Supercomputer investigation of the protein-ligand system low-energy minima

Oferkin I.V.1, Sulimov A.V.2, Katkova E.V.2 , Kutov D.K.2, Grigoriev F.V.2, Kondakova O.A.2, Sulimov V.B.2

1. Dimonta, Ltd., Moscow, Russia
2. Dimonta, Ltd., Moscow, Russia ; Research Computer Center, Moscow State University, Moscow, Russia
Section: Experimental Study
DOI: 10.18097/PBMC20156106712      PubMed Id: 26716742
Year: 2015  Volume: 61  Issue: 6  Pages: 712-716
The accuracy ofthe protein-ligand binding energy calculations andligand positioning isstrongly influenced by the choice of the docking target function. This work demonstrates the evaluation of the five different target functions used in docking: functions based on MMFF94 force field and functions based on PM7 quantum-chemical method accounting orwithout accounting the implicit solvent model (PCM, COSMO or SGB). For these purposes the ligand positions corresponding to the minima of the target function and the experimentally known ligand positions in the protein active site (crystal ligand positions) were compared. Each function was examined on the same test-set of 16 protein-ligand complexes. The new parallelized docking program FLM based on Monte Carlo search algorithm was developed to perform the comprehensive low-energy minima search and to calculate the protein-ligand binding energy. This study demonstrates that the docking target function based on the MMFF94 force field can be used to detect the crystal or near crystal positions of the ligand by the finding the low-energy local minima spectrum of the target function. The importance of solvent accounting in the docking process for the accurate ligand positioning is also shown. The accuracy of the ligand positioning as well as the correlation between the calculated and experimentally determined protein-ligand binding energies are improved when the MMFF94 force field is substituted by the new PM7 method with implicit solvent accounting.
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Keywords: molecular modeling, docking, force field, quantum chemistry, multiwell approximation, high-performance computing

Oferkin, I. V., Sulimov, A. V., Katkova, E. V., Kutov, D. K., Grigoriev, F. V., Kondakova, O. A., Sulimov, V. B. (2015). Supercomputer investigation of the protein-ligand system low-energy minima. Biomeditsinskaya Khimiya, 61(6), 712-716.
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