Parallel Multi-objective GA Based Rotamer Optimization on Grid

Side-chain positioning is a central component of homology modeling and protein design. A simple solution is introduced by assuming a fixed backbone and discretizing the amino acid side-chain conformations into energetically favorable rotamers. For each possible combination of rotamers, an energy function is used to evaluate its fitness for the target conformation. While constructing complete energy functions, the energy terms are linear combined and optimized as one single criterion, this strategy is simple but may undermine the potential solutions. We propose a parallel multi-objective GA based rotamer optimization on grid. The experimental results show that grid-based parallel computing and sub-populations methodology enrich the valid solutions, also shorten the optimization time.