Targeting human inosine 5' monophosphate dehydrogenase type 2 for anti-dengue lead identification - a computational approach.

Dengue is a rapidly evolving arboviral disease that mainly affects tropical and subtropical regions of the world. The lack of therapeutic drugs and effective vaccines suggests that further resources need to be investigated. The effectiveness of the existing dengue vaccine is improbable as its efficacy depends on prior exposure to the dengue virus(DENV). Although the mechanism underlying the action of bioactive compounds to limit viral replication is less studied and still needs to be further explored, medicinal plants are excellent alternatives to combat DENV infection. In the current study, an in silico screening of phytochemicals from Annona reticulata Linn. against human Impdh2 was performed using Autodock Vina. Daucosterol (-9.0 kcal/mol) and Kaurenoic acid (-8.5 kcal/mol) were chosen as the top hits based on molecular interaction analysis. The hits were further exposed to pharmacokinetics and toxicity properties to determine their drug-like parameters. Molecular dynamics simulation studies of the Impdh2-top hits were carried out to investigate their kinetic behaviour and structural stabilities. The binding free energies of the Impdh2-hit complexes were determined using MM-PBSA analysis. According to the overall conclusions of the study, Daucosterol showed good binding affinity and high structural stability to the binding site residues of the target, therefore it is recommended as a lead compound against dengue.Communicated by Ramaswamy H. Sarma.

Computational investigation of Moringa oleifera phytochemicals targeting EGFR: molecular docking, molecular dynamics simulation and density functional theory studies.

Epidermal growth factor receptor (EGFR) is a prominent target for anticancer therapy due to its role in activating several cell signaling cascades. Clinically approved EGFR inhibitors are reported to show treatment resistance and toxicity, this study, therefore, investigates Moringa oleifera phytochemicals to find potent and safe anti-EGFR compounds. For that, phytochemicals were screened based on drug-likeness and molecular docking analysis followed by molecular dynamics simulation, density functional theory analysis and ADMET analysis to identify the effective inhibitors of EGFR tyrosine kinase (EGFR-TK) domain. Known EGFR-TK inhibitors (1-4 generations) were used as control. Among 146 phytochemicals, 136 compounds showed drug-likeness, of which Delta 7-Avenasterol was the most potential EGFR-TK inhibitor with a binding energy of -9.2 kcal/mol followed by 24-Methylenecholesterol (-9.1 kcal/mol), Campesterol (-9.0 kcal/mol) and Ellagic acid (-9.0 kcal/mol). In comparison, the highest binding affinity from control drugs was displayed by Rociletinib (-9.0 kcal/mol). The molecular dynamics simulation (100 ns) exhibited the structural stability of native EGFR-TK and protein-inhibitor complexes. Further, MM/PBSA computed the binding free energies of protein complex with Delta 7-Avenasterol, 24-Methylenecholesterol, Campesterol and Ellagic acid as -154.559 ± 18.591 kJ/mol, -139.176 ± 19.236 kJ/mol, -136.212 ± 17.598 kJ/mol and -139.513 ± 23.832 kJ/mol, respectively. Non-polar interactions were the major contributors to these energies. The density functional theory analysis also established the stability of these inhibitor compounds. ADMET analysis depicted acceptable outcomes for all top phytochemicals without displaying any toxicity. In conclusion, this report has identified promising EGFR-TK inhibitors to treat several cancers that can be further investigated through laboratory and clinical tests.