MMCG: A MONTE CARLO AND METROPOLIS BASED CONFORMER GENERATION TOOL FOR FLEXIBLE DOCKING OF SMALL MOLECULES

Abstract

Drug designing is one of the major thrust area of research these days as it deals with discovery of inhibitors or leads for proteins or targets responsible for various medical conditions. In quest of search for new leads for targets- in sillico drug designing has emerged as very efficient system. Molecular flexibility is one of the well known problems in computer aided drug designing as while mimicking biological system using in sillico approach we have to take in consideration that the molecules do not act as rigid structures moreover there is fluidity of system also which provides some degree of flexibility to the molecules. Up till know many docking softwares have been developed which accounts for molecular flexibility but the needed accuracy that is close to bound form of protein is achieved in very limited cases. Here we introduce a new approach to incorporate ligand flexibility in molecular docking system using monte-carlo metropolis simulations. This system produces 100 conformational decoys from a starting structure by random translational and rotational moves and deciding on their acceptance using the Metropolis criterion. The configurational search space is described using ParDOCK- all atom energy-based Monte Carlo, protein-ligand docking algorithm for rigid docking. Structures with most appropriate conformations and respective configurations are picked through our system to produce results as output. The results produced are further refined by minimization of complex using AMBER10 module. Through this approach we are able to capture conformers having RMSD < 2 Å as compared to the bound form of complex.