Conformational Monte Carlo method

A similar algorithm has been used to sample the equilibrium distribution [p,(r )] in the conformational optimization of a tetrapeptide[5] and atomic clusters at low temperature.[6] It was found that when g > 1 the search of conformational space was greatly enhanced over standard Metropolis Monte Carlo methods. In this form, the velocity distribution can be thought to be Maxwellian. 

RipoU D R and H A Scheraga 1988. On the Multiple-Mirumum Problem in the Conformational Anal of Polypeptides. II. An Electrostatistically Driven Monte Carlo Method Tests on Poly(L-Alani Biopolymers 27 1283-1303. 

Monte Carlo simulations are commonly used to compute the average thermodynamic properties of a molecule or a system of molecules, and have been employed extensively in the study of the structure and equilibrium properties of liquids and solutions. Monte Carlo methods have also been used to conduct conformational searches under non-equilibrium conditions. 

Monte Carlo search methods are stochastic techniques based on the use of random numbers and probability statistics to sample conformational space. The name Monte Carlo was originally coined by Metropolis and Ulam [4] during the Manhattan Project of World War II because of the similarity of this simulation technique to games of chance. Today a variety of Monte Carlo (MC) simulation methods are routinely used in diverse fields such as atmospheric studies, nuclear physics, traffic flow, and, of course, biochemistry and biophysics. In this section we focus on the application of the Monte Carlo method for... 

Recendy, Ronova and Pavlova54 suggested a set of relations between the conformational rigidity and some physical properties of the aromatic polymers. The conformational rigidity is correlated to the Kuhn statistical segment A calculated by die Monte Carlo method ... 

Monte Carlo computer simulations were also carried out on filled networks [50,61-63] in an attempt to obtain a better molecular interpretation of how such dispersed fillers reinforce elastomeric materials. The approach taken enabled estimation of the effect of the excluded volume of the filler particles on the network chains and on the elastic properties of the networks. In the first step, distribution functions for the end-to-end vectors of the chains were obtained by applying Monte Carlo methods to rotational isomeric state representations of the chains [64], Conformations of chains that overlapped with any filler particle during the simulation were rejected. The resulting perturbed distributions were then used in the three-chain elasticity model [16] to obtain the desired stress-strain isotherms in elongation. 

Higo, J. Nakajima, N. Shirai, H. Kidera, A. Nakamura, H., Two-component multicanonical Monte Carlo method for effective conformation sampling, J. Comput. Chem. 1997,18, 2086-2092... 

This criterion requires a search through a nonconvex multidimensional conformation space that contains an immense number of minima. Optimization techniques that have been applied to the problem include Monte Carlo methods, simulated annealing, genetic methods, and stochastic search, among others. For reviews of the application of various optimization methods refer to Pardalos et al. (1996), Vasquez et al. (1994), or Schlick et al. (1999). 

CONFORMATIONAL SAMPLING OF BIOMACROMOLECULES IN THE CANONICAL ENSEMBLE VIA MONTE CARLO METHODS... 

These two methods are different and are usually employed to calculate different properties. Molecular dynamics has a time-dependent component, and is better at calculating transport properties, such as viscosity, heat conductivity, and difftisivity. Monte Carlo methods do not contain information on kinetic energy. It is used more in the lattice model of polymers, protein stmcture conformation, and in the Gibbs ensemble for phase equilibrium. 

There are also hybrid methods which combine features from two or all three of the above. Opinions will freely be offered about which technique is best , but the reality is that different techniques will perform differently depending on the problem at hand. Except for very simple systems with only one or a few degrees of conformational freedom, systematic methods are not practical, and sampling techniques, which do not guarantee location of the lowest-energy structure (because they do not look everywhere), are the only viable alternative. By default, Spartan uses systematic searching for systems with only a few degrees of conformational freedom and Monte-Carlo methods for more complicated systems. 

Methods of Quantum Pharmacology for Conformational Analysis Monte Carlo Methods, Molecular Dynamics, Genetic Algorithms... 

Chang G, Guida WC, Still WC. An internal coordinate monte carlo method for searching conformational space. J Am Chem Soc 1989 111 4379-86. 

The Monte-Carlo method is utilized to investigate the conformational distribution in the central section of a PIB decamer at various temperatures. It is checked that a six-state RIS model based on the two matrices P and Pj constitutes a description of the conformational distribution in PIB. The Monte-Carlo results are in excellent agreement with the experimental data on the average dimensions of PIB chains, as well as with the molecular scattering functions of this polymer in solution and in bulk. 

N 051 "Conformational Statistics of Short Chains of Poly(L-alanfne) and Potygfycine Generated by Monte Carlo Method and the Partition Function of... 

Allowing for rotation about the Ca—C bond (/.e., variation of ijr) and for some degree of freedom about the peptide bond [i.e., small variation of ro), the characteristic ratios of the form / (crs) and form II [trans) poly(L-proline) chain are calculated by a Monte Carlo method in which the conformational energies are used as weighting factors. The Monte Carlo method enabled short-range interactions (beyond those involved in a single residue) to be taken into account. 

A conformational study of novel polyhydroxylated azepanes has been reported in which the 1H NMR spectroscopy and molecular modeling (molecular mechanics, molecular dynamics, and Monte Carlo methods) afforded insights into aspects of the conformational analysis <2004EJ04119>. 

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