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Detalle de: Erratum: Prediction of site-specific amino acid distributions and limits of divergent evolutionary changes in protein sequences (Molecular Biology and Evolution (2005) 22 (630-638) doi:10.1093/molbev/msi116)

Title Erratum: Prediction of site-specific amino acid distributions and limits of divergent evolutionary changes in protein sequences (Molecular Biology and Evolution (2005) 22 (630-638) doi:10.1093/molbev/msi116)
Abstract

We derive an analytic expression for site-specific stationary distributions of amino acids from the structurally constrained neutral (SCN) model of protein evolution with conservation of folding stability. The stationary distributions that we obtain have a Boltzmann-like shape, and their effective temperature parameter, measuring the limit of divergent evolutionary changes at a given site, can be predicted from a site-specific topological property, the principal eigenvector of the contact matrix of the native conformation of the protein. These analytic results, obtained without free parameters, are compared with simulations of the SCN model and with the site-specific amino acid distributions obtained from the Protein Data Bank. These results also provide new insights into how the topology of a protein fold influences its designability, i.e., the number of sequences compatible with that fold. The dependence of the effective temperature on the principal eigenvector decreases for longer proteins, as a possible consequence of the fact that selection for thermodynamic stability becomes weaker in this case.

Apa Reference Porto, M., Roman, H. E., Vendruscolo, M., & Bastolla, U. (2004). Prediction of Site-Specific Amino Acid Distributions and Limits of Divergent Evolutionary Changes in Protein Sequences. Molecular Biology and Evolution, 22(3), 630–638. 10.1093/molbev/msi048
Doi 10.1093/molbev/msi048
Publication Date 10 Nov 2004
Publication Type Article
Researcher Ugo Bastolla
Ontology Functional annotation, Function prediction, Structural bioinformatics, Molecular flexibility, Molecular evolution, Conservation Analysis, Evolutionary modelling, Ecological modelling, Sequence Alignment, Phylogenetic Analysis, Mutation Analysis and design, Network Biology, Structure-function relationship, Evolutionary rates, Microbial communities, Population dynamics
Research Groups Computational biology and Bioinformatics (CBM): from Proteins to Ecosystems
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