Enhancing backbone sampling in Monte Carlo simulations using internal coordinates normal mode analysis

被引:1
作者
Gil, Victor A. [1 ]
Lecina, Daniel [1 ]
Grebner, Christoph [2 ]
Guallar, Victor [1 ,3 ]
机构
[1] Barcelona Supercomp Ctr, Joint BSC CRG IRB Res Program Computat Biol, Barcelona 08034, Spain
[2] AstraZeneca, CVMD iMed, Dept Med Chem, S-43183 Molndal, Sweden
[3] ICREA, Passeig Lluis Companys 23, E-08010 Barcelona, Spain
关键词
Internal coordinates; Normal mode analysis; Monte Carlo; Flexibility sampling; MOLECULAR-DYNAMICS SIMULATIONS; GENERALIZED BORN MODEL; ELASTIC NETWORK MODEL; PROTEIN-STRUCTURE; CONFORMATIONAL TRANSITIONS; PRINCIPAL COMPONENT; CRYSTAL-STRUCTURE; DIHEDRAL ANGLES; LIGAND-BINDING; FORCE-FIELDS;
D O I
10.1016/j.bmc.2016.07.001
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Normal mode methods are becoming a popular alternative to sample the conformational landscape of proteins. In this study, we describe the implementation of an internal coordinate normal mode analysis method and its application in exploring protein flexibility by using the Monte Carlo method PELE. This new method alternates two different stages, a perturbation of the backbone through the application of torsional normal modes, and a resampling of the side chains. We have evaluated the new approach using two test systems, ubiquitin and c-Src kinase, and the differences to the original ANM method are assessed by comparing both results to reference molecular dynamics simulations. The results suggest that the sampled phase space in the internal coordinate approach is closer to the molecular dynamics phase space than the one coming from a Cartesian coordinate anisotropic network model. In addition, the new method shows a great speedup (similar to 5-7 x), making it a good candidate for future normal mode implementations in Monte Carlo methods. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4855 / 4866
页数:12
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