QSARINS‐chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS

Abstract

A database of environmentally hazardous chemicals, collected and modeled by QSAR by the Insubria group, is included in the updated version of QSARINS, software recently proposed for the development and validation of QSAR models by the genetic algorithm-ordinary least squares method. In this version, a module, named QSARINS-Chem, includes several datasets of chemical structures and their corresponding endpoints (physicochemical properties and biological activities). The chemicals are accessible in different ways (CAS, SMILES, names and so forth) and their three-dimensional structure can be visualized. Some of the QSAR models, previously published by our group, have been redeveloped using the free online software for molecular descriptor calculation, PaDEL-Descriptor. The new models can be easily applied for future predictions on chemicals without experimental data, also verifying the applicability domain to new chemicals. The QSAR model reporting format (QMRF) of these models is also here downloadable. Additional chemometric analyses can be done by principal component analysis and multicriteria decision making for screening and ranking chemicals to prioritize the most dangerous.

Prediction of photolysis half-lives of dihydroindolizines by genetic algorithm-multiple linear regression (GA-MLR)

“…GA setup was set on 10, 2000, and 20 for population size, number of GA iterations, and mutation rate, respectively. [29,30] 4 Removed from the study as outlier (Fig. S1).…”

“…[29,30] For GA-MLR analysis, default values of the software were used unless otherwise specified. Fitness function was set on leave-one-out cross-validation coefficient value (Q 2 loo ).…”

Reliable method for safety assessment of melting points of energetic compounds

“…For additional external validation coefficients and two parameters of Roy et al (Chirico and Gramatica, 2011;Roy et al, 2013;Roy and Mitra, 2011), threshold values are more than 0.5 (> 0.5) (Roy and Mitra, 2011) except ΔR 2 m and CCC, which are less than 0.2 (< 0.2) (Roy and Mitra, M a n u s c r i p t 18 2011) and more than 0.8 (> 0.8) (Gramatica et al, 2012), respectively. For additional internal and external validation with using QSARINS software (Gramatica et al, 2014;Gramatica et al, 2013 ), 230 and 58 energetic compounds with different chemical structures were randomly selected as training set (80%) and test (validation) set (20%), respectively.…”

Consistency of QSAR models: Correct split of training and test sets, ranking of models and performance parameters

“…For QSAR model building, Gramatica and coworkers' QSARINS 2.2 software was used [8,19]. QSARINS implements a rich toolbox of statistical methods for the generation, validation and ranking of QSAR models.…”