In silico analysis of a potential antidiabetic phytochemical erythrin against therapeutic targets of diabetes

In Silico Pharmacol. 2021 Jan 3;9(1):5. doi: 10.1007/s40203-020-00065-8. eCollection 2021.

Abstract

Diabetes mellitus is a multifactorial disorder characterized by a chronic elevation in blood glucose levels. Currently, antidiabetic drugs are available to counteract the associated pathologies. Their concomitant effects necessitate the investigation for an effective and safe drug aimed to diminish blood glucose levels with fewer side effects. Several researchers are taking new initiatives to explore plant sources as they are known to contain a wide variety of active agents. Hence, the present study was undertaken to study the role of natural products using in silico interaction studies. Erythrin a compound present in lichens was selected as a potential anti-diabetic agent. Molecular docking studies were carried out with 14 target proteins to evaluate its antidiabetic potential. Molecular docking analysis resulted in favourable binding energy of interaction ranging as low as - 119.676 to - 92.9545 kcal/mol for erythrin, Analogue showed the highest interactions with 3C45 (- 119.676 kcal/mol) followed by 2Q5S (- 118.398 kcal/mol), 1XU7 (- 117.341 kcal/mol), 3K35 (- 114.267 kcal/mol). Erythrin was found to fare better than the three clinically used antidiabetic compounds, metformin, repaglinide and sitagliptin. Further, the molecular interactions between erythrin and the diabetes related target proteins was established by analysing the interactions with associated amino acids. In silico pharmacokinetics and toxicity profile of erythrin using admetSAR software predicted erythrin as non-carcinogenic and non-mutagenic. The drug-likeliness was calculated using molsoft software respecting Lipinski's rule of five. The compound was found to comply with Lipinksi rules violating only one filter criterion. The study suggested that erythrin could be a potential anti-diabetic agent.

Keywords: Diabetes; Docking; Erythrin; Insilico analysis; admetSAR.