2D-QSAR modeling and two-fold classification of 1,2,4-triazole derivatives for antitubercular potency against the dormant stage of Mycobacterium tuberculosis.

The dormant or latent form of Mycobacterium tuberculosis (MTB) is not killed by the conventional antitubercular drugs. The treatment of latent TB is essential to reduce the period of treatment as well as incidences of drug resistance. In this background, we have made an attempt to develop the quantitative structure-activity relationship models (QSAR: regression and classification based) against the dormant form of MTB and later used the developed classifier models (linear discriminant analysis (LDA) and random forest (RF)) for the two-fold classifications.

Pharmacophore modeling of pretomanid (PA-824) derivatives for antitubercular potency against replicating and non-replicating .

Pretomanid (PA-824) is the recently (2019) approved drug for the treatment of extensively drug-resistant (XDR) TB and the multidrug-resistant (MDR) TB by US FDA. The experimental data of antitubercular activity of 543 pretomanid derivatives (total 6 datasets) against replicating (active) and non-replicating (dormant) forms of (strain H37Rv) are available in the literature. Such vast experimental data of pretomanid derivatives against both of these endpoints, and recent approval of pretomanid molecule as a drug encouraged us to utilize this existing experimental information for the development of the 3D-pharmacophore models.

Computational Approaches as Rational Decision Support Systems for Discovering Next-Generation Antitubercular Agents: Mini-Review.

Tuberculosis, malaria, dengue, chikungunya, leishmaniasis etc. are a large group of neglected tropical diseases that prevail in tropical and subtropical countries, affecting one billion people every year. Minimal funding and grants for research on these scientific problems challenge many researchers to find a different way to reduce the extensive time and cost involved in the drug discovery cycle of these problems.

Design of antimalarial transmission blocking agents: Pharmacophore mapping of ligands active against stage-V mature gametocytes of .

The discovery of transmission-blocking (T-B) agents is crucial for preventing and complete removal of malaria infection. However, most of the existing antimalarials are only active against the asexual stages of parasite, but ineffective against the sexual stage (gametocytes). In this background, we have developed pharmacophore models against the stage-V mature gametocytes of parasites.

Understanding the structural requirements in diverse scaffolds for the inhibition of P. falciparum dihydroorotate dehydrogenase (PfDHODH) using 2D-QSAR, 3D-pharmacophore and structure-based energy- optimized pharmacophore models.

P. falciparum dihydroorotate dehydrogenase (PfDHODH) of the pyrimidine biosynthetic pathway offers a promising target for the development of antimalarial drugs in the scenario of widespread P. falciparum resistance.

First report on two-fold classification of Plasmodium falciparum carbonic anhydrase inhibitors using QSAR modeling approaches.

Quantitative structure-activity relationship (QSAR)-based classification approach is one of the important chemometric tools in drug discovery process for categorizing the target protein inhibitors into more active and less active classes. In this background, we have presented here a novel approach of two-fold QSAR-based classification modeling for the Plasmodium falciparum carbonic anhydrase (PfCA) inhibitors using 2D-QSAR and linear discriminant analysis (LDA) methods. The logic of applying this concept is to ensure more accurate classification of compounds and to draw some concrete conclusion about structure-activity relations for further work, in absence of 3D-protein structure and lack of sufficient experimental data using the PfCA target.

Classification SAR modeling of diverse quinolone compounds for antimalarial potency against Plasmodium falciparum.

Both a development of resistance to artemisinin monotherapy and lack of effective vaccine against malaria have created the urgent need for the development of new and efficient antimalarial agents. In this background, we have developed here a linear discriminant analysis (LDA) model and a few 3D-pharmacophore models for the classification of diverse quinolone compounds based on their antimalarial potency against Plasmodium falciparum. The discriminant model shows 70% correct classification for the test set compounds into higher active and lower active analogues.

Dibenzylideneacetone analogues as novel Plasmodium falciparum inhibitors.

A series of dibenzylideneacetones (A1-A12) and some of their pyrazolines (B1-B4) were synthesized and evaluated in vitro for blood stage antiplasmodial properties in Plasmodium falciparum culture using SYBR-green-I fluorescence assay. The compound (1E, 4E)-1,5-bis(3,4-dimethoxyphenyl)penta-1,4-dien-3-one (A9) was found to be the most active with IC(50) of 1.97 μM against chloroquine-sensitive strain (3D7) and 1.