Improving the Development of QSAR Prediction Models with the use of Approximate Similarity Approach

The improvement on the QSAR prediction of the trans-stilbenes affinity for the -amyloid peptide (employed for detecting the Alzheimer disease) achieved by means of using approximate similarity measurement is presented in this work. A wide spectrum of similarity methods is described, and results obtained by approximate similarity are compared with those obtained by constitutional, fingerprint and descriptor-based similarity. The fact of using similarity corrections by considering distances between the non-isomorphic fragments (the approximate similarity concept) led to accurate QSAR models (Q2 > 0.80). The high predictive ability achieved by simple methods is remarked.

• Type: Journal
• Year: 2008
• Where: ENGL
• Authors: Irene Luque Ruiz, Manuel Urbano-Cuadrado, Miguel Ángel Gómez-Nieto
• Keywords: Approximate Similarity, Approximate Similarity Concept, Approximate Similarity Measurement, ENGL 2008