Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0. - Giulio Vistoli; Alessandro Pedretti; Angelica Mazzolari; Bernard Testa (J. Comput. Aided Mol. Des., 2010)

Binding Space Concept: A New Approach To Enhance the Reliability of Docking Scores and Its Application to Predicting Butyrylcholinesterase Hydrolytic Activity. - Giulio Vistoli; Angelica Mazzolari; Bernard Testa; Alessandro Pedretti (J. Chem. Inf. Model., 2017)

WarpEngine, a Flexible Platform for Distributed Computing Implemented in the VEGA Program and Specially Targeted for Virtual Screening Studies. - Alessandro Pedretti; Angelica Mazzolari; Giulio Vistoli (J. Chem. Inf. Model., 2018)

FAME 3: Predicting the Sites of Metabolism in Synthetic Compounds and Natural Products for Phase 1 and Phase 2 Metabolic Enzymes. - Martin Sícho; Conrad Stork; Angelica Mazzolari; Christina de Bruyn Kops; Alessandro Pedretti; Bernard Testa; Giulio Vistoli; Daniel Svozil; Johannes Kirchmair (J. Chem. Inf. Model., 2019)

Impact of the Journal of Chemical Information and Modeling Special Issue on Women in Computational Chemistry. - Angelica Mazzolari; Ariane Nunes-Alves; Habibah A. Wahab; Rommie E. Amaro; Zoe Cournia; Kenneth M. Merz Jr. (J. Chem. Inf. Model., 2020)

What Makes a Paper Be Highly Cited? 60 Years of the Journal of Chemical Information and Modeling. - Ariane Nunes-Alves; Angelica Mazzolari; Kenneth M. Merz Jr. (J. Chem. Inf. Model., 2020)

The VEGA suite of programs: an versatile platform for cheminformatics and drug design projects. - Alessandro Pedretti; Angelica Mazzolari; Silvia Gervasoni; Laura Fumagalli; Giulio Vistoli (Bioinform., 2021)

The (Re)-Evolution of Quantitative Structure-Activity Relationship (QSAR) Studies Propelled by the Surge of Machine Learning Methods. - Thereza A. Soares; Ariane Nunes-Alves; Angelica Mazzolari; Fiorella Ruggiu; Guo-Wei Wei 001; Kenneth M. Merz Jr. (J. Chem. Inf. Model., 2022)

Predicting Metabolic Reactions with a Molecular Transformer for Drug Design Optimization. - Silvia Multari; Riza Özçelik; Angelica Mazzolari; Marco Salvatore Nobile; Francesca Grisoni (CIBCB, 2024)

Active Learning Approach for Guiding Site-of-Metabolism Measurement and Annotation. - Ya Chen 002; Thomas Seidel; Roxane Axel Jacob; Steffen Hirte; Angelica Mazzolari; Alessandro Pedretti; Giulio Vistoli; Thierry Langer; Filip Miljkovic; Johannes Kirchmair (J. Chem. Inf. Model., 2024)

Improving the Efficiency and the Validity of Molecular Transformers. - Leone Bacciu; Matteo Grazioso; Silvia Multari; Francesca Grisoni; Angelica Mazzolari; Marco S. Nobile (CIBCB, 2025)

Automated Annotation of Sites of Metabolism from Biotransformation Data. - Roxane Axel Jacob; Angelica Mazzolari; Johannes Kirchmair (J. Chem. Inf. Model., 2025)

Site-of-Metabolism Prediction with Aleatoric and Epistemic Uncertainty Quantification. - Roxane Axel Jacob; Oliver Wieder; Ya Chen 002; Angelica Mazzolari; Andreas Bergner; Klaus-Jürgen Schleifer; Johannes Kirchmair (J. Chem. Inf. Model., 2025)

Prediction of UGT-mediated phase II metabolism via ligand- and structure-based predictive models. - Ludovica Bono; Filippo Lunghini; Emanuela Sabato; Akash Deep Biswas; Angelica Mazzolari; Alessandro Pedretti; Andrea Rosario Beccari; Giulio Vistoli; Serena Vittorio (J. Cheminformatics, 2025)