Building protein structure-specific rotamer libraries

Author:

Grybauskas Algirdas1ORCID,Gražulis Saulius1ORCID

Affiliation:

1. Sector of Crystallography and Cheminformatics, Institute of Biotechnology, Life Sciences Center, Vilnius University , 7 Saulėtekio Ave , Vilnius, LT- 10257, Lithuania

Abstract

Abstract Motivation Identifying the probable positions of the protein side-chains is one of the protein modelling steps that can improve the prediction of protein–ligand and protein–protein interactions. Most of the strategies predicting the side-chain conformations use predetermined dihedral angle lists, also called rotamer libraries, that are usually generated from a subset of high-quality protein structures. Although these methods are fast to apply, they tend to average out geometries instead of taking into account the surrounding atoms and molecules and ignore structures not included in the selected subset. Such simplifications can result in inaccuracies when predicting possible side-chain atom positions. Results We propose an approach that takes into account both of these circumstances by scanning through sterically accessible side-chain conformations and generating dihedral angle libraries specific to the target proteins. The method avoids the drawbacks of lacking conformations due to unusual or rare protein structures and successfully suggests potential rotamers with average RMSD closer to the experimentally determined side-chain atom positions than other widely used rotamer libraries. Availability and implementation The technique is implemented in open-source software package rotag and available at GitHub: https://www.github.com/agrybauskas/rotag, under GNU Lesser General Public License.

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference40 articles.

1. mixtools: an r package for analyzing mixture models;Benaglia;J Stat Softw,2010

2. Announcing the worldwide Protein Data Bank;Berman;Nat Struct Biol,2003

3. The macromolecular crystallographic information file (mmCIF);Bourne;Methods Enzymol,1997

4. Molecular dynamics-derived rotamer libraries for d-amino acids within homochiral and heterochiral polypeptides;Childers;Protein Eng Des Sel,2018

5. Macromolecular modeling with rosetta;Das;Annu Rev Biochem,2008

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