Abstract
Structure-activity relationships study was performed for a few series of cyclooxygenase-2 (COX-2) inhibitors by using the Electronic-Topological Method combined with Neural Networks (ETM-NN). Specific molecular fragments were found for active compounds (activity features) from both series by the ETM application. After this, a system of prognosis was developed as the result of training Kohonens selforganizing maps (SOM) by the fragments. From the detailed analysis of all compounds under study, requirements necessary for a compound to be COX-2 inhibitor were formulated. The analysis showed that any requirements violation for a molecule resulted in a considerable decrease or even complete loss of its activity. The found activity features identified correctly different marketed drugs and new compounds that had passed pre-clinical and clinical trials; this fact confirms the workability of the system developed for the COX-2 inhibitory activity prediction.
Keywords: cox inhibitors, structure-activity relationships, electronic-topological method, neural networks
Mini-Reviews in Medicinal Chemistry
Title: The Structure - Inhibitory Activity Relationships Study in a Series of Cyclooxygenase-2 Inhibitors: A Combined Electronic-Topological and Neural Networks Approach
Volume: 5 Issue: 10
Author(s): A. Dimoglo, V. Kovalishyn, N. Shvets and V. Ahsen
Affiliation:
Keywords: cox inhibitors, structure-activity relationships, electronic-topological method, neural networks
Abstract: Structure-activity relationships study was performed for a few series of cyclooxygenase-2 (COX-2) inhibitors by using the Electronic-Topological Method combined with Neural Networks (ETM-NN). Specific molecular fragments were found for active compounds (activity features) from both series by the ETM application. After this, a system of prognosis was developed as the result of training Kohonens selforganizing maps (SOM) by the fragments. From the detailed analysis of all compounds under study, requirements necessary for a compound to be COX-2 inhibitor were formulated. The analysis showed that any requirements violation for a molecule resulted in a considerable decrease or even complete loss of its activity. The found activity features identified correctly different marketed drugs and new compounds that had passed pre-clinical and clinical trials; this fact confirms the workability of the system developed for the COX-2 inhibitory activity prediction.
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Cite this article as:
Dimoglo A., Kovalishyn V., Shvets N. and Ahsen V., The Structure - Inhibitory Activity Relationships Study in a Series of Cyclooxygenase-2 Inhibitors: A Combined Electronic-Topological and Neural Networks Approach, Mini-Reviews in Medicinal Chemistry 2005; 5 (10) . https://dx.doi.org/10.2174/138955705774329537
DOI https://dx.doi.org/10.2174/138955705774329537 |
Print ISSN 1389-5575 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5607 |
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