Title:Rational Drug Design for Identifying Novel Multi-target Inhibitors for Hepatocellular Carcinoma
Volume: 12
Issue: 9
Author(s): Ahmed Temirak, Mona Abdulla and Mahmoud Elhefnawi
Affiliation:
Keywords:
Rational multi-targeting drug design, Sorafenib, Hepatocellular carcinoma, Pharmacophore based virtual screening, in silico ADMET, Tyrosine Multi-kinase Inhibitors, Docking Algorithms, co-crystallized structure, meta-trifluoromethyl-para-chlorophenyl ring
Abstract: 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 [1]. Sorafenib is a
multikinase inhibitor targeting the Raf serine/ threonine kinases and the VEGFR1-3, PDGFR-b, c-Kit, Flt3 and p38 tyrosine kinases [1].
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 [2], Zinc [3], Maybridge [4]
and drug bank [5] 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 [6].
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.
