Analysis and comparison of alkaline and acid phosphatases of Gram-negative bacteria by bioinformatic and colorimetric methods

Alkaline phosphatase (ALP) and acid phosphatase (ACP) are two important phosphatase enzymes that play fundamental roles in Gram-negative bacteria. Additionally, they are useful for various biotechnological and industrial applications. In the present study, different aspects of bacterial ALPs and ACPs such as pseudo amino acid composition (PseAAC), amino acid composition, dipeptide composition, physicochemical properties, secondary structures and structural motifs were studied. The binding affinity of the phosphomonoesters to ALP and ACP enzymes was predicted by docking, and the activity of ALPs and ACPs were measured using colorimetric assay. ROC curve statistical analysis the machine learning algorithms were applied for classification of these two phosphatase protein groups. The results indicated that the physicochemical properties of ALPs and ACPs were not significantly different, although the aliphatic index and Extinction coefficient of motifs of these two enzymes were significantly different. Classification based on the concept of PseAAC and dipeptide composition also indicated high accuracy. The result of docking demonstrated that the binding free energy of ALPs was less than ACPs and the experimental results demonstrated that the activity of ACPs was more than ALPs. In conclusion, there is a relationship between efficiency and PseAAC and dipeptide compositions of these two enzymes.