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QSAR Modeling of CCK2 Receptor Antagonists Utilizing Computed Structural Indices: A Case Study

QSAR Modeling of CCK2 Receptor Antagonists Utilizing Computed Structural Indices: A Case Study

Sisir Nandi, Mridula Saxena, Anil Kumar Saxena
Copyright: © 2019 |Volume: 4 |Issue: 3 |Pages: 14
ISSN: 2379-7487|EISSN: 2379-7479|EISBN13: 9781522570547|DOI: 10.4018/IJQSPR.2019070102
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MLA

Nandi, Sisir, et al. "QSAR Modeling of CCK2 Receptor Antagonists Utilizing Computed Structural Indices: A Case Study." IJQSPR vol.4, no.3 2019: pp.20-33. http://doi.org/10.4018/IJQSPR.2019070102

APA

Nandi, S., Saxena, M., & Saxena, A. K. (2019). QSAR Modeling of CCK2 Receptor Antagonists Utilizing Computed Structural Indices: A Case Study. International Journal of Quantitative Structure-Property Relationships (IJQSPR), 4(3), 20-33. http://doi.org/10.4018/IJQSPR.2019070102

Chicago

Nandi, Sisir, Mridula Saxena, and Anil Kumar Saxena. "QSAR Modeling of CCK2 Receptor Antagonists Utilizing Computed Structural Indices: A Case Study," International Journal of Quantitative Structure-Property Relationships (IJQSPR) 4, no.3: 20-33. http://doi.org/10.4018/IJQSPR.2019070102

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Abstract

In the present case study, a QSAR model has been developed to identify CCK2 receptor antagonists. The earlier reported 3D pharmacophore modeling of these molecules involved commercial software. Since the reduction in the cost involved in the drug discovery phase is very crucial, in the present study, QSAR models based on the structural indices including 1D, 2D and 3D indices computed from the structures of CCK2 receptor antagonists has been developed utilizing NanoBRIDGES software which is openly accessible (http://nanobridges.eu/software/). This QSAR model is not only comparable to the earlier reported model, but it also reasonably predicts the external set of nine compounds including the drug benzotript and the most active 6a described in earlier work on structure-based homology model CCK2 receptor antagonists as antiulcer agents and thus may be useful in virtual screening for the identification of new CCK2 receptor antagonists.

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