Tropical Journal of Pharmaceutical Research

Original Research Article | OPEN ACCESS

Application of group-based QSAR and molecular docking in the design of insulin-like growth factor antagonists

Abubakar Danjuma Abdullahi¹ , Abubakar Danjuma Abdullahi¹ , Abdualrahman Mohammed Abdualkader^2,4, Nadiahanis binti Abdulsamat³, Kundan Ingale⁵

¹Department of Basic Medical Sciences; ²Department of Pharmaceutical Chemistry; ³Department of Pharmaceutical Technology, Faculty of Pharmacy, International Islamic University Malaysia, Jalan Istana, 25200, Kuantan, Pahang, Malaysia; ⁴Department of Pharmaceutical Chemistry and Quality Control, Aleppo University, Syria; ⁵VLife Sciences Technologies Pvt Ltd, Pune, India.

For correspondence:- Abubakar Abdullahi Email: bagaruwa@gmail.com Tel:+60199175042

Received: 16 May 2014 Accepted: 14 April 2015 Published: 29 June 2015

Citation: Abdullahi AD, Abdullahi AD, Abdualkader AM, Abdulsamat Nb, Ingale K. Application of group-based QSAR and molecular docking in the design of insulin-like growth factor antagonists. Trop J Pharm Res 2015; 14(6):941-951 doi: 10.4314/tjpr.v14i6.2

© 2015 The authors.
This is an Open Access article that uses a funding model which does not charge readers or their institutions for access and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) and the Budapest Open Access Initiative (http://www.budapestopenaccessinitiative.org/read), which permit unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited..

Abstract

Purpose: To identify the structural requirements for designing a lead key for insulin-like growth factor (IGF-1R) inhibition using group-based quantitative structure activity relationship (GQSAR) and molecular docking.

Methods: GQSAR method requires fragmentation of molecules. The molecules in the current dataset were fragmented into three (R1, R2 and R3) by applying common fragmentation pattern, and fragment-based 2D descriptors were then calculated. GQSAR models were derived by applying various methods including multiple linear regressions and partial least square or k-nearest neighbour.

Results: Four generated GQSAR models were selected based on the statistical significance of the model. It was found that the presence of flexible and non-aromatic groups on fragment R1 was conducive for inhibition. Additionally, the existence of amino groups as hydrogen bond donors at fragments R2 and R3 was fruitful for inhibition. Docking studies revealed the binding orientation adopted by the active compounds at several amino acid residues, including Met 1126, Arg, 1128, Met 1052, GLU 1050, Met 1112, Leu 1051, Met 1049, Val 1033, and Val 983 at ATP binding sites of IGF-1R kinase domain.

Conclusion: The generated models provide a site-specific insight into the structural requirements for IGF-1R inhibition which can be used to design and develop potent inhibitors.

Keywords: Insulin-like growth factor 1 (IGF-1) receptor, Quantitative structure-activity relationship, Adenosine triphosphate, Competitive inhibitors, Electroto