Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was found to be a severe threat to global public health in late 2019. Nevertheless, no approved medicines have been found to inhibit the virus effectively. Anti-malarial and antiviral medicines have been reported to target the SARS-CoV-2 virus. This paper chose eight natural eucalyptus compounds to study their binding interactions with the SARS-CoV-2 main protease (Mpro) to assess their potential for becoming herbal drugs for the new SARS-CoV-2 infection virus. In-silico methods such as molecular docking, molecular dynamics (MD) simulations, and Molecular Mechanics Poisson Boltzmann Surface Area (MM/PBSA) analysis were used to examine interactions at the atomistic level. The results of molecular docking indicate that Mpro has good binding energy for all compounds studied. Three docked compounds, α-gurjunene, aromadendrene, and allo-aromadendrene, with highest binding energies of −7.34 kcal/mol (−30.75 kJ/mol), −7.23 kcal/mol (−30.25 kJ/mol), and −7.17 kcal/mol (−29.99 kJ/mol) respectively, were simulated with GROningen MAchine for Chemical Simulations (GROMACS) to measure the molecular interactions between Mpro and inhibitors in detail. Our MD simulation results show that α-gurjunene has the strongest binding energy of −20.37 kcal/mol (−85.21 kJ/mol), followed by aromadendrene with −18.99 kcal/mol (−79.45 kJ/mol), and finally allo-aromadendrene with −17.91 kcal/mol (−74.95 kJ/mol). The findings indicate that eucalyptus may be used to inhibit the Mpro enzyme as a drug candidate. This is the first computational analysis that gives an insight into the potential role of structural flexibility during interactions with eucalyptus compounds. It also sheds light on the structural design of new herbal medicinal products against Mpro.

Procurement of measuring device, maintenance cost coupled with calibration of the instrument contributed to the difficulty in forecasting of global solar radiation in underdeveloped countries. Most of the available regressional and mathematical models do not capture well the behavior of the global solar radiation. This paper presents the comparison of Adaptive Neuro Fuzzy Inference System (ANFIS) and Autoregressive Moving Average with eXogenous term (ARMAX) in forecasting global solar radiation. Full-Scale (experimental) data of Nigerian metrological agency, Sultan Abubakar III international airport Sokoto was used to validate the models. The simulation results demonstrated that the ANFIS model having achieved MAPE of 5.34% outperformed the ARMAX model. The ANFIS could be a valuable tool for forecasting the global solar radiation.

Background: The consistently increasing reports of bacterial resistance and the reemergence of bacterial epidemics have inspired the health and scientific community to discover new molecules with antibacterial potential continuously. Frog-skin secretions constitute bioactive compounds essential for finding new biopharmaceuticals. The exact antibacterial characterization of dermaseptin related peptides derived from Agalychnis annae, is limited. The resemblance in their conserved and functionally linked genomes indicates an unprecedented opportunity to obtain novel bioactive compounds. Objective: In this study, we derived a novel peptide sequence and determined its antibacterial potentials. Methods: Consensus sequence strategy was used to design the novel and active antibacterial peptide named 'AGAAN' from skin secretions of Agalychnis annae. The in-vitro activities of the novel peptide against some bacterial strains were investigated. Time kill studies, DNA retardation, cytotoxicity, betagalactosidase, and molecular computational studies were conducted. Results: AGAAN inhibited P. aeruginosa, E. faecalis, and S. typhimurium at 20 mu M concentration. E. coli and S. aureus were inhibited at 25 mu M, and lastly, B. subtilis at 50 mu M. Kinetics of inactivation against exponential and stationary growing bacteria was found to be rapid within 1-5 hours of peptide exposure, depending on time and concentration. The peptide displayed weak hemolytic activity between 0.01%-7.31% at the antibacterial concentrations. AGAAN efficiently induced bacterial membrane damage with subsequent cell lysis. The peptide's DNA binding shows that it also targets intracellular DNA by retarding its movement. Our in-silico molecular docking analysis displayed a strong affinity to the bacterial cytoplasmic membrane. Conclusion: AGAAN exhibits potential antibacterial properties that could be used to combat bacterial resistance.

Aldose reductase (AR) is an enzyme of the polyol pathway implicated in long-term effect of diabetes mellitus. The development of new molecules as drugs for the inhibition of this enzyme is a growing area of research. Several in vivo and in vitro studies have been carried out to test the inhibitory effect of many organic compounds against AR, but the results have been limited due to their weak pharmacokinetic parameters and safety profile. In this study, molecular docking and molecular dynamics (MD) simulation were performed to establish the inhibitory effect of two critical bioactive compounds (astaxanthin and zeaxanthin) that were affirmed to be safe and powerful antioxidants. Docking studies revealed that both astaxanthin and zeaxanthin displays good binding affinity and inhibition to AR with binding energies of -5.88 kcal/mol and - 5.63 kcal/mol, respectively. In contrast to epalrestat; the standard inhibitor having a binding energy of - 5.62 kcal/mol. Amino acid residue analysis has shown that both compounds, including the standard inhibitor, bind to the same site due to their common interaction with Trp20 and Tyr48 at AR catalytic site. To complement molecular docking results, we performed MD simulations. The results show that the binding energies of the standard inhibitor, astaxanthin, and zeaxanthin are -134.3486 kJ/mol, -186.271 kJ/mol, and -123.557 kJ/mol, respectively. In both cases, astaxanthin displays better inhibition to AR followed by the standard inhibitor and zeaxanthin.