Tabu Search Based Strategies for Conformational Search

This paper presents an application of the new nonlinear global optimization routine gradient only tabu search (GOTS) to conformational search problems. It is based on the tabu search strategy which tries to determine the global minimum of a function by the steepest descent-modest ascent strategy. The refinement of ranking procedure of the original GOTS method and the exploitation of simulated annealing elements are described, and the modifications of the GOTS algorithm necessary to adopt it to conformation searches are explained. The utility of the GOTS for conformational search problems is tested using various examples.