Pareto-Based Optimal Sampling Method and Its Applications in Protein Structural Conformation Sampling

Efficiently sampling the protein conformation space is a critical step in de novo protein structure modeling. One of the important challenges in sampling is the inaccuracy of available scoring functions, i.e., a scoring function is not always sufficiently accurate to distinguish the correct conformations from the alternatives and thereby exploring the very minimum of a scoring function does not necessary reveal correct conformations. In this paper, we present a Pareto optimal sampling (POS) method to address the inaccuracy problem of scoring functions. The POS method adopts a new computational sampling strategy by exploring diversified conformations on the Pareto optimal front in the function space consisted of multiple scoring functions, representing consensus with different trade-offs among multiple scoring functions. Our computational results in protein loop structure sampling and protein backbone structure sampling have demonstrated the effectiveness of the POS method, where near-natives are found in the ensemble of Pareto-optimal conformations.