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Computational Strategies for the Design of New Bioactive Molecules
Computational Strategies for the Design of New Bioactive Molecules
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This book offers a comprehensive introduction to computational methods used in modern drug discovery, combining theoretical foundations with practical applications. It covers key concepts such as quantum chemistry, molecular modeling, molecular mechanics, and molecular dynamics, along with techniques for analyzing simulations. The text also explores essential drug design approaches, including various QSAR methods, molecular docking strategies, and the use of artificial intelligence and machine…

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This book offers a comprehensive introduction to computational methods used in modern drug discovery, combining theoretical foundations with practical applications. It covers key concepts such as quantum chemistry, molecular modeling, molecular mechanics, and molecular dynamics, along with techniques for analyzing simulations. The text also explores essential drug design approaches, including various QSAR methods, molecular docking strategies, and the use of artificial intelligence and machine learning in predictive modeling. Additionally, it addresses important aspects of drug development such as physicochemical properties, pharmacokinetics, and toxicity prediction. Overall, the book provides a structured workflow and practical guidance for using computational tools in the design and optimization of bioactive molecules, making it valuable for students, researchers, and professionals in medicinal chemistry and pharmaceutical science.

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This book offers a comprehensive introduction to computational methods used in modern drug discovery, combining theoretical foundations with practical applications. It covers key concepts such as quantum chemistry, molecular modeling, molecular mechanics, and molecular dynamics, along with techniques for analyzing simulations. The text also explores essential drug design approaches, including various QSAR methods, molecular docking strategies, and the use of artificial intelligence and machine learning in predictive modeling. Additionally, it addresses important aspects of drug development such as physicochemical properties, pharmacokinetics, and toxicity prediction. Overall, the book provides a structured workflow and practical guidance for using computational tools in the design and optimization of bioactive molecules, making it valuable for students, researchers, and professionals in medicinal chemistry and pharmaceutical science.

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