This volume looks at applications of quantum mechanical (QM) methods in drug discovery. The chapters in this book describe how QM approaches can be applied to address key drug discovery issues, such as characterizing protein-water-ligand and protein-protein interactions, providing estimates of binding affinities, determining ligand energies and bioactive conformations, refinement of molecular geometries, scoring docked protein–ligand poses, describing molecular similarity, structure–activity-relationship (SAR) analysis, and ADMET prediction. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Quantum Mechanics in Drug Discovery is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists, and drug designers.

"Quantum Mechanics in Drug Discovery" is an illuminating guide that navigates the intersection of quantum mechanics and pharmaceutical research. Designed for scientists, researchers, and professionals in the field of drug discovery, this book explores the crucial role of quantum mechanics in understanding molecular interactions, electronic structures, and the behavior of chemical compounds. Covering principles such as quantum molecular modeling and computational chemistry, the book provides valuable insights into predicting and optimizing drug properties with precision. With clarity and practical relevance, it serves as an indispensable resource for those seeking a deeper understanding of how quantum mechanics contributes to the advancement of drug development and innovation.

This volume looks at applications of quantum mechanical (QM) methods in drug discovery. The chapters in this book describe how QM approaches can be applied to address key drug discovery issues, such as characterizing protein-water-ligand and protein-protein interactions, providing estimates of binding affinities, determining ligand energies and bioactive conformations, refinement of molecular geometries, scoring docked protein–ligand poses, describing molecular similarity, structure–activity-relationship (SAR) analysis, and ADMET prediction. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Quantum Mechanics in Drug Discovery is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists, and drug designers.

"A Handbook of Quantum Mechanics in Drug Discovery" is a comprehensive guide tailored for absolute beginners without a mathematical background, offering a clear and accessible introduction to the intricate realm of quantum mechanics as applied to the field of drug discovery. Through simplified explanations and practical examples, this handbook demystifies complex concepts, providing readers with a foundational understanding of quantum mechanics principles and their crucial role in modern pharmaceutical research. From elucidating the electronic structure of molecules to exploring quantum algorithms for drug design and prediction, this book equips readers with the essential knowledge and insights necessary to navigate the intersection of quantum mechanics and drug discovery with confidence and clarity.

Helps you choose the right computational tools and techniques to meet your drug design goals Computational Drug Design covers all of the major computational drug design techniques in use today, focusing on the process that pharmaceutical chemists employ to design a new drug molecule. The discussions of which computational tools to use and when and how to use them are all based on typical pharmaceutical industry drug design processes. Following an introduction, the book is divided into three parts: Part One, The Drug Design Process, sets forth a variety of design processes suitable for a number of different drug development scenarios and drug targets. The author demonstrates how computational techniques are typically used during the design process, helping readers choose the best computational tools to meet their goals. Part Two, Computational Tools and Techniques, offers a series of chapters, each one dedicated to a single computational technique. Readers discover the strengths and weaknesses of each technique. Moreover, the book tabulates comparative accuracy studies, giving readers an unbiased comparison of all the available techniques. Part Three, Related Topics, addresses new, emerging, and complementary technologies, including bioinformatics, simulations at the cellular and organ level, synthesis route prediction, proteomics, and prodrug approaches. The book's accompanying CD-ROM, a special feature, offers graphics of the molecular structures and dynamic reactions discussed in the book as well as demos from computational drug design software companies. Computational Drug Design is ideal for both students and professionals in drug design, helping them choose and take full advantage of the best computational tools available. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

The development of a novel algorithm for treating interloop interactions in proteins will be presented in the context of the Protein Local Optimization Program (PLOP). Finally, the details of a next-generation scoring function, called WSCORE, for molecular docking is presented along with application to MCL-1.

This book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Förster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals from pharmaceutical industry interested in drug design and discovery.