Data · collection · 2015
Towards an accurate prediction of the thermal stability of homologous proteins
Listed in DataCite
Protein thermostability has been the focus of growing research interests in the last decades since its understanding and control play important roles in the optimization of a wide series of bioprocesses of academic and industrial importance.
Description
The complexity of this issue is rooted in the fact that the mechanisms ensuring thermal resistance are not unique and specific, but rather family- or even protein-dependent. Therefore, and despite the amount of research already accomplished, obtaining fast and precise thermal stability predictions is still a challenge, especially on a large scale.
This article deepens the study of protein thermal stability and is focused on the prediction of its best descriptor, the melting temperature T m . The relations between T m and a series of factors that are expected to influence the protein stability are analyzed and discussed. Different T m -prediction methods that utilize these factors, sometimes with additional information about homologous proteins, are introduced, and their individual performances are evaluated.
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The best methods are based on temperature-dependent statistical potentials, on the environmental temperature of the host organism, on the fraction of charged residues, and on the number of residues. They are combined to build an improved prediction method with significantly increased score. The root mean square deviation between the computed and experimental T m -values for 45 proteins of known structure from 11 families is about 7°C in cross-validation and decreases to 5°C when 10% outliers are removed.
The associated linear correlation coefficients are equal to .91 and .95, respectively.
Links
Where it is published
- Repository landing page figshare.com/collections/Towards_an_accurate_prediction_of_the_thermal_stab… ↗
landing page · from DataCite
- Repository landing page figshare.com/collections/Towards_an_accurate_prediction_of_the_thermal_stab… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.2092808 ↗
DOI / persistent id · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.2092808.v1 ↗
DOI / persistent id · from DataCite
Documentation and papers
- CC-BY creativecommons.org/licenses/by/3.0/us ↗
license · from DataCite
- IsSupplementTo 10.1080/07391102.2015.1073631 doi.org/10.1080/07391102.2015.1073631 ↗
publication · from DataCite
Catalogue records · 4
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.c.2092808.v1 ↗
metadata API · from DataCite
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.c.2092808 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.c.2092808.v1 ↗
catalogue entry · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.c.2092808 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Biological sciences · Biological sciences · Chemical sciences · Chemical sciences · Physical sciences · Physical sciences
- From keywords
- Genetics · Inorganic chemistry · Plant biology
Provenance · 2 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.c.2092808 | 15 d ago | JSON v1 |
| DataCite | 10.6084/m9.figshare.c.2092808.v1 | 15 d ago | JSON v1 |
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|---|---|---|---|
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| concepts[field].fos:chemical-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:chemical-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:physical-sciences | source · DataCite | connector:datacite@1.0.0 | |
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