Application of 3D-QSAR techniques in anti-HIV-1 drug design--an overview.

Despite the availability of several classes of drugs against acquired immunodeficiency syndrome (AIDS) caused by human immunodeficiency virus type 1(HIV-1), this deadly disease showing very little sign of containment, especially in Sub-Saharan Africa and South-East Asia. More than 20 million people died since the first diagnosis of AIDS more than twenty years ago and almost 40 million people are currently living with HIV/AIDS. Structure-based drug design effort was immensely successful in identifying several drugs that are currently available for the treatment of HIV-1.

Identification of N-phenyl-N'-(2,2,6,6-tetramethyl-piperidin-4-yl)-oxalamides as a new class of HIV-1 entry inhibitors that prevent gp120 binding to CD4.

We have identified two N-phenyl-N'-(2,2,6,6-tetramethyl-piperidin-4-yl)-oxalamide analogs as a novel class of human immunodeficiency virus type 1 (HIV-1) entry inhibitors that block the gp120-CD4 interaction, using database screening techniques. The lead compounds, NBD-556 and NBD-557, are small molecule organic compounds with drug-like properties. These compounds showed potent cell fusion and virus-cell fusion inhibitory activity at low micromolar levels.

Generation of predictive pharmacophore models for CCR5 antagonists: study with piperidine- and piperazine-based compounds as a new class of HIV-1 entry inhibitors.

Predictive pharmacophore models were developed for a large series of piperidine- and piperazine-based CCR5 antagonists as anti-HIV-1 agents reported by Schering-Plough Research Institute in recent years. The pharmacophore models were generated using a training set consisting of 25 carefully selected antagonists based on well documented criteria. The activity spread, expressed in K(i), of training set molecules was from 0.

Pharmacophore mapping of a series of 2,4-diamino-5-deazapteridine inhibitors of Mycobacterium avium complex dihydrofolate reductase.

Pharmacophore hypotheses were developed for a series of 2,4-diamino-5-deazapteridine inhibitors of Mycobacterium avium complex (MAC) and human dihydrofolate reductase (hDHFR). Training sets consisting of 20 inhibitors were selected in each case on the basis of the information content of the structures and activity data as required by the HypoGen program in the Catalyst software. In the case of MAC DHFR inhibitors, the best pharmacophore in terms of statistics and predictive value consisted of four features: two hydrogen bond acceptors (HA), one hydrophobic (HY) feature, and one ring aromatic (RA) feature.