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You need to supply the structure of your protein and a multiple sequence alignment of your protein sequence with homologuous sequences.

You need the structure of your protein as PDB file or you can use a PDB code to download the structure automatically from the Protein Data Bank.

You need to specify the protein chain. Many PDB files consists of multiple protein molecules (chains). Normally, you want to predict on only one chain.

If your structure (or a close homolog) is deposited in the PDB, you can use the alignment from the HSSP database. The HSSP database contains an alignment for nearly each protein in the PDB. To use the HSSP alignment, specify the corresponding PDB code in the HSSP_id field.

Alternatively, you can supply your own alignment. WHISCY recognizes a number of alignment formats used by major alignment programs: .aln (default output of CLUSTAL), .fasta (default output of MUSCLE), PHYLIP and MSF. Please note WHISCY assumes that the first sequence in the alignment corresponds to the biological sequence of your protein. This can be the sequence of the PDB structure, but only if it is not engineered!

Interface propensities and surface smoothing are features that are used by WHISCY to improve the predictions. They are enabled by default.


Whiscy outputs are displayed online and remain downloadable for 14 days.

WHISCY calculates a prediction score for every surface residue in your protein that can be matched to the provided alignment. A high prediction score means a high probability of that residue to be in a protein-protein interface.

The results returned by the server include:

  • A passive (passive.txt) and active (active.txt) lists including the residue numbers for HADDOCK. A cutoff of 0.18 is used to define active residues and a radius of 6.5Å to define the surrounding passive residues.
  • A file containing the WHISCY scores with extension .pscons.
  • Structures in PDB format with WHISCY (_whiscy.pdb) scores in the b-factor column and HADDOCK active and passive residues (_haddock.pdb).

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This work is co-funded by the Horizon 2020 projects EOSC-hub and EGI-ACE (grant numbers 777536 and 101017567), BioExcel (grant numbers 823830 and 675728)
and by a computing grant from NWO-ENW (project number 2019.053).