Spacers and Mismatches-based Algorithm (SMA): G domain prediction and application in human Biology and human health

Abstract

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 disease-causing 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/.