| Title |
SecA, a remarkable nanomachine
|
|---|---|
| Published in |
Cellular and Molecular Life Sciences, April 2011
|
| DOI | 10.1007/s00018-011-0681-y |
| Pubmed ID | |
| Authors |
Ilja Kusters, Arnold J. M. Driessen |
| Abstract |
Biological cells harbor a variety of molecular machines that carry out mechanical work at the nanoscale. One of these nanomachines is the bacterial motor protein SecA which translocates secretory proteins through the protein-conducting membrane channel SecYEG. SecA converts chemically stored energy in the form of ATP into a mechanical force to drive polypeptide transport through SecYEG and across the cytoplasmic membrane. In order to accommodate a translocating polypeptide chain and to release transmembrane segments of membrane proteins into the lipid bilayer, SecYEG needs to open its central channel and the lateral gate. Recent crystal structures provide a detailed insight into the rearrangements required for channel opening. Here, we review our current understanding of the mode of operation of the SecA motor protein in concert with the dynamic SecYEG channel. We conclude with a new model for SecA-mediated protein translocation that unifies previous conflicting data. |
Mendeley readers
The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | <1% |
| Germany | 1 | <1% |
| Netherlands | 1 | <1% |
| Finland | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 100 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 30 | 29% |
| Student > Master | 15 | 14% |
| Student > Bachelor | 14 | 13% |
| Researcher | 14 | 13% |
| Professor > Associate Professor | 7 | 7% |
| Other | 16 | 15% |
| Unknown | 9 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 57 | 54% |
| Biochemistry, Genetics and Molecular Biology | 23 | 22% |
| Chemistry | 5 | 5% |
| Medicine and Dentistry | 3 | 3% |
| Immunology and Microbiology | 2 | 2% |
| Other | 4 | 4% |
| Unknown | 11 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 25 August 2012.
All research outputs
#7,845,540
of 23,794,258 outputs
Outputs from Cellular and Molecular Life Sciences
#1,655
of 4,151 outputs
Outputs of similar age
#41,132
of 111,082 outputs
Outputs of similar age from Cellular and Molecular Life Sciences
#16
of 34 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,151 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 111,082 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.