Molecular dynamics computational chemistry

Abstract You can calculate molecular geometries, rates and equilibria, spectra, and other physical properties. The tools of computational chemistry are molecular mechanics, ab initio, semiempirical and density functional methods, and molecular dynamics. Computational chemistry is widely used in the pharmaceutical industry to explore the interactions of potential drugs with biomolecules, for example by docking a candidate drug into the active site of an enzyme. It is also used to investigate the properties of solids (e.g. plastics) in materials science. It does not replace experiment, which remains the final arbiter of truth about Nature. 

Central to the understanding of surface-related phenomena has been the study of gas-surface reactions. A comprehensive understanding of these reactions has proven challenging because of the intrinsic many-body nature of surface dynamics. In terms of theoretical methods, this complexity often forces us either to treat complex realistic systems using approximate approaches, or to treat simple systems with realistic approaches. When one is interested in studying processes of technological importance, the latter route is often the most fruitful. One theoretical technique which embodies the many-body aspect of the dynamics of surface chemistry (albeit in a very approximate manner) is molecular dynamics computer simulation. 

D. L. Thompson, Ed., Modern Methods for Multidimensional Molecular Dynamics Computations in Chemistry, World Scientific Pub., New Jersey, 1998. 

One of the fundamental problems in chemistry is understanding at the molecular level the effect of the medium on the rate and the equilibrium of chemical reactions which occur in bulk liquids and at surfaces. Recent advances in experimental techniques[l], such as frequency and time-resolved spectroscopy, and in theoretical methods[2,3], such as statistical mechanics of the liquid state and computer simulations, have contributed significantly to our understanding of chemical reactivity in bulk liquids[4] and at solid interfaces. These techniques are also beginning to be applied to the study of equilibrium and dynamics at liquid interfaces[5]. The purpose of this chapter is to review the progress in the application of molecular dynamics computer simulations to understanding chemical reactions at the interface between two immiscible liquids and at the liquid/vapor interface. 

Modeling of the gas phase chemistry and particle growth shows that homogeneous nucleation occurs early on in the process followed by heterogeneous condensation processes. Molecular dynamics computation have indicated that the iron oxide clusters will phase segregate and migrate toward the inside edge of the silica cluster consistent with experimental observation. 

We do not view the terms theoretical chemistry and computational chemistry as synonymous. Computational chemistry sometimes involves application of computerized algorithms from quantum theory, but computational chemistry is certainly more than quantum chemistry. In fact, in an industrial setting, the latter is a very small part of it. Molecular mechanics, molecular dynamics, computer graphics, molecular modeling, and computer-assisted molecular design are other important aspects of computational chemistry. In industry, a... 

Progress in the theoretical description of reaction rates in solution of course correlates strongly with that in other theoretical disciplines, in particular those which have profited most from the enonnous advances in computing power such as quantum chemistry and equilibrium as well as non-equilibrium statistical mechanics of liquid solutions where Monte Carlo and molecular dynamics simulations in many cases have taken on the traditional role of experunents, as they allow the detailed investigation of the influence of intra- and intemiolecular potential parameters on the microscopic dynamics not accessible to measurements in the laboratory. No attempt, however, will be made here to address these areas in more than a cursory way, and the interested reader is referred to the corresponding chapters of the encyclopedia. 

The visualization of volumetric properties is more important in other scientific disciplines (e.g., computer tomography in medicine, or convection streams in geology). However, there are also some applications in chemistry (Figure 2-125d), among which only the distribution of water density in molecular dynamics simulations will be mentioned here. Computer visualization of this property is usually realized with two or three dimensional textures [203]. 

T.P. Lybrand, Computer simulations of biomolecular systems using molecular dynamics and free energy perturbation methods, in Reviews in Computational Chemistry, Vol. 1, K.B. Lipkowitz, D.B. Boyd (Eds.), VCH, New York, 1990, pp. 295-320. 

L. Pedersen, T. Darden, Molecular dynamics techniques and applications to proteins, in The Encyclopedia of Computational Chemistry, Vbl. 3,... 

Gunsteren W F and H J C Berendsen 1990. Computer Simulation of Molecular Dynamics Methodology, Applications and Perspectives in Chemistry. Angewandte Chemie International Edition in English 29 992-1023. 

Leach A R and T E Klein 1995. A Molecular Dynamics Study of the Inhibitors of Dihydrofola Reductase by a Phenyl Triazine. Journal of Computational Chemistry 16 1378-1393. 

Field M J, P A Bash and M Karplus 1990. A Combined Quantum Mechanical and Molecular Mechanical Potential for Molecular Dynamics Simulations. Journal of Computational Chemistry 11 700-733. 

See van Gunsteren, W.F. Berendsen, H.J.C. Computer simulation of molecular dynamics-methodology, applications, and perspectives in chemistry Angewandre Chemie, International Edition in English, 29 992-1023, 1990, and Karplus, M. Petsko, G.A. Molecular dynamics simulations in biology Nature 347 631-639, 1990. 

Chemistry, like other sciences, progresses through the use of models. Models are the means by which we attempt to understand nature. In this book, we are primarily concerned with models of complex systems, those systems whose behaviors result from the many interactions of a large number of ingredients. In this context, two powerful approaches have been developed in recent years for chemical investigations molecular dynamics and Monte Carlo calculations [4-7]. Both techniques have been made possible by the development of extremely powerful, modern, high-speed computers. 

In this brief review we illustrated on selected examples how combinatorial computational chemistry based on first principles quantum theory has made tremendous impact on the development of a variety of new materials including catalysts, semiconductors, ceramics, polymers, functional materials, etc. Since the advent of modem computing resources, first principles calculations were employed to clarify the properties of homogeneous catalysts, bulk solids and surfaces, molecular, cluster or periodic models of active sites. Via dynamic mutual interplay between theory and advanced applications both areas profit and develop towards industrial innovations. Thus combinatorial chemistry and modem technology are inevitably intercoimected in the new era opened by entering 21 century and new millennium. 

Equation (4-5) can be directly utilized in statistical mechanical Monte Carlo and molecular dynamics simulations by choosing an appropriate QM model, balancing computational efficiency and accuracy, and MM force fields for biomacromolecules and the solvent water. Our group has extensively explored various QM/MM methods using different quantum models, ranging from semiempirical methods to ab initio molecular orbital and valence bond theories to density functional theory, applied to a wide range of applications in chemistry and biology. Some of these studies have been discussed before and they are not emphasized in this article. We focus on developments that have not been often discussed. 

Marx, D., Hutter, J., Ab initio molecular dynamics theory and implementation. In Modern Methods and Algorithms of Quantum Chemistry, Grotendorst, J., Ed. John von Neumann Institute for Computing Jttlich, NIC Series, 2000, pp. 301 149... 

The Car-Parrinello approach combines an electronic structure method with a classical molecular dynamics scheme and thus unifies two major fields of computational chemistry, which have hitherto been essentially orthogonal. Through this unification a... 

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