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Building protein structure-specific rotamer libraries.
Grybauskas, Algirdas; Grazulis, Saulius.
Afiliação
  • Grybauskas A; Sector of Crystallography and Cheminformatics, Institute of Biotechnology, Life Sciences Center, Vilnius University, 7 Sauletekio Ave, Vilnius, LT- 10257, Lithuania.
  • Grazulis S; Sector of Crystallography and Cheminformatics, Institute of Biotechnology, Life Sciences Center, Vilnius University, 7 Sauletekio Ave, Vilnius, LT- 10257, Lithuania.
Bioinformatics ; 39(7)2023 07 01.
Article em En | MEDLINE | ID: mdl-37439702
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Proteínas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Proteínas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article