Conformation sampling genetic algorithms

A molecular dynamics simulation samples the phase space of a molecule (defined by the position of the atoms and their velocities) by integrating Newton s equations of motion. Because MD accounts for thermal motion, the molecules simulated may possess enough thermal energy to overcome potential barriers, which makes the technique suitable in principle for conformational analysis of especially large molecules. In the case of small molecules, other techniques such as systematic, random. Genetic Algorithm-based, or Monte Carlo searches may be better suited for effectively sampling conformational space. 

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

The literature is full of examples of many types of conformational sampling algorithms [17-20]. Some of the principal ones are the model building approach [21], genetic algorithms [22, 23], the Monte Carlo (MC) [24] and simulated annealing [25] protocols. 

Fig. 3 An illustration of the genetic algorithm approach, where the states of the ligand (translation, orientation, and conformation relative to the protein) are interpreted as the ligand genotype and the atomic coordinates represent the phenotype. A plot of the change in the fitness function (f(x)) as the ligand population is allowed to mutate, crossover, and migrate. The genetic evolution of the ligand effectively samples conformational space where the best conformer is identified by a minimum in the fitness function (Reprinted with permission from [179], copyright 1998 by John Wiley and Sons)...

C. S. Ring and F. E. Cohen, Isr.J. Chem., 34,245 (1994). Conformational Sampling of Loop Structures Using Genetic Algorithms. 

In the past, different methods of sampling of protein model conformational space have been employed with various degrees of success. Traditional molecular dynamics can be used only in the case of continuous models. Other sampling schemes, including a variety of Monte Carlo methods, genetic algorithms, and combinations of these methods, could be applied to continuous as well as to the discrete (including lattice representation) models. 

Simulated annealing, ESMC [108,109,161], Monte Carlo with minimization [162], genetic algorithms [64,163-165], and the combination of genetic algorithms with Monte Carlo sampling have been successfully used in the past to find the near-native conformations of reduced models of small proteins [68]. 

Yang YD, Liu HY (2006) Genetic algorithms for protein conformation sampling and optimization in a discrete backbone dihedral angle space. J Comput Chem 27 1593-1602... 

Other methods selectively sample the orientational and conformational space using efficient search engines. For example, the Metropolis algorithm or simulated annealing is used in AutoDock and the genetic algorithm in the... 

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