In silico homology modelling and identification of Tousled-like kinase 1 inhibitors for glioblastoma therapy via high throughput virtual screening protein-ligand docking
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Abstract
Background: Glioblastoma multiforme (GBM) is a grade IV brain tumor that arises from star-shaped glial cells supporting neural cells called astrocytes. The survival of GBM patients remains poor despite many specific molecular targets that have been developed and used for therapy. 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 chromosomal aggregation, cell survival and proliferation. In vitro studies suggested that TLK1 is a potential target for some cancers; hence, the identification of suitable molecular inhibitors for TLK1 is warranted as a new therapeutic agents in GBM. To date, there is no structure available for TLK1. In this study, we aimed to create a homology model of TLK1 and to identify suitable molecular inhibitors or compounds that are likely to bind and inhibit TLK1 activity via in silico high-throughput virtual screening (HTVS) protein-ligand docking. Methods: 3D homology models of TLK1 were derived from various servers including HOmology ModellER, i-Tasser, Psipred and Swiss Model. All models were evaluated using Swiss Model Q-Mean server. Only one model was selected for further analysis. Further validation was performed using PDBsum, 3d2go, ProSA, Procheck analysis and ERRAT. Energy minimization was performed using YASARA energy minimization server. Subsequently, HTVS was performed using Molegro Virtual Docker 6.0 and candidate ligands from ligand.info database. Ligand-docking procedures were analyzed at the putative catalytic site of TLK1. Drug-like molecules were filtered using FAF-Drugs3, which is an ADME-Tox filtering program. Results and conclusion: High quality homology models were obtained from the Aurora B kinase (PDB ID:4B8M) derived from Xenopus levias structure that share 33% sequence identity to TLK1. From the HTVS ligand-docking, two compounds were identified 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.
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2016. In silico homology modelling and identification of Tousled-like kinase 1 inhibitors for glioblastoma therapy via high throughput virtual screening protein-ligand docking. PeerJ Preprints 4:e1582v3 https://doi.org/10.7287/peerj.preprints.1582v3Author comment
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Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Kamariah Ibrahim conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables.
Abubakar Danjuma performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables.
Chyan Leong Ng reviewed drafts of the paper.
Nor Azian Abdul Murad reviewed drafts of the paper.
Roslan Harun conceived and designed the experiments, reviewed drafts of the paper.
Wan Zurinah Wan Ngah reviewed drafts of the paper.
Rahman Jamal reviewed drafts of the paper.
Data Deposition
The following information was supplied regarding data availability:
The research in this article did not generate any raw data.
Funding
This study was funded by the Higher Institution Centre of Excellence (HICOE) research grant (JJ-015-2011), Ministry of Education, Malaysia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
