Chemo-informatics guided study of natural inhibitors targeting rho GTPase: a lead for treatment of glaucoma

The discovery of subunit-selective GluN1/GluN2B NMDAR antagonist via pharmacophere-based virtual screening

The incidence and mortality rates of neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease, are gradually increasing worldwide. Numerous studies have demonstrated that N-methyl-D-aspartic acid receptor (NMDAR)-mediated excitotoxicity contributes to neurodegenerative diseases. Ifenprodil, a subtype-selective NMDAR antagonist, showed strong therapeutic potential. However, it suffers from low oral bioavailability and off-target side effects. In this study, natural compounds were identified for selective inhibition of GluN1/GluN2B NMDAR of human. We obtained a set of natural compounds (n = 81,366) from COCONUT, TIPdb, PAMDB, CMNPD, YMDB, and NPAtlas databases, and then virtually screened by an ifenprodil-structure-based pharmacophore model and molecular docking. The top 100 compounds were selected for binding affinity prediction via batch drug-target affinity (BatchDTA). Then, the top 50 compounds were analyzed by absorption, distribution, metabolism, excretion, toxicity (ADMET). Molecular dynamics involving molecular mechanics/position-Boltzmann surface area (MM-PBSA) calculation were performed to further screening. The top 15 compounds with strong binding affinity and ifenprodil, a proven GluN2B-selective NMDAR antagonist, were subjected to molecular dynamic simulations (100 ns), root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), H-bonds, solvent accessible surface area (SASA), principal component analysis (PCA), and binding free energy calculations. Based on these analyses, one possible lead compound carrying positive charges (CNP0099440) was identified, with great binding affinity and less off-target activity by contrast to ifenprodil. CNP0099440 has great potential to be a GluN1/GluN2B NMDAR antagonist candidate and can be further detected via in vitro and in vivo experiments.

Unraveling structural and conformational dynamics of DGAT1 missense nsSNPs in dairy cattle

Cattle are domestic animals that have been nourishing humans for thousands of years. Milk from cattle represents a key source of high-quality protein, fat, and other nutrients. The nutritional value of milk and dairy products is closely associated with the fat content, providing up to 30% of the total fat consumed in the human diet. The fat content in cattle milk represents a major concern for the scientific community due to its association with human health. The relationship between milk fat content and diacylglycerol o-acyltransferase 1 gene (DGAT1) is well described in literature. Several studies demonstrated the difference in fat contents and other milk production traits in a wide range of cattle breeds, to be associated with missense non-synonymous single nucleotide polymorphisms (nsSNPs) of the DGAT1 gene. As a result, an nsSNPs analysis is crucial for unraveling the DGAT1 structural and conformational dynamics linked to milk fat content. DGAT1-nsSNPs are yet to be studied in terms of their structural and functional impact. Therefore, state-of-the-art computational and structural genomic methods were used to analyze five selected variants (W128R, W214R, C215G, P245R, and W459G), along with the wild type DGAT1. Significant structural and conformational changes in the variants were observed. We illustrate how single amino acid substitutions affect DGAT1 function, how this contributes to our understanding of the molecular basis of variations in DGAT1, and ultimately its impact in improving fat quality in milk.

Structural insights into inhibition of PRRSV Nsp4 revealed by structure-based virtual screening, molecular dynamics, and MM-PBSA studies

BACKGROUND

Porcine reproductive and respiratory syndrome respiratory sickness in weaned and growing pigs, as well as sow reproductive failure, and its infection is regarded as one of the most serious swine illnesses worldwide. Given the current lack of an effective treatment, in this study, we identified natural compounds capable of inhibiting non-structural protein 4 (Nsp4) of the virus, which is involved in their replication and pathogenesis.

RESULTS

We screened natural compounds (n = 97,999) obtained from the ZINC database against Nsp4 and selected the top 10 compounds for analysing protein-ligand interactions and physicochemical properties. The five compounds demonstrating strong binding affinity were then subjected to molecular dynamics simulations (100 ns) and binding free energy calculations. Based on analysis, we identified four possible lead compounds that represent potentially effective drug-like inhibitors.

CONCLUSIONS

These methods identified that these natural compounds are capable of inhibiting Nsp4 and possibly effective as antiviral therapeutics against PRRSV.