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Computer
ViníciusGonçalvesMaltarolloEditor
–
Aided Drug Discovery and Design 3
Computer-Aided
and Machine
Learning-Driven
Drug Design
From Theory toApplications
Computer-Aided Drug Discovery and Design
Volume 3
Series Editor
Alan Talevi, Facultad de Ciencias Exactas, Universidad Nacional de La Plata,
La Plata, Argentina
The series covers all the stages of drug discovery and development that use computational approximations, including bioinformatics, cheminformatics, structure-based
approximations, ligand-based approximations and network-approaches. Drug discovery and development stages include target identification and validation, hit
identification and hit-to-lead and lead optimization programs.
• The series covers the early drug disco very and development process in a
comprehensive manner.
• It explains both the historical background and underlying principles of each
methodology, as well as state-of-the-art innovations within each field. For
instance, when dealing with structure-based approximations, both classical
universal scoring functions and the novel trend in the field (tailored scoring
functions) will be considered.
• Accordingly, both experts and students taking their first steps in computer-
guided drug discovery will find the series of interest. Students can resort to the
series volumes to get familiarized with the basics of the methodologies, and
experts can turn to the series for trends in the field.
• No other series covers all the fields and approximations in a deep,updated and
comprehensive manner.
• For an integrative perspective, the potential readers might acquire all the books
that compose the series; on the contrary, people with a narrower, more specific
scope can resor t to a particular volume of choice
Vinícius Gonçalves Maltarollo
Editor
Computer-Aided
and Machine
Learning-Driven Drug
Design
From Theory to Applications
Editor
Vinícius Gonçalves Maltarollo
Departamento de Produtos Farmacêuticos,
Faculdade de Farmácia
Universidade Federal de Minas Gerais
Belo Horizonte, Minas Gerais, Brazil
ISSN 2730-5457 ISSN 2730-5465 (electronic)
Computer-Aided Drug Discovery and Design
ISBN 978-3-031-76717-3 ISBN 978-3-031-76718-0 (eBook)
https://doi.org/10.1007/978-3-031-76718-0
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland
AG 2024
This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether
the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of
illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and
transmission or information storage and retrieval, electronic adaptation, computer software, or by
similar or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this
book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or
the editors give a warranty, expressed or implied, with respect to the material contained herein or for any
errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional
claims in published maps and institutional affiliations.
This Springer imprint is published by the registered company Springer Nature Switzerland AG
The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
If disposing of this product, please recycle the paper.
This book is dedicated to the most impor tant
women in my life. To Tereza, my mother,
whose wisdom and nurturing spirit gave
me the foundation to question and grow.
To Renata, my wife and dearest companion,
whose love and support have helped me
become the best version of myself, guiding
me to places I never imagined I could reach.
And to Nina, my daughter, whose presence
fills me with the strength to face every
challenge with courage and resilience.
Foreword
For several decades, Computer-Aided Drug Design (CADD) and Machine Learning
have been applied in drug discovery projects, and now there are several drugs in the
market developed with the aid of such techniques. Computational techniques,
methods, and concepts such as quantitative structure-activity relationships
(QSAR), molecular docking, molecular dynamics, free-energy perturbation and
quantum mechanics, and virtual screening of compounds databases, among several
others, have been cornerstones in several drug discovery projects. These methods
have now been boosted by data-driven artificial intelligence (AI) methods. Although
it is anticipated that drugs cannot be designed and developed solely by computers,
novel computational approaches are emerging, and existing techniques continue to
evolve rapidly. Therefore, the scientific community must keep up to date with the
most recent developments and practical applications.
The CADD research field comprises several different knowledge areas, and often,
researchers are only familiar or experienced with a small fraction of them. Indeed,
pharmaceutical industries and large academic groups rely on a broad range of
professionals, including chemists, biologists, pharmacists, computer scientists, and
other related ones. In this sense, being an expert in every CADD approac h is
challenging. Furthermore, well-established methods are constantly revisited, and
novel approaches and modifications are introduced, such as machine-learningbased scoring functions for molecular docking.
The book “Computer-Aided and Machine Learning-Driven Drug Design” discusses theoretical and successful practical applications of computational techniques.
The book, written by authors from diverse countries and geographical regions, is
expected to serve the scientific community by providing an overview and solid
concepts related to chemoinformatic, bioinformatics, and molecular modeling in the
context of AI; key considerations at the interface between computational and the
required experimental validation; and practical and recent applications of such
technique to real-world drug discovery campaigns. The book can be used as a
vii
viii Foreword
textbook for courses that include or are focused on CADD and as reference material
for researchers and practitioners of current CADD and machine learning.
The editor and all contributor authors are very grateful to the Springer editorial
staff for their support in developing and publishing the book.
DIFACQUIM Research Group,
Department of Pharmacy, School of
Chemistry, National Autonomous
University of Mexico, Mexico City,
Mexico
José L. Medina-Franco
Acknowledgments
All the chapters were subject of a blind peer-reviewing process and were approved
for publication. Therefore, I would like to thank all the colleagues that put their hard
efforts to review the technical content of this book prior to publication. Your
contribution definitively enhanced the quality of the presented content and ensured
the state of the art of each subject. Thank you very much.
Aaron Sweeney (Centre for Structural Systems Biology, Germany)
Adolfo Henrique de Morae s (Federal University of Minas Gerais, Brazil)
Albérico Borges Ferreira da Silva (University of São Paulo, Brazil)
Alessandro Silva Nascimento (University of São Paulo, Brazil)
Antti Poso (University of East Finla nd, Finland)
Azam Rashidian (University of Tübingen, Germany)
Diego Magno Martins (Federal University of Minas Gerais, Brazil)
Emmanuela Ferreira de Lima (Federal Institute of Paraíba, Brazil)
Fernanda Rodrigues Soares (Federal University of Triângulo Mineiro, Brazil)
Frederico Gualberto Ferreira Coelho (Federal University of Minas Gerais, Brazil)
Gabriel Corrêa Veríssimo (Federal University of Minas Gerais, Brazil)
Hongtao Zhao (AstraZeneca, Sweden)
Jadson Castro Gertrudes (Federal University of Ouro Preto, Brazil)
José Teófilo Moreira Filho (National Institute of Environmental Health Sciences,
USA)
Karen Cacilda Weber (Federal University of Paraíba, Brazil)
Katarina Nikolic (University of Belgrade, Republic of Serbia)
Kathia Maria Honório (University of São Paulo, Brazil)
Lauren Hubert Jaeger (Federal University of Juiz de Fora, Brazil )
Lílian Sibelle Campos Bernardes (Federal University of Santa Catarina, Brazil)
Luan Carvalho (Europharma, Brazil)
Lucas Nicolás Alberca (National University of La Plata, Argentine)
Mateus de Sá Magalhães Se rafim (Federal University of Minas Gerais, Brazil )
Maya Topf (Centre for Structural System s Biology, Germany)
ix
x Acknowledgments
Michell de Oliveira Almeida (University of São Paulo, Brazil)
Paavo Honkakoski (University of East Finland, Finland)
Paula Homem-de-Mello (Federal University of ABC, Brazil)
Petr Pavek (Charles University, Czech Republic)
Rafael Lopes Almeida (Federal University of Minas Gerais, Brazil)
Rafaela Salgado Ferreira (Federal University of Minas Gerais, Brazil)
Renata Barbosa de Oliveira (Federal University of Minas Gerais, Brazil)
Renato Dias da Cunha (Federal University of ABC, Brazil)
Rodrigo Bentes Kato (Federal University of Minas Gerais, Brazil)
Saulo Fehelberg Pinto Braga (Federal University of Ouro Preto, Brazil )
Thales Kronenberger (University of Tübingen, Germany)