Model studies

This tutorial describes how to build a QSPR model using Alvascience tools. The selected endpoint is the aqueous solubility (LogS). The scope of this tutorial is to describe, step-by-step, the development of QSAR/QSPR regression models, from data curation to the use of models with a new set of molecules.

This project includes the models presented in the paper “F. Grisoni, V.Consonni, M.Vighi (2018). Acceptable-by-design QSARs to predict the dietary biomagnification of organic chemicals in fish, Integrated Environmental Assessment and Management“. The authors presented QSAR regression models to predict the laboratory-based fish Biomagnification Factor (BMF) of chemicals.

This project includes the models presented in the paper “M. Cassotti, D. Ballabio, R. Todeschini, V. Consonni (2015). A similarity-based QSAR model for predicting acute toxicity towards the fathead minnow (Pimephales promelas)“. The authors presented a study on the prediction of the acute toxicity of chemicals to fish. In particular, they presented QSAR models to predict the LC₅₀ 96 hours for the fathead minnow (Pimephales promelas).

This project includes the models presented in the papers “M. Cassotti, D. Ballabio, V. Consonni, A. Mauri, I.V. Tetko, R. Todeschini (2014). Prediction of Acute Aquatic Toxicity Toward Daphnia magna by using the GA-kNN Method” and “M. Cassotti, V. Consonni, A. Mauri, D. Ballabio (2014). Validation and extension of a similarity-based approach for prediction of acute aquatic toxicity towards Daphnia magna“. The authors presented QSAR models to predict acute aquatic toxicity (LC₅₀ 48 hours) towards Daphnia magna.

This project includes the models presented in the paper “G.K. Jillella, K. Khan, K. Roy (2020). Application of QSARs in identification of mutagenicity mechanisms of nitro and amino aromatic compounds against Salmonella typhimurium species“. The authors presented QSAR models to predict mutagenicity mechanisms of nitro and amino aromatic compounds against Salmonella typhimurium species.