Thursday 6th June, 2013
11:30am to 12:00pm
Understanding protein and/or ligand hydration state is helpful for drug discovery process. Recently, several application tools such as SZMAP@OpenEye, WaterMap@Schrödinger, and 3D-RISM@CCG were released and applied to drug discovery. We propose a new virtual screening method based on solvent dipole ordering (SDO), called SDOVS. SDO is one of the physical quantity that charactalized hydration structure that is proposed by Higo and Nakasako. It originated that solvent dipole is the time-averaged picture as to the orientational ordering of water molecules around the protein and the SDO might be related to molecular recognition of the ligand by protein.
At first, FK506 binding protein (FKBP) and dihydrofolate reductase (DHFR) were selected as model proteins and run short time MD simulations (ca. 600 ps) that filled water molecules within ligand binding pocked and calculated the solvent dipoles from their trajectories. The high SDO region and the 3D ligand shapes were good overlapped each other. Especially, in the case of the FKBP, various size of the 3D ligand shape was projected according to the strength of SDO. Thus, the SDO region within ligand binding site might be useful to predict the preferred molecular shape of ligands. Then, we considered the results of SDO analysis was applicable to virtual screening. A number of pseudo-molecules, which consists of sp3 carbon skeleton, were generated by tracing the high SDO region. Then these pseudo-molecules were converted to a ROCS shape query and tried to a solvent dipole ordering-based virtual screening (SDOVS). Four typical drug target proteins (CDK2, PDE5, ALR2, and ENR) were selected and compared the performance of SDOVS with FRED which is a well known rigid docking tool. As a result, SDOVS could obtain more diverse compound structures than FRED. The advantages of SDOVS are: 1) SDO cover whole ligand binding site, 2) easy to obtain flexible compounds, 3) applicable without real active molecules, and so on.
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