Computer-Aided and Machine Learning-Driven Drug Design

Vinícius Gonçalves Maltarollo is a Professor of Medicinal Chemistry at the Faculty of Pharmacy, Federal University of Minas Gerais in Brazil since 2016. Before that, he taught several other disciplines related to biology/pharmacy for more than 10 years to high school and undergraduate students. In terms of education, he is a Pharmacist (University of ABC, Brazil, 2006). He earned a Master of Science degree (2009) and a PhD (2013) in Chemistry, both from the Federal University of ABC in Brazil. Furthermore, he completed his postdoctoral research at the University of São Paulo (2013-2015), and was a visiting researcher at the Eberhard-Karls Universität Tübingen in Germany (2022). To date, he has published more than 70 research and review articles in peer-reviewed scientific journals with a focus on Computer-Aided Drug Design (CADD) and 3 book chapters. Finally, he is a reviewer for more than 30 scientific periodicals  withmore than 120 revisions completed.

Echoes from the past, visions from the future: a journey into the Medicinal Chemistry and the Computational Drug Discovery.- Molecular Databases.- A Brief Introduction to Pharmacogenomics and Personalized Medicine in the Drug Design Context.- Machine Learning and Neural Networks Methods Applied to Drug Discovery.- Clustering of Small Molecules.- QSAR and Machine learning predictors.- Molecular docking: state-of-art scoring functions and search algorithms.- Drug Design in Motion: concepts and applications of classical Molecular Dynamics simulations.- Conformational sampling of proteins: methods for simulate protein plasticity and ensemble docking.- Free energy perturbation and free energy calculations ap-plied to drug design.- Ultra-large-scale Virtual Screening.- Experimental assays: chemical properties, biochemical and cellular assays, and in vivo evaluations.- Challenges faced in the development of computational methods for predicting pharmacokinetics behavior.- Exploring the Significance of Experimental and Computational Methods in Protein Structure Determination.- Molecular modeling strategies in drug design, development, and discovery targeting proteases.- Computational study of conformational changes in nuclear receptors upon ligand binding.- An Overview on Computational Methods Targeting the Endocannabinoid System.- Kinase Inhibitors and Computer-aided Drug Design Methods.- Prediction of Drug Metabolism with In Silico Models: A Case Study of Doping Detection.