New User Question- HADDOCK

I’m a grad student using HADDOCK2.4 for the first time. I want to use this for protein-peptide docking. I am not too sure on the significance of the restraints as to the context of my docking. Is there ant literature that describes desirable settings for the restraints? Also, when evaluating the results, I haven’t found a site that describes what the values mean and what is an indicator of a stronger docking. For example, is it better to have a smaller cluster size? Or what would be a good RMSD?
Any help would be much appreciated.

Hi Sabrina

I recommend to follow a few of our online tutorials (check Education & Tutorials of the Bonvin Lab – Bonvin Lab)

A tutorial specific to protein-peptide docking can be found at:

https://www.bonvinlab.org/education/molmod_online/#part-3-protein-peptide-data-driven-docking

I’m a grad student using HADDOCK2.4 for the first time. I want to use this for protein-peptide docking. I am not too sure on the significance of the restraints as to the context of my docking. Is there ant literature that describes desirable settings for the restraints?

What do you mean by settings? HADDOCK works best if you have some knowledge of the binding site.
Our protein-peptide docking protocol is described in the following publications:

Also, when evaluating the results, I haven’t found a site that describes what the values mean and what is an indicator of a stronger docking.

The more negative the HADDOCK score the better.

For example, is it better to have a smaller cluster size? Or what would be a good RMSD?

Large clusters would be nicer. And RMSD is irrelevant, it only tells you how far a given cluster is from the best (lowest HADDOCK score) model

Thank you, as I am completely new to docking, do you know of any other resources that explain the foundations needed to understand this software better. I am also just using the online version of HADDOCK2.4 instead of through python. I suppose there is no major difference.
In terms of settings, I mean is there any paper that discusses the significance of the restraints to set? Or is the default accurate? I know the binding sites of my protein (based on PDB). I am just not sure on the significance of all the restraints. Thank you! Btw I am doing a protein-peptide docking

The defaults are only for the parameter settings - restraints must be defined or provided by the users

I would not start changing parameters if inexperienced with haddock.

And take the time to do some reading I would say.

Hello, I want to also dock nafamostat. Would this be considered a ligand? I found ’ Information-driven modelling of protein-peptide complexes’ a good paper to help determine the restraints for my peptide docking. However, I would like to know if you know of any similar papers for ligand-protein docking? I have not been able to find any. Thank you

Check out tutorials (for haddock2.4) at Education & Tutorials of the Bonvin Lab – Bonvin Lab

There are two that are ligand-related.

Thank you. I did a docking with nafamostat, but as it is a synthetic compound I am not sure what kind of molecule would best describe it, as ligand docking didn’t appear to be successful.
Thank you.

That should be defined as ligand.

And the PDB file for it should have HETATM instead of ATOM statements

Is that just for the case of ligands or should peptides also have HETATM statements instead?

No peptides consist of standard amino acids.

But the server has a molecule type peptide which changes some parameter settings

is there any reason why when checking the 3D view of the docking the ligand (nafamostat) isn’t present. As thought the molecule wasn’t recognized. A preview of the structure could be seen when checking the active residues. So I don’t know why it disappeared and if it has something to do with the HETATM?

FYI, I did confirm that the statement is in HETATM

If you are referring to the online visualisation in the results page, you will need to switch to the lines representation to see the ligand.

And otherwise simply use another software to view the models, e.g. PyMol.