Molecular Recognition of Proteins and Ligand Design

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DESCRIPTION (provided by applicant): The primary goal of the research is to develop and use computational tools to make quantitative predictions on the structure, reactivity and inhibition of proteins. Sophisticated software is being created for drug design with specific applications to cancer, arthritis, bacterial infections, sleep disorders, and Parkinson's disease. The research includes fundamental advances in the development of methods and software for modeling proteins and features applications on protein-ligand binding, inhibitor design, protein folding, and enzymatic reactions. Atomic-level computer simulations are the primary tool at three levels of complexity: a scoring function approach with the GenMol program, which can rapidly build combinatorial libraries of protein-ligand complexes, and extended linear response (ELR) and rigorous free-energy perturbation (FEP) calculations using Monte Carlo statistical mechanics (MC). The MC simulations are performed for the protein-ligand complexes in the presence of explicit water molecules and involve sampling of all degrees of freedom for the systems. The resultant detailed structural and energetic information helps elucidate variations in binding affinities as either the structure of the ligand or the protein sequence is modified. In turn, this knowledge forms the basis for the design of high-affinity, protein-selective ligands. In order to refine the predictive abilities of the methods, training and testing will use a database of ca. 2000 protein-ligand complexes with known activity data for analog series. Specific extensive studies of protein-ligand binding and drug-lead optimization are targeted for several proteins including CDK2 kinase, cyclooxygenases, DNA gyrase, and fatty acid amide hydrolase. The drug design is enhanced by application of the QikProp program, which analyzes the drug-likeness of input organic molecules through estimation of pharmaceutically relevant properties including aqueous solubility, cell permeabilities, blood-brain barrier permeability, and serum protein binding. Other activities are the development of an improved "force field" for the description of intra and inter-molecular energetics, examination of the mechanisms of enzymatic reactions, and prediction of the structures of polypeptides in aqueous solution using new MC sampling methods with a continuum solvent model.