Many cellular communications and cellular activities are regulated by a class
of enzyme tyrosine kinases. Mutations or increased expression of these enzymes lead to
many proliferative cancers as well as other non-proliferative diseases such as psoriasis,
atherosclerosis and some inflammatory diseases. Hence, they are considered vital and
prospective therapeutic targets. Over the past decade, considerable research work has
been carried out to develop potential inhibitors against these tyrosine kinases. So far, a
number of compounds have been identified successfully as tyrosine kinase inhibitors
and many compounds were developed as drugs to treat tyrosine kinase-induced
diseases. Behind the successful development of these inhibitors, many Computer Aided
Drug Design (CADD) (in silico) approaches include molecular modelling, high
throughput virtual screening against various chemical databases, and docking (both
rigid and flexible method of docking). Further many studies identified the possible
features which are responsible for tyrosine kinase inhibition activities for a number of
series of compounds through the quantitative structure-activity/property relationship
(QSAR/QSPR) process. In this review article, the structural characteristics, mechanism
of action, and mode of inhibition of tyrosine kinases are discussed followed by the
successful applications of a variety of in silico approaches in tyrosine kinase inhibitors
development.
Keywords: Artificial intelligence, Computer-aided drug design, Computational intelligence, Docking, EGFR, In silico approaches, Ligand based drug design, Machine learning, Pharmacophore, Protein tyrosine kinases, QSAR, Structure based drug design, Tyrsoine kinase inhibitors (TKI), Virtual screening, VEGFR.
