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Volume 12
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10.3390/ijms12129236
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Article

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

by
Mahreen Arooj
1,†,
Sundarapandian Thangapandian
1,†,
Shalini John
1,
Swan Hwang
1,
Jong Keun Park
2 and
Keun Woo Lee
1,*
1
Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center (SSAC), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Research Institute of Natural Science(RINS), Gyeongsang National University (GNU), 501 Jinju daero, Gazwa-dong, Jinju 660-701, Korea
2
Department of Chemistry Education, Research Institute of Natural Science (RINS), Educational Research Institute, Gyeongsang National University, Jinju 660-701, Korea
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Mol. Sci. 2011, 12(12), 9236-9264; https://doi.org/10.3390/ijms12129236
Received: 24 October 2011 / Revised: 18 November 2011 / Accepted: 23 November 2011 / Published: 12 December 2011
(This article belongs to the Section Biochemistry)
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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. View Full-Text
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
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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. https://doi.org/10.3390/ijms12129236

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. https://doi.org/10.3390/ijms12129236

Chicago/Turabian Style

Arooj, Mahreen, Sundarapandian Thangapandian, Shalini John, Swan Hwang, Jong Keun Park, and Keun Woo Lee. 2011. "3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors" International Journal of Molecular Sciences 12, no. 12: 9236-9264. https://doi.org/10.3390/ijms12129236

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