ArticleCurrent topics in medicinal chemistry2026
Discovery of Diphenylsilane Compounds as Potential Inhibitors of Zn-Metalloproteinase Thermolysin Using Artificial Neural Networks.
Article in Current topics in medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionArtificial neural networks are very powerful machine learning and artificial intelligence tools for computer-aided drug discovery. This method offers advantages over traditional approaches related to saving time and money. The aim of this work is to develop machine- learning artificial neural networks for computer-aided discovery of potential thermolysin metalloprotease inhibitor drug candidates.
methodsIn this work, MLP (Multilayer Perceptron) and RBF (Radial Basis Function) neural networks with a general 5:n:1 architecture are developed to find a non-linear correlation between five molecular descriptors obtained by genetic algorithm, and the inhibition of the enzyme thermolysin, expressed as pK
resultsThe proposed models show a better fit than the linear model in both series (R
conclusionThis methodology offers advantages over traditional methods related to saving time and money. Furthermore, the results obtained suggest that the three identified compounds could be used for the treatment of cardiovascular pathologies because of their homology with human vasopeptidases.
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