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The -cofactors flag and dataset cofactors column accept LigandDefinition
specifiers ("FAD", "FAD[atom_id:N]", "FAD[contact_res_ids:A_T259,A_D246]").
Matched HET groups merge into the protein surface (proteinAtoms) and are
excluded from ligand listings; per-item resolution lets a dataset column
override the global Params.cofactors.
New: analyze cofactors subcommand (HETATM survey + specifier dry-run),
PyMOL teal-stick visualization (vis_highlight_cofactors), distant-cofactor
and chain-excluded WARN diagnostics, aa_mapping collision WARN (R19),
drop-in safety benchmark with byte-equality on a never-present specifier.
Documentation in documentation/cofactors.md (user-facing) and
documentation/dev/cofactors.md (engineering record with R1-R24 design choices
and post-merge audit fixes). Tests in CofactorHandlerTest,
CofactorIntegrationTest, CofactorPipelineTest, CofactorAnalyzeTest,
DataTableCsvTest plus a Log4jCapture test helper.
Documentation
This directory contains documentation and tutorials for P2Rank. Note that the coverage is spotty and incomplete -- not all features and workflows are documented here.
Usage
| File | Description |
|---|---|
| rescoring.md | Rescoring predictions from other pocket prediction methods (Fpocket, Pocketeer, etc.) |
| export-points.md | Exporting SAS points with feature vectors and predicted ligandability scores |
| aa-mapping.md | Non-canonical amino acid residue mapping to standard residues |
| hidden-commands.md | Miscellaneous hidden commands and analysis tools |
| random-examples.md | Assorted command-line examples for prediction and evaluation |
Training
| File | Description |
|---|---|
| training-tutorial.md | Training and evaluating custom models, crossvalidation, grid optimization |
| feature-setup.md | Feature vector configuration and introduction to adding new features |
| new-feature-evaluation-tutorial.md | Implementing a new feature and evaluating its contribution to prediction |
| hyperparameter-optimization-tutorial.md | Grid and Bayesian optimization of algorithm parameters |
| training-score-transformers.md | Training probability and z-score transformers for pocket and residue scores |