| Title |
Evolutionary relationships between heme-binding ferredoxin α + β barrels
|
|---|---|
| Published in |
BMC Bioinformatics, April 2016
|
| DOI | 10.1186/s12859-016-1033-6 |
| Pubmed ID | |
| Authors |
Giriraj Acharya, Gurmeet Kaur, Srikrishna Subramanian |
| Abstract |
The α + β barrel superfamily of the ferredoxin-like fold consists of a functionally diverse group of evolutionarily related proteins. The barrel architecture of these proteins is formed by either homo-/hetero-dimerization or duplication and fusion of ferredoxin-like domains. Several members of this superfamily bind heme in order to carry out their functions. We analyze the heme-binding sites in these proteins as well as their barrel topologies. Our comparative structural analysis of these heme-binding barrels reveals two distinct modes of packing of the ferredoxin-like domains to constitute the α + β barrel, which is typified by the Type-1/IsdG-like and Type-2/OxdA-like proteins, respectively. We examine the heme-binding pockets and explore the versatility of the α + β barrels ability to accommodate heme or heme-related moieties, such as siroheme, in at least three different sites, namely, the mode seen in IsdG/OxdA, Cld/DyP/EfeB/HemQ and siroheme decarboxylase barrels. Our study offers insights into the plausible evolutionary relationships between the two distinct barrel packing topologies and relate the observed heme-binding sites to these topologies. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 5% |
| Unknown | 21 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 36% |
| Researcher | 7 | 32% |
| Unspecified | 1 | 5% |
| Student > Bachelor | 1 | 5% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 41% |
| Agricultural and Biological Sciences | 7 | 32% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Unspecified | 1 | 5% |
| Computer Science | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 2 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 April 2016.
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#20,320,000
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Outputs from BMC Bioinformatics
#6,868
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Outputs of similar age from BMC Bioinformatics
#95
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