main-chain contact density measures and with relative solvent accessibility (RSA). We found that side-chain contact density is the best predictor of rate variation among sites (it explains 39.2% of the variation). Moreover, the independent contribution of main-chain contact density measures and RSA are negligible. Thus, as predicted by the stress theory, site-specific evolutionary rates are determined by side-chain packing.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.