Machine Learning and Deep Learning in Drug Design

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Inbunden, Engelska, 2026

5 299 kr

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Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipeline—from target identification and protein structure prediction to virtual screening, pharmacokinetic modelling, and drug repurposing.Bridging cheminformatics, chemometrics, and computational science, the book offers practical case studies, emerging methodologies, and curated e-resources. Readers will discover how ML/DL techniques are used to predict drug–target interactions, optimize molecular properties, repurpose previously used drugs, and design multi-target therapeutics. Special topics include chemical language models, natural product-based drug discovery, and modelling drug-induced toxicities.With contributions from leading experts worldwide, this book is an essential resource for researchers, postgraduate students, and professionals in medicinal chemistry, pharmacology, and pharmaceutical sciences. It provides both foundational knowledge and advanced applications, equipping readers to harness AI for innovative and efficient drug development.

Produktinformation

Utgivningsdatum2026-07-22
Mått156 x 234 x 39 mm
Vikt1 065 g
FormatInbunden
SpråkEngelska
SerieDrug Discovery Series
Antal sidor798
FörlagRoyal Society of Chemistry
ISBN9781837070183

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Farmakologi inom Medicin
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A Perspective on the Application of Machine Learning and Deep Learning in the Drug Discovery PipelineAI-driven Approaches for Target Discovery in Drug DesignMachine Learning in Protein Structure PredictionMachine Learning Approaches to Chemical Space ExplorationMachine Learning in Structure-based Drug DesignMachine Learning in Molecular Dynamics Applications in Medicinal ChemistryMachine Learning in Ligand-based Drug DesignMachine Learning in Virtual Screening of DatabasesMachine Learning in Predicting the Physicochemical Properties of Drug CandidatesMachine Learning-augmented Rapid Screening and Scoring for an Effective Search for Lead Molecules in Computer-aided Drug DiscoveryMachine Learning in Drug–Drug InteractionsMachine Learning in Natural Product-based Drug DiscoveryMachine Learning in the Optimization of Pharmacokinetic ParametersMachine Learning in Drug-induced Adverse Reaction Modeling: Case Studies of Drug-induced Cardiotoxicity ModelingMachine Learning in Drug RepurposingMachine Learning (ML) and Deep Learning (DL) Approaches in Multi-target Drug DesignChemical Language Model Applications in Medicinal Chemistrye-Resources Relevant to Machine Learning Tools for Medicinal ChemistryMachine Learning-based Methods for Designing Protein-based DrugsMachine Learning Applications in Vaccine DesignLeveraging Machine Learning for Network Pharmacology