Spacers and Mismatches-Based Algorithm (SMA): G Domain Prediction and Application in Human Biology and Human Health

Guanine nucleotide-binding proteins (G proteins) are seen to play an important role in cellular processes such as sensual and visual perception, protein synthesis, vesicular transport, cell growth and differentiation to name a few. The ability of G proteins to function as molecular switches that cycle between a GTP bound (Active) and GDP bound (Inactive) states mediates their cellular functions. A structurally and mechanistically conserved GTP-binding domain (G domain) allows GTP binding to G proteins. The G domain comprises five adjacent consensus motifs called G boxes, which are separated by amino acid spacers of different lengths. Mutations in the G domain coding region of G proteins lead to heritable disorders. Changes in expression of G proteins lead to physiological or neurodegenerative disorders and their treatment. Accurate determination of the G domain sequence in G proteins is of utmost importance for their use in the identification of diseasecausing mutations, identification of mechanism of disorders and exploring their use as therapeutic proteins. In the current study, we introduce a Spacers and Mismatch Algorithm (SMA) which can predict G domains in a given protein sequence, based on user-specified constraints. SMA can be implemented via a web-based server at https://labs.iitgn.ac.in/datascience/gboxes/.