Protein Folding and Optimization Algorithms

In the literature, some computer models describing the evolution of copolymer sequences have been proposed [26,28]. Most of them are based on a stochastic Monte Carlo optimization principle (Metropolis scheme) and aimed at the problems of protein physics. Such optimization algorithms start with arbitrary sequences and proceed by making random substitutions biased to minimize relative potential energy of the initial sequence and/or to maximize the folding rate of the target structure. 

The computational requirement of the aBB algorithm depends on the number of variables on which branching occurs. The most important variables are those variables that substantially influence the nonconvexity of the surface and the location of the global minimum. In the protein-folding problem, the backbone dihedral angles ( and ip) are the most influential variables. Therefore, in very large problems, to further reduce the dimensions of the problem, only these variables were involved in the optimization. 

D. B. Gordon, S. L. Mayo. Branch-and-terminate a combinatorial optimization algorithm for protein design. Structure Fold Des. 1999, 7, 1089-1098. 

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