preparation for 2.0-rc.2

build.gradle

@@ -4,7 +4,7 @@ apply plugin: 'idea'
 
 
 group = 'cz.siret'
-version = '2.0_RC2'
+version = '2.0-rc.2'
 
 
 description = 'Ligand binding site prediction based on machine learning.'

distro/README.md

@@ -0,0 +1,127 @@
+
+P2RANK 
+======
+Ligand-binding site prediction tool based on machine learning.
+
+
+### Requirements
+
+* Java 1.8 or newer for execution
+* PyMOL 1.7.x for viewing visualizations
+
+### Setup
+
+P2RANK requires no installation. Binary packages can be downloaded from the project website.
+
+* **Download**: http://siret.ms.mff.cuni.cz/p2rank
+* Source code: https://github.com/rdk/p2rank
+* Datasets: https://github.com/rdk/p2rank-datasets
+
+### Usage
+
+<pre>
+<b>prank</b> predict -f test_data/1fbl.pdb         # predict pockets on a single pdb file 
+</pre>  
+
+See more usage examples below...
+
+### Compilation
+
+To compile P2RANK you need Gradle (https://gradle.org/). Build with `./make.sh` or `gradle assemble`.
+
+### Algorithm
+
+P2RANK makes predictions by scoring and clustering points on the protein's Connolly surface. Ligandability score of individual points is determined by a machine learning based model trained on the dataset of known protein-ligand complexes.
+
+Slides: http://bit.ly/p2rank_slides (somewhat dated overview)
+
+
+Usage Examples
+--------------
+
+Following commands can be executed in the installation directory.
+
+### Print help
+
+~~~
+prank help
+~~~
+
+### Predict ligand binding sites (P2RANK algorithm)
+
+~~~
+prank predict test.ds                             # run on whole dataset (containing list of pdb files)
+
+prank predict -f test_data/1fbl.pdb               # run on single pdb file
+prank predict -f test_data/1fbl.pdb.gz            # run on single gzipped pdb file
+
+prank predict -threads 8          test.ds         # specify no. of working threads for parallel processing
+prank predict -o output_here      test.ds         # explicitly specify output directory
+prank predict -c predict2.groovy  test.ds         # specify configuration file (predict2.groovy uses 
+                                                    different prediction model and combination of parameters)
+~~~
+
+### Evaluate prediction model
+...on a file or a dataset with known ligands.
+
+~~~
+prank eval-predict -f test_data/1fbl.pdb
+prank eval-predict test.ds
+~~~
+
+### Prediction output 
+
+   For each file in the dataset program produces a CSV file in the output directory named 
+   `<pdb_file_name>_predictions.csv`, which contains an ordered list of predicted pockets, their scores, coordinates 
+   of their centroids and list of PDBSerials of adjacent amino acids and solvent exposed atoms.
+
+   If coordinates of Connolly points that belong to predicted pockets are needed they can be found
+   in `visualizations/data/<pdb_file_name>_points.pdb`. There "Residue sequence number" (23-26) of HETATM record 
+   cocrresponds to the rank of corresponding pocket (points with value 0 do not belong to any pocket).
+
+### Configuration
+
+You can override default params with custom config file:
+
+~~~
+prank predict -c config/example.groovy  test.ds
+prank predict -c example.groovy         test.ds
+~~~
+
+
+It is also possible to override the default params on the command line using their full name. To see complete list of params look into `config/default.groovy`.
+
+~~~
+prank predict                   -seed 151 -threads 8  test.ds
+prank predict -c example.groovy -seed 151 -threads 8  test.ds
+~~~
+
+### Rescoring (PRANK algorithm)
+
+In addition to predicting new ligand binding sites, P2RANK is also able to rescore pockets predicted by other methods (Fpocket and ConCavity are supported at the moment).
+
+~~~
+prank rescore test_data/fpocket.ds
+prank rescore fpocket.ds                 # test_data/ is default 'dataset_base_dir'
+prank rescore fpocket.ds -o output_dir   # test_output/ is default 'output_base_dir'
+~~~
+
+### Evaluate rescoring model
+
+~~~
+prank eval-rescore fpocket-pairs.ds
+~~~
+
+
+## Thanks
+
+This program builds upon software written by other people, either through library dependencies or through code included in it's source tree (where no library builds were available). Notably:
+* FastRandomForest by Fran Supek (https://code.google.com/archive/p/fast-random-forest/)
+* KDTree by Rednaxela (http://robowiki.net/wiki/User:Rednaxela/kD-Tree)
+* BioJava (https://github.com/biojava)
+* Chemistry Development Kit (https://github.com/cdk)
+* Weka (http://www.cs.waikato.ac.nz/ml/weka/)
+
+## Contributing
+
+We welcome any bug reports, enhancement requests, and other contributions. To submit a bug report or enhancement request, please use the [GitHub issues tracker](https://github.com/rdk/p2rank/issues). For more substantial contributions, please fork this repo, push your changes to your fork, and submit a pull request with a good commit message. 

new.groovy

@@ -12,7 +12,7 @@ import cz.siret.prank.program.params.Params
      * all output of the prorgam will be stored in subdirectores of this directory
      * (set absolute path or path relative to install dir, null defaults to working dir)
      */
-    output_base_dir = "../../p2rank-results/2.0_RC2"
+    output_base_dir = "../../p2rank-results/2.0-rc.2"
 
     visualizations = false
 

workdef.groovy

@@ -15,7 +15,7 @@ import cz.siret.prank.program.params.Params
      * all output of the prorgam will be stored in subdirectores of this directory
      * (set absolute path or path relative to install dir, null defaults to working dir)
      */
-    output_base_dir = "../../p2rank-results/2.0_RC2"
+    output_base_dir = "../../p2rank-results/2.0-rc.2"
 
 
     visualizations = false

working.groovy

@@ -12,7 +12,7 @@ import cz.siret.prank.program.params.Params
      * all output of the prorgam will be stored in subdirectores of this directory
      * (set absolute path or path relative to install dir, null defaults to working dir)
      */
-    output_base_dir = "../../p2rank-results/2.0_RC2"
+    output_base_dir = "../../p2rank-results/2.0-rc.2"
 
     visualizations = false