An in-silico scaffold- hopping approach to design novel inhibitors against gp130: A potential therapeutic application in cancer and Covid-19.

Abstract

An upregulation of the gp130-signalling cascade has been reported in multiple cancers, making gp130 an attractive target for the development of anticancer drugs. An inverted-funnel-like approach was utilised along with various structure-based drug designing strategies to discover and optimise novel potential inhibitors of gp130. The study resulted in the discovery of 2 ligands- 435 and 510, both of which exhibit a very high-binding affinity towards the gp130 D1 domain which controls cytokine recognition and interaction thus being involved in complexation. The two resulting complexes remained stable over time with the ligands maintaining a steady interaction with the target. This inference is drawn from their RMSD, R_g, SASA and RMSF analysis. We also tested the protein folding patterns based on their principal component analysis, energy of surface and landscape. The leads also displayed a more favourable ADMET profile than their parent compounds. The two lead candidates show a better therapeutic profile in comparison to the two existing drugs- bazedoxifene and raloxifene. Both these potential leads can be addressed for their activity in-vitro and can be used as a potential anti-cancer treatment as well as to combat Covid-19 related cytokine storm.