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A protein is a linear chain containing a set of amino acids, which folds onitself to create a specific native structure, also called the minimum energyconformation. It is the native structure that determines the functionality ofeach protein. The protein folding problem (PFP) remains one of the moredifficult problems in computational and chemical biology. The principalchallenge of PFP is to predict the optimal conformation of a given protein byconsidering only its amino acid sequence. As the conformational space containsa very large number of conformations, even when addressing short sequences,different simplified models have been developed and applied to make the PFPless complex. In the last few years, many computational approaches have beenproposed to solve the PFP. They are based on simplified lattice models such asthe hydrophobic-polar model. In this paper, we present a new Hybrid CuckooSearch Algorithm (HCSA) to solve the 3D-HP protein folding optimizationproblem. Our proposed algorithm consists of combining the Cuckoo SearchAlgorithm (CSA) with the Hill Climbing (HC) algorithm. Simulation results ondifferent benchmark sequences are presented and compared to thestate-of-the-art algorithms.

Protein folding simulations in the hydrophobic-polar model using a hybrid cuckoo search algorithm