Peptide Self-Assembly
Humana Press
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Attention Score in Context
| Chapter title |
Replica Exchange Molecular Dynamics: A Practical Application Protocol with Solutions to Common Problems and a Peptide Aggregation and Self-Assembly Example
|
|---|---|
| Chapter number | 5 |
| Book title |
Peptide Self-Assembly
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7811-3_5 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7809-0, 978-1-4939-7811-3
|
| Authors |
Ruxi Qi, Guanghong Wei, Buyong Ma, Ruth Nussinov |
| Abstract |
Protein aggregation is associated with many human diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and type II diabetes (T2D). Understanding the molecular mechanism of protein aggregation is essential for therapy development. Molecular dynamics (MD) simulations have been shown as powerful tools to study protein aggregation. However, conventional MD simulations can hardly sample the whole conformational space of complex protein systems within acceptable simulation time as it can be easily trapped in local minimum-energy states. Many enhanced sampling methods have been developed. Among these, the replica exchange molecular dynamics (REMD) method has gained great popularity. By combining MD simulation with the Monte Carlo algorithm, the REMD method is capable of overcoming high energy-barriers easily and of sampling sufficiently the conformational space of proteins. In this chapter, we present a brief introduction to REMD method and a practical application protocol with a case study of the dimerization of the 11-25 fragment of human islet amyloid polypeptide (hIAPP(11-25)), using the GROMACS software. We also provide solutions to problems that are often encountered in practical use, and provide some useful scripts/commands from our research that can be easily adapted to other systems. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Bosnia and Herzegovina | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 198 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 198 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 50 | 25% |
| Researcher | 19 | 10% |
| Student > Doctoral Student | 14 | 7% |
| Student > Bachelor | 13 | 7% |
| Student > Master | 13 | 7% |
| Other | 19 | 10% |
| Unknown | 70 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 40 | 20% |
| Biochemistry, Genetics and Molecular Biology | 29 | 15% |
| Engineering | 11 | 6% |
| Agricultural and Biological Sciences | 8 | 4% |
| Materials Science | 6 | 3% |
| Other | 34 | 17% |
| Unknown | 70 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 20 January 2020.
All research outputs
#3,107,130
of 23,049,027 outputs
Outputs from Methods in molecular biology
#662
of 13,196 outputs
Outputs of similar age
#71,678
of 442,440 outputs
Outputs of similar age from Methods in molecular biology
#44
of 1,499 outputs
Altmetric has tracked 23,049,027 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,196 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 94% of its peers.
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 442,440 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.