Computational prediction and analysis of targeting 17-beta-hydroxysteroid dehydrogenase (17-beta-HSD1) with natural products for colorectal cancer treatment

J Biomol Struct Dyn. 2023 Sep-Oct;41(16):7966-7974. doi: 10.1080/07391102.2022.2127904. Epub 2022 Oct 13.

Abstract

Colorectal cancer (CRC) is a type of cancer that occurs in the colon or rectum and kills millions of people each year. Steroid hormones are interconverted between their potent, high-affinity forms by using 17-beta hydroxysteroid dehydrogenase for their respective receptors in these tissues, with a high probability of random genetic errors. Currently, 17-beta-HSD1 studies have revealed the role of steroid metabolism in the development and proliferation of colorectal cancer. However, there is little information on how to target this enzyme with either modern medicine or natural products. In this study, we looked at 17-beta-HSD1 as a target for treating CRC development and proliferation using selected plant metabolites from previous studies. Plants are used to produce medicinal and novel bioactive compounds that are used to treat different infection. They primarily demonstrated anti-cancer effects through the regulation of cancer-related proteins, epigenetic factors and reactive oxygenase species. The study utilized Avogadro, ADMET lab 2.0, SWISS-MODEL, AutoDock, and Gromacs. Five lead molecules were chosen from a pool of plant metabolites based on their affinity for the 17-beta-HSD1 enzyme. Furthermore, two bind with high affinity are resveratrol (DG 11.29 kcal/mol) and folate (DG 12.23 kcal/mol) with low Ki values, while the rest binds with moderate affinity. Molecular dynamic simulation results also revealed that the folate-17-beta-HSD complex and reserverol- 17-beta-HSD1 complex maintained a stable conformation until the end of 100 ns. As a result, reserverol and folate could be used as lead molecules to target 17-beta-HSD1 and provide a promising starting point for further in vivo research.Communicated by Ramaswamy H. Sarma.

Keywords: AutoDock; Colorectal cancer; molecular dynamic simulation; silico study and cancer therapy.