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Many problems arise in computational biology can be reduced to theminimization of energy function, that determines on the geometry of consideredmolecule. The solution of this problem allows in particular to solve foldingand docking problems in structural biology. For the small molecules thisproblem is well solved. But for the large molecules ($10^4$ atoms and more)this is still an open problem. In this work we consider energy minimizationproblem (OPLS force field) for the large molecules but with good enough initial(starting) point. In the paper one can find a biological explanation of thisassumption. Due to this assumption we reduce the global optimization problem tothe local one. We compare different methods: gradient-free methods, gradienttype methods (gradient method, fast gradient method, conjugate gradients (CG),LBFGS), high-order (tensor) methods. We observe that the most convenient onesin GPU realization are fast gradient descent with special line-search and CG(Polak--Ribiere--Polyak), LBFGS (memory = 3 iteration). Finally, we demonstratehow all these method work on real data set provided by BIOCAD.

Algorithms for local optimization of OPLS energy for large protein structures