Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a member of the Coronaviridae family, causing major destructions to human life directly and indirectly to the economic crisis around the world. Although there is significant reporting on the whole genome sequences and updated data for the different receptors are widely analyzed and screened to find a proper medication. Only a few bioassay experiments were completed against SARS-CoV-2 spike protein. We collected the compounds dataset from the PubChem Bioassay database having 1786 compounds and split it into the ratio of 80–20% for model training and testing purposes, respectively. Initially, we have created 11 models and validated them using a fivefold validation strategy. The hybrid consensus model shows a predictive accuracy of 95.5% for training and 94% for the test dataset. The model was applied to screen a virtual chemical library of Natural products of 2598 compounds. Our consensus model has successfully identified 75 compounds with an accuracy range of 70–100% as active compounds against SARS-CoV-2 RBD protein. The output of ML data (75 compounds) was taken for the molecular docking and dynamics simulation studies. In the complete analysis, the Epirubicin and Daunorubicin have shown the docking score of −9.937 and −9.812, respectively, and performed well in the molecular dynamics simulation studies. Also, Pirarubicin, an analogue of anthracycline, has widely been used due to its lower cardiotoxicity. It shows the docking score of −9.658, which also performed well during the complete analysis. Hence, after the following comprehensive pipeline-based study, these drugs can be further tested in vivo for further human utilization. Communicated by Ramaswamy H. Sarma

Background: The plant growth is influenced by multiple interactions with biotic (microbial) and abiotic components in their surroundings. These microbial interactions have both positive and negative effects on plant. Plant growth promoting bacterial (PGPR) interaction could result in positive growth under normal as well as in stress conditions. Methods: Here, we have screened two PGPR’s and determined their potential in induction of specific gene in host plant to overcome the adverse effect of biotic stress caused by Magnaporthe grisea, a fungal pathogen that cause blast in rice. We demonstrated the glucanase protein mode of action by performing comparative modeling and molecular docking of guanosine triphosphate (GTP) ligand with the protein. Besides, molecular dynamic simulations have been performed to understand the behavior of the glucanase-GTP complex. Results: The results clearly showed that selected PGPR was better able to induce modification in host plant at morphological, biochemical, physiological and molecular level by activating the expression of β-1,3-glucanases gene in infected host plant. The docking results indicated that Tyr75, Arg256, Gly258, and Ser223 of glucanase formed four crucial hydrogen bonds with the GTP, while, only Val220 found to form hydrophobic contact with ligand. Conclusions: The PGPR able to induce β-1,3-glucanases gene in host plant upon pathogenic interaction and β-1,3-glucanases form complex with GTP by hydrophilic interaction for induction of defense cascade for acquiring resistance against Magnaporthe grisea. Graphical

In our presented research, we made an attempt to predict the 3D model for cysteine synthase (A2GMG5_TRIVA) using homology-modeling approaches. To investigate deeper into the predicted structure, we further performed a molecular dynamics simulation for 10 ns and calculated several supporting analysis for structural properties such as RMSF, radius of gyration, and the total energy calculation to support the predicted structured model of cysteine synthase. The present findings led us to conclude that the proposed model is stereochemically stable. The overall PROCHECK G factor for the homology-modeled structure was −0.04. On the basis of the virtual screening for cysteine synthase against the NCI subset II molecule, we present the molecule 1-N, 4-N-bis [3-(1H-benzimidazol-2-yl) phenyl] benzene-1,4-dicarboxamide (ZINC01690699) having the minimum energy score (−13.0 Kcal/Mol) and a log Pvalue of 6 as a potential inhibitory molecule used to inhibit the growth ofT. vaginalisinfection.