Integrating computational methods guided the discovery of phytochemicals as potential Pin1 inhibitors for cancer: pharmacophore modeling, molecular docking, MM-GBSA calculations and molecular dynamics studies

Pin1 is a pivotal player in interactions with a diverse array of phosphorylated proteins closely linked to critical processes such as carcinogenesis and tumor suppression. Its axial role in cancer initiation and progression, coupled with its overexpression and activation in various cancers render it a potential candidate for the development of targeted therapeutics. While several known Pin1 inhibitors possess favorable enzymatic profiles, their cellular efficacy often falls short. Consequently, the pursuit of novel Pin1 inhibitors has gained considerable attention in the field of medicinal chemistry. In this study, we employed the Phase tool from Schrödinger to construct a structure-based pharmacophore model. Subsequently, 449,008 natural products (NPs) from the SN3 database underwent screening to identify compounds sharing pharmacophoric features with the native ligand. This resulted in 650 compounds, which then underwent molecular docking and binding free energy calculations. Among them, SN0021307, SN0449787 and SN0079231 showed better docking scores with values of −9.891, −7.579 and −7.097 kcal/mol, respectively than the reference compound (−6.064 kcal/mol). Also, SN0021307, SN0449787 and SN0079231 exhibited lower free binding energies (−57.12, −49.81 and −46.05 kcal/mol, respectively) than the reference ligand (−37.75 kcal/mol). Based on these studies, SN0021307, SN0449787, and SN0079231 showed better binding affinity that the reference compound. Further the validation of these findings, molecular dynamics simulations confirmed the stability of the ligand-receptor complex for 100 ns with RMSD ranging from 0.6 to 1.8 Å. Based on these promising results, these three phytochemicals emerge as promising lead compounds warranting comprehensive biological screening in future investigations. These compounds hold great potential for further exploration regarding their efficacy and safety as Pin1 inhibitors, which could usher in new avenues for combating cancer

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

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