Humans life depends on the functionality of molecules in the body. One of these essential molecules is the protein that plays a vital role in our life, such that its malfunction can cause severe damages. Such roles make protein structure and its functionality necessary to understand. One of the problems that help us understand the relation between protein structure is the well-known protein design problem which attempts to find an amino acid sequence that can fold into a desired tertiary

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... re. However, despite having an acceptable accuracy in protein design, this accuracy is an identical percentage of amino acid retrieving. At the same time, it is well-known that amino acids can replace each other in evolution while the function and structure of protein stay the same. Thus the designed sequence does not have the opportunity to be close to the target in the evolutionary aspect. This paper presents an extension to Wang's deep learning model, which uses evolutionary information in the Blosum62 substitution matrix to take amino acid replacement probability into account while designing a sequence.