Configurational-bias sampling technique for predicting side-chain conformations in proteins.
Prediction of side-chain conformations is an important component of several biological modeling applications. In this work, we have developed and tested an advanced Monte Carlo sampling strategy for predicting side-chain conformations. Our method is based on a cooperative rearrangement of atoms that belong to a group of neighboring side-chains. This rearrangement is accomplished by deleting groups of atoms from the side-chains in a particular region, and regrowing them with the generation of trial positions that depends on both a rotamer library and a molecular mechanics potential function. This method allows us to incorporate flexibility about the rotamers in the library and explore phase space in a continuous fashion about the primary rotamers. We have tested our algorithm on a set of 76 proteins using the all-atom AMBER99 force field and electrostatics that are governed by a distance-dependent dielectric function. When the tolerance for correct prediction of the dihedral angles is a <20 degrees deviation from the native state, our prediction accuracies for chi1 are 83.3% and for chi1 and chi2 are 65.4%. The accuracies of our predictions are comparable to the best results in the literature that often used Hamiltonians that have been specifically optimized for side-chain packing. We believe that the continuous exploration of phase space enables our method to overcome limitations inherent with using discrete rotamers as trials.
Jain
Tushar
T
Howard Hughes Medical Institute, University of California, San Diego, CA 92093-0365, USA. tjain@mccammon.ucsd.edu
Cerutti
David S
DS
McCammon
J Andrew
JA
D015982:Bias; D003198:Computer Simulation; D016208:Databases, Factual; D008958:Models, Molecular; D009010:Monte Carlo Method; D011237:Predictive Value of Tests; D011487:Protein Conformation; D015203:Reproducibility of Results