ABSTRACT
Michael Gaus, Puja Goyal, Guanhua Hou, Xiya Lu, Xueqin Pang, Jan Zienau, Xin Xu, Marcus Elstner, and Qiang Cui
2.1 Introduction 34 2.2 Basic Methodologies: Classical (MM) and Hybrid (QM/MM) Models 35
2.2.1 MM Models 35 2.2.2 QM/MM Models 37
2.2.2.1 QM Methods: Ab Initio vs. Approximate Approaches 37 2.2.2.2 QM/MM Interface and Boundary Conditions 42
2.3 Illustrative Examples: Value and Limitations of Computational Models 49 2.3.1 MM Model: Substrate Selectivity of AlkB Enzymes 49
2.3.1.1 General Background 49 2.3.1.2 Structural Features of AlkB-dsDNA Complexes 51 2.3.1.3 Energetic Features 54
2.3.2 SCC-DFTB/MM for Metalloenzymes: Catalytic Promiscuity of Enzymes in the AP Superfamily 55 2.3.2.1 General Background 55 2.3.2.2 Diester Substrates 56 2.3.2.3 Monoester Substrates 60
2.3.3 DFTB3/MM for Open-Shell Systems: A Preliminary Study of Redox Potential in Blue Copper Proteins 62
Transition metal ions play essential structural and catalytic roles in metalloenzymes.1,2 For example, a recent survey2 indicated that, among 1371 dierent enzymes for which 3D structures are available, ~47% contain metal ions with 41% hosting metals at the catalytic site. Since many transition metal ions are redox active, most transition metal enzymes catalyze complex chemical transformations that require mechanisms beyond relatively simple general acid/base pathways and involve unusual chemical intermediates; although the nature of these intermediates can often be probed with various spectroscopic techniques, the interpretation of the data at a molecular scale is often not straightforward.3,4 Moreover, although many mechanistic studies focus on the coordination chemistry of metal ions, the importance of second-sphere eects and other long-range (allosteric) contributions has been increasingly recognized5,6; the relative contributions of various factors, however, are often dicult to untangle. To eectively complement experimental investigations in tackling these mechanistic issues, it is essential to develop quantitative computational approaches for structural, reactive (energetic), and spectroscopic properties of metalloenzymes.
