b2bTools: online predictions for protein biophysical features and their conservation

Luciano Porto Kagami, Gabriele Orlando, Daniele Raimondi, Francois Ancien, Bhawna Dixit, Jose Gavaldá-García, Pathmanaban Ramasamy, Joel Roca-Martínez, Konstantina Tzavella, Wim Vranken

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
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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.

Original languageEnglish
Pages (from-to)W52-W59
Number of pages8
JournalNucleic Acids Research
Issue numberW1
Publication statusPublished - 31 May 2021

Bibliographical note

© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.


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