ArticleProteins2018
A new parameter-rich structure-aware mechanistic model for amino acid substitution during evolution.
Article in Proteins, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 9 citations in OpenAlex.
- A review of visualisations of protein fold networks and their relationship with sequence and function.Biological reviews of the Cambridge Philosophical Society · 2023Review
- Ancestral Sequence Reconstruction: From Chemical Paleogenetics to Maximum Likelihood Algorithms and Beyond.Journal of molecular evolution · 2021Article
- Characterizing lineage-specific evolution and the processes driving genomic diversification in chordates.BMC evolutionary biology · 2020Article
- mtProtEvol: the resource presenting molecular evolution analysis of proteins involved in the function of Vertebrate mitochondria.BMC evolutionary biology · 2019Article
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
Improvements in the description of amino acid substitution are required to develop better pseudo-energy-based protein structure-aware models for use in phylogenetic studies. These models are used to characterize the probabilities of amino acid substitution and enable better simulation of protein sequences over a phylogeny. A better characterization of amino acid substitution probabilities in turn enables numerous downstream applications, like detecting positive selection, ancestral sequence reconstruction, and evolutionarily-motivated protein engineering. Many existing Markov models for amino acid substitution in molecular evolution disregard molecular structure and describe the amino acid substitution process over longer evolutionary periods poorly. Here, we present a new model upgraded with a site-specific parameterization of pseudo-energy terms in a coarse-grained force field, which describes local heterogeneity in physical constraints on amino acid substitution better than a previous pseudo-energy-based model with minimum cost in runtime. The importance of each weight term parameterization in characterizing underlying features of the site, including contact number, solvent accessibility, and secondary structural elements was evaluated, returning both expected and biologically reasonable relationships between model parameters. This results in the acceptance of proposed amino acid substitutions that more closely resemble those observed site-specific frequencies in gene family alignments. The modular site-specific pseudo-energy function is made available for download through the following website: https://liberles.cst.temple.edu/Software/CASS/index.html.
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Registered trials
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