GCPred

GCPred predicts guanylyl cyclase (GC) functional centres from amino acid sequences to identify catalytic motifs that synthesize cyclic guanosine 3',5'-monophosphate from guanosine-5'-triphosphate and to facilitate discovery of novel GC centres (GCCs) in complex proteins.

Key Features:

• Automated prediction: Identifies guanylyl cyclase functional centres (GCCs) from amino acid sequences by leveraging existing experimental data.
• Physicochemical modeling: Incorporates physicochemical properties of amino acids that constitute the GCC and analyzes conserved residues within the centre.
• Quantitative outputs: Produces tables of GCC values and graphical representations of deviations from mean values for analytical interpretation.
• Demonstrated on diverse proteins: Applied to plant proteins and the human interleukin-1 receptor-associated kinase family to illustrate utility across biological contexts.

Scientific Applications:

• GCC discovery in plants: Identification and characterization of novel GC centres in complex plant proteins to support plant signaling research.
• Human protein analysis: Assessment of potential GC activity within the human interleukin-1 receptor-associated kinase family to explore roles in cellular signaling.
• Molecular mechanism studies: Support for investigations into molecular mechanisms underlying GC activity and cGMP-mediated signaling pathways.

Methodology:

Computational identification of GC functional centres from amino acid sequences using a predictive model that incorporates physicochemical amino acid properties, conserved-residue analysis, and existing experimental data.