Theoretical and Computational Inorganic Chemistry (eBook)

Rudi van Eldik, Jeremy Harvey (Herausgeber)

eBook Download: PDF | EPUB

2010 | 1. Auflage
536 Seiten
Elsevier Science (Verlag)
978-0-12-380875-2 (ISBN)

Infos

The Advances in Inorganic Chemistry series present timely and informative summaries of the current progress in a variety of subject areas within inorganic chemistry, ranging from bio-inorganic to solid state studies. This acclaimed serial features reviews written by experts in the field and serves as an indispensable reference to advanced researchers. Each volume contains an index, and each chapter is fully referenced. - Features comprehensive reviews on the latest developments - Includes contributions from leading experts in the field - Serves as an indispensable reference to advanced researchers

Inhalt

Cover 1
Advances in Inorganic Chemistry 2
Copyright 5
Contents 6
List of Contributors 10
Preface 12
Molecular Mechanics for Transition Metal Centers:From Coordination Complexes to Metalloproteins 14
I. Introduction 14
II. Conventional Molecular Mechanics 15
III. Shortcomings of MM for TM Systems: Angular Potentials 17
IV. Effects from d Electrons 18
V. Ligand Field Molecular Mechanics 21
VI. LFMM Parameterization 23
VII. Simple Metal, Simple Ligand: Ga(III) Hydroxamates 24
VIII. Simple Metal, Complex Ligand: Mn(II) Carboxylates 26
IX. Difficult Metals: Jahn–Teller Effects in Cu(II) and the transInfluence in Pt(II) 29
X. Spin States 33
XI. Metalloproteins and Molecular Dynamics: Copper Proteins 35
XII. Bond Energies and Reaction Mechanisms: Water Exchange 41
XIII. Effects of M-L p Bonding 46
XIV. Conclusions 49
Summary 50
References 50
Calculation of Magnetic Circular Dichroism SpectraWith Time-Dependent Density Functional Theory 54
I. Introduction 54
II. Theory 60
III. Applications 87
IV. Concluding Remarks 113
List of Symbols 114
Acknowledgments 116
References 117
Theoretical Investigation of Solvent Effects and Complex Systems: Towardthe calculations of bioinorganic systems from ab initio molecular dynamicssimulations and static quantum chemistry 124
I. Introduction 124
II. AIMD Simulations 126
III. Static Quantum Chemical Calculations 146
IV. Conclusion 149
Acknowledgment 150
References 150
Simulations of Liquids and Solutions Basedon Quantum Mechanical Forces 156
I. Introduction 156
II. Methodology of the QMCF Approach 160
III. Applications of the QMCF MD Methodology 172
IV. Conclusions 185
Acknowledgment 185
References 186
Spin Interactions in Cluster Chemistry 190
I. Introduction 190
II. Theoretical Foundations 192
III. From Dirac–Breit to Breit–Pauli Hamiltonians 202
IV. Phenomenological Spin Hamiltonians 216
V. Concept of Local Electronic Spins 216
VI. Technical Issues: Optimization of Broken-Symmetry Determinants 226
VII. Studies on Open-Shell Polynuclear Transition-Metal Clusters 229
VIII. Conclusions 237
Acknowledgments 238
References 238
Inner- and Outer-Sphere Hydrogenation Mechanisms:A Computational Perspective 244
I. Introduction 244
II. Reaction Mechanisms for Hydrogenation Reactions:The Substrate Viewpoint 246
III. Computational Investigation of Hydrogenation Mechanisms 253
IV. Concluding Remarks 268
Acknowledgements 270
References 270
Computational Studies on Properties, Formation, and Complexationof M(II)-Porphyrins 274
I. Introduction 274
II. Models and Methods 277
III. Geometries and Electronic States of Metalloporphyrins 279
IV. Metalation of Porphyrins 282
V. Binding of Small Molecules 292
VI. Summary and Conclusions 305
Acknowledgements 306
References 306
Dealing with Complexity in Open-Shell Transition Metal Chemistryfrom a Theoretical Perspective: Reaction Pathways, Bonding,Spectroscopy, and Magnetic Properties 314
I. Introduction 314
II. Calculation of Reaction Pathways 316
III. EPR of Degenerate Systems 326
IV. Metal Radical Interactions 337
V. Magnetic Properties of Oligonuclear Clusters 346
VI. Concluding Remarks 357
References 358
Vibronic Coupling in Inorganic Systems: Photochemistry,Conical Intersections, and the Jahn–Teller andPseudo-Jahn–Teller Effects 364
I. Introduction 364
II. Theoretical and Computational Background 367
III. Important Computational Results in Inorganic Photochemistry 375
IV. Case Studies 378
V. Conclusions and Outlook 399
Acknowledgments 399
References 399
Elementary Reactions in Polynuclear Ionsand Aqueous–Mineral Interfaces: A New Geology 404
I. Molecular Geology 404
II. Modeling Tools for Geochemical Systems 406
III. Example Systems 415
IV. Geological Problems with Molecular Level Solutions 441
References 446
The Aromatic Amino Acid Hydroxylase Mechanism:A Perspective from Computational Chemistry 450
I. Introduction 450
II. Structural Information 462
III. The Cluster Model Approach to Quantum Chemical Studiesof Enzyme Reactions 465
IV. DFT Investigations of the AAH Mechanism 469
V. Conclusions 504
Acknowledgment 508
References 508
Index 514
Contents of Previous Volumes 528

Textauszug

Molecular Mechanics for Transition Metal Centers: From Coordination Complexes To Metalloproteins

Robert J. Deeth    Inorganic Computational Chemistry Group, Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom

Abstract

Computer modeling of transition metal centers presents many challenges. Whether in relatively small complexes or attached to large biomolecules, the electronic structure arising from the open-shell dn configuration can be complicated. Most workers therefore resort to quantum mechanical (QM) methods, notably density functional theory (DFT). However, many problems require large numbers of calculations: e.g., high-throughput screening, comprehensive conformational searching, and molecular dynamics. In these cases, all forms of QM, including DFT, are prohibitively expensive and impractical. In contrast, classical molecular mechanics (MM) is fast enough and has for many years been used for such large-scale computations. Unfortunately, while MM works well for “organic” systems, it is not well suited to TM systems since it misses many important d-electron effects which are implicit in QM methods. However, since we cannot make QM methods much faster, the only option is to make MM smarter. We have combined ligand field theory (LFT), in its angular overlap model (AOM) form, with “normal” MM to give ligand field molecular mechanics (LFMM). LFMM has a sophisticated AOM description of metal–ligand bonding which can be designed to emulate DFT. However, since LFT is empirical, LFMM is up to four orders of magnitude faster than DFT. Illustrative applications are presented which span the structural chemistry of Ga(III) and Mn(II) complexes, Jahn–Teller effects in Cu(II) and Fe(II) systems, the trans-influence in Pt(II) chemistry, spin-state changes in Ni(II) and Co(III) species, transition states for water exchange at first-row M(II) centers, through to 16 ns molecular dynamics simulations of copper proteins. Provided the necessary investment in parameter development is justifiable, LFMM provides DFT-like accuracy at a MM cost and represents a powerful, general tool for modeling TM centers in coordination complexes and metalloproteins.

Keywords

Ligand field theory

molecular mechanics

Jahn–Teller effect

spin states

copper enzymes

I Introduction

Transition metal (TM) systems present a fundamental dilemma for computational chemists. On the one hand, TM centers are often associated with relatively complicated electronic structures which appear to demand some form of quantum mechanical (QM) approach (1). On the other hand, all forms of QM are relatively compute intensive and are impractical for conformational searching, virtual high-throughput screening, or dynamics simulations since all these approaches may require many hundreds of thousands of individual calculations. Consequently, TM computational chemists tend to restrict themselves to smaller “model” systems with limited conformational freedom. This is particularly marked in bioinorganic chemistry where the calculation focuses on the “important” active site region but the bulk of the protein is not treated explicitly (2,3).

In contrast, those interested in purely “organic” systems have long enjoyed the advantages of “cheap,” classical molecular mechanics (MM) and molecular dynamics (MD) to study the entire molecular system including the surrounding solvent. However, conventional MM is not well suited to TM systems since it does not provide a general way of accounting for the important effects arising from the d electrons (4,5). In response, hybrid QM/MM methods have appeared (6). The metal center and its immediate environment is handled by a “high level” QM method, typically based on Density Functional Theory (DFT), with the rest of the system treated by MM. As the many technical difficulties of QM/MM have progressively been solved—most importantly how to couple the quantum region to the classical region—QM/MM has grown in popularity. However, the inclusion of any QM, even on a relatively small piece of the whole system, soon exacts a huge cost in execution time. Just a few minutes per calculation soon equates to years of CPU time. The only options are either to use thousands of computers or to develop a method which is as accurate as QM, but many orders of magnitude more efficient. We have taken the second path by augmenting MM with additional terms designed to provide a physically meaningful description of metal–ligand bonding and thus be able to emulate the behavior of more sophisticated, but expensive, QM methods. However, in order to put our model into perspective, we must first appreciate the nature of “conventional” MM and its shortcomings when applied to TM systems.

II Conventional Molecular Mechanics

Molecular mechanics in its simplest form expresses the total potential energy, Etot, as a sum of terms describing bond stretching, Estr, angle bending, Ebend, torsional twisting, Etor, and nonbonding interactions, Enb(1). The latter can include both van der Waals (vdW) interactions and, by assigning to each atom a partial atomic charge, electrostatics.

tot=∑Estr+∑Ebend+∑Etor+∑Enb

  (1)

Each term in (1) is represented by a simple mathematical expression as exemplified in (2), where the k are appropriate force constants, θ are bond angles, τ are torsion angles, n is the torsional periodicity parameter, ϕ is the torsion offset, ρ are partial atomic charge, ε is the dielectric constant, A and B are Lennard-Jones vdW parameters, and the summations run over bonded atom pairs (ij), angle triples (ijk) and torsional quadruples (ijkl). The nonbonded terms are summed over the distances, dij, between unique atom pairs excluding bonded pairs and the atoms at either end of an angle triple. For the atoms at the ends of a torsion quadruple, the nonbonded term may be omitted or scaled.

tot=∑i,jkij(rij−r0,ij)2+∑i,j,kkijk(θijk−θ0,ijk)2+∑i,j,k,lkijkl[1+cos(nijklτ−ϕijkl)]+[∑i<jρiρjεdij∑i<j(Aijdij12−Bijdij6)]

  (2)

These potential energy terms and their attendant empirical parameters define the force field (FF). More complicated FFs which use different and/or more complex functional forms are also possible. For example, the simple harmonic oscillator expression for bond stretching can be replaced by a Morse function, EMorse(3), or additional FF terms may be added such as the stretch-bend cross terms, Estb, (4) used in the Merck molecular force field (MMFF) (7–10) which may be useful for better describing vibrations and conformational energies.

Morse=D{1−ea(r−r0)}2−D

  (3)

stb=∑i,j,k{kijk(rij−r0,ij)+kkji(rjk−r0,jk)}θ0,ijk

  (4)

MM is a very successful model but it is clear from expressions such as (2) that the FF may comprise a very large number of parameters and since the quality of the FF will depend crucially on these parameters, developing a truly “universal” FF is an enormous (perhaps impossible) challenge (11). Consequently, FFs tend to be applicable to a specific class of molecular system such as small organic molecules (e.g., MMFF (7–10)), or large biomolecules like proteins and DNA (e.g., AMBER (12) or CHARMM (13)) for which the expressions in (2) are suited. Fortunately, these specific classes encompass an enormous amount of organic chemistry and biology plus the FFs are continually being revised to increase their applicability.

The computational efficiency of a FF approach also enables simulations of dynamical behavior—molecular dynamics (MD). In MD, the classical equations of motion for a system of N atoms are solved to generate a search in phase space, or trajectory, under specified thermodynamic conditions (e.g., constant temperature or constant pressure). The trajectory provides configurational and momentum information for each atom from which thermodynamic properties such as the free energy, or time-dependent properties such as diffusion coefficients, can be calculated.

MD introduces a time dependence but to avoid numerical instability, the time step δt needs to be quite small (∼1 fs) which places strong limitations on the total simulation time. Nevertheless, compared to QM-based schemes such as Carr-Parinello MD, classical MD is currently the only really viable method for computing the dynamical behavior of large systems like biomolecules for any appreciable length of...

Produkt-Details

• Erscheint lt. Verlag: 22.11.2010
• Sprache: englisch
• Themenwelt: Sachbuch/Ratgeber
• Themenwelt: Naturwissenschaften ► Chemie ► Anorganische Chemie
• Themenwelt: Naturwissenschaften ► Chemie ► Physikalische Chemie
• Themenwelt: Technik ► Maschinenbau
• ISBN-10: 0-12-380875-8 / 0123808758
• ISBN-13: 978-0-12-380875-2 / 9780123808752