Performance of An All-Atom Free Energy Approach For Protein Structure Prediction

Abstract

With the completion of sequencing efforts for many important genomes, protein structure and function prediction, emerge as important challenges. Physics-based or forcefield-based methods, which were initially believed to hold great promise for protein structure prediction, now play only a marginal role in the biannual comparative assessment of methods for protein structure prediction (CASP). Most of the models submitted to this computational experiment presently originate from similarity-based methods however structure prediction for low-homology targets leave significant room for improvement. Here we present some of the results from CASP9, were we combine physics based methods along with homology modeling. However, in case of low homology targets we generated libraries comprising of 10,000-20,000 decoys using the standard ROSETTA fragment assembly protocol and then energy-ranked using the POEM≅HOME, which explores the free-energy surface in many parallel Monte-Carlo random walks, the conformation which is near the native conformations from the large set of decoys was reliably selected.Some experimental structures of CASP9 targets have been released till date and the comparisons of our predictions are encouraging.