Assessment of Genetic Diversity, Micromorphology and Antimicrobial Activity in Nepeta cataria L.

The mosquito repellent Nepetalactone rich Nepeta cataria L. (catmint) plant has a variety of therapeutic and industrial potential. Reports on the genetic diversity of N. cataria germplasm are minimal globally and need attention for adding a new variety into commercial cultivation. The present study, therefore, assessed the genetic diversity among thirteen half-sib genotypes of N. cataria using agro economic and phytochemical traits. The experimental set has shown substantial variation for agro economic traits studied. Among all the studied populations, fresh herb-based essential oil content ranged from 0.1 % to 0.3 %, with a grand mean of 1.67 %. However, the estimated oil yield ranged from 44.4 kg/h to 120.73 kg/h with an average of 71.34 kg/h. Among the eleven phytochemical constituents detected in different concentrations in the essential oil of experimental sets, 4aα,7α,7aα-Nepetalactone (67.9-87.5 %) constituted the significant proportion of essential oil. Altogether, based on mean comparison, the population NC8 was found to be promising for estimated oil yield and 4aα,7α,7aα-Nepetalactone content. The greater heritability estimates (h2 bs) and genetic advance as percent of mean (GAM) were observed for important economic parameters, i. e., oil content, herb yield, and oil yield. The cluster analysis revealed the least interactions between various agro economic and phytochemical variables. The microscopic study of trichome showed a positive correlation of abaxial leaf surface with essential oil content. The promising antimicrobial potential of catmint oil was also observed against human health-related pathogens. The results infer from our study provide valuable insight for genetic improvement and product development in the catmint germplasm.

Cryptosporidiosis, a public health challenge: A combined 3D shape-based virtual screening, docking study, and molecular dynamics simulation approach to identify inhibitors with novel scaffolds for the treatment of cryptosporidiosis

Cryptosporidiosis is a neglected tropical disease caused by the protozoan parasite Cryptosporidium parvum. Limited therapeutic options, limitation in in vitro parasite culture, and lack of a reliable animal model of parasite for replication of in vivo life cycle and drug testing demand alternative methods for drug development. The in silico methods of drug discovery prove a crucial process in such conditions.Recent research reported a limited number of small molecules for drug development. Purine nucleotide biosynthesis in Cryptosporidium species is dependent on the IMPDH (CpIMPDH) enzyme, so distortion of parasite IMPDH has been pursued as a compelling strategy for curbing Cryptosporidium infection due to its different kinetics from the host enzyme. Our study's primary aim was to discover novel ligand molecules with noticeable activity against Cryptosporidium parvum IMPDH. For this purpose, we selected 18 previously discovered ligands to understand the interaction feature between ligand and receptor, and their shape and electronic features are employed as a template for shape-based virtual screening of the ZINC database (drug-like subset) search approach via Schrodinger-2019 (Maestro 11.9). The obtained hits were subsequently subjected to structure-based screening, quantum polarized ligand docking (QPLD), and molecular dynamics simulations to fetch potential small molecules with the highest binding affinity for CpIMPDH protein. Further ligand binding energy and pharmacokinetic analysis were also taken into consideration as filtering criteria for selecting the most promising drug-like compounds. On this experimentation analysis, three top-ranked (ZINC24855054, ZINC58171263, and ZINC08000072) molecules were found to have appropriate pharmacokinetic properties along with surpassing in silico inhibitory potential towards the CpIMPDH compared to known inhibitors. The molecular docking and molecular dynamics simulation analysis results satisfactorily confirmed the inhibitory action. Therefore, these new scaffolds deduced by the presented computational methodology could recommend lead molecules for designing promising anti-cryptosporidial drugs targeting CpIMPDH protein.