Malaria continues to be a global health threat, with approximately 247 million cases worldwide. Despite therapeutic interventions being available, patient compliance is a problem due to the length of treatment. Moreover, drug-resistant strains have emerged over the years, necessitating urgent identification of novel and more potent treatments. Given that traditional drug discovery often requires a great deal of time and resources, most drug discovery efforts now use computational methods. In silico techniques such as quantitative structure-activity relationship (QSAR), docking, and molecular dynamics (MD) can be used to study protein-ligand interactions and determine the potency and safety profile of a set of candidate compounds to help prioritize those tested using assays and animal models. This paper provides an overview of antimalarial drug discovery and the application of computational methods in identifying candidate inhibitors and elucidating their potential mechanisms of action. We conclude with the continued challenges and future perspectives in the field of antimalarial drug discovery.

Human immunodeficiency virus remains a serious health threat, with an increase of 24% newly cases globally. Targeting Tat protein is an emerging therapeutic strategy for inhibiting the feedback loop that drives the exponential increase in viral transcription and particle production of the virus. The study aimed to determine the inhibitory potential of phenolic compounds from Ricinus communis L. and Jatropha curcas L., against the Tat C protein using in silico techniques. Phenolic compounds identified from both plants were screened by absorption-distribution-metabolism-excretion (ADME) analysis using drug-likeness prediction. Molecular docking analysis of the compounds with drug-like properties against the receptor and ligand-protein complexes’ analysis and visualization were performed. The results revealed three phenolic compounds with the highest negative binding affinity to the receptor’s active site: ellagic and neochlorogenic acids with - 7.2 kcal/mol and isohemiphloin with -7.3 kcal/mol. The interacting amino acids of the complexes were majorly His13, Lys19, Lys28, Thr64, His65, Gln66, Pro70, Gln72, and Pro73 via non-covalent interactions: hydrogen bonds, hydrophobic, and electrostatic interactions. The identified phenolic compounds provide a core structure that can be candidate for plant-based antiviral drugs development to potentially aiding in the virus’s therapeutic challenge.