Fibroblast growth factor 2 is a druggable target against glioblastoma: A computational investigation

Abstract

Fibroblast growth factor 2 (FGF2) is a key player in cancer and tissue homeostasis and regulates renewal of several stem cell types. The FGF2 role in malignant glioma is proven and tagged FGF2, a novel druggable target, is used for developing potent drugs against glioblastoma. In this study, Asinex 51412372, Asinex 51217461, and Asinex 51216586 were filtered to show the best binding affinity for FGF2 with binding energy scores of -8.3 kcal/mol, -8.2 kcal/mol, and -7.8 kcal/mol, respectively. The compounds showed chemical interactions with several vital residues of FGF2 along the compound length. The noticeable residues that interacted with the compounds were Arg15, Asp23, Arg63, and Gln105. In dynamic investigation in solution, the FGF2 reported unstable dynamics in the first 100 ns and gained structural equilibrium in the second phase of 100 ns. The maximum root mean square deviation (RMSD) value touched by the systems is 3 Å. Similarly, the residue flexibility of FGF2 in the presence of compounds was within a stable range and is compact along the simulation time length. The compounds showed robust atomic-level stable energies with FGF2, which are dominated by both van der Waals and electrostatic interactions. The net binding energy of systems varies between -40 kcal/mol and -86 kcal/mol, suggesting the formation of strong intermolecular docked complexes. The drug-likeness and pharmacokinetic properties also pointed toward good structures that are not toxic, have high gastric absorption, showed good distribution, and readily excreted from the body. In summary, the predicted compounds in this study might be ideal hits that might be further optimized for structure and activity during experimental studies.

Keywords: computer-aided drug design; drug–target; fibroblast growth factor 2; glioma; molecular dynamic simulation; virtual screening.