ABSTRACT
In-silico Computer-Aided Drug Design (CADD) significantly relies on cybernetic screening of Plant Based Natural Products (PBNPs) as a prime source of bioactive compounds/ drug leads due to their unique chemical structural scaffolds and distinct functional characteristic features amenable to drug design and development. In the Post-COVID-Era a large number of publications have focused on PBNPs. Moreover, PBNPs still remain as an ideal source of novel therapeutic agents of GRAS standard. However, a well-structured, in-depth ADME/Tox profile with deeper dimensions of PBNPs has been lacking for many of natural pharma lead molecules that hamper successful exploitation of PBNPs. In the present study, ADMET-informatics of Octadecanoic Acid (Stearic Acid - SA) from ethyl acetate fraction of Moringa oleifera leaves has been envisaged to predict ADMET and pharmacokinetics (DMPK) outcomes. This work contributes to the deeper understanding of SA as major source of drug lead from Moringa oleifera with immense therapeutic potential. The data generated herein could be useful for the development of SA as plant based natural product lead (PBNPL) for drug development programs.