Abstract

COMPUTATIONAL APPROACH FOR THE EVALUATION OF BIOACTIVE COMPOUNDS FROM ETHNOBOTANICALS FOR THEIR PHARMACOLOGICAL POTENTIAL AND BIOLOGICAL ACTIVITY

Suhail Mohammed Hussain, Arbaaz Ahmed L., Shrihith A., Sateesh M. K.*

ABSTRACT

Providing safe and effective drug therapy requires knowledge on the pharmacokinetics and pharmacodynamics of drugs. Many synthetic drugs often fail to enter the market as a result of poor pharmacokinetic and pharmacodynamics profile. Medicinal plants have traditionally proven their value as a basis for molecules with therapeutic potential, and currently they represent a significant pool for novel drug leads. Plants contain a number of phytopharmaceuticals that are responsible for various biological activities. Traditionally, drugs are discovered by testing compounds synthesized in time-consuming multi-step processes against a battery of in vivo biological screening. The use of computational tools in prediction of pharmacological and biological properties of phytochemical compounds is growing rapidly in drug discovery as the benefits they provide in high throughput and early application in drug design are realized. In the present study we have tested 330 GC- MS derived phytocompounds from ten ethnobotanicals viz., Eupatorium triplinerve, Abrus precatorius, Stylosanthes fruticosa, Epipremnium aureum, Annona squamosa, Ficus carica, Punica granatum, Cassia italic, Madhuca longifolia and Aegle marmelos for their biological activity as promising therapeutic compounds. The drug likeliness of the selected compounds were predicted by WDI and Lipinski‟s “rule of five” using Molsoft Online Tool. The ADMET properties, Ames test, Carcinogenic and Mutagenic properties were checked by PreADMET server. Out of 330 compounds analyzed, sixteen compounds were reported as non-mutagenic and non-carcinogenic phytocompounds. Biological activity of these sixteen compounds were predicted individually using PASS server, activities such as antibacterial, antifungal, antihelmenthic, antidiabetic and antieczematic etc. were reported for these compounds. In the present article, an effort has been made to reveal various pharmacological potentiality of phytocompounds and these compounds can be further studied in vitro and in vivo for the discovery of novel drugs.

Keywords: ADME, PASS, Computational tools, biological activity, Drug Discovery.