Protein Flexibility and Function

Proteins are intrinsically flexible molecules, thus function is often associated to flexibility. Experimental methods to determine protein flexibility are expensive and often time consuming. Over the past few years an efficient complementing method, molecular dynamics (MD) simulations, more and more proved to be a powerful tool to yield information on protein dynamics. In MD methods, successive conformations of proteins can be calculated using Newton’s law of motion. As a result a trajectory is produced that describes how the positions and velocities of all atoms vary with time. This way important observations can be made, helping to understand proteins, mutations and eventually associated diseases better.

In a large-scale study we try to learn how and to what extent MD simulations can help us understand the effect of Single Nucleotide Polymorphisms (SNPs) on protein flexibility, and thus, function. One main objective is to learn about the advances of additional structural information, compared to sequence-based predictions only that are produced by the SNAP software developed in our lab. For this project we have created a comprehensive dataset including synonymous and non-synonymous SNPs that we have mapped to known PDB structures at different resolutions and sequence identity cutoffs.

This work is done in the context of the SCALALIFE (Scalable Software Services for Life Science) framework, together with Leibnitz-Rechenzentrum (LRZ), facilitating the MD package GROMACS.