First Report on the Validated Classification-Based Chemometric Modeling of Human Rhinovirus 3C Protease (HRV 3Cpro) Inhibitors
Human rhinoviruses (HRVs), a major cause of common cold and upper respiratory infections, may trigger severe respiratory complications like asthma and COPD. To date, no drugs are available in the market which are designed as novel HRV inhibitors despite the involvement of some pharmaceutical companies' due to economical and clinical constraints. HRV 3C protease may be a potential target for drug design as it plays crucial role in viral RNA replication and virion assembly process. Therefore, designing novel HRV 3Cpro inhibitors is necessary and demanding in the field of antiviral drug design. In this article, statistically significant and validated classification-based QSARs of a series of HRV 3Cpro inhibitors were performed for the first time as per the authors' knowledge. Results suggest that oxopyrrolidine and piperidinone rings are favored whereas carboxybenzyl and unsubstituted benzyl functions may be unfavorable. Moreover, this group, along with cyclic alkyl or aryl ring structures may favor HRV 3Cpro inhibition. These observations may be utilized for the design of a higher active anti-HRV agent in future.
Year of publication: |
2018
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Authors: | Jha, Tarun ; Amin, Sk. Abdul ; Adhikari, Nilanjan ; Gayen, Shovanlal |
Published in: |
International Journal of Quantitative Structure-Property Relationships (IJQSPR). - IGI Global, ISSN 2379-7479, ZDB-ID 2845245-8. - Vol. 3.2018, 2 (01.07.), p. 1-20
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Publisher: |
IGI Global |
Subject: | Bayesian Classification Model | Bayesian Fingerprint | Classification-Based QSAR | Human Rhinovirus 3C Protease Inhibitors | Linear Discriminant Analysis |
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