Use of the UM-164 scaffold to design the Tyrosine-Protein Kinase SRC inhibitors

Abstract

Studies show that c-Src plays a vital role in the progression, angiogenesis, and metastasis of cancer cells. This knowledge is mitigated by the fact that the Src kinase inhibitors tested on triple negative breast cancer xenograft models did not show promising results. UM-164 however, has been observed to have the dual activity of both Src kinase and p-38 kinase inhibition . This study aims to use the novel UM-164 scaffold in order to probe the c-Src kinase ligand binding pocket, and to, through virtual screening, identify analog structures capable of similar target receptor modulation. Ligand based drug design (Virtual Screening) and structure-based drug design (de novo) are the two approaches which will be used in this study. In phase 1 of the study, a consensus pharmacophore representing an average of the UM-164 and sulfonamide inhibitor scaffolds was modelled in LigandScout®. The consensus pharmacophore was then read into the online database ZincPharmer ® where 340 hit structures with a molecular weight of less than or equal to 300 were obtained. The molecules obtained were filtered in MONA and inputted into SybylX®v2.1.1 and Surflex docking was carried out. The molecules with the highest affinity seen as ‘Total Score’ were viewed and the interactions with the ligand binding pocket were observed. In phase 2, UM-164 was edited according to the interactions with the ligand binding pocket which was viewed from the topology map to create seeds. The GROW algorithm in LigBuilder® v1.2 was used on the previously generated seeds which were planted into the c-Src kinase key site and were left to grow within the parameters of Lipinski’s Rules. The topology maps of the highest and lowest binding affinities of the resulting molecules were compared. Finally, the structures of both the highest affinity molecules from the virtual screening and de novo approach were compared and the interactions with the ligand binding pocket were viewed. The select molecules with the highest affinities will be suggested for refinement, synthesis and in vitro validation to determine clinical efficacy.