Evaluation of the Docking Algorithm Based on Tensor Train Global Optimization

Effectiveness of modern rational new drugs development is connected with accurate modelling of binding between target-proteins responsible for the disease and small molecules (ligands) candidates to become drugs. The main modeling tools are docking programs for positioning of the ligands in the target proteins. Ligand positioning is realized in the frame of the docking paradigm: the ligand binds to the protein in the pose corresponding to the global energy minimum on the complicated multidimensional energy surface of the protein-ligand system. Docking algorithm on the base of the novel method of tensor train global optimization is presented. The respective novel docking program SOL-T is validated on the set of 30 protein-ligand complexes with known 3D structures. The energy of the protein-ligand system is calculated in the frame of MMFF94 force field. SOL-T performance is compared with the results of exhaustive low energy minima search carried out by parallel FLM docking program on the base of Monte Carlo method using large supercomputer resources. It is shown that SOL-T docking program is about 100 times faster than FLM program, and SOL-T is able to find the global minimum (found by FLM docking program) for 50% investigated protein-ligand complexes. Dependence of SOL-T performance on the rank of tensor train decomposition is investigated, and it is shown that SOL-T with rank 16 has almost the same performance as SOL-T with rank 64. It is shown that the docking paradigm is true not for all investigated complexes in the frame of MMFF94 force field.

Keywords

docking; global optimization; tensor train; protein-ligand complex; drug design.

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