Eigen value analysis of HIV-1 integrase inhibitors

Analogue and structure based approaches for modelling HIV-1 integrase inhibitors

A set of 220 inhibitors belonging to different structure classes and having HIV-1 integrase activity were collected along with their experimental pIC50 values. Geometries of all the inhibitors were fully optimized using B3LYP/6-31 + G(d) level of theory. These ligands were docked against 4 different HIV-1 integrase receptors (PDB IDs: 4LH5, 5KRS, 3ZSQ and 3ZSV). 30 docked poses were generated for all 220 inhibitors and ligand interaction of the first docked pose and the docked pose with the highest score were analysed. Residue GLU170 of 4LH5 receptor shows the highest number of interactions followed by ALA169, GLN168, HIS171 and ASP167 residues. Hydrogen bonding and stacking are mainly responsible for the interactions of these inhibitors with the receptor. We performed Molecular Dynamics (MD) simulation to observe the root-mean-square deviation (RMSD), for measure the average change of displacement between the atoms for a particular frame with respect to a reference and The Root Mean Square Fluctuation (RMSF) for characterization of local changes along the protein chain of the docked complexes. Analogue based models were generated to predict the pIC50 values for integrase inhibitors using various types of descriptors such as constitutional, geometrical, topological, quantum chemical and docking based descriptors. The best models were selected on the basis of statistical parameters and were validated by training and test set division. A few new inhibitors were designed on the basis of structure activity relationship and their pIC50 values were predicted using the generated models. All the designed new inhibitors a very high potential and may be used as potent inhibitors of HIV integrase. These models may be useful for further design and development of new and potent HIV integrase inhibitors.Communicated by Ramaswamy H. Sarma.

Computer tools in the discovery of HIV-1 integrase inhibitors

Computer-aided drug design (CADD) methodologies have made great advances and contributed significantly to the discovery and/or optimization of many clinically used drugs in recent years. CADD tools have likewise been applied to the discovery of inhibitors of HIV-1 integrase, a difficult and worthwhile target for the development of efficient anti-HIV drugs. This article reviews the application of CADD tools, including pharmacophore search, quantitative structure-activity relationships, model building of integrase complexed with viral DNA and quantum-chemical studies in the discovery of HIV-1 integrase inhibitors. Different structurally diverse integrase inhibitors have been identified by, or with significant help from, various CADD tools.

CoMFA, CoMSIA and eigenvalue analysis on dibenzodioxepinone and dibenzodioxocinone derivatives as cholesteryl ester transfer protein inhibitors

CoMFA, CoMSIA and eigenvalue analysis (EVA) were performed to study the structural features of 61 diverse dibenzodioxepinone and dibenzodioxocinone analogues to probe cholesteryl ester transfer protein (CETP) inhibitory activity. Three methods yielded statistically significant models upon assessment of cross-validation, bootstrapping, and progressive scrambling. This was further validated by an external set of 13 derivatives. Our results demonstrate that three models have a good interpolation as well as extrapolation. The hydrophobic features were confirmed to contribute significantly to inhibitor potencies, while a pre-oriented hydrogen bond provided by the hydroxyl group at the 3-position indicated a good correlation with previous SAR, and a hydrogen bond acceptor may play a crucial role in CETP inhibition. These derived models may help us to gain a deeper understanding of the binding interaction of these lactone-based compounds and aid in the design of new potent compounds against CETP.

Quantitative structure–activity relationship studies of HIV-1 integrase inhibition. 1. GETAWAY descriptors

The GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) approach has been applied to the study of the HIV-1 integrase inhibition of 172 compounds that belong to 11 different chemistry families. A model able to describe more than 68.5% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, none of the five different approaches, including the use of Randić Molecular Profiles, Geometrical, RDF, 3D-MORSE and WHIM descriptors was able to explain more than 62.4% of the variance in the mentioned property with the same number of variables in the equation. Finally, after extracting five compounds considered by us as outliers the model was able to describe more than 72.5% of the variance in the experimental activity.

A structure-odour relationship study using EVA descriptors and hierarchical clustering

Structure-odour relationship analyses using hierarchical clustering were carried out on a diverse dataset of 47 molecules. These molecules were divided into seven odour categories: ambergris, bitter almond, camphoraceous, rose, jasmine, muguet, and musk. The alignment-independent descriptor EVA (EigenVAlue) was used as the molecular descriptor. The results were compared with those of another kind of descriptor, the UNITY 2D fingerprint. The dendrograms obtained with these descriptors were compared with the seven odour categories using the adjusted Rand index. The dendrograms produced by EVA consistently outperformed those from UNITY 2D in reproducing the experimental odour classifications of these 47 molecules.

De novo design and synthesis of HIV-1 integrase inhibitors

Existing AIDS therapies are out of reach for most HIV-infected people in developing countries and, where available, they are limited by their toxicity and their cost. New anti-HIV agents are needed urgently to combat emerging viral resistance and reduce the side effects associated with currently available drugs. Toward this end, LeapFrog, a de novo drug design program was used to design novel, potent, and selective inhibitors of HIV-1 integrase. The designed compounds were synthesized and tested for in vitro inhibition of HIV-1 integrase. Out of the 25 compounds that were designed, and synthesized, four molecules (compounds 23, 26, 43, and 59) showed moderate to low inhibition of HIV-1 integrase for 3'-processing and 3'-strand transfer activities. Nonetheless, these compounds possess structural features not seen in known HIV-1 integrase inhibitors and thus can serve as excellent leads for further optimization of anti-HIV-1 integrase activity.

Eigenvalue Analysis of Peroxisome Proliferator-Activated Receptor γ Agonists

Eigenvalue analysis (EVA) was conducted on a series of potent agonists of peroxisome proliferator-activated receptor gamma (PPARgamma). Predictive EVA quantitative structure-activity relationship (QSAR) models were established using the SYBYL package, which had conventional r2 and cross-validated coefficient (q2) values up to 0.920 and 0.587 for the AM1 method and 0.863 and 0.586 for the PM3 method, respectively. These models were validated by a test set containing 18 compounds. The capability to predict by these two models for PPARgamma agonists, with the best predictive r2pred value of 0.614 for AM1 and 0.822 for PM3 methods, set a successful example for applying a similar approach in building QSAR models for PPARalpha and -delta that could potentially offer a new opportunity in the design of novel PPAR modulators.

Molecular electrostatic potentials as input for the alignment of HIV-1 integrase inhibitors in 3D QSAR

Comparative molecular similarity indices analysis (CoMSIA), a three-dimensional quantitative structure activity relationship (3D QSAR) paradigm, was used to examine the correlations between the calculated physicochemical properties and the in vitro activities (3'-processing and 3'-strand transfer inhibition) of a series of human immunodeficiency virus type 1 (HIV-1) integrase inhibitors. The training set consisted of 34 molecules from five structurally diverse classes: salicylpyrazolinones, dioxepinones, coumarins, quinones, and benzoic hydrazides. The data set was aligned using extrema of molecular electrostatic potentials (MEPs). The predictive ability of the resultant model was evaluated using a test set comprised of 7 molecules belonging to a different structural class of thiazepinediones. A CoMSIA model using an MEP-based alignment showed considerable internal as well external predictive ability (r2(cv) = 0.821, r2(pred) = 0.608 for 3'-processing; and r2(cv) = 0.759, r2(pred.) = 0.660 for 3'-strand transfer).