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Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure-function insights.

Shrilakshmi Sheshagiri RaoShankar V KundapuraDebayan DeyChandrasekaran PalaniappanKanagaraj SekarAnanda KulalUdupi A Ramagopal
Published in: Molecular informatics (2024)
The insulin superfamily proteins (ISPs), in particular, insulin, IGFs and relaxin proteins are key modulators of animal physiology. They are known to have evolved from the same ancestral gene and have diverged into proteins with varied sequences and distinct functions, but maintain a similar structural architecture stabilized by highly conserved disulphide bridges. The recent surge of sequence data and the structures of these proteins prompted a need for a comprehensive analysis, which connects the evolution of these sequences (427 sequences) in the light of available functional and structural information including representative complex structures of ISPs with their cognate receptors. This study reveals (a) unusually high sequence conservation of IGFs (>90 % conservation in 184 sequences) and provides a possible structure-based rationale for such high sequence conservation; (b) provides an updated definition of the receptor-binding signature motif of the functionally diverse relaxin family members (c) provides a probable non-canonical C-peptide cleavage site in a few insulin sequences. The high conservation of IGFs appears to represent a classic case of resistance to sequence diversity exerted by physiologically important interactions with multiple partners. We also propose a probable mechanism for C-peptide cleavage in a few distinct insulin sequences and redefine the receptor-binding signature motif of the relaxin family. Lastly, we provide a basis for minimally modified insulin mutants with potential therapeutic application, inspired by concomitant changes observed in other insulin superfamily protein members supported by molecular dynamics simulation.
Keyphrases
  • type diabetes
  • glycemic control
  • molecular dynamics simulations
  • binding protein
  • dna binding
  • healthcare
  • high resolution
  • insulin resistance
  • health information
  • deep learning
  • heat stress