The first book in the newly created book series,
Computer-Aided Drug Discovery and Design, focuses on the computational aspects of early drug discovery, drug target identification, and validation. It revises current classical paradigms in target and phenotypic-based drug design with still ingrained approximations and concepts and discusses the research in the new network approach concept that include kinetic selectivity and metabolic analysis.
Many often-overlooked approximations and concepts in drug discovery are fully covered. Drug Target Selection and Validation includes both introductory sections and research-based sections to be of use to both students and research scientists in drug discovery, design, kinetics and metabolic analysis. Pharmaceutical scientists, pharmaceutics, drug developers, pharmacologists, biomedical researchers in computer science, medicinal chemists, and precision medicine developers benefit from the information provided. The book concludes with a chapter on chemical and structural databases.
Prof. Marcus Tullius Scotti studied chemical engineering at Universidade de São Paulo (USP - São Paulo University) and finished his degree in 1999. After, he worked for four years in a Brazilian electronics and telecommunications services company called Gradiente. At the same time, he started to study specialization on Industrial Administration at the University of São Paulo. After that, he started post-graduation in organic chemistry at the University of São Paulo in 2003 and finished his Master in 2005 and Ph.D. in 2008. In January of 2009, he moved to João Pessoa and started to work as Professor of Organic Chemistry at Universidade Federal da Paraíba (Federal University of Paraíba), Brazil. At beginning of 2014 finished Post-doc in cheminformatics at Universidade Nova de Lisboa, Portugal,
Prof. Marcus research interests are in the area of chemistry of the natural products, acting on the following subjects: QSAR, Virtual Screening, molecular descriptors, and chemotaxonomy using cheminformatics methods using several statistical tools and machine learning algorithms. He has published over 230 papers.
Prof. Carolina Bellera obtained her Pharmacy degree in 2007 and completed her PhD studies in 2014, both at the National University of La Plata (Argentina). She obtained the award for the best PhD thesis on Bioorganic Chemistry from the Argentinean Chemical Society (2015) and the Award to Innovation from the National University of La Plata (2015). In 2019 she obtained a Tony B Award recognition for outstanding achievement in life sciences and technology in Spain.
She holds a permanent position at the Argentinean National Council of Scientific and Technical Research since 2016 (currently as Associate Researcher) and she is the professor in charge of the Medicinal Chemistry course at the Faculty of Exact Sciences, National University of La Plata, since 2018. She has published over 25 papers and 16 book chapters, mostly in the fields of rational drug discovery, in silico drug design, QSAR, virtual screening, tropical neglected diseases and biopharmacy. Recipient of several travel grants.
Prof. Bellera research interests are in the area of tropical neglected diseases, acting on the following subjects: Virtual Screening, cheminformatics, machine learning algorithms, QSAR and molecular descriptors.
