Accuracy of protein hydropathy predictions.
Jääskeläinen, Satu ; Riikonen, Pentti ; Salakoski, Tapio and Vihinen, Mauno LU
(2010)
In International Journal of Data Mining and Bioinformatics
4(6).
p.735-754
- Abstract
- Hydropathy is a dominant force in protein folding. Sequence-based hydropathy predictions are widely used, without knowledge about their accuracy and reliability. We investigated the prediction accuracy of 56 hydropathy scales by correlating predicted values with the accessible surface area in known protein structures. Results for different amino acids vary greatly within each scale. We also investigated prediction accuracies of amino acids separately in secondary structural elements and in protein fold families. Despite very low overall correlation, hydropathy predictions can still be used if the shape of the plot is important instead of the prediction values.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3634747
- author
- Jääskeläinen, Satu
; Riikonen, Pentti
; Salakoski, Tapio
and Vihinen, Mauno
LU
- publishing date
- 2010
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Computational Biology: methods, Proteins: chemistry, Proteins: metabolism
- in
- International Journal of Data Mining and Bioinformatics
- volume
- 4
- issue
- 6
- pages
- 735 - 754
- publisher
- Inderscience Publishers
- external identifiers
-
- pmid:21355504
- scopus:78650482076
- ISSN
- 1748-5673
- language
- English
- LU publication?
- no
- id
- c462f08b-f26a-4692-a513-89eb7f0bc5eb (old id 3634747)
- alternative location
- http://www.ncbi.nlm.nih.gov/pubmed/21355504?dopt=Abstract
- date added to LUP
- 2016-04-04 07:13:47
- date last changed
- 2022-01-29 01:55:04
@article{c462f08b-f26a-4692-a513-89eb7f0bc5eb,
abstract = {{Hydropathy is a dominant force in protein folding. Sequence-based hydropathy predictions are widely used, without knowledge about their accuracy and reliability. We investigated the prediction accuracy of 56 hydropathy scales by correlating predicted values with the accessible surface area in known protein structures. Results for different amino acids vary greatly within each scale. We also investigated prediction accuracies of amino acids separately in secondary structural elements and in protein fold families. Despite very low overall correlation, hydropathy predictions can still be used if the shape of the plot is important instead of the prediction values.}},
author = {{Jääskeläinen, Satu and Riikonen, Pentti and Salakoski, Tapio and Vihinen, Mauno}},
issn = {{1748-5673}},
keywords = {{Computational Biology: methods; Proteins: chemistry; Proteins: metabolism}},
language = {{eng}},
number = {{6}},
pages = {{735--754}},
publisher = {{Inderscience Publishers}},
series = {{International Journal of Data Mining and Bioinformatics}},
title = {{Accuracy of protein hydropathy predictions.}},
url = {{http://www.ncbi.nlm.nih.gov/pubmed/21355504?dopt=Abstract}},
volume = {{4}},
year = {{2010}},
}