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Accurately predicting protein structure properties is essential in analyzing the structure and function of a protein, such as secondary structure, solvent accessibility, and dihedral angles. Multiple Sequence Alignment (MSA), which is a sequence alignment of multiple homologous protein sequences for the target protein, is widely used in the protein structure property prediction. The most popular strategy to exploit MSA is converting it into a position-specific scoring matrice (PSSM), then inputs the PSSM to the relevant prediction networks. PSSM is obtained by simply counting the frequency of amino acids presented at each position in the corresponding MSA, which means, each sequence in the MSA has the same weight to the target protein. However, simply setting the weights of homologous protein sequences of a protein as same cannot sufficiently model the complex relationships between them. Moreover, some …