Computational Approaches for the Identification and Optimization of Src Family Kinases Inhibitors
Src family kinases (SFKs) are a group of non-receptor tyrosine kinases whose activity is involved in the regulation
of cellular morphology, motility, proliferation and survival. An aberrant activation and expression of these kinases
contribute to the pathogenesis and progression of a broad range of diseases, such as a large number of solid tumors, various
hematological malignancies and some neuronal pathologies. The search for SFK inhibitors is therefore a promising
research topic in medicinal chemistry. Computational studies such as receptor-based and/or ligand-based virtual screening,
docking, and molecular modeling proved to be a powerful tool for identifying new SFKs inhibitors. In this review we
report and analyze the main examples of computational approaches that allowed the identification of new SFKs ligands
and the optimization of either activity and pharmacokinetic profile of lead compounds.
Keywords: c-Src, Fyn, Hck, Lck, Lyn, Src family kinases, virtual screening, yes.
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