Conformational sampling

Bruccoleri R E and M Karplus 1987. Prediction of the Folding of Short Polypeptide Segments by Uniform Conformational Sampling. Biopolymers 26 137-168. 

Another approach is to run multiple MD simulations with different initial conditions. The recent work by Karplus and coworkers [19] observes that multiple trajectories with different initial conditions improve conformational sampling of proteins. They suggest that multiple trajectories should be used rather than a single long trajectory. 

A successful application of GA to conformation sampling is, for example, as a part of flexible docking [12-14], It should be noted, however, that none of the three sampling methods discussed above, MD, MC, and GA, was shown to outperform the other two in any general way. In fact, a comparison of the three methods in the context of flexible docking showed similar efficiency for all three [12], although specific advantages are likely to exist for particular apphcations. 

Principal component analysis (PCA) takes the m-coordinate vectors q associated with the conformation sample and calculates the square m X m matrix, reflecting the relationships between the coordinates. This matrix, also known as the covariance matrix C, is defined as... 

RE Bruccoleri, M Karplus. Conformational sampling using high-temperature molecular dynamics. Biopolymers 29 1847-1862, 1990. 

R Bruccoleri, M Karplus. Prediction of the folding of short polypeptide segments by uniform conformational sampling. Biopolymers 26 137-168, 1987. 

CS Ring, FE Cohen. Conformational sampling of loop structures using genetic algorithm. Isr I Chem 34 245-252, 1994. 

The systematic, or grid, search is only possible for small molecules. For larger systems tlrere are methods which can be used for perturbing a geometry from a local minimum to another minimum. Some commonly used methods for conformational sampling are ... 

W. L. Jorgensen and J. Tirado-Rives, Monte Carlo vs molecular dynamics for conformational sampling. J. Phys. Chem., 100, 1996, 14508-14513. 

In recent years, density-functional theory has emerged as the computational quantum chemistry method of choice for biological problems of medium size range (up to a few hundreds of atoms) in applications that do not require extensive conformational sampling. The field continues to advance in the accuracy of new functionals, the improvement of algorithms and the functionality and computational performance of software [81]. 

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