Abstract

An efficient automatic method has been developed for docking a ligand molecule to a protein molecule. The method can construct energetically favorable docking models, considering specific interactions between the two molecules and conformational flexibility in the ligand. In the first stage of docking, likely binding modes are searched and estimated effectively in terms of hydrogen bonds, together with conformations in part of the ligand structure that includes hydrogen bonding groups. After that part is placed in the protein cavity and is optimized, conformations in the remaining part are also examined systematically. Finally, several stable docking models are obtained after optimization of the position, orientation and conformation of the whole ligand molecule. In all the screening processes, the total potential energy including intra- and intermolecular interaction energy, consisting of van der Waals, electrostatic and hydrogen bonding energies, is used as the index. The characteristics of our docking method are high accuracy of the results, fully automatic generation of models and short computational time. The efficiency of the method was confirmed by four docking trials using two enzyme systems. In two attempts to dock methotrexate to dihydrofolate reductase and 2′-GMP to ribonuclease T 1, the exact structures of complexes in crystals were reproduced as the most stable docking models, without any assumptions concerning the binding modes and ligand conformations. The most stable docking models of dihydrofolate and trimethoprim, respectively, to dihydrofolate reductase were also in good agreement with those suggested by experiment. In all test cases, it was shown that our method can accurately predict the correct docking structures, discriminating the correct model from incorrect one. The efficiency of our method was further tested from the viewpoint of ability to predict the relative stability of the docking structures of two triazine derivatives to dihydrofolate reductase. Our docking method provides a useful tool for rational drug design and investigations of biochemical reaction mechanisms.

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