Simulated annealing and Monte Carlo

A. Nayeem, J. Vila, and H. A. Scheraga. A comparative study of the simulated-annealing and monte carlo-with-minimization approaches to the minimum-energy structures of polypeptides [met]-enkephalin. J. Comp. Chem., 12(5) 594-605, 1991. 

Other methods which are applied to conformational analysis and to generating multiple conformations and which can be regarded as random or stochastic techniques, since they explore the conformational space in a non-deterministic fashion, arc genetic algorithms (GA) [137, 1381 simulation methods, such as molecular dynamics (MD) and Monte Carlo (MC) simulations 1139], as well as simulated annealing [140], All of those approaches and their application to generate ensembles of conformations arc discussed in Chapter II, Section 7.2 in the Handbook. 

Tidor B (1993) Simulated annealing on free energy surfaces by a combined molecular dynamics and monte carlo approach, J Phys Chem, 97 1069-1073... 

Powder diffraction techniques have become increasingly useful as tools for crystal structure determination especially in cases where it is sometimes difficult to get a single crystal of sufficient size and quality for traditional single-crystal studies. The solution of a structure can be considered as a three-step process (i) data collection and indexing, (ii) data preparation and Pawley refinement, and (iii) Monte Carlo simulated annealing and rigid-body Rietveld refinement. 

Molecular dynamics can be coupled to a heat bath (see below) so that the resulting ensemble asymptotically approaches that generated by the Metropolis Monte Carlo acceptance criterion (Eq. 10). Thus, molecular dynamics and Monte Carlo are in principle equivalent for the purpose of simulated annealing although in practice one implementation may be more efficient than the other. Recent comparative work (Adams, Rice, Brunger, in preparation) has shown the molecular dynamics implementation of crystallographic refinement by simulated annealing to be more efficient than the Monte Carlo one. 

Configurationally biased Monte Carlo techniques [63-65] have made it possible to compute adsorption isotherms for linear and branched hydrocarbons in the micropores of a siliceous zeolite framework. Apart from Monte Carlo techniques, docking techniques [69] have also been implemented in some available computer codes. Docking techniques are convenient techniques that determine, by simulated annealing and subsequent freezing techniques, local energy minima of adsorbed molecules based on Lennard-Jones-or Buckingham-type interaction potentials. 

Simulation is the modelling of a system with its dynamic processes to gain knowledge, which can be transferred into reality. The most important simulation methods in the field of conformational analysis are molecular dynamics (MD) and Monte Carlo simulations, as well as simulated annealing [56,57], All these approaches are based on extensive numerical calculations and transformations. Therefore, only a brief introduction to these methods and their application to conformational searches is given in the following. 

Day PN, Pachter R, Gordon MS, Merrill GN. A study of water clusters using the effective fragment potential and Monte Carlo simulated annealing. J Chem Phys 2000 112 2063-2073. 

Day, P. N., Pachter, R., Gordon, M. S., Merrill, G. N. (2000). A Study of Water Clusters Using the Effective Fragment Potential and Monte Carlo Simulated Annealing,/ Chem. Phys., 112,2063-2073. 

Higher-dimensional problems, such as G > 2 or very flexible molecules, might require more efficient algorithms to provide complete sets of structures in a reasonable time. More sophisticated approaches that have been implemented include genetic algorithms,Monte Carlo simulated annealing and conformation-family Monte Carlo. These... 

Okamoto, Y. Tackling the multiple-minima problem in protein folding by Monte Carlo simulated annealing and generalized-ensemble algorithms. Int. J. Mod. Phys. C 1999, 10 (8), 1571-1582. 

H. Meirovitch and M. Vasquez, Efficiency of simulated annealing and the monte carlo minimization method for generating a set of low energy structures of peptides. J. MoL Struct. (Theochem.) 398-399, 517-522 (1997). 

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