A molecular modeling study of combretastatin-like chalcones as anticancer agents using PLS, ANN and consensus models
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Combretastatin-like chalcones are promising anticancer compounds that inhibit the mitotic process through interactions with β-tubulin. A detailed study of these compounds can contribute for the rational drug design of new structures aiming at compounds with high biological activity. For this purpose, we have studied 87 combretastatin-like chalcones and proposed multivariate models based on partial least squares (PLS), artificial neural network consensus model (ANN-CM), and general consensus model (GCM). The proposed models have showed good predictive ability with r2test = 0.812 and MSE (test set) = 0.327 for the PLS model, r2test = 0.829 and MSE (test set) = 0.286 for the ANN-CM, and r2test = 0.822 and and MSE (test set) = 0.302 for the GCM. The selected molecular and electronic descriptors (RDF045e, RTv, RDF155u, RDF035m, SP02, PI, UNIP and EHOMO-3) represent molecular features of the compounds that can be associated to the biological activity and can be employed to help the design of new bioactive ligands with improved biological activity.
KeywordsCancer Microtubules Chalcones QSAR ANN Consensus modeling
The authors would like to thank CNPq, CAPES and FAPESP (Brazilian agencies) for the financial support.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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