A Confidence Estimation Approach for Applicability Domain Assessment of QSAR Classification Models

MARÍA JIMENA MARTÍNEZ; FIORELLA CRAVERO; SCHUSTIK, SANTIAGO; MONICA F. DIAZ; IGNACIO PONZONI

Posadas

Congreso; 8vo Congreso Argentino de Bioinformática y Biología Computacional; 2017

A2B2C

The applicability domain (AD) is a crucial step in the modeling QSAR/QSPR by which we can estimate the reliability of a model. Once the model has been trained, it should be possible to determine if, for a new compound, the prediction will be reliable or not. In other words, what we want to find is the AD of the QSAR/QSPR classification model. There are several techniques for its definition. A strategy for its definition is to propose a first instance in which the structural similarity between the new compound (NC) and the compounds of the training set is analyzed. Once this is done, in a second instance, the confidence estimation of the model is evaluated.