Evaluation of accuracy and applicability of protein models: retrospective analysis of biological and biomedical predictions.
Khan, Sofia and Vihinen, Mauno LU
(2009)
In In Silico Biology
9(5).
p.307-331
- Abstract
- In order to study protein function and activity structural data is required. Since experimental structures are available for just a small fraction of all known protein sequences, computational methods such as protein modelling can provide useful information. Over the last few decades we have predicted, with homology modelling methods, the structures for numerous proteins. In this study we assess the structural quality and validity of the biological and medical interpretations and predictions made based on the models. All the models had correct scaffolding and were ranked at least as correct or good by numerical evaluators even though the sequence identity with the template was as low as 8%. The biological explanations made based on models... (More)
- In order to study protein function and activity structural data is required. Since experimental structures are available for just a small fraction of all known protein sequences, computational methods such as protein modelling can provide useful information. Over the last few decades we have predicted, with homology modelling methods, the structures for numerous proteins. In this study we assess the structural quality and validity of the biological and medical interpretations and predictions made based on the models. All the models had correct scaffolding and were ranked at least as correct or good by numerical evaluators even though the sequence identity with the template was as low as 8%. The biological explanations made based on models were well in line with experimental structures and other experimental studies. Retrospective analysis of homology models indicates the power of protein modelling when made carefully from sequence alignment to model building and refinement. Modelling can be applied to studying and predicting different kinds of biological phenomena and according to our results it can be done so with success. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3634993
- author
- Khan, Sofia
and Vihinen, Mauno
LU
- publishing date
- 2009
- type
- Contribution to journal
- publication status
- published
- subject
- in
- In Silico Biology
- volume
- 9
- issue
- 5
- pages
- 307 - 331
- publisher
- IOS Press
- external identifiers
-
- pmid:22430434
- scopus:84885917614
- ISSN
- 1386-6338
- DOI
- 10.3233/ISB-2009-0408
- language
- English
- LU publication?
- no
- id
- 80e2e706-41c0-44c0-8926-d5c20941e683 (old id 3634993)
- alternative location
- http://www.ncbi.nlm.nih.gov/pubmed/22430434?dopt=Abstract
- date added to LUP
- 2016-04-04 07:55:28
- date last changed
- 2022-01-29 02:49:02
@article{80e2e706-41c0-44c0-8926-d5c20941e683,
abstract = {{In order to study protein function and activity structural data is required. Since experimental structures are available for just a small fraction of all known protein sequences, computational methods such as protein modelling can provide useful information. Over the last few decades we have predicted, with homology modelling methods, the structures for numerous proteins. In this study we assess the structural quality and validity of the biological and medical interpretations and predictions made based on the models. All the models had correct scaffolding and were ranked at least as correct or good by numerical evaluators even though the sequence identity with the template was as low as 8%. The biological explanations made based on models were well in line with experimental structures and other experimental studies. Retrospective analysis of homology models indicates the power of protein modelling when made carefully from sequence alignment to model building and refinement. Modelling can be applied to studying and predicting different kinds of biological phenomena and according to our results it can be done so with success.}},
author = {{Khan, Sofia and Vihinen, Mauno}},
issn = {{1386-6338}},
language = {{eng}},
number = {{5}},
pages = {{307--331}},
publisher = {{IOS Press}},
series = {{In Silico Biology}},
title = {{Evaluation of accuracy and applicability of protein models: retrospective analysis of biological and biomedical predictions.}},
url = {{http://dx.doi.org/10.3233/ISB-2009-0408}},
doi = {{10.3233/ISB-2009-0408}},
volume = {{9}},
year = {{2009}},
}