Abstract
In the dynamite field of biological and protein research, the protein fold recognition for long pattern
protein sequences is a great confrontation for many years. With that consideration, this paper contributes
to the protein folding research field and presents a novel procedure for mapping appropriate protein
structure to its correct 2D fold by a concrete model using swarm intelligence. Moreover, the model
incorporates Extended Genetic Algorithm (EGA) with concealed Markov model (CMM) for effectively
folding the protein sequences that are having long chain lengths. The protein sequences are preprocessed,
classified and then, analyzed with some parameters (criterion) such as fitness, similarity and sequence gaps
for optimal formation of protein structures. Fitness correlation is evaluated for the determination of
bonding strength of molecules, thereby involves in efficient fold recognition task. Experimental results have
shown that the proposed method is more adept in 2D protein folding and outperforms the existing
algorithms.
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