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Update README.md
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README.md
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README.md
@@ -31,11 +31,11 @@ binding affinity, and identifying interface residue contacts, respectively.
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- Linux Kernel OS
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## Software & Dataset Requirements (for PPLM-Contact)
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1. **HH-suite3** for MSA Search: [Install HH-suite3](https://github.com/soedinglab/hh-suite)
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2. **Uniclust Database**: [Download Uniclust](http://wwwuser.gwdg.de/~compbiol/uniclust/2021_03/)
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3. **CCMpred** for DCA: [Install CCMpred](https://github.com/soedinglab/CCMpred)
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4. **LoadHHM** for PSSM Calculation: [LoadHHM.py](https://github.com/j3xugit/RaptorX-Contact/blob/master/Common/LoadHHM.py)
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5. **ESM-MSA** for Feature Generation: [Install ESM](https://github.com/facebookresearch/esm)
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1. **HH-suite3** for MSA Search: Install [HH-suite3](https://github.com/soedinglab/hh-suite) and set the "hhsuite_dir" parameter in the "pplm_contact/config.py" file.
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2. **Uniclust Database**: Download the [Uniclust30 database](http://wwwuser.gwdg.de/~compbiol/uniclust/2021_03/) and set the "UniRef_database" parameter in the "config.py" file.
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3. **CCMpred** for DCA: Install [ccmpred](https://github.com/soedinglab/CCMpred), or use the pre-packaged version in the "pplm_contact/external_tools" directory. Set the "ccmpred" parameter in the "config.py" file.
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4. **LoadHHM** for PSSM Calculation: Download [LoadHHM.py](https://github.com/j3xugit/RaptorX-Contact/blob/master/Common/LoadHHM.py) and place the file in the "pplm_contact" directory of the PPLM package, or use the pre-packaged version within the "pplm_contact" directory.
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5. **ESM-MSA** for Feature Generation: Install the [ESM package](https://github.com/facebookresearch/esm), or use the pre-packaged version within "pplm_contact/external_tools" directory. Download the pre-trained [ESM-MSA model](https://dl.fbaipublicfiles.com/fair-esm/models/esm_msa1_t12_100M_UR50S.pt) and set the "esm_msa_model" parameter in the "config.py" file.
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## Download parameters
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Run the download_parameter.sh script located in the models/ folder of pplm/, pplm_ppi/, pplm_affinity/, and pplm_contact/
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