The study presents two new nonlinear global optimization routines; the Gradient Only Tabu Search (GOTS) and the Tabu Search with Powell's Algorithm (TSPA). They are based on the Tabu-Search strategy, which tries to determine the global minimum of a function by the steepest descent-mildest ascent strategy. The new algorithms are explained and their efficiency is compared with other approaches by determining the global minima of various well-known test functions with varying dimensionality. These tests show that for most tests the GOTS possesses a much faster convergence than global optimizer taken from the literature. The efficiency of the TSPA compares to the efficiency of genetic algorithms.

Efficient conformational search or sampling approaches play an integral role in molecular modeling, leading to a strong demand for even faster and more reliable conformer search algorithms. This article compares the efficiency of a molecular dynamics method, a simulated annealing method, and the basin hopping (BH) approach (which are widely used in this field) with a previously suggested tabu-search-based approach called gradient only tabu search (GOTS). The study emphasizes the success of the GOTS procedure and, more importantly, shows that an approach which combines BH and GOTS outperforms the single methods in efficiency and speed. We also show that ring structures built by a hydrogen bond are useful as starting points for conformational search investigations of peptides and organic ligands with biological activities, especially in structures that contain multiple rings.

This paper presents a modification of the tabu search called gradient tabu search (GTS). It uses analytical gradients for a fast minimization to the next local minimum and analytical diagonal elements of the Hessian to escape local minima. For an efficient blocking of already visited areas tabu regions and tabu directions are introduced into the tabu list (TL). Trials with various well-known test functions indicate that the GTS is a very promising approach to determine local and global minima of differentiable functions. Possible application areas could be optimization routines for force field parameters or conformational searches for large molecules.

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.

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