Computational chemistry molecular simulations

Interestingly, in the experiments devoted solely to computational chemistry, molecular dynamics calculations had the highest representation (96-98). The method was used in simulations of simple liquids, (96), in simulations of chemical reactions (97), and in studies of molecular clusters (98). One experiment was devoted to the use of Monte Carlo methods to distinguish between first and second-order kinetic rate laws (99). One experiment used DFT theory to study two isomerization reactions (100). 

The protein folding problem - the ability to predict a protein fold from its sequence - is one of the major prizes in computational chemistry. Molecular dynamics simulations of solvated proteins is currently not a feasible approach to this problem. However, Duan and Kollman have shown that a 1 ps simulation on a small hydrated protein, here the 36 residue villin headpiece, is now possible using a massively parallel super computer.33 The native protein is estimated to fold in about 10-100 ps and so the simulation can only be used to study the early stages of protein folding. Nevertheless, starting from an extended structure the authors were able to observe hydrophobic collapse and secondary structure formation (helix 2 was well formed, helices 1 and 3 were partially formed and the loop connecting helices 1 and 2 was also partially... 

In computational chemistry, molecular dynamics (MD) is the most widely used methodology to study the kinetic and thermodynamic properties of atomic and molecular systems [1-3]. These properties are obtained by solving the microscopic equations of motion for the system under consideration. Due to the short time step that is needed to keep numerical stability, the time scales that can be reached in these simulations are not long, typically on the order of nanosecond to microsecond depending on the complexity of the system. For many systems, like biomolecules, this simulation time is not enough to sample conformational space or to study rare but important events. 

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. 

There is a lot of confusion over the meaning of the terms theoretical chemistry, computational chemistry and molecular modelling. Indeed, many practitioners use all three labels to describe aspects of their research, as the occasion demands "Theoretical chemistry is often considered synonymous with quantum mechanics, whereas computational chemistry encompasses not only quantum mechanics but also molecular mechaiucs, minimisation, simulations, conformational analysis and other computer-based methods for understanding and predicting the behaviour of molecular systems. Molecular modellers use all of these methods and so we shall not concern ourselves with semantics but rather shall consider any theoretical or computational tecluiique that provides insight into the behaviour of molecular systems to be an example of molecular modelling. If a distinction has to be... 

Kurst G R, R A Stephens and R W Phippen 1990. Computer Simulation Studies of Anisotropic iystems XIX. Mesophases Formed by the Gay-Berne Model Mesogen. Liquid Crystals 8 451-464. e F J, F Has and M Orozco 1990. Comparative Study of the Molecular Electrostatic Potential Ibtained from Different Wavefunctions - Reliability of the Semi-Empirical MNDO Wavefunction. oumal of Computational Chemistry 11 416-430. 

Dauber-Osguthorpe P and D J Osguthorpe 1993. Partitioning the Motion in Molecular Dynamii Simulations into Characteristic Modes of Motion. Journal of Computational Chemistry 14 1259-127... 

Straatsma T P 1996. Free Energy by Molecular Simulation. In Lipkowitz K B and D B Boyd (Edito Reviews in Computational Chemistry Volume 9. New York, VCH Publishers, pp. 81-127. 

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. 

Singh U C and P A Kollman 1986. A Combined Ab Initio Quantum Mechanical and Molecule Mechanical Method for Carrying out Simulations on Complex Molecular Systems Applicatior to the CHsQ + Cr Exchange Reaction and Gas Phase Protonation of Polyethers. Journal Computational Chemistry 7 718-730. 

However, theories that are based on a basis set expansion do have a serious limitation with respect to the number of electrons. Even if one considers the rapid development of computer technology, it will be virtually impossible to treat by the MO method a small system of a size typical of classical molecular simulation, say 1000 water molecules. A logical solution to such a problem would be to employ a hybrid approach in which a chemical species of interest is handled by quantum chemistry while the solvent is treated classically. 

Contemporary s Tithetic chemists know detailed information about molecular structures and use sophisticated computer programs to simulate a s Tithesis before trying it in the laboratory. Nevertheless, designing a chemical synthesis requires creativity and a thorough understanding of molecular structure and reactivity. No matter how complex, every chemical synthesis is built on the principles and concepts of general chemistry. One such principle is that quantitative relationships connect the amounts of materials consumed and the amounts of products formed in a chemical reaction. We can use these relationships to calculate the amounts of materials needed to make a desired amount of product and to analyze the efficiency of a chemical synthesis. The quantitative description of chemical reactions is the focus of Chapter 4. 

Khandogin J, Brooks CL III (2007) Annual report of computational chemistry, volume 3, chapter Molecular Simulations of pH-Mediated Biological Processes, Elsevier, Amsterdam, pp 3-11. 

When addressing problems in computational chemistry, the choice of computational scheme depends on the applicability of the method (i.e. the types of atoms and/or molecules, and the type of property, that can be treated satisfactorily) and the size of the system to be investigated. In biochemical applications the method of choice - if we are interested in the dynamics and effects of temperature on an entire protein with, say, 10,000 atoms - will be to run a classical molecular dynamics (MD) simulation. The key problem then becomes that of choosing a relevant force field in which the different atomic interactions are described. If, on the other hand, we are interested in electronic and/or spectroscopic properties or explicit bond breaking and bond formation in an enzymatic active site, we must resort to a quantum chemical methodology in which electrons are treated explicitly. These phenomena are usually highly localized, and thus only involve a small number of chemical groups compared with the complete macromolecule. 

T. P. Straatsma, Free Energy by Molecular Simulation, in Reviews in Computational Chemistry, Vol. 9, K. B. Lipkowitz and D. B. Boyd, eds., VCH Publishers, New York, 1996, p. 81 H. Meirovitch, Calculation of the free energy and the entropy of macromol-ecular systems by computer simulation. Rev. in Computational Chem. 13, 1 (1998). 

Onufriev, A. Implicit solvent models in molecular dynamics simulations a brief overview. In Annual Reports in Computational Chemistry (eds R.A. Wheeler and D.C. Spellmeyer), Vol. 4, Elsevier, Amsterdam, 2008, pp. 125-37. 

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