Artificial Intelligence for Drug Design
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Beschreibung
The use of artificial intelligence in drug research and development plays an increasingly important role in evaluating the interaction between biological targets and drug molecules, optimizing drug design paths, etc., helping to accelerate the process of drug research and development and reduce the cost of research and development risks.
This book is jointly compiled by more than twenty young and middle-aged scientists who are fighting on the front line of scientific research, led by Professor Li Honglin, director of the Shanghai Key Laboratory of New Drug Design, and is aimed at researchers or technicians who are interested in cross-research in the field of life sciences and drug research and development.
The content of the book includes the following four aspects:
• Fundamentals of Artificial Intelligence Algorithms By systematically introducing artificial intelligence algorithms, explaining the principles, application scenarios, and characteristics of different algorithms, it provides a basis for the subsequent introduction of the intersection of artificial intelligence and drug research and development.
• Data Foundation and Representation Mainly introduces the key data resources of biomedicine, especially some data mining methods based on artificial intelligence.
• Artificial Intelligence and Drug Design With the drug research and development process as the main line, for each key step where the artificial intelligence algorithm is integrated, it first introduces the basic principles and existing challenges of drug design, and then systematically reviews the progress of AI algorithms in this research direction.
Program Code Provides direct materials for readers to carry out practical applications, deepens the understanding of the content of the book, and realizes the continuity of "teaching-learning-use".
This book focuses on the application of artificial intelligence in drug research and development, particularly its growing role in evaluating interactions between biological targets and drug molecules and optimizing drug design pathways. It offers a comprehensive structure divided into four parts: fundamentals of AI algorithms, data foundations and representations, AI driven drug design, and program code. The book systematically introduces key AI methodologies, highlights essential biomedical data resources, and presents data mining approaches based on artificial intelligence. Following the workflow of drug R&D, each chapter explains the basic principles and challenges of specific drug design steps and then reviews the corresponding advances in AI algorithms, supplemented by cross-disciplinary application examples. Readers will gain a clear understanding of how AI integrates into and accelerates the drug development process while reducing associated risks and costs, making the book particularly valuable for researchers and technical professionals engaged in life sciences and pharmaceutical R&D.
Provides comprehensive coverage of AI fundamentals Bridges cross-disciplinary fields by integrating AI with drug design Features contributions from outstanding scientists with expertise in AI driven drug development
Autor*in
Honglin Li
Themen in »Artificial Intelligence for Drug Design«
Drug Target Discovery Drug Repositioning Molecular Generative Modeling Quantum Chemistry Computational Chemistry Small Molecule Drug Synthesis De Novo Design Drug Toxicity Prediction