How to improve the modelling of proteins mutations? A preliminary assessment

Department of Chemistry and Biology "A. Zambelli", University of Salerno, Fisciano, Italy
DOI
10.7287/peerj.preprints.27326v1
Subject Areas
Biochemistry, Bioinformatics, Computational Biology
Keywords
protein, modelling, structures, mutations
Copyright
© 2018 Napoli et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Napoli C, Marabotti A. 2018. How to improve the modelling of proteins mutations? A preliminary assessment. PeerJ Preprints 6:e27326v1

Abstract

Several programs have been developed that are able to replace a residue with another one in a protein structure, but usually they are not able to simulate the short- and long-range effects of a real single point mutation. We tested if the approach of re-modelling the entire protein structure of a mutant protein using the wild type structure as a template can correctly reproduce the structural features of mutant proteins. To do this, we selected a benchmark of 4 different families of proteins for which a large group of mutants are available in the PDB database and we used MODELLER by applying different modelling strategies. Our results showed that different starting templates of the same wild type protein can affect the structures of the mutants, and that often structural peculiarities attributed to the effect of the mutations are strictly related to low quality electron density or alterations in the quality parameters used to evaluate the proteins. In general, the standard modelling procedure allows creating mutants more similar to the wild type protein than to the mutant one, but we devised possible suggestions to improve the ability of this approach to predict the effects of mutations on protein structure.

Author Comment

This is an abstract which has been accepted for the BBCC2018 Conference