Prediction of the interaction of HIV-1 integrase and its dicaffeoylquinic acid inhibitor through molecular modeling approach.

An essential step in the life cycle of human immunodeficiency virus type 1 (HIV-1) is integration of the double-stranded retroviral DNA into the genome of the host cell. HIV-1 integrase, the enzyme that inserts the vital DNA into the host chromosome, is an attractive and rational target for anti-AIDS drug design because it is essential for HIV replication and there are no known counterparts in the host cell. Inhibitors of this enzyme have a great potential to complement the therapeutic use of HIV protease and reverse transcriptase inhibitors. Natural products have provided a source of new drug candidates for anti-AIDS therapy. Dicaffeoylquinic acids, isolated from traditional medicinal plants, are a novel class of integrase inhibitors. These compounds are potent inhibitors of HIV-1 replication in cultured cell lines and catalytic activities of integrase in vitro. They are therefore promising compounds for developing new anti-AIDS drugs. To understand how the inhibitors work and therefore design more potent and specific inhibitors, we have used molecular modeling techniques to investigate the binding modes of 3,4-dicaffeoylquinic acid. Our computational modeling study demonstrated that the inhibitor of this compound on HIV integrase is likely to proceed by two different but equivalent mechanisms with one bound to the active site region of the enzyme and another docked into the binding pocket located on the other side of the catalytic site. Our study will be of help to design new pharmaceuticals for the treatment of AIDS.

Computational modeling study of human nicotinic acetylcholine receptor for developing new drugs in the treatment of alcoholism.

Alcohol abuse and alcoholism are serious and costly problem in USA. Thus, the development of anti-alcoholism agents could be very significant. The understanding of the neurochemical basis underlying the addictive properties of drugs of abuse is imperative for the development of new pharmacological means to reverse the addictive state, prevent relapse or to reduce the intake of addictive compounds. The nicotinic acetylcholine receptors (nAChRs) are important therapeutic targets for various diseases. Recent studies have revealed that the alpha3beta2, alpha3beta3, and alpha6 subunits of nAChR protein family might be pharmacological targets for developing new drugs in the treatment of alcoholism. We have performed computational homology modeling of the alpha3beta2, alpha3beta3, and alpha6 subunits of human nACHRs based upon the recently determined crystal structure of the extracellular domain (ECD) of the mouse nAChR alpha1 subunit complexed with alpha-bungarotoxin at 1.94 A resolution. For comparison, we also built the ECD models of alpha4beta2, and alpha7 subunits of human nACHRs which are neurochemical targets for cessation of smoking. The three-dimensional (3D) models of the ECD of the monomer, and pentamer of these human nAChR were constructed. The docking of the agonist in the ligand-binding pocket of the human nAChR dimers was also performed. Since the nAChR ligand-binding site is a useful target for mutagenesis studies and the rational design of drugs against various diseases, these models provide useful information for future investigation.

Ligand binding and circular permutation modify residue interaction network in DHFR.

Residue interaction networks and loop motions are important for catalysis in dihydrofolate reductase (DHFR). Here, we investigate the effects of ligand binding and chain connectivity on network communication in DHFR. We carry out systematic network analysis and molecular dynamics simulations of the native DHFR and 19 of its circularly permuted variants by breaking the chain connections in ten folding element regions and in nine nonfolding element regions as observed by experiment. Our studies suggest that chain cleavage in folding element areas may deactivate DHFR due to large perturbations in the network properties near the active site. The protein active site is near or coincides with residues through which the shortest paths in the residue interaction network tend to go. Further, our network analysis reveals that ligand binding has "network-bridging effects" on the DHFR structure. Our results suggest that ligand binding leads to a modification, with most of the interaction networks now passing through the cofactor, shortening the average shortest path. Ligand binding at the active site has profound effects on the network centrality, especially the closeness.

WinDock: structure-based drug discovery on Windows-based PCs.

In recent years, virtual database screening using high-throughput docking (HTD) has emerged as a very important tool and a well-established method for finding new lead compounds in the drug discovery process. With the advent of powerful personal computers (PCs), it is now plausible to perform HTD investigations on these inexpensive PCs. To make HTD more accessible to a broad community, we present here WinDock, an integrated application designed to help researchers perform structure-based drug discovery tasks under a uniform, user friendly graphical interface for Windows-based PCs. WinDock combines existing small molecule searchable three-dimensional (3D) libraries, homology modeling tools, and ligand-protein docking programs in a semi-automatic, interactive manner, which guides the user through the use of each integrated software component. WinDock is coded in C++.

Discovery of embelin as a cell-permeable, small-molecular weight inhibitor of XIAP through structure-based computational screening of a traditional herbal medicine three-dimensional structure database.

The X-linked inhibitor of apoptosis (XIAP) is a promising new molecular target for the design of novel anticancer drugs aiming at overcoming apoptosis-resistance of cancer cells to chemotherapeutic agents and radiation therapy. Recent studies demonstrated that the BIR3 domain of XIAP where caspase-9 and Smac proteins bind is an attractive site for designing small-molecule inhibitors of XIAP. Through computational structure-based screening of an in-house traditional herbal medicine three-dimensional structure database of 8221 individual natural products, followed by biochemical testing of selected candidate compounds, we discovered embelin from the Japanese Ardisia herb as a small-molecular weight inhibitor that binds to the XIAP BIR3 domain. We showed that embelin binds to the XIAP BIR3 protein with an affinity similar to that of the natural Smac peptide using a fluorescence polarization-based binding assay. Our NMR analysis further conclusively confirmed that embelin interacts with several crucial residues in the XIAP BIR3 domain with which Smac and caspsase-9 bind. Embelin inhibits cell growth, induces apoptosis, and activates caspase-9 in prostate cancer cells with high levels of XIAP, but has a minimal effect on normal prostate epithelial and fibroblast cells with low levels of XIAP. In stably XIAP-transfected Jurkat cells, embelin effectively overcomes the protective effect of XIAP to apoptosis and enhances the etoposide-induced apoptosis and has a minimal effect in Jurkat cells transfected with vector control. Taken together, our results showed that embelin is a fairly potent, nonpeptidic, cell-permeable, small-molecule inhibitor of XIAP and represents a promising lead compound for designing an entirely new class of anticancer agents that target the BIR3 domain of XIAP.

Molecular modeling of the three-dimensional structure of dopamine 3 (D3) subtype receptor: discovery of novel and potent D3 ligands through a hybrid pharmacophore- and structure-based database searching approach.

The dopamine 3 (D3) subtype receptor has been implicated in several neurological conditions, and potent and selective D3 ligands may have therapeutic potential for the treatment of drug addiction, Parkinson's disease, and schizophrenia. In this paper, we report computational homology modeling of the D3 receptor based upon the high-resolution X-ray structure of rhodopsin, extensive structural refinement in the presence of explicit lipid bilayer and water environment, and validation of the refined D3 structural models using experimental data. We further describe the development, validation, and application of a hybrid computational screening approach for the discovery of several classes of novel and potent D3 ligands. This computational approach employs stepwise pharmacophore and structure-based searching of a large three-dimensional chemical database for the identification of potential D3 ligands. The obtained hits are then subjected to structural novelty screening, and the most promising compounds are tested in a D3 binding assay. Using this approach we identified four compounds with K(i) values better than 100 nM and eight compounds with K(i) values better than 1 microM out of 20 compounds selected for testing in the D3 receptor binding assay. Our results suggest that the D3 structural models obtained from this study may be useful for the discovery and design of novel and potent D3 ligands. Furthermore, the employed hybrid approach may be more effective for lead discovery from a large chemical database than either pharmacophore-based or structure-based database screening alone.