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Int. J. Mol. Sci. 2011, 12(12), 9236-9264; doi:10.3390/ijms12129236
Article

3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors

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Received: 24 October 2011; in revised form: 18 November 2011 / Accepted: 23 November 2011 / Published: 12 December 2011
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Abstract: Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (r = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating “Hypo1”, it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high GOLD fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC50) data thus successfully validating “Hypo1” by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors.
Keywords: chymase; pharmacophore; molecular docking; in silico screening; density functional theory; molecular electrostatic potential chymase; pharmacophore; molecular docking; in silico screening; density functional theory; molecular electrostatic potential
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Arooj, M.; Thangapandian, S.; John, S.; Hwang, S.; Park, J.K.; Lee, K.W. 3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors. Int. J. Mol. Sci. 2011, 12, 9236-9264.

AMA Style

Arooj M, Thangapandian S, John S, Hwang S, Park JK, Lee KW. 3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors. International Journal of Molecular Sciences. 2011; 12(12):9236-9264.

Chicago/Turabian Style

Arooj, Mahreen; Thangapandian, Sundarapandian; John, Shalini; Hwang, Swan; Park, Jong Keun; Lee, Keun Woo. 2011. "3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors." Int. J. Mol. Sci. 12, no. 12: 9236-9264.



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