» Articles » PMID: 28232898

Understanding the Roles of Intrinsic Disorder in Subunits of Hemoglobin and the Disease Process of Sickle Cell Anemia

Overview
Date 2017 Feb 25
PMID 28232898
Citations 3
Authors
Affiliations
Soon will be listed here.
Abstract

One of the common genetic disorders is sickle cell anemia, in which 2 recessive alleles must meet to allow for destruction and alteration in the morphology of red blood cells. This usually leads to loss of proper binding of oxygen to hemoglobin and curved, sickle-shaped erythrocytes. The mutation causing this disease occurs in the 6 codon of the gene encoding the hemoglobin subunit β (β-globin), a protein, serving as an integral part of the adult hemoglobin A (HbA), which is a heterotetramer of 2 α chains and 2 β chains that is responsible for binding to the oxygen in the blood. This mutation changes a charged glutamic acid to a hydrophobic valine residue and disrupts the tertiary structure and stability of the hemoglobin molecule. Since in the field of protein intrinsic disorder, charged and polar residues are typically considered as disorder promoting, in opposite to the order-promoting non-polar hydrophobic residues, in this study we attempted to answer a question if intrinsic disorder might have a role in the pathogenesis of sickle cell anemia. To this end, several disorder predictors were utilized to evaluate the presence of intrinsically disordered regions in all subunits of human hemoglobin: α, β, δ, ε, ζ, γ1, and γ2. Then, structural analysis was completed by using the SWISS-MODEL Repository to visualize the outputs of the disorder predictors. Finally, Uniprot STRING and DP were used to determine biochemical interactome and protein partners for each hemoglobin subunit along with analyzing their posttranslational modifications. All these properties were used to determine any differences between the 6 different types of subunits of hemoglobin and to correlate the mutation leading to sickle cell anemia with intrinsic disorder propensity.

Citing Articles

AI-Driven Spectral Decomposition: Predicting the Most Probable Protein Compositions from Surface Enhanced Raman Spectroscopy Spectra of Amino Acids.

Srivastava S, Sandhu N, Liu J, Xie Y Bioengineering (Basel). 2024; 11(5).

PMID: 38790349 PMC: 11117800. DOI: 10.3390/bioengineering11050482.


Enhancing diagnostic precision for acute chest syndrome in sickle cell disease: insights from dual-energy CT lung perfusion mapping.

Chamberlin J, Ogbonna A, Abrol S, Maisuria D, Miller E, McGuire A Emerg Radiol. 2024; 31(1):73-82.

PMID: 38224366 DOI: 10.1007/s10140-024-02200-w.


Plasma Interleukin-33 Cannot Predict Hip Osteonecrosis in Patients With Sickle Cell Disease: A Case-Control Study.

Agrawal A, Mohapatra E, Nanda R, Bodhey N, Sakale H, Garg A Cureus. 2022; 14(3):e23556.

PMID: 35371856 PMC: 8971072. DOI: 10.7759/cureus.23556.

References
1.
Sievers F, Wilm A, Dineen D, Gibson T, Karplus K, Li W . Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol. 2011; 7:539. PMC: 3261699. DOI: 10.1038/msb.2011.75. View

2.
Hemmings Jr H, Nairn A, Aswad D, Greengard P . DARPP-32, a dopamine- and adenosine 3':5'-monophosphate-regulated phosphoprotein enriched in dopamine-innervated brain regions. II. Purification and characterization of the phosphoprotein from bovine caudate nucleus. J Neurosci. 1984; 4(1):99-110. PMC: 6564759. View

3.
Gast K, Damaschun H, Eckert K, Maurer H, Muller-Frohne M, Zirwer D . Prothymosin alpha: a biologically active protein with random coil conformation. Biochemistry. 1995; 34(40):13211-8. DOI: 10.1021/bi00040a037. View

4.
Berman H, Westbrook J, Feng Z, Gilliland G, Bhat T, Weissig H . The Protein Data Bank. Nucleic Acids Res. 1999; 28(1):235-42. PMC: 102472. DOI: 10.1093/nar/28.1.235. View

5.
Chu X, Gan L, Wang E, Wang J . Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition. Proc Natl Acad Sci U S A. 2013; 110(26):E2342-51. PMC: 3696809. DOI: 10.1073/pnas.1220699110. View