This 3D proximity tool can be used to identify mutation hotspots from the linear protein sequence and correlates the hotspots with known or potentially interacting domains and mutations. Mutation-mutation and mutation-drug clusters can also be identified and viewed.

    Program:     HotSpot3D - 3D mutation proximity analysis program.
    Version:     V0.4
     Author:     Beifang Niu, John Wallis, Adam D Scott, & Sohini Sengupta

      Usage:     hotspot3d <command> [options]

Key commands:

    search    --  3D mutation proximity searching
	post      --  Post-processing on pairwise data
    cluster   --  Determine clusters from HotSpot3D inter, intra, and druggable pairwise data 
	sigclus   --  Determine significance of clusters
	summary   --  Determine cluster-level measures
    visual    --  Visulization of 3D proximity

    drugport  --  Parse drugport database 
    uppro     --  Update proximity files
    calpro    --  Calculate proximity file for one UniProt ID
    calroi    --  Generate region of interest (ROI) information
    statis    --  Calculate p_values for pairs of mutations
    anno      --  Add region of interest (ROI) annotation
    trans     --  Add transcript annotation 
    homo      --  Add homology PDB structures 
    cosmic    --  Add COSMIC annotation to proximity file
    prior     --  Prioritization
    help      --  this message

SUPPORT For user support please mail [email protected]

Prerequisites:

In order to install HotSpot3D package, first install CPANM (cpanm - get, unpack build and install modules from CPANM) NOTE: Some steps may require adding --force to install successfully.

    sudo apt-get install cpanminus

Another way to install cpanminus is to just download it, as per the installer

    curl -LO http://xrl.us/cpanm
    chmod +x cpanm

Or by using cpan

	cpan App::cpanminus

Intall Perl5 local lib

    cpanm --local-lib=~/perl5 local::lib && eval $(perl -I ~/perl5/lib/perl5/ -Mlocal::lib)

Intall LWP::Simple module

    sudo apt-get install libwww-perl

Intall Test::Most module

    wget http://search.cpan.org/CPAN/authors/id/O/OV/OVID/Test-Most-0.34.tar.gz
    cpanm Test-Most-0.34.tar.gz

Install HotSpot3D package:

    git clone https://github.com/ding-lab/hotspot3d
    cd hotspot3d
    cpanm HotSpot3D-#.#.tar.gz

(Installations under some organizations may use an internal perl version. To make use of the /usr/ perl, edit the first line of ~/perl5/bin/hotspot3d. from: #!/org/bin/perl to: #!/usr/bin/perl)

Preprocessing procedure

1. Run drugport module to parse Drugport data and generate a drugport parsing results flat file :

    hotspot3d drugport --pdb-file-dir=pdb_files_dir --output-file=drugport_parsing_results_file
   

2. Run 3D proximity calculation ( this step needs one output directory to store all of the data from the pre-processing procedure and one directory which contains pdb files downloaded from the PDB website. This step will automatically download PDB files if the necessary PDB file is not yet in the pdb files directory) :

    hotspot3d uppro --output-dir=preprocessing_output --pdb-file-dir=pdb_files_dir --drugport-file=drugport_parsing_results_file --max-3d-dis=100 1>hotspot3d.preprocessing.t.err 2>hotspot3d.preprocessing.t.out
   

3. Calculate protein domain information for each UniProt ID :

    hotspot3d calroi --output-dir=preprocessing_output
   

4. Significance determination calculation :

    hotspot3d statis --output-dir=preprocessing_output
   

5. Add protein domain annotation information to 3D proximity information :

    hotspot3d anno --output-dir=preprocessing_output
   

6. Choose transcripts based on the alignment between Uniprot sequence and human peptides sequences :

    hotspot3d trans --output-dir=preprocessing_output
   

7. Add cosmic v67 information to 3D proximity results :

    mkdir preprocessing_output/cosmic
    cp COSMIc/cosmic_67_for_HotSpot3D_missense_only.tsv.bz2 ./preprocessing_output/cosmic/
    cd ./preprocessing_output/cosmic/ 
    bzip2 -d cosmic_67_for_HotSpot3D_missense_only.tsv.bz2
    hotspot3d cosmic --output-dir=preprocessing_output
   

8. Prioritization :

    hotspot3d prior --output-dir=preprocessing_output --p-value=0.1 --3d-dis=20 --linear-dis=0.5
   

3D proximity searching based on prioritization results and visualization

1. Proximity searching (acquire proximity information for input mutations):

    hotspot3d search --maf-file=pancan19_input.maf --data-dir=preprocessing_output --output-prefix=pancan19 --skip-silent 1>pancan19.t.out 2>pancan19.t.err
   

2. Post-processing of pairwise data (required for cluster step):

    hotspot3d post --maf-file=pancan19_input.maf --input-prefix=pancan19
   

3. Cluster pairwise data:

    hotspot3d cluster --inter-intra-proximity-file=interactions_file --data-location-file=location_data --output-file=clustering.out --target-nontarget-file=drug_data_file
   

4. Cluster significance calculation:

    hotspot3d sigclus --prep-dir=preprocessing_output --pairwise=pairwise_file --clusters=clusters_file --output=output_file
   

5. Clustering Summary:

    hotspot3d summary --clusters-file=cluster_file --output-file=output_summary
   

6. Visualization:

    hotspot3d visual --pymol-dir=/usr/bin/pymol --output-dir=pymol_out --pdb-dir=pdb_files_dir