The identification of metal ion binding sites is important for protein function annotation and the design of new drug molecules. This study presents an effective method of analyzing and identifying the binding residues of metal ions based solely on sequence information. , and Co 2+ were sensitive to the conservation of amino acids at binding sites, and promising results can be achieved using the Position Weight Scoring Matrix algorithm, with an accuracy of over 79.9% and a Matthews correlation coefficient of over 0.6. The binding sites of other metals can also be accurately identified using the Support Vector Machine algorithm with multifeature parameters as input. In addition, we found that Ca 2+ was insensitive to hydrophobicity and hydrophilicity information and Mn 2+ was insensitive to polarization charge information. An online server was constructed based on the framework of the proposed method and is freely available at
Cao et al. REF utilized the position-weighted scoring matrix (PWSM) and SVM algorithm for the identification of metal-ion-binding sites with an accuracy of 79.9% and an MCC of 0.6.
Identification of metal ion binding sites based on amino acid sequences
PLoS ONE
PLoS ONE
Chemistry Medicine