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The IntFOLD Integrated Protein Structure and Function Prediction Server

About the server

The IntFOLD server provides a unified interface for:

  1. Tertiary structure prediction/3D modelling
  2. 3D model quality assessment
  3. Intrinsic disorder prediction
  4. Domain prediction
  5. Prediction of protein-ligand binding residues

IntFOLD submission form (latest version)


McGuffin, L.J., Atkins, J., Salehe, B.R., Shuid, A.N. & Roche, D.B. (2015) IntFOLD: an integrated server for modelling protein structures and functions from amino acid sequences. Nucleic Acids Research, 43, W169-73. PubMed

Help page

Sample output

Case study

The animation below shows the top IntFOLD model for CSRP3 from mouse, which serves to demonstrate results from each of the integrated methods. Two globular zinc binding domains are linked by an intrinsically disordered region. The model helps us to understand how this protein might act as a stress sensor in cardiac myocytes. Click on the image to view the full IntFOLD results.

News and updates

  • Feb 2015: Science paper published containing results from the IntFOLD server. Press release.
  • Dec 2014: new interactive model visualisations implemented using the JSmol/HTML5 framework (also works on tablets and phones).
  • Dec 2014: improved job status notification system implemented.
  • Dec 2014: Success at CASP11, especially in the Quality Assessment (QA3) category
  • Aug 2014: CASP11 prediction season complete.
  • May 2014: CASP11 starts! New versions of the server component methods will be benchmarked. Provision of new CASP & CAMEO structural and functional data types/formats.
  • Sep 2013: IntFOLD2 integrated with the Protein Model Portal
  • Dec 2012: success at CASP10 - short talks given on quality assessment and function prediction
  • Dec 2012: paper reporting extensive application of servers has been published in BMC Genomics
  • Aug 2012: IntFOLD2 open beta version online for testing please send feedback to
  • May 2012: Multi-Template Modelling (MTM) method Bioinformatics paper published (Buenavista et al., Bioinformatics, 2012), the method forms the basis of IntFOLD2-TS predictions
  • Sept 2011: Confidence scores (p-values) now included in graphical output. Help page
  • Aug 2011: Interactive IntFOLD-TS output now includes model-template superpositions - Example
  • May 2011: IntFOLD-TS method paper now in press (CASP9 special issue) - Publications
  • May 2011: FunFOLD paper now in press - Publications Download FunFOLD
  • March 2011: IntFOLD server paper now in press (NAR Web Server issue) - Publications
  • March 2011: Methods paper describing application of servers to Blumeria proteome now in press - Publications
  • Dec 2010: The IntFOLD server version is now out of beta.
  • Dec 2010: The IntFOLD-TS method was the focus of our invited talk for the CASP9 methods session. Download slides (.pptx).

Original server reference:

Roche, D. B., Buenavista, M. T., Tetchner, S. J. & McGuffin, L. J. (2011) The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction. Nucleic Acids Res., 39, W171-6. PubMed

The IntFOLD component standalone methods

  • Buenavista, M. T., Roche, D. B., & McGuffin, L. J. (2012) Improvement of 3D protein models using multiple templates guided by single-template model quality assessment. Bioinformatics, 28, 1851-1857. PubMed
  • IntFOLD-TS (original nFOLD4 version):
  • McGuffin, L. J. & Roche, D. B. (2011) Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method. Proteins: Structure, Function, and Bioinformatics, 79 Suppl 10, 137-46. PubMed
  • IntFOLD-FN (FunFOLD):
  • Roche, D. B., Tetchner, S. J. & McGuffin, L. J. (2011) FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins. BMC Bioinformatics, 12, 160. PubMed
  • IntFOLD-QA (ModFOLD):
  • McGuffin, L. J. & Roche, D. B. (2010) Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments. Bioinformatics, 26, 182-188. PubMed
  • IntFOLD-DR (DISOclust):
  • McGuffin, L. J. (2008) Intrinsic disorder prediction from the analysis of multiple protein fold recognition models. Bioinformatics, 24, 1798-804. PubMed
  • Older versions

    IntFOLD2 submission form

    IntFOLD submission form (original version)


    Tel: 0118 378 6332

    Email: l.j.mcguffin

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