Dataset on substituents effect on biological activities of linear RGD-containing peptides as potential anti-angiotensin converting enzyme

Data Brief. 2023 Aug 6:50:109478. doi: 10.1016/j.dib.2023.109478. eCollection 2023 Oct.

Abstract

The angiotensin converting enzyme inhibiting activity of linear rgd-containing peptides was investigated using in silico approach. The synthesized compound (parent compound) using experimental approach as well as its derivatives was subjected to computational examination using appropriate software. The investigated compounds were optimized using Spartan 14 while the docking study was executed via Pymol, AutoDock Tool, AutoDock Vina and discovery studio. The descriptors obtained (2D and 3D) were screened and the descriptor with highest capacity (squared correlation coefficient) was correlated to the calculated binding affinity. More so, the docking analysis was performed on the investigated linear rgd-containing peptides and angiotensin converting enzyme (PDB ID: 3nxq) via docking software and the resulted scoring and the types of the interaction observed were presented. Furthermore, (S)-dimethyl 2-(2-((S)-2-((R)-1-((S)-2-((S)-2-((S)-3-(4-chlorophenyl)-2-(1,3-dioxoisoindolin-2-yl)propanamido)-4-(methylthio)butanamido)-4-methylpentanoyl)pyrrolidine-2-carboxamido)-5-(3-((2,2,4,5,7-pentamethyl-2,3-dihydrobenzofuran-6-yl)sulfonyl)guanidino)pentanamido)acetamido)succinate (AB5) (compound with lowest binding affinity) and metformin were subjected to ADMET analysis and the resulted outcome were reported appropriately.

Keywords: Angiotensin converting enzyme; DFT; Diabetes; Disease; In silico; Peptides; RGD.