Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors

Synthesis, antitumor evaluation and 3D-QSAR studies of [1,2,4]triazolo[4,3-b][1,2,4,5]tetrazine derivatives

A series of [1,2,4]triazolo[4,3-b][1,2,4,5]tetrazine derivatives have been synthesized and their structures were confirmed by single-crystal X-ray diffraction. Compared to some reported structures of 1,6-dihydro-1,2,4,5-tetrazine, these compounds can't be considered as having homoaromaticity. Their antiproliferative activities were evaluated against MCF-7, Bewo and HL-60 cells in vitro. Two compounds were highly effective against MCF-7, Bewo and HL-60 cells with IC50 values in 0.63-13.12μM. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were carried out on 51 [1,2,4]triazolo[4,3-b][1,2,4,5]tetrazine derivatives with antiproliferative activity against MCF-7 cell. Models with good predictive abilities were generated with the cross validated q(2) values for CoMFA and CoMSIA being 0.716 and 0.723, respectively. Conventional r(2) values were 0.985 and 0.976, respectively. The results provide the tool for guiding the design and synthesis of novel and more potent tetrazine derivatives.

2,4,5-Trisubstituted thiazole derivatives: a novel and potent class of non-nucleoside inhibitors of wild type and mutant HIV-1 reverse transcriptase

Novel 2,4,5-trisubstituted thiazole derivatives (TSTs) were designed and synthesized as HIV-1 non-nucleoside reverse transcriptase inhibitors (NNRTIs). Among the thirty-eight synthesized target compounds, thirty TSTs showed potent inhibition against HIV-1 replication in wild type HIV-1 at submicromolar concentrations (from 0.046 to 9.59 μM). Compounds 21, 23 and 24 were also tested on seven NNRTI-resistant HIV-1 strains, and all exhibited inhibitory effects with fold changes in IC50 ranging from 2.6 to 111, which were better than those of nevirapine (15.6-fold-371-fold). Docking simulations of compound 24 revealed a reasonable mechanism for the binding mode, and three-dimensional quantitative structure activity relationship (3-DQSAR) studies on this novel series of TST further elucidated the structure-activity relationship (SAR). The results suggested the great potential of TSTs as a novel class of NNRTIs with antiviral efficacy and a good resistance profile.

Identification of novel HIV 1--protease inhibitors: application of ligand and structure based pharmacophore mapping and virtual screening

A combined ligand and structure-based drug design approach provides a synergistic advantage over either methods performed individually. Present work bestows a good assembly of ligand and structure-based pharmacophore generation concept. Ligand-oriented study was accomplished by employing the HypoGen module of Catalyst in which we have translated the experimental findings into 3-D pharmacophore models by identifying key features (four point pharmacophore) necessary for interaction of the inhibitors with the active site of HIV-1 protease enzyme using a training set of 33 compounds belonging to the cyclic cyanoguanidines and cyclic urea derivatives. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, two hydrogen bond acceptors and two hydrophobic, showed a correlation (r) of 0.90 and a root mean square of 0.71 and cost difference of 56.59 bits between null cost and fixed cost. The model was validated using CatScramble technique, internal and external test set prediction. In the second phase of our study, a structure-based five feature pharmacophore hypothesis was generated which signifies the importance of hydrogen bond donor, hydrogen bond acceptors and hydrophobic interaction between the HIV-1 protease enzyme and its inhibitors. This work has taken a significant step towards the full integration of ligand and structure-based drug design methodologies as pharmacophoric features retrieved from structure-based strategy complemented the features from ligand-based study hence proving the accuracy of the developed models. The ligand-based pharmacophore model was used in virtual screening of Maybridge and NCI compound database resulting in the identification of four structurally diverse druggable compounds with nM activities.