3D-QSAR and molecular docking studies of amino-pyrimidine derivatives as PknB inhibitors

作者：Damre Mangesh V; Gangwal Rahul P; Dhoke Gaurao V; Lalit Manisha; Sharma Dipna; Khandelwal Kanchan; Sangamwar Abhay T^*

来源：Journal of the Taiwan Institute of Chemical Engineers, 2014, 45(2): 354-364.

DOI：10.1016/j.jtice.2013.05.016

• PknB inhibitors
• QSAR
• CoMFA
• CoMSIA
• Molecular docking
• LeapFrog

PknB is an essential serine/threonine kinase of Mycobacterium tuberculosis, which plays an important role in a number of signalling pathways involved in cell division and metabolism. This finding supports the development of protein kinase inhibitors as new potential anti-tubercular agents. The reported PknB inhibitors were found to be less potent against whole cells as compared to the purified protein. This difference in potency might be due to the cell wall permeability factor in the whole cells. On analyzing various molecular properties of known PknB inhibitors, it was found that the inhibitors with PSA less than 60 angstrom(2) were showing better inhibitory activity in both whole cell and purified protein. In the present study, we have employed 3D-QSAR and molecular docking approach on the novel series of aminopyrimidine to design potent PknB inhibitors with improved permeability. This study correlates the PknB inhibitory activities of 36 amino-pyrimidine derivatives to several stereo-chemical parameters representing steric, electrostatic, hydrophobic, hydrogen bond donor and acceptor fields. The resulting model from CoMFA and CoMSIA exhibited excellent r(ncv)(2) values of 0.999 and 0.998, and r(cv)(2) values of 0.781 and 0.641, respectively. CoMFA predicted r(pred)(2) of 0.94 and CoMSIA predicted r(pred)(2) of 0.85 showed that the predicted values were in good agreement with the experimental values. Molecular docking studies of all inhibitors showed hydrogen bond interactions with important amino acids (Glu93 and Val95) and these interactions were compared with the contour maps, which shows that the developed models have a good predictive ability. We have accordingly designed novel PknB kinase inhibitors by utilizing the LeapFrog and predicted excellent activity in the developed models. It is anticipated that the findings reported here may provide useful information for designing effective PknB inhibitors as anti-tubercular agents.

• 出版日期2014-3