In silico homology modelling and identification of Tousled-like kinase 1 inhibitors for glioblastoma therapy via high throughput virtual screening protein-ligand docking

• Main Authors: Kamariah Ibrahim,, Abubakar Danjuma Abdullahi,, Nor Azian Abdul Murad,, Roslan Harun,, Rahman Jamal,
• Format: Article
• Language: English
• Published: Pusat Perubatan Universiti Kebangsaan Malaysia 2018
• Online Access: http://journalarticle.ukm.my/13245/1/38-134-1-PB.pdf; http://journalarticle.ukm.my/13245/; http://spaj.ukm.my/apjmm/index.php/apjmm/issue/view/18

Glioblastoma multiforme (GBM) is a high-grade brain tumor of which the survival patients remain poor. Tousled-like kinase 1 (TLK1), a serine-threonine kinase, was identified to be overexpressed in cancers such as GBM. TLK1 plays an important role in controlling survival pathways. To date, there is no structure available for TLK1 as well as its inhibitors. We aimed to create a homology model of TLK1 and to identify suitable molecular inhibitors that are likely to bind and inhibit TLK1 activity via in silico high-throughput virtual screening (HTVS) protein-ligand docking. The 3D homology models of TLK1 were derived from various servers. All models were evaluated using Swiss Model QMEAN server. Validation was performed using multiple tools. Energy minimization was performed using YASARA. Subsequently, HTVS was performed using Molegro Virtual Docker 6.0 and ligands derived from ligand.info database. Drug-like molecules were filtered using ADME-Tox filtering program. Best homology model was obtained from the Aurora B kinase (PDB ID:4B8M) derived from Xenopus levias structure that share sequence similarity with human TLK1. Two compounds were identified from HTVS to be the potential inhibitors as it did not violate the Lipinski rule of five and the CNS-based filter as a potential drug-like molecule for GBM.