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Title

Molecular modeling and docking of small molecule inhibitors against NEK2

Authors

Balaji Ramachandran*,$, Sabitha Kesavan$ & Thangarajan Rajkumar

Affiliation

Department of Molecular Oncology, Cancer Institute (W.I.A), No.38, Sardar Patel Road, Adyar, Chennai - 600 036

 

Email

Balaji Ramachandran Email: balajiphd@gmail.com; Phone: +914422209150; *Corresponding author; $Equal contribution

 

Article Type

Hypothesis

 

Date

Received February 25, 2016; Revised March 18, 2016; Accepted March 19, 2016; Published April 10, 2016

 

Abstract

Aberrant expression of NEK2 (NIMA-related kinase 2) is indicated in a wide variety of human cancers. NEK2 is highly correlated to multi drug resistance by activating drug efflux activity. Identification of new small molecule inhibitors targeted against NEK2 therefore, facilitates to increase drug sensitivity of cancer cells, by stabilizing drug influx and minimizes the dose of therapeutic drug. Our work investigates to screen for optimal small molecule inhibitors against NEK2. In this study, we used a computational approach by modeling NEK2 protein using I-TASSER (Iterative Threading ASSEmbly Refinement) software. The modeled structure was subjected to protein preparation wizard; to add hydrogens and to optimize the protonation states of His, Gln and Asn residues. Active site of the modeled protein was identified using SiteMap tool of Schrodinger package. We further carried out docking studies by means of Glide, with various ligands downloaded from EDULISS database. Based on glide score, potential ligands were screened and their interaction with NEK2 was identified. The best hits were further screened for Lipinskiís rule for drug-likeliness, bioactivity scoring and ADME properties. Thus, we report two (didemethylchlorpromazine and 2-[5-fluoro-1Hindol-3-yl] propan-1-amine) compounds that have successfully satisfied all in silico parameters, necessitating further in vitro and in vivo studies.

 

Keywords

Glide; NEK2; Multi-drug resistance; Docking; Molecular modelling

Citation

Ramachandran et al. Bioinformation 12(2): 62-68 (2016)
 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.