Catalytic residues play a significant role in enzyme functions. With the recent accumulation
of experimentally determined enzyme 3D structures and network theory on protein structures, the prediction
of catalytic residues by amino acid network (AAN, where nodes are residues and links are residue
interactions) has gained much interest. Computational methods of identifying catalytic residues are
traditionally divided into two groups: sequence-based and structure-based methods. Two new structure-
based methods are proposed in current advances: AAN and Elastic Network Model (ENM) of enzyme
structures. By concentrating on AAN-based approach, we herein summarized network properties
for predictions of catalytic residues. AAN attributes were showed responsible for performance improvement,
and therefore the combination of AAN with previous sequence and structural information will be a promising
direction for further improvement. Advantages and limitations of AAN-based methods, future perspectives on the application
of AAN to the study of protein structure-function relationships are discussed.
Keywords: Amino acid network, prediction of catalytic residues, protein residue contact map, protein structure network, structure
and function relationship.
Rights & PermissionsPrintExport