The NLR family of innate immune and cell death sensors.

Nucleotide-binding oligomerization domain (NOD)-like receptors, also known as nucleotide-binding leucine-rich repeat receptors (NLRs), are a family of cytosolic pattern recognition receptors that detect a wide variety of pathogenic and sterile triggers. Activation of specific NLRs initiates pro- or anti-inflammatory signaling cascades and the formation of inflammasomes-multi-protein complexes that induce caspase-1 activation to drive inflammatory cytokine maturation and lytic cell death, pyroptosis. Certain NLRs and inflammasomes act as integral components of larger cell death complexes-PANoptosomes-driving another form of lytic cell death, PANoptosis. Here, we review the current understanding of the evolution, structure, and function of NLRs in health and disease. We discuss the concept of NLR networks and their roles in driving cell death and immunity. An improved mechanistic understanding of NLRs may provide therapeutic strategies applicable across infectious and inflammatory diseases and in cancer.

Computational investigation of natural compounds as potential main protease (Mpro) inhibitors for SARS-CoV-2 virus.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is significantly impacting human lives, overburdening the healthcare system and weakening global economies. Plant-derived natural compounds are being largely tested for their efficacy against COVID-19 targets to combat SARS-CoV-2 infection. The SARS-CoV-2 Main protease (Mpro) is considered an appealing target because of its role in replication in host cells. We curated a set of 7809 natural compounds by combining the collections of five databases viz Dr Duke's Phytochemical and Ethnobotanical database, IMPPAT, PhytoHub, AromaDb and Zinc. We applied a rigorous computational approach to identify lead molecules from our curated compound set using docking, dynamic simulations, the free energy of binding and DFT calculations. Theaflavin and ginkgetin have emerged as better molecules with a similar inhibition profile in both SARS-CoV-2 and Omicron variants.

MDCKpred: a web-tool to calculate MDCK permeability coefficient of small molecule using membrane-interaction chemical features.

Structure-based models to understand the transport of small molecules through biological membrane can be developed by enumerating intermolecular interactions of the small molecule with a biological membrane, usually a dimyristoylphosphatidylcholine (DMPC) monolayer. This ADME (absorption, distribution, metabolism, and excretion) property based on Madin-Darby Canine Kidney (MDCK) cell line demonstrates intestinal drug absorption of small molecules and correlated to human intestinal absorption which acts as a determining factor to forecast small-molecule prioritization in drug-discovery projects. We present here the development of MDCKpred web-tool which calculates MDCK permeability coefficient of small molecule based on the regression model, developed using membrane-interaction chemical features. The web-tool allows users to calculate the MDCK permeability coefficient (nm/s) instantly by providing simple descriptor inputs. The chemical-interaction features are derived from different parts of the DMPC molecule viz. head, middle, and tail regions and accounts overall intermolecular contacts of the small molecule when passively diffused through the phospholipid-rich biological membrane. The MDCKpred model is both internally (R2 = .76; [Formula: see text]= .68; Rtrain = .87; Rtest = .69) and externally (Rext = .55) validated. Furthermore, we used natural molecules as application examples to demonstrate its utility in lead exploration and optimization projects. The MDCKpred web-tool can be accessed freely at http://www.mdckpred.in . This web-tool is designed to offer an intuitive way of prioritizing small molecules based on calculated MDCK permeabilities.

Ameliorative effects of curcumin towards cyclosporine-induced genotoxic potential: an in vitro and in silico study.

Several studies documented the ameliorative effects of curcumin which plays a pivotal role in radical scavenging activities. It also participates in various cellular pathways and interacts with multiple targets. In the present study, we investigated the ameliorative effect of curcumin upon chromosomal genotoxicity induced by cyclosporine, an immunosuppressant, using in vitro approaches. A plausible mechanism of how curcumin mitigates the genotoxic implications of cyclosporine was ascertained using in silico tools. We observed that the curcumin reduces the genotoxic consequences made by cyclosporine upon cell cycle checkpoints and associated chromosomal/DNA manifestations. In addition, we presented the mechanistic details of curcumin interaction with various biomacromolecule types using docking experiments which showed that the possible radical scavenging activities can only be emerged by inducing the expression of antioxidant enzymes, supported by available experimental evidences. We anticipate that the induction of antioxidant enzymes by curcumin would activate Nrf2-Keap1 pathway as the plausible mechanism to exert anti-inflammatory response as demonstrated in renal epithelial cells.

Pharmacophore-similarity-based QSAR (PS-QSAR) for group-specific biological activity predictions.

Recent technological breakthroughs in medicinal chemistry arena had ameliorated the perspectives of quantitative structure-activity relationship (QSAR) methods. In this direction, we developed a group-based QSAR method based on pharmacophore-similarity concept which takes into account the 2D topological pharmacophoric descriptors and predicts the group-specific biological activities. This activity prediction may assist the contribution of certain pharmacophore features encoded by respective fragments toward activity improvement and/or detrimental effects. We termed this method as pharmacophore-similarity-based QSAR (PS-QSAR) and studied the activity contribution of fragments from 3-hydroxypyridinones derivatives possessing antimalarial activities.

A Computational Approach towards the Understanding of Plasmodium falciparum Multidrug Resistance Protein 1.

The emergence of drug resistance in Plasmodium falciparum tremendously affected the chemotherapy worldwide while the intense distribution of chloroquine-resistant strains in most of the endemic areas added more complications in the treatment of malaria. The situation has even worsened by the lack of molecular mechanism to understand the resistance conferred by Plasmodia species. Recent studies have suggested the association of antimalarial resistance with P. falciparum multidrug resistance protein 1 (PfMDR1), an ATP-binding cassette (ABC) transporter and a homologue of human P-glycoprotein 1 (P-gp1). The present study deals about the development of PfMDR1 computational model and the model of substrate transport across PfMDR1 with insights derived from conformations relative to inward- and outward-facing topologies that switch on/off the transportation system. Comparison of ATP docked positions and its structural motif binding properties were found to be similar among other ATPases, and thereby contributes to NBD domains dimerization, a unique structural agreement noticed in Mus musculus Pgp and Escherichia coli MDR transporter homolog (MsbA). The interaction of leading antimalarials and phytochemicals within the active pocket of both wild-type and mutant-type PfMDR1 demonstrated the mode of binding and provided insights of less binding affinity thereby contributing to parasite's resistance mechanism.