Site-specific structure and stability constrained substitution models improve phylogenetic inference

In previous studies, we presented site-specific substitution models of protein evolution based on selection on the folding stability of the native state (Stab-CPE), which predict more realistically the evolutionary variability across protein sites. However, those Stab-CPE present qualitative differences from observed data, probably because they ignore changes in the native structure, despite empirical studies suggesting that conservation of the native structure is a stronger selective force than selection on folding stability. 
Here we present novel structurally constrained substitution models (Str-CPE) based on Julian Echave's model of the structural change due to a mutation as the linear response of the protein to a perturbation and on the explicit model of the perturbation generated by a specific amino-acid mutation. Compared to our previous Stab-CPE models, the novel Str-CPE models are more stringent (they predict lower sequence entropy and substitution rate), provide higher likelih..., The data were generated by the programs tnm (torsional network model, Mendez and Bastolla 2010) and Prot_evol, whose last version is presented in the paper related with the dataset., The files are text files that can be open with any text editor., # SSCPE

This repository contains programs and data used for calibrating and testing the Structure and stability constrained protein evolution (SSCPE) substitution models computed by the program Prot_evol [https://github.com/ugobas/Prot_evol](https://github.com/ugobas/Prot_evol)

The program Prot_evol takes as input a list of protein structures (PDB files) and a multiple sequence alignment (MSA) at the amino acid level. It can be run directly through the framework SSCPE.pl, which computes the site-specific substitution models with Prot_evol and input them to the program RAxML-NG (Kozlov AM, Darriba D, Flouri T, Morel B, Stamatakis A. 2019. RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics 35: 4453-4455) for inferring maximum likelihood phylogenetic trees.

We adopted 3 data sets: 203 monomeric proteins with known structure and 10-300 sequences MSAs for which we computed the SSCPE models, a selection of 10 of these proteins f...