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Original Research Article


Molecular Dynamics and Bioactivity of a Novel Mutated Human Parathyroid Hormone

 

Yueshui Jiang1, Jiande Gu2, Jianyong Lei1, Yun Chen1 and Jian Jin1,3*

1School of Pharmaceutical Sciences, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, 2Drug Design & Discovery Center, Shanghai Institute of Materia Medica, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 201203, 3Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences & Shanghai Jiao-Tong University School of Medicine, 320 Yue-Yang Road, Shanghai 200031, PR China

 

*For correspondence: Email: jinjian31@126.com; Tel/Fax: +86 510 8591 8219

 

Received: 3 May 2013                                                                            Revised accepted: 28 February 2014

 

Tropical Journal of Pharmaceutical Research, April 2014; 13(4): 511-518

http://dx.doi.org/10.4314/tjpr.v13i4.4   

Abstract

 

Purpose: To design and evaluate a novel human parathyroid hormone (hPTH) analog.

Methods: Mutation stability prediction was processed on hPTH, docked the mutant hPTH with its receptor, and then proceeded with molecular dynamics using Discovery Studio 3.5 software package for the complex. The bioactivity of the hPTH on the expression levels of the Rps27, RANKL and OPG genes were assessed in UAMS-32P cells.

Results:  A three-site mutant, hPTH (R25Q:K26E:K27L), was obtained and MD trajectory analysis showed a decrease in the root mean square deviation by 51.95%, in the radius of gyration by 3.57%, and in the interaction energy by 10%, compared with the wild-type hPTH. Bioactivity assessment demonstrated that this mutant stimulated the ratio of RANKL/OPG 30-fold higher than the wild-type.

Conclusion:  We successfully designed a new hPTH mutant with a stable conformation and high bioactivity, and this may be useful for elucidating ligand-receptor recognition mechanism and discovering novel hPTH analogs.

 

Keywords: Parathyroid hormone, Mutation prediction, Molecular dynamics, RANKL/OPG, UAMS-32P cell

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