Computer Aided Drug Design Drug Discovery Computational Modelling And Artificial Intelligence

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Computer Aided Drug Design Drug Discovery Computational Modelling And Artificial Intelligence

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Author : Fei Ye
language : en
Publisher: Frontiers Media SA
Release Date : 2022-08-17

Computer Aided Drug Design Drug Discovery Computational Modelling And Artificial Intelligence written by Fei Ye and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-17 with Science categories.

Computer Aided Drug Design

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Author : Dev Bukhsh Singh
language : en
Publisher: Springer Nature
Release Date : 2020-10-09

Computer Aided Drug Design written by Dev Bukhsh Singh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-09 with Medical categories.

This book provides up-to-date information on bioinformatics tools for the discovery and development of new drug molecules. It discusses a range of computational applications, including three-dimensional modeling of protein structures, protein-ligand docking, and molecular dynamics simulation of protein-ligand complexes for identifying desirable drug candidates. It also explores computational approaches for identifying potential drug targets and for pharmacophore modeling. Moreover, it presents structure- and ligand-based drug design tools to optimize known drugs and guide the design of new molecules. The book also describes methods for identifying small-molecule binding pockets in proteins, and summarizes the databases used to explore the essential properties of drugs, drug-like small molecules and their targets. In addition, the book highlights various tools to predict the absorption, distribution, metabolism, excretion (ADME) and toxicity (T) of potential drug candidates. Lastly, it reviews in silico tools that can facilitate vaccine design and discusses their limitations.

Text Book Of Computer Aided Drug Design

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Author : Valapa Anusha, Lalbihari Barik, Prashant Gupta, Dr Pichika Mallikarjuna Rao, Mak Kit-Kay
language : en
Publisher: Shashwat Publication
Release Date : 2025-05-30

Text Book Of Computer Aided Drug Design written by Valapa Anusha, Lalbihari Barik, Prashant Gupta, Dr Pichika Mallikarjuna Rao, Mak Kit-Kay and has been published by Shashwat Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Fiction categories.

The Text Book of Computer Aided Drug Design is a comprehensive guide covering modern techniques used in computational drug discovery. It begins with an introduction to Computer Aided Drug Design (CADD), highlighting its history, fundamental principles, and wide-ranging applications. The book then delves into Quantitative Structure-Activity Relationships (QSAR), explaining basics, the evolution of QSAR methodologies, and the importance of physicochemical parameters like electronic, lipophilicity, and steric effects. Both experimental and theoretical approaches for parameter determination are detailed. Further, it elaborates on Hansch and Free Wilson analysis, deriving 2D-QSAR equations, and advanced 3D-QSAR approaches along with contour map interpretation. A dedicated section discusses the crucial role of molecular modeling and quantum mechanics in drug design. It contrasts global minimum energy conformations with bioactive conformations and thoroughly explains rigid, flexible, and extra-precision molecular docking techniques. The text also explores enzyme targets such as DHFR, HMG-CoA reductase, HIV protease, and cholinesterases, emphasizing the design of inhibitors. Another highlight is the prediction of ADMET properties essential for successful drug candidates. De novo drug design is explored with focus on receptor/enzyme interactions, cavity predictions, and fragment-based approaches. Techniques like homology modeling and generation of 3D protein structures are covered to support structure-based drug design. The final chapters are dedicated to pharmacophore mapping and virtual screening methods. Readers learn about pharmacophore identification, conformational search techniques, in silico drug design strategies, and both similarity-based and structure-based virtual screening approaches. Rich in theory and practical approaches, this book serves as an essential resource for pharmacy, medicinal chemistry, and computational biology students. It bridges fundamental concepts with advanced drug discovery techniques. It is ideal for both beginners seeking a strong foundation and researchers aiming for advanced applications. Comprehensive examples, models, and updated techniques make it highly relevant to current pharmaceutical research and industry needs.

Computer Aided Drug Design

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Author : Aman Thakur
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-08-19

Computer Aided Drug Design written by Aman Thakur and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-19 with Science categories.

Computer-Aided Drug Design (CADD) is a comprehensive guide designed for both beginners and experienced users in CADD. This book covers the fundamental principles and gradually delves into more advanced concepts and techniques, making it an invaluable resource to anyone interested in CADD. It begins by establishing a solid foundation, explaining the core concepts of CADD, the user interface and essential tools. It covers QSAR, molecular docking, homology modeling, virtual screening, pharmacophore modeling, ensuring that the reader can quickly become proficient in CADD. The book provides in-depth insights into 3D modeling, rendering, and parametric design. The style of the book is simple, every topic begins from the very basics and explores advanced levels with clarity. Practical examples, step-by-step tutorials and hands-on exercises, are included for better understanding.

Intelligent And Fuzzy Systems

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Author : Cengiz Kahraman
language : en
Publisher: Springer Nature
Release Date : 2025-07-25

Intelligent And Fuzzy Systems written by Cengiz Kahraman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-25 with Computers categories.

Artificial Intelligence in Human-Centric, Resilient & Sustainable Industries This book focuses on benefiting artificial intelligent tools in our business and social life under emerging conditions. Human-centric, resilient, and sustainable industries are built on ideals like human-centricity, ecological advantages, or social benefits. The mission of human-centric artificial intelligence is to improve people’s lives by offering solutions that boost productivity, accessibility to resources, security, well-being, and general quality of life. The latest intelligent methods and techniques on human-centric, resilient, and sustainable industries are introduced by theory and applications. This book covers the chapters of world-wide known experts on machine learning, medical image processing, process intelligence, process mining, and others. The intended readers are intelligent systems researchers, lecturers, M.Sc. and Ph.D. students trying to develop approaches giving human needs, values, and viewpoints top priority through artificial intelligent systems.

Machine Learning For Drug Discovery

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Author : Marcelo C. R. Melo
language : en
Publisher: American Chemical Society
Release Date : 2022-03-11

Machine Learning For Drug Discovery written by Marcelo C. R. Melo and has been published by American Chemical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Computers categories.

Machine Learning for Drug Discovery is designed to suit the needs of graduate students, advanced undergraduates, chemists or biologists otherwise new to this research domain with minimal previous exposure to Machine Learning (ML) methods, or computational scientists with minimal exposure to medicinal chemistry. The e-book covers basic algorithmic theory, data representation methods, and generative modeling at a high level. The authors spotlight antibiotic discovery as a case study in ML for drug development and discuss diverse applications in drug-likeness prediction, antimicrobial resistance, and areas for future inquiry. For a more dynamic learning experience, open-source code demonstrations in Python are included.

Artificial Intelligence And Machine Learning In Drug Design And Development

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Author : Abhirup Khanna
language : en
Publisher: John Wiley & Sons
Release Date : 2024-07-18

Artificial Intelligence And Machine Learning In Drug Design And Development written by Abhirup Khanna and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-18 with Computers categories.

The book is a comprehensive guide that explores the use of artificial intelligence and machine learning in drug discovery and development covering a range of topics, including the use of molecular modeling, docking, identifying targets, selecting compounds, and optimizing drugs. The intersection of Artificial Intelligence (AI) and Machine Learning (ML) within the field of drug design and development represents a pivotal moment in the history of healthcare and pharmaceuticals. The remarkable synergy between cutting-edge technology and the life sciences has ushered in a new era of possibilities, offering unprecedented opportunities, formidable challenges, and a tantalizing glimpse into the future of medicine. AI can be applied to all the key areas of the pharmaceutical industry, such as drug discovery and development, drug repurposing, and improving productivity within a short period. Contemporary methods have shown promising results in facilitating the discovery of drugs to target different diseases. Moreover, AI helps in predicting the efficacy and safety of molecules and gives researchers a much broader chemical pallet for the selection of the best molecules for drug testing and delivery. In this context, drug repurposing is another important topic where AI can have a substantial impact. With the vast amount of clinical and pharmaceutical data available to date, AI algorithms find suitable drugs that can be repurposed for alternative use in medicine. This book is a comprehensive exploration of this dynamic and rapidly evolving field. In an era where precision and efficiency are paramount in drug discovery, AI and ML have emerged as transformative tools, reshaping the way we identify, design, and develop pharmaceuticals. This book is a testament to the profound impact these technologies have had and will continue to have on the pharmaceutical industry, healthcare, and ultimately, patient well-being. The editors of this volume have assembled a distinguished group of experts, researchers, and thought leaders from both the AI, ML, and pharmaceutical domains. Their collective knowledge and insights illuminate the multifaceted landscape of AI and ML in drug design and development, offering a roadmap for navigating its complexities and harnessing its potential. In each section, readers will find a rich tapestry of knowledge, case studies, and expert opinions, providing a 360-degree view of AI and ML’s role in drug design and development. Whether you are a researcher, scientist, industry professional, policymaker, or simply curious about the future of medicine, this book offers 19 state-of-the-art chapters providing valuable insights and a compass to navigate the exciting journey ahead. Audience The book is a valuable resource for a wide range of professionals in the pharmaceutical and allied industries including researchers, scientists, engineers, and laboratory workers in the field of drug discovery and development, who want to learn about the latest techniques in machine learning and AI, as well as information technology professionals who are interested in the application of machine learning and artificial intelligence in drug development.

Computer Aided And Machine Learning Driven Drug Design

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Author : Vinícius Gonçalves Maltarollo
language : en
Publisher: Springer Nature
Release Date : 2025-02-27

Computer Aided And Machine Learning Driven Drug Design written by Vinícius Gonçalves Maltarollo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Science categories.

The computer-aided drug design 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, and computer scientists. In this sense, it is difficult to be an expert in every single CADD approach. Furthermore, there are well-established methods that are constantly revisited, and novel approaches are introduced, such as machine-learning based scoring functions for molecular docking. This book provides an organized update of the most commonly employed CADD techniques, as well as successful examples of actual applications to develop bioactive compounds/drug candidates. Also includes is a section of case studies that cover certain pharmacological/target classes, focusing on the applications of the previously described methods. This part will especially appeal to professionals who are not as interested in the theoretical aspects of CADD. This is an ideal book for students, researchers, and industry professionals in the fields of pharmacy, chemistry, biology, bioinformatics, computer sciences, and medicine who are seeking a go-to reference on drug design and medicinal chemistry.

Molecular Docking For Computer Aided Drug Design

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Author : Mohane S. Coumar
language : en
Publisher: Academic Press
Release Date : 2021-02-17

Molecular Docking For Computer Aided Drug Design written by Mohane S. Coumar and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-17 with Medical categories.

Molecular Docking for Computer-Aided Drug Design: Fundamentals, Techniques, Resources and Applications offers in-depth coverage on the use of molecular docking for drug design. The book is divided into three main sections that cover basic techniques, tools, web servers and applications. It is an essential reference for students and researchers involved in drug design and discovery. - Covers the latest information and state-of-the-art trends in structure-based drug design methodologies - Includes case studies that complement learning - Consolidates fundamental concepts and current practice of molecular docking into one convenient resource

Cheminformatics Qsar And Machine Learning Applications For Novel Drug Development

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Author : Kunal Roy
language : en
Publisher: Elsevier
Release Date : 2023-05-23

Cheminformatics Qsar And Machine Learning Applications For Novel Drug Development written by Kunal Roy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-23 with Medical categories.

Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development aims at showcasing different structure-based, ligand-based, and machine learning tools currently used in drug design. It also highlights special topics of computational drug design together with the available tools and databases. The integrated presentation of chemometrics, cheminformatics, and machine learning methods under is one of the strengths of the book.The first part of the content is devoted to establishing the foundations of the area. Here recent trends in computational modeling of drugs are presented. Other topics present in this part include QSAR in medicinal chemistry, structure-based methods, chemoinformatics and chemometric approaches, and machine learning methods in drug design. The second part focuses on methods and case studies including molecular descriptors, molecular similarity, structure-based based screening, homology modeling in protein structure predictions, molecular docking, stability of drug receptor interactions, deep learning and support vector machine in drug design. The third part of the book is dedicated to special topics, including dedicated chapters on topics ranging from de design of green pharmaceuticals to computational toxicology. The final part is dedicated to present the available tools and databases, including QSAR databases, free tools and databases in ligand and structure-based drug design, and machine learning resources for drug design. The final chapters discuss different web servers used for identification of various drug candidates. - Presents chemometrics, cheminformatics and machine learning methods under a single reference - Showcases the different structure-based, ligand-based and machine learning tools currently used in drug design - Highlights special topics of computational drug design and available tools and databases