Computer-aided molecular docking represents an important approach to identify more biologically active chemical species for drug design.Ligand-protein inverse docking allows docking small molecule into a number of biological targets giving optimized conformation. The aim of this study is to find and select possible biological targets for such nanoparticles as fullerene derivatives, and then compile potentially active and/or toxic fullerene derivatives that have high binding affinity with chosen targets (protein molecules) for further analysis.  In current study, different computational approaches such as quantum-mechanical studies and a series of docking simulations are carried out to evaluate the protein binding sites with optimal binding affinity for fullerene derivatives. Linux-based PatchDock program is used first to rank quantum-chemically optimized fullerene derivatives as potentially bioactive ligands. Then Schr�dinger Suite is utilized for selected top ranked ligands to obtain ligand-protein binding energy and possible binding interactions. In result, the database of potential biological targets for fullerene nanoparticles will be created with calculated binding affinities. This can be extremely helpful in drug discovery and structural design of fullerene-like drug agents.

Computational profiling of fullerene nanoparticles for biological targets: Ligand-protein inverse docking

247th National Meeting (2014)

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