Generally speaking, quantitative-structure activity relationship (QSAR) is a technique which correlates the biological activities of a set of compounds to their structures using a mathematical equation represented in its general form by Biological Activity = f (x1, ..., xn), where f is a mathematical function and x1, ..., xn are n molecular descriptors. Since the introduction of the initial concept of QSAR in the early 1960s, numerous advances have been introduced into the field transforming it into an essential tool in drug discovery and medicinal chemistry. Quantitative Structure - Activity Relationship: A Practical Approach provides a detailed overview of computational approaches in QSAR studies. It covers the applications of different algorithms in various steps of a QSAR analysis and shows clear examples. Each chapter introduces the tools and software involved. Moreover, challenges and issues which may be faced in any step of the analysis are thoroughly broken down based on the OECD guidelines, enabling the reader to familiarize themselves with potential end results. The book was kept concise, making it suitable for students (pharmacy, chemistry and biological science) and lecturers, as well as researchers in the field.

Generally speaking, quantitative-structure activity relationship (QSAR) is a technique which correlates the biological activities of a set of compounds to their structures using a mathematical equation represented in its general form by Biological Activity = f (x1, ..., xn), where f is a mathematical function and x1, ..., xn are n molecular descriptors. Since the introduction of the initial concept of QSAR in the early 1960s, numerous advances have been introduced into the field transforming it into an essential tool in drug discovery and medicinal chemistry. Quantitative Structure - Activity Relationship: A Practical Approach provides a detailed overview of computational approaches in QSAR studies. It covers the applications of different algorithms in various steps of a QSAR analysis and shows clear examples. Each chapter introduces the tools and software involved. Moreover, challenges and issues which may be faced in any step of the analysis are thoroughly broken down based on the OECD guidelines, enabling the reader to familiarize themselves with potential end results. The book was kept concise, making it suitable for students (pharmacy, chemistry and biological science) and lecturers, as well as researchers in the field.

As the pharmaceutical industry continues to advance, new techniques in drug design are emerging. In order to deliver optimal care to patients, the development of innovative pharmacological techniques has become a widely studied topic. The Handbook of Research on Molecular Docking-Based Drug Design and Discovery investigates the evolution of pharmaceutical design and computational approaches in the field of molecular docking. Highlighting theoretical backgrounds and emergent research in the area of computer-assisted drug design, this publication is a pivotal source for professionals, researchers, medical chemists, pharmaceutical experts, and students interested in innovative practices and findings within the fields of computational chemistry and pharmaceutical sciences.

As the pharmaceutical industry continues to advance, new techniques in drug design are emerging. In order to deliver optimum care to patients, the development of innovative pharmacological techniques has become a widely studied topic. Applied Case Studies and Solutions in Molecular Docking-Based Drug Design is a pivotal reference source for the latest scholarly research on the progress of pharmaceutical design and computational approaches in the field of molecular docking. Highlighting innovative research perspectives and real-world applications, this book is ideally designed for professionals, researchers, practitioners, and medical chemists actively involved in computational chemistry and pharmaceutical sciences.