From cf26aa9c9448b2f9181ef56b77c5ec3b860b7486 Mon Sep 17 00:00:00 2001 From: rdk Date: Mon, 4 Nov 2024 08:13:08 +0100 Subject: [PATCH] update readme --- README.md | 11 +++++++---- .../cz/siret/prank/program/params/Params.groovy | 1 + 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 7cc879b4..6edac944 100644 --- a/README.md +++ b/README.md @@ -111,7 +111,8 @@ prank predict -c alphafold test.ds # use alphafold config and model (confi mapping to predicted pockets, and a calibrated probability of being a ligand-binding residue * PyMol and ChimeraX visualizations in `visualizations/` directory (`.pml` and `.cxc` scripts with data files in `data/`) * generating visualizations can be turned off by `-visualizations 0` parameter - * coordinates of the SAS points can be found in `visualizations/data/_points.pdb.gz`. There the "Residue sequence number" (23-26 of HETATM record) + * `-vis_renderers 'pymol,chimerax'` parameter can be used to turn individual visualization renderers on/off + * coordinates of SAS points can be found in `visualizations/data/_points.pdb.gz`. There the "Residue sequence number" (23-26 of HETATM record) corresponds to the rank of the corresponding pocket (points with value 0 don't belong to any pocket) * `-vis_copy_proteins 0` parameter can be used to turn off copying of protein structures to the visualizations directory (faster but visualizations won't be portable) @@ -163,20 +164,22 @@ are supported at the moment). Rescoring output: * `_rescored.csv`: list of pockets sorted by the new score * `_predictions.csv`: same as with `prank predict` (since 2.5) + * Note: probability column is calibrated for rescoring fpocket predictions * visualizations -Note: probability column in `predictions.csv` is calibrated for rescoring fpocket predictions. - ~~~bash prank rescore fpocket.ds prank rescore fpocket.ds -o output_here # explicitly specify output directory -prank rescore fpocket.ds -c rescore_2024 # use a new experimental rescoring model +prank rescore fpocket.ds -c rescore_2024 # use new experimental rescoring model (recommended for alphafold models) prank eval-rescore fpocket.ds # evaluate rescoring model on a dataset with known ligands ~~~ For rescoring the dataset file needs to have a specific 2-column format. See examples in `test_data/`: `fpocket.ds`, `concavity.ds`, `puresnet.ds`. +New experimental rescoring model `-c rescore_2024` shows promising result but hasn't been fully evaluated yet. It is recommended for AlphaFold models, NMR and cryo-EM structures since it doesn't depend on b-factor as a feature. + + #### Run fpocket and rescore in one command diff --git a/src/main/groovy/cz/siret/prank/program/params/Params.groovy b/src/main/groovy/cz/siret/prank/program/params/Params.groovy index 38d912f2..6199e3ae 100644 --- a/src/main/groovy/cz/siret/prank/program/params/Params.groovy +++ b/src/main/groovy/cz/siret/prank/program/params/Params.groovy @@ -726,6 +726,7 @@ class Params { /** * zip PyMol visualizations to save space */ + @Deprecated @RuntimeParam boolean zip_visualizations = false