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_and note the location of the extracted PDB files in your system_.
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__If running as part of a BioExcel workshop or summerschool see the instructions in the next section.__
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_If running as part of the ASM HPC/AI school or a BioExcel workshop or summerschool see the instructions in the respective next sections._
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_Note_ that you can also download and unzip this archive directly from the Linux command line:
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<hr>
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### ASM 2026 HPC/AI school, Kobe, Japan, February 2026
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You can either:
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* make use of the Fugaku supercomputer for this tutorial, working at the command line,
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* or [start a Colab notebook](https://colab.research.google.com/github/haddocking/haddock3/blob/main/notebooks/HADDOCK3-antibody-antigen.ipynb){:target="_blank"} (provided you have Google credentials) and follow the instructions in that notebook (simpler).
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If running on Fugaku, the software and data required for this tutorial have been pre-installed.
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Please connect to Fugaku using your credentials either via ssh connection or from a web browser using OnDemand:
If using OnDemand, open then a terminal session, requiring one node and 48 processes and change the working directory to your directory under _/vol0300/data/hp250477/Students/..._.
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</a>
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In order to run the tutorial, go into you data directory, then copy and unzip the required data:
This will create the `HADDOCK3-antibody-antigen` directory with all necessary data and scripts and job examples ready for submission to the batch system.
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HADDOCK3 has been pre-installed on the compute nodes. To test the installation, first create an interactive session on a node with:
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In this case we are providing the known crystal structure of the complex as reference.
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**_Note_**: For making best use of the available CPU resources it is recommended to adapt the sampling parameter to be a multiple of the number of available cores when running in local mode. For this reason, for the ASEAN HPC school the sampling is set to be a multiple of 48.
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**_Note_**: For making best use of the available CPU resources it is recommended to adapt the sampling parameter to be a multiple of the number of available cores when running in local mode. For this reason, for the ASM HPC/AI school the sampling is set to be a multiple of 48.
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**_Note_**: In case no reference is available (the usual scenario), the best ranked model is used as reference for each stage.
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Including `caprieval` at the various stages even when no reference is provided is useful to get the rankings and scores and visualise the results (see Analysis section below).
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#### Execution of HADDOCK3 on Fugaku (ASEAN 2025 HPC school)
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#### Execution of HADDOCK3 on Fugaku (ASM 2026 HPC/AI school, Kobe Japan)
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<detailsstyle="background-color:#DAE4E7">
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<summarystyle="bold">
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