The effects of biasing torsional mutations in a conformational GA

This paper describes the effects of incorporating torsional bias into a conformational Genetic Algorithm (GA) such as that found in the GASP program. Several major conclusions can be drawn. Biasing torsional angles toward values associated with local energy minima increases the rate of convergence of the fitness function (consisting of energy, steric, and pharmacophoric compatibility terms) for a set of molecules, but a definite tradeoff exists between total model energy and the steric and pharmacophoric compatibility terms in the fitness score. Biasing torsions in favor of sets of angles drawn from low-energy conformations does not guarantee low total energy, but biased torsional sampling does generally produce less strained models than does the uniform torsional sampling in classical GASP. Overall, torsionally biased sampling produces good models comprised of energetically favorable ligand conformations.