Utilization of computational methods for the identification of new natural inhibitors of human neutrophil elastase in inflammation therapy

Abstract

Human neutrophil elastase (HNE) plays a crucial role in causing tissue damage in various chronic and inflammatory disorders, making it a target for treating inflammatory diseases. While some inhibitors of HNE’s activity have been identified, only a few have made it to clinical trials. In this study, computational methods were employed to identify potential natural products (NPs) capable of targeting the active site of HNE. The protein–ligand complex has been used to generate a pharmacophore model. A library of 449,008 NPs from the SN3 database was screened against the generated model, resulting in 29,613 NPs that matched the pharmacophore hypothesis. These compounds were docked into the protein active site, resulting in the identification of six promising NPs with better docking scores than the bound ligand to HNE. The top two NPs (SN0338951 and SN0436937) were further evaluated for their interaction stability with HNE through molecular dynamics simulations. Further, the pharmacokinetics and toxicity properties of these compounds were predicted. The results indicated that these two compounds have stable interactions with HNE, as well as, acceptable pharmacokinetic properties. These findings pave the path for further in vitro and in vivo studies of SN0338951 and SN0436937 as promising agents against inflammatory diseases.

Keywords

• hne
• inflammatory diseases
• natural products
• pharmacophore modeling
• docking
• admet
• md