Pykvfinder

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, hydropathy and interface residues and their frequencies) in target biomolecular structures using a dual-probe system.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables the full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterization are depth (per cavity point, maximum and average) and hydropthy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, WimleyWhite and ZhaoLondon).

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, hydropathy and interface residues and their frequencies) in target biomolecular structures using a dual-probe system.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables the full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterization are depth (per cavity point, maximum and average) and hydropthy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, WimleyWhite and ZhaoLondon).

Python-C parallel KVFinder

The Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth, hydropathy and interface residues and their frequencies) in target biomolecular structures using a dual-probe system.

Python package

The pyKVFinder package is easily imported into Python scripts with a set of functions that enables the full and standard workflows and step-by-step analysis.

Command-line interface

The integrated command-line interface performs cavity detection and characterization with a customizable set of parameters. The standard characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterization are depth (per cavity point, maximum and average) and hydropthy (per surface point and average) with six options of built-in hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, WimleyWhite and ZhaoLondon).

Python-C parallel KVFinder
=====================

Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth [optional], hydropathy [optional] and interface residues and their frequencies) in biomolecular structures.

The default characterization includes shape, volume, area, and interface residues and their frequencies. The optional characterization are depth (per cavity point, maximum and average) and hydropthy (per surface point and average) with five choices of native hydrophobicity scales (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, WimleyWhite and ZhaoLondon).

New features
-----------------
- Hydropathy mapping (CLI and package):
- Hydrophobicity scale mapped at surface points and exported as B-factor in a hydropathy PDB file;
- Average hydropathy per cavity in TOML results file.
- Six options of hydrophobicity scale (EisenbergWeiss, HessaHeijne, KyteDoolittle, MoonFleming, WimleyWhite and ZhaoLondon) or a TOML-formatted file with a mandatory format.

Python-C parallel KVFinder
=====================

Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities (shape, volume, area, depth [optional] and interface residues) in biomolecular structures. The characterization includes shape, volume, area and interface residues.

New feature
----------------
- Depth calculation (CLI and package):
- Depth of cavity points exported as B-factor in cavity PDB file;
- Maximum depth per cavity in TOML results file;
- Average depth per cavity in TOML results file.
- Add benchmarking script

Bug fixes
------------
- Installation error: `duplicate vol definition in grid.h`
- Conditions in define_surface_points function

Python-C parallel KVFinder
=====================

Python-C parallel KVFinder (pyKVFinder) detects and characterizes cavities in biomolecular structures. The characterization includes shape, volume, area and interface residues.

Improvements compared to parKVFinder:
- Integration with numpy (SWIG-C);
- Parallel routines for filling atoms into the 3D grid (Probe In and Probe Out) and defining interface residues surrounding detected cavities;
- Argument to exclude backbone atoms when defining interface residues: `--ignore_backbone`;
- Simpler installation: `pip install -e pyKVFinder`;
- Python package: `import pyKVFinder`;
- Simpler box adjustment mode: only use configuration file for defining 3D custom grid (`--box <.toml>`);
- No need for parameters file (`parameters.toml`) anymore.

Box Configuration File Templates
--------------------------------------------
There are two methods for defining a custom 3D grid in pyKVFinder.

The first directly defines four vertices of the 3D grid (origin, X-axis, Y-axis and Z-axis), the template is shown above:

TOML
[box]