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Updated: Apr 19, 2026

Synthesis and Structure Determination of µ-Conotoxin PIIIA Isomers with Different Disulfide Connectivities
Published on: October 2, 2018
Clustering-based model of cysteine co-evolution improves disulfide bond connectivity prediction and reduces
Daniele Raimondi1, Gabriele Orlando1, Wim F Vranken1
1Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, La Plaine Campus, Triomflaan, CP 263, Structural Biology Brussels, Vrije Universiteit Brussel, Pleinlaan 2 and Structural Biology Research Center, VIB, 1050 Brussels, Belgium Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, La Plaine Campus, Triomflaan, CP 263, Structural Biology Brussels, Vrije Universiteit Brussel, Pleinlaan 2 and Structural Biology Research Center, VIB, 1050 Brussels, Belgium Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, La Plaine Campus, Triomflaan, CP 263, Structural Biology Brussels, Vrije Universiteit Brussel, Pleinlaan 2 and Structural Biology Research Center, VIB, 1050 Brussels, Belgium.
Motivation:
Cysteine residues have particular structural and functional relevance in proteins because of their ability to form covalent disulfide bonds. Bioinformatics tools that can accurately predict cysteine bonding states are already available, whereas it remains challenging to infer the disulfide connectivity pattern of unknown protein sequences. Improving accuracy in this area is highly relevant for the structural and functional annotation of proteins.
Results:
We predict the intra-chain disulfide bond connectivity patterns starting from known cysteine bonding states with an evolutionary-based unsupervised approach called Sephiroth that relies on high-quality alignments obtained with HHblits and is based on a coarse-grained cluster-based modelization of tandem cysteine mutations within a protein family. We compared our method with state-of-the-art unsupervised predictors and achieve a performance improvement of 25-27% while requiring an order of magnitude less of aligned homologous sequences (∼10(3) instead of ∼10(4)).
Availability And Implementation:
The software described in this article and the datasets used are available at http://ibsquare.be/sephiroth.
Contact:
wvranken@vub.ac.be
Supplementary Information:
Supplementary material is available at Bioinformatics online.
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