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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 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.
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