Parallel cascade selection molecular dynamics to screen for protein complexes generated by rigid docking.
J Mol Graph Model
; 92: 94-99, 2019 11.
Article
em En
| MEDLINE
| ID: mdl-31344548
ABSTRACT
We propose a flexible docking simulation based on parallel cascade selection molecular dynamics (PaCS-MD) as a post-processing treatment after a rigid docking simulation. PaCS-MD has been proposed as an enhanced sampling method for generating structural transition pathways from a given reactant to a product. The PaCS-MD cycle consists of the following two steps:
(1) selections of important initial structures and (2) their conformational resampling from the selected initial structures. By repeating the conformational resampling from the important initial structures, structural transitions from the reactant to the product are gradually promoted. In the present flexible docking simulation, decoys (protein complexes) are generated by the rigid docking simulation a priori and employed as products of PaCS-MD. Then PaCS-MD is applied to reproduce association processes to the decoys from a reactant (completely separated proteins). To judge whether PaCS-MD found the association processes or not, the root-mean-square deviation measured from decoy (RMSDdecoy) was defined and monitored during the PaCS-MD cycles. By checking the RMSDdecoy values, a set of decoys is screened as a non-near native protein complex. In more detail, PaCS-MD detects near native protein complexes from the generated decoys by imposing a threshold (cutoff) for RMSDdecoy, i.e. RMSDdecoyâ¯<â¯cutoff. As a demonstration, the present flexible docking addressed dimerization processes of K48-linked ubiquitin dimer without a covalent bond between its monomers. Finally, PaCS-MD screened out non-near native protein complexes from decoys generated by a rigid docking simulation.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Proteínas
/
Complexos Multiproteicos
/
Simulação de Dinâmica Molecular
/
Simulação de Acoplamento Molecular
Idioma:
En
Revista:
J Mol Graph Model
Assunto da revista:
BIOLOGIA MOLECULAR
Ano de publicação:
2019
Tipo de documento:
Article