A hybrid global optimization algorithm for polypeptide structure determination

A new hybrid global optimization algorithm is proposed to search for the global optimum conformation of a given polypeptide amino acid sequences. Consider the limitation of Conformational Space Annealing (CSA) and Cutting Angle Method (CAM), we combine the two methods to enhance the strengths of each algorithm. Firstly, CAM is applied to the generation of 50 initial conformations, improving the diversity of the initial conformations for CSA. Then CSA takes over to acquire 50 biased sample points based on CAM, which contributes to the formation of some good modals. Subsequently, CAM is employed again to enhance the local exploitation ability, constructing underestimates close enough to the objective function in each modal. This hybrid algorithm can effectively reduce the times of function evaluation for original force field model. Finally, experiment results demonstrate that proposed algorithm can efficiently find the well-known lowest energy configuration of Met-enkephalin.