GCPred: a web tool for guanylyl cyclase functional centre prediction from amino acid sequence

Area of Science:

• Biochemistry
• Bioinformatics
• Enzymology

Background:

• Guanylyl cyclases (GCs) are enzymes crucial for synthesizing cyclic guanosine 3', 5'-monophosphate.
• A novel class of GC centers (GCCs) has been identified in complex plant proteins.

Purpose of the Study:

• To develop GCPred, a webserver for automated prediction of guanylyl cyclase functional centers (GCCs) from amino acid sequences.
• To facilitate the identification of novel GCCs by analyzing physicochemical and conserved amino acid properties.

Main Methods:

• GCPred utilizes physicochemical properties of amino acids within potential GCCs.
• Conserved amino acids within the potential GCC are also considered in the prediction algorithm.
• The server processes user-submitted amino acid sequences to predict GCC values.

Main Results:

• GCPred provides a table of predicted GCC values.
• Graphical representations of deviations from mean GCC values are generated.
• The utility of GCPred was demonstrated on plant proteins and human interleukin-1 receptor-associated kinase family proteins.

Conclusions:

• GCPred is an effective tool for predicting guanylyl cyclase functional centers.
• The server aids researchers in identifying novel GCCs across different protein families.
• GCPred facilitates the study of guanylyl cyclase function and evolution.