Discovery of novel small molecule enzyme inhibitors and receptor modulators through structure-based computational design

Discovery of novel drug candidates for a particular disease condition has traditionally been carried out by experimentally screening thousands of compounds for desired activity in anticipation of a few being successful. However, this approach is expensive because a large number of compounds need to be synthesized or purchased and tested for biological activity. The success rates of such blind screens are very poor. Recently, rational drug design methods have gained popularity due to progress in structural genomics, chemical biology, and computational chemistry. In particular, in silico methods have improved the screening efficiency in the past five years due to advancement in multi-core, multi-threaded computational hardware and software development. By utilizing rational approaches, we have developed and applied protocols capable of rapidly and inexpensively screen hundreds of thousands of compounds virtually to disease targets.;A novel kinase, maternal embroyonic leucine zipper kinase (MELK), has been reported to be involved in tumor progression. We developed an ensemble virtual screening method utilizing multiple induced fit models of MELK to screen 500,000 compounds. We tested 23 compounds and identified one potent (15; K_d =0.37 µM), one moderate (9; K_d=3.2 µM), and several weak MELK inhibitors.;Human protein arginine methyl transferase 5 (PRMT5) has been shown to methylate arginine residues of histone protein, subsequently silencing tumor suppressor genes. To target this aberrant epigenetic pathway, a comparative model of the PRMT5 was constructed. We computationally screened 10,000 compounds and eight small molecules were selected for biological assay. Enzyme inhibition assays show that two compounds were capable of selectively inhibiting PRMT5 activity. The compounds were also proven to inhibit cellular proliferation in several cancer cell lines.;Leishmaniasis is a parasitic disease which affects millions of people all over the world. The Leishmania UDP-glucose pyrophosphorylase enzyme, which is required for the parasite to survive in the host environment, has recently been proposed as a potential molecular drug target for Leishmaniasis. We have carried out virtual screening and molecular dynamic study to understand the drug design aspects of this enzyme.;The kinase profiling for MELK inhibitors resulted in the discovery a potent Glycogen synthase kinase 3β (GSK3β) inhibitor (ML-18; K _d=0.056 µM) which is currently being investigated for experimental therapeutics of Alzheimer's disease. Ensemble docking of ML-18 to GSK3β X-ray crystal structures shows critical interactions to the protein binding site residues. Molecular dynamics simulation of 50 ns revealed an induced-fit GSK3β conformation.;A member of the membrane receptor class, α4β2 nicotinic acetylcholine receptor (nAChR), has been implicated in nicotine addiction as well as other disease conditions. We virtually screened 10,000 compounds to a novel binding pocket of this receptor model. Four of the eleven compounds tested selectively inhibited the receptor activity.;In conclusion, we successfully applied computational methods to discover novel small molecule chemical classes for different drug targets for various disease conditions. In silico methods have been proven to be fast, efficient and economical compared to traditional random screening approach and such methods would complement the rational drug discovery efforts carried out in industry and academia.