Autorentext

Jean-Didier Maréchal is a Full Professor of Physical Chemistry at the 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, metallopeptides, and metallodrugs, as well as uncovering the molecular mechanisms that sustain metal homeostasis in humans and pathogens.

Klappentext

An in-depth overview of what computation can do in bioinorganic chemistry, written for experimentalists and theoreticians The last decades have shown the emergence of numerous exiting fields in bioinorganic chemistry, such as the design of de novo 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. Computational Bioinorganics: From Description to Prediction 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. 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.

Inhalt

Preface ix

1 What Could Bring Theory to Modern Bioinorganics: A Conversation? 1
Gerard Roelfes and Jean-Didier Maréchal

2 Computational Prediction and Modeling of Metal-binding Sites in Proteins 9
José-Emilio Sánchez-Aparicio, Giuseppe Sciortino, and Jean-Didier Maréchal

2.1 Introduction 9

2.2 Experimental Tools 10

2.3 Computational Tools 10

2.3.1 Pattern Recognition Algorithms 11

2.3.2 The Backbone Preorganization Hypothesis 14

2.3.3 Protein-Ligand Dockings 17

2.3.4 GaudiMM Platform 19

2.3.5 Quantum Mechanical and Hybrid Approaches 21

2.3.6 Molecular Dynamics, Integrative or Multiscale Approaches 22

2.4 Conclusions 25

References 25

3 Quantum-mechanics Approaches in Bioinorganic Chemistry: Targeting the Oxidation State 33
Marcel Swart

3.1 Introduction 33

3.2 Experimental Observations 35

3.3 Quantum-chemistry Approaches 37

3.3.1 Chemical Bonding Analyses 38

3.3.2 Oxidation States from Wavefunctions or Densities 41

3.4 Classical Examples 43

3.5 Intriguing Examples 46

3.6 Summary and Outlook 48

Acknowledgments 49

References 49

4 Computation and Spectroscopy 57
Eugenio Garribba

4.1 Introduction 57

4.2 Software, Computational Techniques, and Statistical Indicators 58

4.3 Electron Paramagnetic Resonance 61

4.4 Electron Spin Echo Envelope Modulation and Electron-nuclear Double Resonance 67

4.5 Nuclear Magnetic Resonance 69

4.6 Electron Absorption Spectroscopy 77

4.7 Circular Dichroism and Magnetic Circular Dichroism 81

4.8 Vibrational Spectroscopy 83

4.9 Mossbauer Spectroscopy 84

4.10 Conclusions 88

References 89

5 Multiscale Computational Modeling for the Discovery and Characterization of New Metalloenzyme-catalyzed Reactions 99
Ferran Feixas and Marc Garcia-Borràs

5.1 Importance of Metalloenzymes 99

5.2 Multi-scale Computational Microscope for Modeling Metalloenzymatic Reaction Mechanisms 100

5.2.1 Classical Molecular Dynamics Simulations 102

5.2.2 Truncated Active Site Models at the Quantum Mechanics Level 103

5.2.3 Hybrid Quantum Mechanics/Molecular Mechanics 103

5.3 Practical Considerations for Computational Modeling of Metalloenzymes 104

5.3.1 Selecting the Starting Structure 104

5.3.2 Initial Exploration of Conformational Dynamics 105

5.3.3 Placement of Substrate or Reaction Intermediate 106

5.4 The Mechanistic Versatility of P450s Through the Lens of a Computational Microscope: Practical Examples 107

5.4.1 Practical Example: Anti-Markovnikov Alkene Oxidations Catalyzed by P450s 108

5.4.2 Molecular Dynamics Simulations for Modeling the Protein Environment 112

5.4.3 Insightful Revelations from QM/MM Calculations 114

5.4.4 The Role of Local Electric Fields in Enzymatic Reactions 116

5.5 Conclusions 117

Acknowledgments 118

References 119

6 Force Fields and Metals 123
José-Emilio Sánchez-Aparicio, Lorena Roldán-Martín, Jean-Didier Maréchal, and Giuseppe Sciortino

6.1 Introduction 123

6.2 Overview on Molecular Mechanics and How to Deal with Metals 124

6.3 Bonded Model 126

6.3.1 Cu(II) Binding to Polyhistidine Peptides 126

6.3.2 Interaction of Oxaliplatin with Insulin 127

6.3.3 Artificial Metallohydratase 128

6.4 Nonbonded Models 131

6.4.1 The Dummy Atom 131

6.5 The 12-6(-4) Lennard-Jones Potentials 132

6.6 Conclusions 134

References 135

7 Modeling Thermally Activated Processes 139
Pietro Vidossich and Alessandra Magistrato

7.1 Introduction 139

7.2 Modeling Transitions 140

7.2.1 Theoretical Framework 141

7.2.2 Collective Variables 142

7.2.3 Biased Methods 144

7.3 Illustrative Studies 147

7.3.1 Metal Coordination 147

7.3.2 Enzymatic Reactions 150

7.4 Conclusion 153

References 154

8 Metal-induced Folding of Oligopeptides 159
L. Roldán-Martín, L. Rodríguez-Santiago, J. Alí-Torres, J. D. Maréchal, and M. Sodupe

8.1 Introduction 159

8.2 Metal-Ligand Interactions with Short Peptides (n = 2-8) 160

8.2.1 Gly n and Ala n Metal Complexes 160

8.2.2 Metal-Peptide Complexes Involving Residues Other than Gly and Ala 163

8. 165

8.3.1 Construction of Three-dimensional Models. Application to Cu 2+ - A ß 1-16 166

8.3.2 Impact of Cu 2+ and Al 3+ Binding on the A ß 1-42 Conformational Landscape 169

8.4 Conclusions 172

References 172

9 Computational Studies of Metallodrugs 179
James A. Platts and Matthew Turner

9.1 Introduction 179

9.2 QM Studies of Metallodrugs and Their Solvation 179

9.3 QM Studies of Metallodrug-Biomolecule Interactions 181

9.4 QM/MM Modeling of Drug-Biomolecule Interactions 184

9.5 Classical MM Description of Drugs and Their Interactions 186

9.6 Docking and QSAR Studies 190

9.7 Conclusion 191

References 192

10 Computational Design of Artificial Metalloenzymes 195
Laura Tiessler-Sala, Maria Fatima Lucas, and Emanuele Monza

10.1 Introduction 195

10.2 Typical Computational Pipeline 196

10.3 Critical Aspects and Frontiers of ArM Design 198

10.3.1 Challenges in Modeling Metallic Centers 198

10.3.2 Unnatural Amino Acids Can Unlock New Reactivity 200

10.3.3 Beyond TS Stabilization 202

10.3.4 The New Era: De Novo Protein Design with DL 204

10.4 Concluding Remarks 205

References 206

11 How Computational Chemistry Can Contribute to the Understanding of the Effects of Metal Ions in Biological Systems: Aluminum as a Case Study 213
J.I. Mujika and X. Lopez

11.1 Introduction 213

11.2 Aluminum 215

11.2.1 Aluminum Speciation in Water 2…