Cardiovascular diseases (CVDs) have become the leading cause of disability and death worldwide, particularly in low- and middle-income countries. Hypertension, a major cause of CVD progression, is widely attributable to genetic, behavioral, and environmental risk factors. Among the genetic reasons, angiotensin II enzyme, produced as a result of abnormal functioning of the renin–angiotensin system, is reported as the foremost cause of hypertension. A cascade of genes, including those encoding for WNK kinases (WNK1 and WNK4), Bp1, Bp2, angiotensinogen, and other enzymes, is involved in the conversion of angiotensin I to angiotensin II. However, the angiotensin-converting enzyme (ACE) plays a crucial role in this pathway. Therefore, ACE could be a potential therapeutic target in regulating the conversion of angiotensin I to angiotensin II and eventually controlling hypertension. In this study, a molecular docking-based approach was utilized for identifying and evaluating potential inhibitors of ACE present in herbs, other natural sources, and synthetic sources, on the basis of these compounds’ binding affinities and other physicochemical features. In addition, the suitability of these inhibitors as drugs for biological systems, considering their adsorption, distribution, metabolism, and excretion (ADME), was predicted using Lipinski’s rule. In conclusion, our study provides a novel and clearer insight into the interaction properties of known putative inhibitors of ACE.

Methicillin‐resistant Staphylococcus aureus (MRSA) has evolved resistance even against the last resort β‐lactam antibiotics. This is because of the acquisition of an additional penicillin‐binding protein 2a (PBP2a) which is a resistance determinant in MRSA. Currently, available PBP2a inhibitors are ineffective against life‐threatening and fatal infections caused by microorganisms. Therefore, there is an urgent need to screen natural compounds that could overpass the resistance issue alone or in combination with antibacterial drugs. We studied the interactions of different phytochemicals with PBP2a so that crosslinking of peptidoglycans could be inhibited. In structure‐based drug designing, in silico approach plays a key role in determining phytochemical interactions with PBP2a. In this study, a total of 284 antimicrobial phytochemicals were screened using the molecular docking approach. The binding affinity of methicillin, ‐11.241 kcal/mol, was used as the threshold value. The phytochemicals having binding affinities with PBP2a stronger than methicillin were identified, and the drug‐likeness properties and toxicities of the screened phytochemicals were calculated. Out of the multiple phytochemicals screened, nine were found as good inhibitors to be PBP2a, among which cyanidin, tetrandrine, cyclomorusin, lipomycin, and morusin showed strong binding potential with the receptor protein. These best‐selected phytochemicals were also docked to the allosteric site of PBP2a, and most of the compounds revealed strong interactions with the allosteric site. These compounds were safe to be used as drugs because they did not show any toxicity and had good bioactivity scores. Cyanidin had the highest binding affinity (S‐score of ‐16.061 kcal/mol) with PBP2a and with high gastrointestinal (GI) absorption. Our findings suggest that cyanidin can be used as a drug against MRSA infection either in purified form or that its structure can lead to the development of more potent anti‐MRSA medicines. However, experimental studies are required to evaluate the inhibitory potential of these phytochemicals against MRSA.

Interleukin 17 F is a member of IL-17 cytokine family with a 50% structural homology to IL-17A and plays a significant role either alone or in combination with IL-17A towards inflammation in Rheumatoid arthritis (RA). A growing number of drugs targeting IL-17 pathway are being tested against population specific disease markers. The major objective of this research was to investigate the anti-inflammatory effect of Anakinra (an IL-1 R1 inhibitor) and Ustekinumab (an IL-12 and IL-23 inhibitor) by targeting IL17F. The three dimensional structures of IL17F was taken from PDB while structures of drugs were taken from PubChem database. Docking was performed using MOE and Schrodinger ligand docking software and binding energies, including s-score using London-dG fitness function and glide score using glide internal energy function, between drug and targets were compared. Furthermore, Protein-Drug complex were subjected to 150 ns Molecular Dynamics (MD) Simulations using Schrodinger's Desmond Module. Docking and MD simulation results suggest anakinra as a more potent IL17F inhibitor and forming a more structurally stable complex.Communicated by Ramaswamy H. Sarma.

Hepatitis E virus (HEV) is the notable causative agent of acute and chronic hepatic, renal, pancreatic, neurological, and hematopoietic blood cell infections with high risk in immunocompromised patients. Hepatic failure is mostly documented among adults, pregnant women, and patients with preexisting liver disease. HEV is a positive sense RNA virus of 7.2 kb genome size with typically three open reading frames (ORFs) which play essential roles in viral replication, genome assembly, and transcription. The mutational substitution in the viral RNA genome makes more it difficult to understand the actual relationship in the host–virus association. ORFs of HEV encode different structural and non-structural proteins and one of them is the capsid protein which is coded by ORF2. The capsid protein mediates the encapsulation of the viral genome as well as being involved in virion assembly. In the current study, the ligand-based docking approach was employed to inhibit the active amino acids of the viral capsid protein. Depending upon S-score, ADMET profiling, and drug scanning, the top ten tetrapeptides were selected as potential drug candidates with no toxicity counter to HEV receptor protein. The S-score or docking score is a mathematical function which predicts the binding affinities of docked complexes. The binding affinity of the predicted drug–target complexes helps in the selectivity of the desired compound as a potential drug. The best two selected peptides (i.e., TDGH with S-score of −8.5 and EGDE with S-score of −8.0) interacted with the active site amino acids of the capsid protein (i.e., Arg399, Gln420, and Asp444). The molecular dynamics simulations of RMSD trajectories of TDGH–capsid protein and EDGE–capsid protein have revealed that both docked complexes were structurally stable. The study revealed that these tetrapeptides would serve as strong potential inhibitors and a starting point for the development of new drug molecules against the HEV capsid protein. In future, in vivo studies are needed to explore selected peptides as potential drug candidates.