Computational methods applied to the discovery of stem cell factor ligands

摘要

A computational study of the stem cell factor (SCF) and potential ligands was carried out starting with a crystallographic model deposited in the protein data bank. The inhibition of the SCF dimerization equilibrium was considered as the rationale for the lead identification of specific ligands. A preliminary molecular dynamics characterization of the SCF dimer allowed to verify the most flexible loop involved in the dimeric area. Then a virtual screening, coupled with energy minimization in GB/SA water, scored the compounds implemented in the NCI diversity molecular database. Ten top ranked ligands were analyzed considering both the SCF loop perturbation in the dimerization area and the network of intermolecular hydrogen bonds. Among these ten compounds two natural agents were identified. The computational work revealed useful new insights for rational design of novel SCF dimerization inhibitors.