Living organisms have a variety of macromolecules which play crucial role in the biological funtions. These are comprised of amino acids chains. The structure and folding patterns of amino acids decide the functions and features of proteins. The knowledge of the functions of proteins play important role in identifying their biological processes, disorders, therapeutics and medicine and accordingly the measures to prevent the biological disorders can be taken. In the process of achieving the goals, related to proteins and their processes the classification of proteins is vital. This research helps in demonstrating the relationship between protein sequences and its related classification type. The objective is achieved by applying 1D convolutional neural network model on a dataset comprising of more than 3 lakh tuples. The results of above method is compared using learning rate charts. In the current work, researchers have focused on understanding the structural protein sequences dataset accessed from Protein Data Bank database available at https://www.rcsb.org/ website of Research Collaboratory for structural bioinformatics. Also after the detailed analyses of protein dataset, the classification of proteins has been demonstrated using deep learning approaches(convolutional neural network model).