{"product_id":"computational-bioinorganics-from-description-to-prediction-hardback-9781119415138","title":"Computational Bioinorganics; From Description to Prediction (Hardback) 9781119415138","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eComputational Bioinorganics\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eFrom Description to Prediction\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eJean-Didier Maréchal (Edited by), Maréchal (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781119415138, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 12 January 2026\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e256 pages\u003cbr\u003e24.4 x 17 x 1.6 cm, 0.595 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eAn in-depth overview of what computation can do in bioinorganic chemistry, written for experimentalists and theoreticians\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eThe last decades have shown the emergence of numerous exiting fields in bioinorganic chemistry, such as the design of \u003ci\u003ede novo\u003c\/i\u003e metalloenzymes, the discovery of new bioactive metallodrugs, or the characterization of molecular mechanisms by which living organisms acquire their metal. In parallel, the computational chemistry community has been working hard on optimizing its framework to deal with biometallic systems; a phenomenon magnified by the increase of computational power and the advent of AI approaches. \u003c\/p\u003e\n\u003cp\u003e\u003ci\u003eComputational Bioinorganics: From Description to Prediction\u003c\/i\u003e provides an updated view on the current state-of-the-art of the field. The book first intends to clarify how computational and experimental researchers in bioinorganic chemistry can now collaborate under this new computational paradigm. It then follows with a series of chapters that cover a wide range of computational approaches, strategies, and applications. Contributions from a team of experts in computational chemistry expose methods that range from structural bioinformatics, quantum chemistry, large-scale molecular dynamics or multi-scale strategies. They illustrate how these tools can be applied to a wide variety of topics such as the modeling of metal-mediated folding processes, the computer-aided design of metalloenzymes, spectroscopic analysis, the prediction of metal binding sites in proteins or the characterization of the interaction of metallodrugs with biomolecules. \u003c\/p\u003e\n\u003cp\u003eEdited by a recognized leader in the field, \u003ci\u003eComputational Bioinorganics: From Description to Prediction\u003c\/i\u003e 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.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 What Could Bring Theory to Modern Bioinorganics: A Conversation? 1\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGerard Roelfes and Jean-Didier Maréchal\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Computational Prediction and Modeling of Metal-binding Sites in Proteins 9\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJosé-Emilio Sánchez-Aparicio, Giuseppe Sciortino, and Jean-Didier Maréchal\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 9\u003c\/p\u003e \u003cp\u003e2.2 Experimental Tools 10\u003c\/p\u003e \u003cp\u003e2.3 Computational Tools 10\u003c\/p\u003e \u003cp\u003e2.3.1 Pattern Recognition Algorithms 11\u003c\/p\u003e \u003cp\u003e2.3.2 The Backbone Preorganization Hypothesis 14\u003c\/p\u003e \u003cp\u003e2.3.3 Protein–Ligand Dockings 17\u003c\/p\u003e \u003cp\u003e2.3.4 GaudiMM Platform 19\u003c\/p\u003e \u003cp\u003e2.3.5 Quantum Mechanical and Hybrid Approaches 21\u003c\/p\u003e \u003cp\u003e2.3.6 Molecular Dynamics, Integrative or Multiscale Approaches 22\u003c\/p\u003e \u003cp\u003e2.4 Conclusions 25\u003c\/p\u003e \u003cp\u003eReferences 25\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Quantum-mechanics Approaches in Bioinorganic Chemistry: Targeting the Oxidation State 33\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMarcel Swart\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 33\u003c\/p\u003e \u003cp\u003e3.2 Experimental Observations 35\u003c\/p\u003e \u003cp\u003e3.3 Quantum-chemistry Approaches 37\u003c\/p\u003e \u003cp\u003e3.3.1 Chemical Bonding Analyses 38\u003c\/p\u003e \u003cp\u003e3.3.2 Oxidation States from Wavefunctions or Densities 41\u003c\/p\u003e \u003cp\u003e3.4 Classical Examples 43\u003c\/p\u003e \u003cp\u003e3.5 Intriguing Examples 46\u003c\/p\u003e \u003cp\u003e3.6 Summary and Outlook 48\u003c\/p\u003e \u003cp\u003eAcknowledgments 49\u003c\/p\u003e \u003cp\u003eReferences 49\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Computation and Spectroscopy 57\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eEugenio Garribba\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 57\u003c\/p\u003e \u003cp\u003e4.2 Software, Computational Techniques, and Statistical Indicators 58\u003c\/p\u003e \u003cp\u003e4.3 Electron Paramagnetic Resonance 61\u003c\/p\u003e \u003cp\u003e4.4 Electron Spin Echo Envelope Modulation and Electron-nuclear Double Resonance 67\u003c\/p\u003e \u003cp\u003e4.5 Nuclear Magnetic Resonance 69\u003c\/p\u003e \u003cp\u003e4.6 Electron Absorption Spectroscopy 77\u003c\/p\u003e \u003cp\u003e4.7 Circular Dichroism and Magnetic Circular Dichroism 81\u003c\/p\u003e \u003cp\u003e4.8 Vibrational Spectroscopy 83\u003c\/p\u003e \u003cp\u003e4.9 Mossbauer Spectroscopy 84\u003c\/p\u003e \u003cp\u003e4.10 Conclusions 88\u003c\/p\u003e \u003cp\u003eReferences 89\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Multiscale Computational Modeling for the Discovery and Characterization of New Metalloenzyme-catalyzed Reactions 99\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eFerran Feixas and Marc Garcia-Borràs\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Importance of Metalloenzymes 99\u003c\/p\u003e \u003cp\u003e5.2 Multi-scale Computational Microscope for Modeling Metalloenzymatic Reaction Mechanisms 100\u003c\/p\u003e \u003cp\u003e5.2.1 Classical Molecular Dynamics Simulations 102\u003c\/p\u003e \u003cp\u003e5.2.2 Truncated Active Site Models at the Quantum Mechanics Level 103\u003c\/p\u003e \u003cp\u003e5.2.3 Hybrid Quantum Mechanics\/Molecular Mechanics 103\u003c\/p\u003e \u003cp\u003e5.3 Practical Considerations for Computational Modeling of Metalloenzymes 104\u003c\/p\u003e \u003cp\u003e5.3.1 Selecting the Starting Structure 104\u003c\/p\u003e \u003cp\u003e5.3.2 Initial Exploration of Conformational Dynamics 105\u003c\/p\u003e \u003cp\u003e5.3.3 Placement of Substrate or Reaction Intermediate 106\u003c\/p\u003e \u003cp\u003e5.4 The Mechanistic Versatility of P450s Through the Lens of a Computational Microscope: Practical Examples 107\u003c\/p\u003e \u003cp\u003e5.4.1 Practical Example: Anti-Markovnikov Alkene Oxidations Catalyzed by P450s 108\u003c\/p\u003e \u003cp\u003e5.4.2 Molecular Dynamics Simulations for Modeling the Protein Environment 112\u003c\/p\u003e \u003cp\u003e5.4.3 Insightful Revelations from QM\/MM Calculations 114\u003c\/p\u003e \u003cp\u003e5.4.4 The Role of Local Electric Fields in Enzymatic Reactions 116\u003c\/p\u003e \u003cp\u003e5.5 Conclusions 117\u003c\/p\u003e \u003cp\u003eAcknowledgments 118\u003c\/p\u003e \u003cp\u003eReferences 119\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Force Fields and Metals 123\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJosé-Emilio Sánchez-Aparicio, Lorena Roldán-Martín, Jean-Didier Maréchal, and Giuseppe Sciortino\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 123\u003c\/p\u003e \u003cp\u003e6.2 Overview on Molecular Mechanics and How to Deal with Metals 124\u003c\/p\u003e \u003cp\u003e6.3 Bonded Model 126\u003c\/p\u003e \u003cp\u003e6.3.1 Cu(II) Binding to Polyhistidine Peptides 126\u003c\/p\u003e \u003cp\u003e6.3.2 Interaction of Oxaliplatin with Insulin 127\u003c\/p\u003e \u003cp\u003e6.3.3 Artificial Metallohydratase 128\u003c\/p\u003e \u003cp\u003e6.4 Nonbonded Models 131\u003c\/p\u003e \u003cp\u003e6.4.1 The Dummy Atom 131\u003c\/p\u003e \u003cp\u003e6.5 The 12-6(-4) Lennard–Jones Potentials 132\u003c\/p\u003e \u003cp\u003e6.6 Conclusions 134\u003c\/p\u003e \u003cp\u003eReferences 135\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Modeling Thermally Activated Processes 139\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePietro Vidossich and Alessandra Magistrato\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 139\u003c\/p\u003e \u003cp\u003e7.2 Modeling Transitions 140\u003c\/p\u003e \u003cp\u003e7.2.1 Theoretical Framework 141\u003c\/p\u003e \u003cp\u003e7.2.2 Collective Variables 142\u003c\/p\u003e \u003cp\u003e7.2.3 Biased Methods 144\u003c\/p\u003e \u003cp\u003e7.3 Illustrative Studies 147\u003c\/p\u003e \u003cp\u003e7.3.1 Metal Coordination 147\u003c\/p\u003e \u003cp\u003e7.3.2 Enzymatic Reactions 150\u003c\/p\u003e \u003cp\u003e7.4 Conclusion 153\u003c\/p\u003e \u003cp\u003eReferences 154\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Metal-induced Folding of Oligopeptides 159\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eL. Roldán-Martín, L. Rodríguez-Santiago, J. Alí-Torres, J. D. Maréchal, and M. Sodupe\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 159\u003c\/p\u003e \u003cp\u003e8.2 Metal–Ligand Interactions with Short Peptides (n = 2–8) 160\u003c\/p\u003e \u003cp\u003e8.2.1 Gly n and Ala n Metal Complexes 160\u003c\/p\u003e \u003cp\u003e8.2.2 Metal–Peptide Complexes Involving Residues Other than Gly and Ala 163\u003c\/p\u003e \u003cp\u003e8.3 Metal-oligopeptides (n \u0026gt;8) 165\u003c\/p\u003e \u003cp\u003e8.3.1 Construction of Three-dimensional Models. Application to Cu 2+ -​A​β​ 1–16 ​\u003ci\u003e166\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.3.2 Impact of Cu 2+ and Al 3+ Binding on the ​A​β​ 1–42 ​Conformational Landscape 169\u003c\/p\u003e \u003cp\u003e8.4 Conclusions 172\u003c\/p\u003e \u003cp\u003eReferences 172\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Computational Studies of Metallodrugs 179\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJames A. Platts and Matthew Turner\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 179\u003c\/p\u003e \u003cp\u003e9.2 QM Studies of Metallodrugs and Their Solvation 179\u003c\/p\u003e \u003cp\u003e9.3 QM Studies of Metallodrug–Biomolecule Interactions 181\u003c\/p\u003e \u003cp\u003e9.4 QM\/MM Modeling of Drug–Biomolecule Interactions 184\u003c\/p\u003e \u003cp\u003e9.5 Classical MM Description of Drugs and Their Interactions 186\u003c\/p\u003e \u003cp\u003e9.6 Docking and QSAR Studies 190\u003c\/p\u003e \u003cp\u003e9.7 Conclusion 191\u003c\/p\u003e \u003cp\u003eReferences 192\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Computational Design of Artificial Metalloenzymes 195\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eLaura Tiessler-Sala, Maria Fatima Lucas, and Emanuele Monza\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 195\u003c\/p\u003e \u003cp\u003e10.2 Typical Computational Pipeline 196\u003c\/p\u003e \u003cp\u003e10.3 Critical Aspects and Frontiers of ArM Design 198\u003c\/p\u003e \u003cp\u003e10.3.1 Challenges in Modeling Metallic Centers 198\u003c\/p\u003e \u003cp\u003e10.3.2 Unnatural Amino Acids Can Unlock New Reactivity 200\u003c\/p\u003e \u003cp\u003e10.3.3 Beyond TS Stabilization 202\u003c\/p\u003e \u003cp\u003e10.3.4 The New Era: De Novo Protein Design with DL 204\u003c\/p\u003e \u003cp\u003e10.4 Concluding Remarks 205\u003c\/p\u003e \u003cp\u003eReferences 206\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 How Computational Chemistry Can Contribute to the Understanding of the Effects of Metal Ions in Biological Systems: Aluminum as a Case Study 213\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJ.I. Mujika and X. Lopez\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 213\u003c\/p\u003e \u003cp\u003e11.2 Aluminum 215\u003c\/p\u003e \u003cp\u003e11.2.1 Aluminum Speciation in Water 216\u003c\/p\u003e \u003cp\u003e11.2.2 Mapping Aluminum Speciation with Biological Building Molecules 217\u003c\/p\u003e \u003cp\u003e11.3 The Pro-oxidant Activity of Aluminum 217\u003c\/p\u003e \u003cp\u003e11.4 Unveiling the ​Al(III) − Aβ​ Complex 223\u003c\/p\u003e \u003cp\u003e11.4.1 Step 1: Most Favorable First Coordination Spheres of Aluminum 225\u003c\/p\u003e \u003cp\u003e11.4.2 Step 2: The Building of Preliminary ​Al.Aβ​Complexes 227\u003c\/p\u003e \u003cp\u003e11.4.3 Step 3: Refinement of the ​Al.Aβ​Complexes 228\u003c\/p\u003e \u003cp\u003e11.5 In Silico Design of Novel Aluminum Chelators 231\u003c\/p\u003e \u003cp\u003e11.6 Concluding Remarks 237\u003c\/p\u003e \u003cp\u003eReferences 237\u003c\/p\u003e \u003cp\u003eIndex 239\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Chemistry [\u003ca title=\"See our other books on Chemistry\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Chemistry%20%5BPN%5D%22\"\u003ePN\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52428583108888,"sku":"9781119415138","price":109.55,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781119415138.jpg?v=1784680499","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/computational-bioinorganics-from-description-to-prediction-hardback-9781119415138","provider":"Freshly Printed Books","version":"1.0","type":"link"}