Validating a Coarse-Grained Potential Energy Function through Protein Loop Modelling.

ABSTRACT: Coarse-grained (CG) methods for sampling protein conformational space have the potential to increase computational efficiency by reducing the degrees of freedom. The gain in computational efficiency of CG methods often comes at the expense of non-protein like local conformational features. This could cause problems when transitioning to full atom models in a hierarchical framework. Here, a CG potential energy function was validated by applying it to the problem of loop prediction. A novel method to sample the conformational space of backbone atoms was benchmarked using a standard test set consisting of 351 distinct loops. This method used a sequence-independent CG potential energy function representing the protein using [Formula: see text]-carbon positions only and sampling conformations w

SUBMITTER: Macdonald JT 

PROVIDER: S-EPMC3688807 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature