New Graph Similarity Measurements based on Isomorphic and Nonisomorphic Data Fusion and their Use in the Prediction of the Pharmacological Behavior of Drugs

Autor: Ruiz, Irene Luque, Cuadrado, Manuel Urbano, Gómez-Nieto, Miguel Ángel
Jazyk: angličtina
Rok vydání: 2007
Předmět:
DOI: 10.5281/zenodo.1076224
Popis: New graph similarity methods have been proposed in this work with the aim to refining the chemical information extracted from molecules matching. For this purpose, data fusion of the isomorphic and nonisomorphic subgraphs into a new similarity measure, the Approximate Similarity, was carried out by several approaches. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting several pharmacological parameters: binding of steroids to the globulin-corticosteroid receptor, the activity of benzodiazepine receptor compounds, and the blood brain barrier permeability. Acceptable results were obtained for the models presented here.
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