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° deviation from the native state, our prediction accuracies for χ₁ are 83.3% and for χ₁ and χ₂ 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.