Posebench

- Added results with AlphaFold 3 predicted structures (now the default)
- Added results for the new Chai-1 model from Chai Discovery
- Added a new inference sweep pipeline for HPC clusters to allow users to quickly run an exhaustive sweep of all baseline methods, datasets, and tasks e.g., using generated batch scripts and a SLURM scheduler
- Updated Zenodo links to point to the latest version of the project's Zenodo record, which now includes the above-mentioned AlphaFold 3 predicted structures and baseline method results using them
- Updated documentation project-wide according to the additions listed above
- Fixed some CI testing issues

- Renamed `src` root directory to `posebench` to support `pip` packaging
- Added and documented `pip` installation option
- Added mmCIF to PDB file conversion script
- Added apo-to-holo predicted protein structure accuracy assessment and plotting script
- Added support to `notebooks/dockgen_inference_results_plotting.ipynb` for analyzing the protein-ligand interactions within the PDBBind 2020 dataset's experimental structures
- Updated dataset documentation in `README.md`

- Added a notebook for plotting expanded DockGen benchmark results
- Added support for scoring relaxed-protein predictions
- Fixed runtime error for relaxed-protein energy minimization
- Fixed runtime error for compute benchmarking RoseTTAFold-All-Atom predictions

- Added P2Rank as a new binding site prediction method available to use with AutoDock-Vina
- Added OpenJDK to the `PoseBench` Conda environment to enable P2Rank inference
- Added a script to benchmark the required compute resources for each baseline method
- Updated citation
- Corrected directory navigation instructions (i.e., `cd` references) in `README.md` to reflect the directory structure of each Zenodo archive file
- Corrected Biopython, NumPy, and ProDy versions in the DiffDock Conda environment to avoid GCC compilation errors

- First public release