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An in-depth overview of what computation can do in bioinorganic chemistry, written for experimentalists and theoreticians working at the interface between chemistry and biology
Until recently, the field of computational bioinorganics has been governed by the application of quantum mechanical approaches. The emergence of metal-related biomolecular fields and increased computational capabilities have enabled the development of novel artificial metalloenzymes, new metallodrugs strategies, and advanced biosensor technologies.
Computational Bioinorganics: From Description to Prediction provides a state-of-the-art overview of the field, covering a wide range of computational approaches, strategies, and applications. Contributions from a team of experts in bioinorganic chemistry discuss recent advances in sequence and structural bioinformatics, multi-scale strategies, large-scale molecular dynamics, and more. Divided into three parts, the book opens with a thorough introduction to computational bioinorganic chemistry, followed by an extensive summary of the computational methods available in bioinorganic chemistry. The book concludes with a series of detailed reviews of various applications, including computational studies of metal-mediated folding and computer-aided metalloenzyme design.
Edited by a recognized leader in the field, Computational Bioinorganics: From Description to Prediction is an essential resource for academic and industrial researchers working in the fields of bioinorganic chemistry, coordination chemistry, biochemistry, computational chemistry, biophysics, bioinformatics, and protein engineering.
Author: Jean-Didier Maréchal
ISBN-10: 1119415136
ISBN-13: 9781119415138
Publisher: Wiley
Language: English
Published: 02/24/2026
Pages: 244
Format: Hardcover
Jean-Didier Maréchal is Associate Professor of Physical Chemistry at Universitat Autònoma de Barcelona (Autonomous University of Barcelona), Spain. An expert in modeling bioinorganic systems, Professor Maréchal's research focuses on computational bioinorganics applied to topics such as the design of artificial metalloenzymes, artificial metallopeptides, and metallopeptide-based biosensors.
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