Identification of novel PARP-1 inhibitors by structure-based virtual screening.

Poly(ADP-ribose)polymerase-1 (PARP-1) is an abundant and ubiquitous chromatin-bound nuclear protein. PARP-1, a DNA repair enzyme, has been in the limelight as a chemotherapeutic target. In this study, we demonstrated the successful use of structure-based virtual screening to identify inhibitors of PARP-1 from Otava databases comprised of nearly 260,000 compounds. Five novel inhibitors belonging to thienopyrimidinone, isoquinolinoquinazolinone, pyrroloquinazolinone, and cyclopentenothienopyrimidinone scaffolds revealed inhibitory potencies with IC50 values ranged from 9.57µM to 0.72µM. Structural features relevant to the activity of these novel compounds within the active site of PARP-1 are discussed in detail and will guide future SAR investigation on these scaffolds.

Synthesis and SAR optimization of quinazolin-4(3H)-ones as poly(ADP-ribose)polymerase-1 inhibitors.

We have demonstrated that quinazolin-4(3H)-one, a nicotinamide (NI) mimic with PARP-1 inhibitory activity in the high micromolar range (IC(50) = 5.75 µM) could be transformed into highly active derivatives with only marginal increase in molecular weight. Convenient one to two synthetic steps allowed us to explore extensive SAR at the 2-, and 5- through 8-positions of the quinazolin-4(3H)-one scaffold. Substitutions at the 2- and 8-positions were found to be most favorable for improved PARP-1 inhibition. The amino group at 8-position resulted in compound 22 with an IC(50) value of 0.76 µM. Combination of the 8-amino substituent with an additional methyl substituent at the 2-position provided the most potent compound 31 [8-amino-2-methylquinazolin-4(3H)-one, IC(50) = 0.4 µM] in the present study. Compound 31 inhibited the proliferation of Brca1-deficient cells with an IC(50) value of 49.0 µM and displayed >10-fold selectivity over wild type counterparts. Binding models of these derivatives within the active site of PARP-1 have further supported the SAR data and will be useful for future lead optimization efforts.

The synthesis of phenylalanine-derived C5-substituted rhodanines and their activity against selected methicillin-resistant Staphylococcus aureus (MRSA) strains.

A series of rhodanine compounds containing various substituents at the N3- and C5-positions were synthesized and their in vitro activity against a panel of clinically relevant MRSA strains was determined. The anti-MRSA activity of compounds 21 (MIC=3.9 µg/mL, MBC=7.8 µg/mL) and 22 (MIC=1.95 µg/mL, MBC=7.8 µg/mL) was significantly greater than that of the lead compounds, 1-3 and reference antibiotics penicillin G (MIC=31.25 µg/mL) and ciprofloxacin (MIC=7.8 µg/mL) and comparable to that of vancomycin (MIC=0.97 µg/mL). Compounds 21 and 22 were found to be bactericidal at only 2-4-fold higher than their MIC concentrations. In addition, their MIC values remained unchanged in the presence or absence of 10% serum. Overall, the results suggest that compounds 21 and 22 may be of potential use in the treatment of MRSA infections.

Structure-based virtual screening, synthesis and SAR of novel inhibitors of hepatitis C virus NS5B polymerase.

Hepatitis C virus (HCV) NS5B polymerase is a key target for the development of therapeutic agents aimed at the treatment of HCV infections. Here we report on the identification of novel allosteric inhibitors of HCV NS5B through a combination of structure-based virtual screening, synthesis and structure-activity relationship (SAR) optimization approach. Virtual screening of 260,000 compounds from the ChemBridge database against the tetracyclic indole inhibitor binding pocket of NS5B (allosteric pocket-1, AP-1), sequentially down-sized the library by 4 orders of magnitude to yield 23 candidates. In vitro evaluation of the NS5B inhibitory activity of the in-silico selected compounds resulted in 17% hit rate, identifying two novel chemotypes. Of these, compound 3, bearing the rhodanine scaffold, proved amenable for productive SAR exploration and synthetic modification. As a result, 25 derivatives that exhibited IC50 values ranging from 7.7 to 68.0 µM were developed. Docking analysis of lead compound 28 within the tetracyclic indole- and benzylidene-binding allosteric pockets (AP-1 and AP-3, respectively) of NS5B revealed topological similarities between these two pockets. Compound 28, a novel rhodanine analog with NS5B inhibitory potency in the low micromolar level range may be a promising lead for future development of more potent NS5B inhibitors.

CoMFA and HQSAR studies on 6,7-dimethoxy-4-pyrrolidylquinazoline derivatives as phosphodiesterase10A inhibitors.

Phosphodiesterase10A (PDE10A) is an important enzyme with diverse biological actions in intracellular signaling systems, making it an emerging target for diseases such as schizophrenia, Huntington's disease, and diabetes mellitus. The objective of the current 3D QSAR study is to uncover some of the structural parameters which govern PDE10A inhibitory activity over PDE3A/B. Thus, comparative molecular field analysis (CoMFA) and hologram quantitative structure-activity relationship (HQSAR) studies were carried out on recently reported 6,7-dimethoxy-4-pyrrolidylquinazoline derivatives as PDE10A inhibitors. The best CoMFA model using atom-fit alignment approach with the bound conformation of compound 21 as the template yielded the steric parameter as a major contributor (nearly 70%) to the observed variations in biological activity. The best CoMFA model produced statistically significant results, with the cross-validated (r(cv)(2)) and conventional correlation (r(ncv)(2)) coefficients being 0.557 and 0.991, respectively, for the 21 training set compounds. Validation of the model by external set of six compounds yielded a high (0.919) predictive value. The CoMFA models of PDE10A and PDE3A/B activity were compared in order to address the selectivity issue of these inhibitors. The best HQSAR model for PDE10A was obtained with an r(cv)(2) of 0.704 and r(ncv)(2) of 0.902 using atoms, bonds, connections, chirality, donor, and acceptor as fragment distinction and default fragment size of 4-7 with three components for the 21 compounds. The HQSAR model predicted the external test-set of compounds well since a good agreement between the experimental and predicted values was verified. Taken together, the present QSAR models were found to accurately predict the PDE10A inhibitory activity of the test-set compounds and to yield reliable clues for further optimization of the quinazoline derivatives in the dataset.