ENCoM server: exploring protein conformational space and the effect of mutations on protein function and stability.

Vincent Frappier,Rafael J Najmanovich,Matthieu Chartier

doi:10.1093/nar/gkv343

Abstract

ENCoM is a coarse-grained normal mode analysis method recently introduced that unlike previous such methods is unique in that it accounts for the nature of amino acids. The inclusion of this layer of information was shown to improve conformational space sampling and apply for the first time a coarse-grained normal mode analysis method to predict the effect of single point mutations on protein dynamics and thermostability resulting from vibrational entropy changes. Here we present a web server that allows non-technical users to have access to ENCoM calculations to predict the effect of mutations on thermostability and dynamics as well as to generate geometrically realistic conformational ensembles. The server is accessible at: http://bcb.med.usherbrooke.ca/encom.

Highlights

Proteins are dynamic objects with movements ranging from sub-rotameric side-chain movements to domain movements intrinsically associated to their function
The following properties are common to both techniques: (i) both can be used to explore the conformational space; (ii) may use the same force fields and the accuracy of the simulation depends on the quality of the potential; (iii) both techniques are as exact descriptions of the dynamics as the level of detail of the representation of the protein structure and the force field used permits
The major difference between molecular dynamics (MD) and normal mode analysis (NMA) is that the former produces an actual trajectory in conformational space while the later produces a basis set of movements described as a set of normal modes (Eigenvectors) and associated frequencies (Eigenvalues) with which individual points in conformational space can be sampled

Summary

Introduction

Proteins are dynamic objects with movements ranging from sub-rotameric side-chain movements to domain movements intrinsically associated to their function. As a consequence of the limitations of the sequenceagnostic coarse-grained NMA models on which they are all based, none of the existing servers can be used to predict the effect of mutations on dynamics or stability.

Results

Conclusion