Affiliation: Biomedical Informatics and Chemoinformatics Group, Centre of Excellence for Advanced Sciences, National Research Centre, and Cairo, Egypt.
Hepatocellular carcinoma (HCC) is one of the hard-treating and high mortality cancers for which novel therapies are very much in need. Sorafenib is the first medication that is now approved for the treatment of patients with advanced HCC . Sorafenib is a multikinase inhibitor targeting the Raf serine/ threonine kinases and the VEGFR1-3, PDGFR-b, c-Kit, Flt3 and p38 tyrosine kinases .
Here, an in silico approach was directed to identify novel multi-kinase inhibitors as potential candidate therapies for HCC. The Molecular Operating Environment (MOE) was used for docking studies, pharmacophore building and virtual screening of chemical molecules databases. The docking/scoring methods of MOE were validated by reproducing the docking interactions and poses of Sorafenib with smallest root mean square deviations. The three receptors for which multi-targeting compounds were screened for were: B-Raf, p38 and VEGFR-2 tyrosine kinases. After identifying the main binding sites of the target receptors, we started our studies by the docking of Sorafenib in comparison to tyrosine kinase inhibitors collected from the literature. A pharmacophore based on the SAR of Sorafenib was built using flexible alignment methods.
Next, pharmacophore based virtual screening on four chemical molecules databases; Open NCI Database , Zinc , Maybridge  and drug bank  was done resulting in 2928 hit compounds that were subsequently subjected to filtration according to their binding free energies, interactions exhibited with the receptors, in silico ADMET properties and Lipinski’s rule of five for molecule drugability . Finally 7 compounds were selected as they exhibited excellent binding interactions with the receptors in addition to their high safety profile that are recommended for further development.