-
Something wrong with this record ?
FireProtDB: database of manually curated protein stability data
J. Stourac, J. Dubrava, M. Musil, J. Horackova, J. Damborsky, S. Mazurenko, D. Bednar
Language English Country Great Britain
Document type Journal Article, Research Support, Non-U.S. Gov't
NLK
Directory of Open Access Journals
from 2005
Free Medical Journals
from 1996
PubMed Central
from 1974
Europe PubMed Central
from 1974
Open Access Digital Library
from 1996-01-01 to 2030-12-31
Open Access Digital Library
from 1974-01-01
Open Access Digital Library
from 1996-01-01
Open Access Digital Library
from 1996-01-01
Medline Complete (EBSCOhost)
from 1996-01-01
Oxford Journals Open Access Collection
from 1996-01-01
ROAD: Directory of Open Access Scholarly Resources
from 1974
PubMed
33166383
DOI
10.1093/nar/gkaa981
Knihovny.cz E-resources
- MeSH
- Molecular Sequence Annotation MeSH
- Point Mutation * MeSH
- Databases, Protein * MeSH
- Datasets as Topic MeSH
- Internet MeSH
- Models, Molecular MeSH
- Proteins chemistry genetics MeSH
- Software MeSH
- Protein Stability MeSH
- Machine Learning statistics & numerical data MeSH
- Computational Biology methods MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The majority of naturally occurring proteins have evolved to function under mild conditions inside the living organisms. One of the critical obstacles for the use of proteins in biotechnological applications is their insufficient stability at elevated temperatures or in the presence of salts. Since experimental screening for stabilizing mutations is typically laborious and expensive, in silico predictors are often used for narrowing down the mutational landscape. The recent advances in machine learning and artificial intelligence further facilitate the development of such computational tools. However, the accuracy of these predictors strongly depends on the quality and amount of data used for training and testing, which have often been reported as the current bottleneck of the approach. To address this problem, we present a novel database of experimental thermostability data for single-point mutants FireProtDB. The database combines the published datasets, data extracted manually from the recent literature, and the data collected in our laboratory. Its user interface is designed to facilitate both types of the expected use: (i) the interactive explorations of individual entries on the level of a protein or mutation and (ii) the construction of highly customized and machine learning-friendly datasets using advanced searching and filtering. The database is freely available at https://loschmidt.chemi.muni.cz/fireprotdb.
References provided by Crossref.org
- 000
- 00000naa a2200000 a 4500
- 001
- bmc21011619
- 003
- CZ-PrNML
- 005
- 20240801104250.0
- 007
- ta
- 008
- 210420s2021 xxk f 000 0|eng||
- 009
- AR
- 024 7_
- $a 10.1093/nar/gkaa981 $2 doi
- 035 __
- $a (PubMed)33166383
- 040 __
- $a ABA008 $b cze $d ABA008 $e AACR2
- 041 0_
- $a eng
- 044 __
- $a xxk
- 100 1_
- $a Stourac, Jan $u Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic ; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
- 245 10
- $a FireProtDB: database of manually curated protein stability data / $c J. Stourac, J. Dubrava, M. Musil, J. Horackova, J. Damborsky, S. Mazurenko, D. Bednar
- 520 9_
- $a The majority of naturally occurring proteins have evolved to function under mild conditions inside the living organisms. One of the critical obstacles for the use of proteins in biotechnological applications is their insufficient stability at elevated temperatures or in the presence of salts. Since experimental screening for stabilizing mutations is typically laborious and expensive, in silico predictors are often used for narrowing down the mutational landscape. The recent advances in machine learning and artificial intelligence further facilitate the development of such computational tools. However, the accuracy of these predictors strongly depends on the quality and amount of data used for training and testing, which have often been reported as the current bottleneck of the approach. To address this problem, we present a novel database of experimental thermostability data for single-point mutants FireProtDB. The database combines the published datasets, data extracted manually from the recent literature, and the data collected in our laboratory. Its user interface is designed to facilitate both types of the expected use: (i) the interactive explorations of individual entries on the level of a protein or mutation and (ii) the construction of highly customized and machine learning-friendly datasets using advanced searching and filtering. The database is freely available at https://loschmidt.chemi.muni.cz/fireprotdb.
- 650 _2
- $a výpočetní biologie $x metody $7 D019295
- 650 12
- $a databáze proteinů $7 D030562
- 650 _2
- $a datové soubory jako téma $7 D066264
- 650 _2
- $a internet $7 D020407
- 650 _2
- $a strojové učení $x statistika a číselné údaje $7 D000069550
- 650 _2
- $a molekulární modely $7 D008958
- 650 _2
- $a anotace sekvence $7 D058977
- 650 12
- $a bodová mutace $7 D017354
- 650 _2
- $a stabilita proteinů $7 D055550
- 650 _2
- $a proteiny $x chemie $x genetika $7 D011506
- 650 _2
- $a software $7 D012984
- 655 _2
- $a časopisecké články $7 D016428
- 655 _2
- $a práce podpořená grantem $7 D013485
- 700 1_
- $a Dúbrava, Juraj $u Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic ; Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic $7 xx0065297
- 700 1_
- $a Musil, Milos $u Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic ; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic ; Department of Information Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic
- 700 1_
- $a Horackova, Jana $u Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic
- 700 1_
- $a Damborsky, Jiri $u Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic ; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
- 700 1_
- $a Mazurenko, Stanislav $u Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic
- 700 1_
- $a Bednar, David $u Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Masaryk University, Brno, Czech Republic ; International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
- 773 0_
- $w MED00003554 $t Nucleic acids research $x 1362-4962 $g Roč. 49, č. D1 (2021), s. D319-D324
- 856 41
- $u https://pubmed.ncbi.nlm.nih.gov/33166383 $y Pubmed
- 910 __
- $a ABA008 $b sig $c sign $y p $z 0
- 990 __
- $a 20210420 $b ABA008
- 991 __
- $a 20240801104246 $b ABA008
- 999 __
- $a ok $b bmc $g 1650093 $s 1131998
- BAS __
- $a 3
- BAS __
- $a PreBMC
- BMC __
- $a 2021 $b 49 $c D1 $d D319-D324 $e 20210108 $i 1362-4962 $m Nucleic acids research $n Nucleic Acids Res $x MED00003554
- LZP __
- $a Pubmed-20210420