Role of Disulfide Bonds in Membrane Partitioning of a Viral Peptide
Sikdar, S.; Banerjee, M.; Vemparala, S.
Show abstract
The importance of disulfide bond in mediating viral peptide entry into host cells is well known. In the present work, we elucidate the role of disulfide (SS) bond in partitioning mechanism of membrane active Hepatitis A Virus-2B (HAV-2B) peptide, which harbours three cysteine residues promoting formation of multiple SS-bonded states. The inclusion of SS-bond not only results in a compact conformation but also induces distorted -helical hairpin geometry in comparison to SS-free state, resulting in reduced hydrophobic exposure. Owing to this, the partitioning of HAV-2B peptide is completely or partly abolished. In a way, the disulfide bond regulates the partitioning of HAV-2B peptide, such that the membrane remodelling effects of this viral peptide are significantly reduced. The current findings may have potential implications in drug designing, targeting the HAV-2B protein by promoting disulfide bond formation within its membrane active region.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Investigating the effect of POPC-POPG Lipid Bilayer Composition on PAP248-286 Binding using CG Molecular Dynamics Simulations 97%
- A computational model to unravel the function of amyloid-β peptide in contact with a phospholipid membrane 96%
- The Role of Negatively Charged Groups in Antimicrobial Cationic Peptide Mimics: Insights into Membrane Interactions 96%
Similar papers in this journal
- Ionpair-π interactions favor cell penetration of arginine/tryptophan-rich cell-penetrating peptides 96%
- Structural characterization of the antimicrobial peptides myxinidin and WMR in bacterial membrane mimetic micelles and bicelles 96%
- Formation of aggregates, icosahedral structures and percolation clusters of fullerenes in lipids bilayers: The key role of lipid saturation 95%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.