Development and validation of a robust QSAR model for benzothiazole hydrazone derivatives as Bcl-XL inhibitors

dc.contributor.authorGupta P.
dc.contributor.authorGutcaits A.
dc.date.accessioned2019-03-22T09:22:48Z
dc.date.accessioned2024-08-13T11:13:29Z
dc.date.available2019-03-22T09:22:48Z
dc.date.available2024-08-13T11:13:29Z
dc.date.issued2018
dc.description.abstractBackground: B-cell Lymphoma Extra Large (Bcl-XL) belongs to B-cell Lymphoma two (Bcl-2) family. Due to its over-expression and anti-apoptotic role in many cancers, it has been proven to be a more biologically relevant therapeutic target in anti-cancer therapy. In this study, a Quantitative Structure Activity Relationship (QSAR) modeling was performed to establish the link between structural properties and inhibitory potency of benzothiazole hydrazone derivatives against Bcl-XL. Methods: The 53 benzothiazole hydrazone derivatives have been used for model development using genetic algorithm and multiple linear regression methods. The data set is divided into training and test set using Kennard-Stone based algorithm. The best QSAR model has been selected with statistically significant r2 = 0.931, F-test =55.488 RMSE = 0.441 and Q2 0.900. Results: The model has been tested successfully for external validation (r2 pred = 0.752), as well as different criteria for acceptable model predictability. Furthermore, analysis of the applicability domain has been carried out to evaluate the prediction reliability of external set molecules. The developed QSAR model has revealed that nThiazoles, nROH, EEig13d, WA, BEHv6, HATS6m, RDF035u and IC4 descriptors are important physico-chemical properties for determining the inhibitory activity of these molecules. Conclusion: The developed QSAR model is stable for this chemical series, indicating that test set molecules represent the training dataset. The model is statistically reliable with good predictability. The obtained descriptors reflect important structural features required for activity against Bcl-XL. These properties are designated by topology, shape, size, geometry, substitution information of the molecules (nThiazoles and nROH) and electronic properties. In a nutshell, these characteristics can be successfully utilized for designing and screening of novel inhibitors.en_US
dc.identifier.citationGupta P., Gutcaits A.(2018) Development and validation of a robust QSAR model for benzothiazole hydrazone derivatives as Bcl-XL inhibitorsen_US
dc.identifier.doi10.2174/1570180815666180502093039
dc.identifier.issn15701808
dc.identifier.urihttps://kr.cup.edu.in/handle/32116/2117
dc.language.isoenen_US
dc.publisherBentham Science Publishers B.V.en_US
dc.subjectBcl-XLen_US
dc.subjectDescriptorsen_US
dc.subjectDomain of applicability analysisen_US
dc.subjectGenetic algorithmen_US
dc.subjectMLRen_US
dc.subjectQSAR modelen_US
dc.subjectValidationen_US
dc.titleDevelopment and validation of a robust QSAR model for benzothiazole hydrazone derivatives as Bcl-XL inhibitorsen_US
dc.title.journalLetters in Drug Design and Discovery
dc.typeArticleen_US

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