Learning probabilistic models of hydrogen bond stability from molecular dynamics simulation trajectories.

ABSTRACT:

Background

Hydrogen bonds (H-bonds) play a key role in both the formation and stabilization of protein structures. They form and break while a protein deforms, for instance during the transition from a non-functional to a functional state. The intrinsic strength of an individual H-bond has been studied from an energetic viewpoint, but energy alone may not be a very good predictor.

Methods

This paper describes inductive learning methods to train protein-independent probabilistic models of H-bond stability from molecular dynamics (MD) simulation trajectories of various proteins. The training data contains 32 input attributes (predictors) that describe an H-bond and its local environment in a conformation c and the output attribute is the probability that the H-bond will be pre

SUBMITTER: Chikalov I 

PROVIDER: S-EPMC3044290 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature