The amino acids consist of vast range of uncertain protein sequences which are key elements for structural analysis of the cell function. This paper has proposed an ANN (Artificial Neural Network) incorporated through GA (Genetic Algorithm) for classification of protein sequences. The proposed ANN incorporated through GA(ANN-GA) utilized flower pollination algorithm (FPA) for identification of optimal points in the code of a protein data pattern. Components Essential Amino Acids composite consist of structural and solvent factors. Through formulation of objective function structural composites of protein sequences for classification. The developed ANN-GA estimates the sequence of protein fold prediction within the collected dataset. The dimensional analysis of data expressed that set of protein classification incorporates distinct structural folds and information. The ANN-GA performance is evaluated by means of accuracy of classification for recognized structural characteristics of protein sequences. The simulation analysis expressed that developed ANN-GA exhibits improved performance compared to the conventional techniques.