3D-QSAR and docking studies of aldehyde inhibitors of human cathepsin K

Docking-based virtual screening of covalently binding ligands: an orthogonal lead discovery approach

In pharmaceutical industry, lead discovery strategies and screening collections have been predominantly tailored to discover compounds that modulate target proteins through noncovalent interactions. Conversely, covalent linkage formation is an important mechanism for a quantity of successful drugs in the market, which are discovered in most cases by hindsight instead of systematical design. In this article, the implementation of a docking-based virtual screening workflow for the retrieval of covalent binders is presented considering human cathepsin K as a test case. By use of the docking conditions that led to the best enrichment of known actives, 44 candidate compounds with unknown activity on cathepsin K were finally selected for experimental evaluation. The most potent inhibitor, 4-(N-phenylanilino)-6-pyrrolidin-1-yl-1,3,5-triazine-2-carbonitrile (CP243522), showed a K(i) of 21 nM and was confirmed to have a covalent reversible mechanism of inhibition. The presented approach will have great potential in cases where covalent inhibition is the desired drug discovery strategy.

COMPARATIVE MOLECULAR FIELD ANALYSIS OF ANTI-TUBULIN AGENTS WITH INDOLE RING BINDING AT THE COLCHICINE BINDING SITE

A 3D-QSAR study using comparative molecular field analysis (CoMFA) was carried out on anti-tubulin agents with indole as a nucleus core. The structures of the compounds were obtained using docking calculations, and were then subjected to alignment procedures. CoMFA calculations for the 42 ligands that were examined as the training set gave a q2 value of 0.623 in correlation with experimental IC50 values for the inhibition of MKN-45 gastric cancer cells. Calculation for the test set of 17 ligands resulted in an r2 value of 0.714. The calculated results suggest that the R3 functional group site (see structure in Fig. 1) favored bulky groups while R1, R2, and R4 sites favored the opposite. At the R5 and R6 sites, parts of the region favored bulky groups while other parts favored the opposite. As for the electrostatic aspect, the R3 site was found to favor groups with a negative partial charge. At the R2 site, part of the region favored the group with a negative partial charge while other regions favored groups with a positive partial charge. The R4 and R5 sites favored groups with negative and positive partial charges, respectively, with a less favorable magnitude when compared with the R2 and R3 sites. The R1 and R6 sites did not exhibit significant electrostatic favor. Correlation of the results with IC50 values of ligands were analyzed and discussed.

A QSAR-like analysis of the adsorption of endocrine disrupting compounds, pharmaceuticals, and personal care products on modified activated carbons

Rapid small-scale column tests (RSSCTs) examined the removal of 29 endocrine disrupting compounds (EDCs) and pharmaceutical/personal care products (PPCPs). The RSSCTs employed three lignite variants: HYDRODARCO 4000 (HD4000), steam-modified HD4000, and methane/steam-modified HD4000. RSSCTs used native Lake Mead, NV water spiked with 100-200 ppt each of 29 EDCs/PPCPs. For the steam and methane/steam variants, breakthrough occurred at 14,000-92,000 bed volumes (BV); and this was 3-4 times more bed volumes than for HD4000. Most EDC/PPCP bed life data were describable by a normalized quantitative structure-activity relationship (i.e. QSAR-like model) of the form: where TPV is the pore volume, rho(mc) is the apparent density, CV is the molecular volume, C(o) is the concentration, (8)chi(p) depicts the molecule's compactness, and FOSA is the molecule's hydrophobic surface area.

Receptor-based modeling and 3D-QSAR for a quantitative production of the butyrylcholinesterase inhibitors based on genetic algorithm

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of structurally related steroidal alkaloids as butyrylcholinesterase (BuChE) inhibitors. Docking studies were employed to position the inhibitors into the BuChE active site to determine the most probable binding mode. The strategy was to explore multiple inhibitor conformations in producing a more reliable 3D-QSAR model. These multiple conformations were derived using the FlexS program. The conformation selection step for CoMFA was done by genetic algorithm. The genetic algorithm based CoMFA approach was found to be the best. Both CoMFA and CoMSIA yielded significant cross-validated q(2) values of 0.701 and 0.627 and the r(2) values of 0.979 and 0.982, respectively. These statistically significant models were validated by a test set of five compounds. Comparison of CoMFA and CoMSIA contour maps helped to identify structural requirements for the inhibitors and serves as a basis for the design of the next generation of the inhibitor analogues. The results demonstrate that the combination of ligand-based and receptor-based modeling with use of a genetic algorithm is a powerful approach to build 3D-QSAR models. These data can be used for the lead optimization process with respect to inhibition enhancement which is important for the drug discovery and development for Alzheimer's disease.

3D-QSAR study of sulfonamide inhibitors of human carbonic anhydrase II

3D-QSAR models of Comparative of Molecular Field Analysis (CoMFA) and Comparative of Molecular Similarity Indices Analysis (CoMSIA) of 61 potent carbonic anhydrase II (CAII) sulfonamide inhibitors were performed using two methods. The conventional ligand-based 3D-QSAR studies were performed based on the lower energy conformations employing database alignment rule. The receptor-based 3D-QSAR models were also derived using bioactive conformations obtained by docking compounds to the active sites of CAII. The receptor-based model gave q(2) values of 0.623 and 0.562, r(2) values of 0.986 and 0.987 for CoMFA and CoMSIA, respectively, which were much better than those of ligand-based model (q(2) values of 0.532 and 0.466). The predictive ability of the models was validated using the test set of 10 compounds that were not included in the training set of 51 compounds. Results of CoMFA and CoMSIA suggested that heterocyclic sulfonamides are more active than aromatic sulfonamides, in the latter 1,3,5-triazole group substituting one hydrogen atom of the amido is favored and moderate groups in its 4- and 6-position are required. These results provided further understanding of the relationship between the structural features of CAII and its activities, which should be applicable to design and find new potential CAII inhibitors.

Combining docking, scoring and molecular field analyses to probe influenza neuraminidase-ligand interactions

In this project, several docking conditions, scoring functions and corresponding protein-aligned molecular field analysis (CoMFA) models were evaluated for a diverse set of neuraminidase (NA) inhibitors. To this end, a group of inhibitors were docked into the active site of NA. The docked structures were utilized to construct a corresponding protein-aligned CoMFA models by employing probe-based (H+, OH, CH3) energy grids and genetic partial least squares (G/PLS) statistical analysis. A total of 16 different docking configurations were evaluated, of which some succeeded in producing self-consistent and predictive CoMFA models. However, the best model coincided with docking the ionized ligands into the hydrated form of the binding site via PLP1 scoring function (r2LOO=0.735, r2PRESS against 24 test compounds=0.828). The highest-ranking CoMFA models were employed to probe NA-ligand interactions. Further validation by comparison with a co-crystallized ligand-NA crystallographic structure was performed. This combination of docking/scoring/CoMFA modeling provided interesting insights into the binding of different NA inhibitors.

Natural biflavones as novel inhibitors of cathepsin B and K

Cathepsin B and K, two important members in lysosomal proteases, involve in many serious human diseases, such as tumor and osteoporosis. In order to find their novel inhibitors, we performed the inhibition assays of cathepsin B and cathepsin K in vitro, randomly screened compounds from plants, and found six biflavones, named AMF1-5 and HIF, can potently inhibit cathepsin B and cathepsin K, especially AMF4 and HIF with IC(50) of 0.62 and 0.58 microM against cathepsin B. They are novel inhibitors for cathepsin B and K. Inhibition and flexible docking studies indicated that these biflavones are reversible inhibitors of cathepsin B, and their binding patterns and interaction modes with cathepsin B made them more specific to cathepsin B endopeptidase.