In silico analysis of antidiabetic activity and admet prediction of potential compounds from luffa acutangula

Luffa acutangula is commonly used and considerable potential as an alternative treatment of diabetic with a molecular target action are not yet known. Preliminary study of bioinformatics to decipher the various chemical constituents of L. acutangula able to interact with the protein targets of an antidiabetic therapeutic. This study aims to identify the chemical constituents of L. acutangula are thought to interact with insulin receptor, aldose reductase, α-glucosidase, PTP-1B, GSK-3B, PPARγ, and accompanied by predictions of pharmacokinetic and toxicity. Docking molecular was conducted in AutoDock 4.2.6 with the stages initiated by preparation of macromolecule (PDB ID: 1IR3; 2PEV; 2QMJ; 4Y14; 4PTE; 4R06) and ligand, method validation, simulation to the result visualization of docking molecular. The pharmacokinetic profiles are predictable by using the SwissADME webform and toxicity estimated by Toxtree related to three best ligands on each macromolecule. The results showed that cucurbitacin B and cucurbitacin E are the most potential compounds to interact with the macromolecular with a binding energy response similar to the native ligand. Pharmacokinetic predictions show that cucurbitacin B and cucurbitacin E are deviate from one Lipinski rules (BM> 500), do not diffuse into the blood brain barrier, not as a CYP450 inhibitor and classified as Pgp substrates. The prediction of toxicity indicates that all potential compounds are classified as high toxicity compounds with risk of narcosis, except oleanolic acid and ferulic acid. But these compounds are not genotoxic or non-genotoxic carcinogens.