Computational based in-silico and molecular docking approach for screening of phyto-constituents on PPAR targets in the treatment of NAFLD

Non-alcoholic fatty liver disease (NAFLD) has gradually become one of the most common liver diseases in the world, with high global occurrence whilst lacking the presence of effective treatment strategies. Herbal medicines known as “nature’s pharmacy” are an important component of all indigenous conventional therapies. A wide variety of herbal formulations are available in the market for varied uses, but limited bioavailability and scarce information of their ADME properties restrict their use and application. Experimental and computational approaches have hence now been readily employed to minimise the cost, time, and risk involved in the new drug discovery. In the current study, we have employed similar computational approaches to identify the target proteins of NAFLD i.e. (peroxisome proliferator-activated receptors )PPAR-α and PPAR-γ, which are the most well-known anti-obesity transcription factor found in the adipose and liver, followed by use of in-silicoand molecular docking analysis tools, to select the appropriate phyto-constituents for further formulation and evaluation. A reverse pharmacology based approach to identify phyto-constituents and the analysing of their in-silicoADME properties and binding actions on the PPARs by using docking studies were hence the aim of the current study. Identification of the important protein targets i.e PPAR-α, PPAR- γ, in-silico ADME analysis and screening, followed by molecular docking studies yielded Silymarin and Glycyrrhizic acid as the final lead molecules for further studies(-8.6,-8.4,-8.3,-8.9 kcal/mol respectively).The docking energies for each protein-ligand complex provided the insights that these said phytomolecules can further be used for studying their use as potential therapeutic agents for the alleviation of NAFLD.