Structure based pharmacophore modelling and Docking with adam 33 for identification of natural lead compounds.

Abstract

ADAM33 (a disintegrin and metalloproteinase 33) plays a vital role in asthma for children. It is identified as a major susceptibility gene in asthma linked to bronchial hyper- responsiveness. ADAM33 is involved in many other anomalies. It is a novel molecular biomarker of Triple-negative breast cancer. The aim of the study is to identify potential natural inhibitors for ADAM33 as therapeutic targets for asthma as the synthetic compounds may have side effects. The pharmacophore of known inhibitor from binding database was developed and screened against 100,000 Natural compounds from Phase Database using Schrodinger software. Short listed natural compounds were docked with ADAM33 and the best three compounds were checked for ADMET properties. The compounds which had acceptable ADMET property range are identified as the best leads and will be used for further studies.