In silico approaches and proportional odds model towards identifying selective ADAM17 inhibitors from anti-inflammatory natural molecules

Abstract

ADAM metallopeptidase domain 17 (ADAM17) is an attractive target for the development of new anti-inflammatory drugs. We aimed to identify selective inhibitors of ADAM17 against matrix metalloproteinase enzymes (MMP-1, MMP-2, MMP-3, MMP-7, MMP-8, MMP-9, MMP-13, and MMP-16) which have substantial structural similarity. Target proteins were docked with 29 anti-inflammatory natural molecule ligands and a known selective inhibitor IK682. The ligands were screened based on Lipinski rules, interaction with the ADAM17 active site cavity, and then ranked using the proportional odds model multinomial logistic regression. Silymarin was the most selective inhibitor of ADAM17 exhibiting H-bonding with Glu 406, Gly 349, Glu 398, Asn 447, Tyr 433, and Lys 432. Molecular dynamics simulations were carried out for 10ns. The root mean square deviation (RMSD), root mean squared fluctuations (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), and H-bonding indicated the induced metastability. A comparison of the principal component analysis revealed that the silymarin complex also explored lesser region compared to IK682 complex. A control study on ADAM17 protein (2OI0) is included. These observations present silymarin (widely present in plants such as milk thistle (Silybum maianum), wild artichokes (Cynara cardunculus), turmeric (Curcuma longa) roots, coriander (Coriandrum sativum) seeds, etc.) as a promising natural template for development of ADAM17 selective drugs.