B2bTools: online predictions for protein biophysical features and their conservation. Issue Volume 49:Issue W1(2021) (31st May 2021)
- Record Type:
- Journal Article
- Title:
- B2bTools: online predictions for protein biophysical features and their conservation. Issue Volume 49:Issue W1(2021) (31st May 2021)
- Main Title:
- B2bTools: online predictions for protein biophysical features and their conservation
- Authors:
- Kagami, Luciano Porto
Orlando, Gabriele
Raimondi, Daniele
Ancien, Francois
Dixit, Bhawna
Gavaldá-García, Jose
Ramasamy, Pathmanaban
Roca-Martínez, Joel
Tzavella, Konstantina
Vranken, Wim - Abstract:
- Abstract: We provide integrated protein sequence-based predictions via https://bio2byte.be/b2btools/ . The aim of our predictions is to identify the biophysical behaviour or features of proteins that are not readily captured by structural biology and/or molecular dynamics approaches. Upload of a FASTA file or text input of a sequence provides integrated predictions from DynaMine backbone and side-chain dynamics, conformational propensities, and derived EFoldMine early folding, DisoMine disorder, and Agmata β-sheet aggregation. These predictions, several of which were previously not available online, capture 'emergent' properties of proteins, i.e. the inherent biophysical propensities encoded in their sequence, rather than context-dependent behaviour (e.g. final folded state). In addition, upload of a multiple sequence alignment (MSA) in a variety of formats enables exploration of the biophysical variation observed in homologous proteins. The associated plots indicate the biophysical limits of functionally relevant protein behaviour, with unusual residues flagged by a Gaussian mixture model analysis. The prediction results are available as JSON or CSV files and directly accessible via an API. Online visualisation is available as interactive plots, with brief explanations and tutorial pages included. The server and API employ an email-free token-based system that can be used to anonymously access previously generated results. Graphical Abstract:
- Is Part Of:
- Nucleic acids research. Volume 49:Issue W1(2021)
- Journal:
- Nucleic acids research
- Issue:
- Volume 49:Issue W1(2021)
- Issue Display:
- Volume 49, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 49
- Issue:
- 1
- Issue Sort Value:
- 2021-0049-0001-0000
- Page Start:
- W52
- Page End:
- W59
- Publication Date:
- 2021-05-31
- Subjects:
- Nucleic acids -- Periodicals
Molecular biology -- Periodicals
572.805 - Journal URLs:
- http://nar.oxfordjournals.org/ ↗
http://www.ncbi.nlm.nih.gov/pmc/journals/4 ↗
http://ukcatalogue.oup.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1093/nar/gkab425 ↗
- Languages:
- English
- ISSNs:
- 0305-1048
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6183.850000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17589.xml