Reducing computational time

HADDOCK
1

The HADDOCK category is meant to discuss any HADDOCK-related issue. For general information about HADDOCK refer to HADDOCK – Bonvin Lab

Hi, I apologize for starting so many new topics lately, but beyond setting delenph = true, how can one reduce the computational time of HADDOCK runs without compromising quality of the output? I have a massive number of docking runs to perform, because I have many proteins and DNAs to dock. And it gets worse, because I am using samples of normal modes from each of the partners in ensemble pdb files, so for each HADDOCK run I need to set the sampling parameters to a very high number and partition the normal modes into different ensemble pdb files.

I am using haddock3 locally.

Thanks in advance

2

Dear stianale,

Thanks for your interest in using haddock3 in for your research.

Unfortunately, running computationally heavy runs will take some time.

To reduce the time, you could:

  • increase the number of cores to be used (with the ncores parameter)
  • reduce the sampling in [rigidbody] (at a cost of possible missing good poses)
  • provide meaningful ambiguous restraints to better guide the docking and therefore safely reduce the sampling
  • reduce the number of selected top models for refinements ([seletop] select=100)
  • perform some clustering to only refine diverse models ([clustfcc] or [rmsdmatrix][clustrmsd] followed by [seletopclusts])
  • not do [mdref] step, but only rely on the [emref] instead

Also, please note that you can also provide ensemble pdb files as input to haddock3.

With the hope that this answer will help you.