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  ---
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  license: cc-by-4.0
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  tags:
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- - Protein Binder Design
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- - Proteins
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- - Structural Biology
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- - synthetic
 
 
 
 
 
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  pretty_name: Human Bindome
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  size_categories:
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  - 100K<n<1M
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  ---
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- # Dataset Card for Human Bindome
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- The Human Bindome
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- This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
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- ## Dataset Details
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- ### Dataset Description
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- <!-- Provide a longer summary of what this dataset is. -->
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- - **Curated by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **License:** [More Information Needed]
 
 
 
 
 
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- ### Dataset Sources [optional]
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- <!-- Provide the basic links for the dataset. -->
 
 
 
 
 
 
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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- ## Uses
 
 
 
 
 
 
 
 
 
 
 
 
 
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- <!-- Address questions around how the dataset is intended to be used. -->
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- ### Direct Use
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- <!-- This section describes suitable use cases for the dataset. -->
 
 
 
 
 
 
 
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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- [More Information Needed]
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- ## Dataset Structure
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- <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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- [More Information Needed]
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- ## Dataset Creation
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- ### Curation Rationale
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- <!-- Motivation for the creation of this dataset. -->
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- [More Information Needed]
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- ### Source Data
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- <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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- #### Data Collection and Processing
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- <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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- [More Information Needed]
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- #### Who are the source data producers?
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-
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- <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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-
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- [More Information Needed]
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-
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- ### Annotations [optional]
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-
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- <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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-
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- #### Annotation process
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- <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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- [More Information Needed]
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-
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- #### Who are the annotators?
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- <!-- This section describes the people or systems who created the annotations. -->
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- [More Information Needed]
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- #### Personal and Sensitive Information
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-
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- <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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- [More Information Needed]
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-
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- [More Information Needed]
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- **APA:**
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- [More Information Needed]
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- [More Information Needed]
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- ## Dataset Card Authors [optional]
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- [More Information Needed]
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- ## Dataset Card Contact
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- [More Information Needed]
 
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  ---
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  license: cc-by-4.0
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  tags:
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+ - protein-design
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+ - target-binder-design
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+ - protein-interface
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+ - protein-protein-interaction
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+ - structural-biology
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+ - benchmark
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+ - bindcraft
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+ - foldseek
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+ - pinder
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  pretty_name: Human Bindome
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  size_categories:
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  - 100K<n<1M
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  ---
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+ # Designed Target-Binder Interface Benchmark
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+ ## Dataset Description
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+ This dataset contains designed target-binder protein complexes generated with [BindCraft](https://www.nature.com/articles/s41586-025-09429-6). Each row in `metadata.csv` corresponds to one designed two-chain target-binder complex and links the design metadata, benchmark split assignment, interface-cluster assignment, [ProteinMPNN](https://www.science.org/doi/10.1126/science.add2187) binder variant information, and associated structure files. For each design, the release includes the bound target-binder complex structure as well as predicted apo structures for the target and binder.
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+ The dataset is intended for machine-learning studies of designed protein-protein interactions, including model training, validation, and benchmark evaluation.
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+ ## Files
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+ The dataset is indexed by a single `metadata.csv` file. Benchmark partitions are encoded in the `split` column. Structure paths are provided directly in the metadata table.
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+ The released complex structures are full target-binder complex models in a superimposed coordinate frame. The relative path to each structure is given in the `target_binder_complex_pdb_path` column. Predicted apo structures for the target and binder are provided under `target_alone_pdb_path` and `binder_alone_pdb_path`.
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+ Repository organization:
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+ ```text
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+ .
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+ ├── README.md
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+ ├── metadata.csv
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+ └── structures/
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+ ├── [target_name_1].tar.gz
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+ ├── [target_name_2].tar.gz
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+ └── ...
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+ ```
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+ Each archive contains the structure files for one target:
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+ ```text
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+ [target_name].tar.gz
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+ └── [target_domain]/
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+ ├── [design_name].pdb
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+ ├── [design_name]_binder_alone.pdb
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+ └── [design_name]_full_target_structure.pdb
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+ ```
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+ ## Metadata Columns
 
 
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+ | Column | Description |
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+ | -------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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+ | `design_name` | Unique identifier for the designed target-domain–binder complex. |
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+ | `target_domain` | Target domain or subdomain used for design. |
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+ | `target_name` | Name or identifier of the full target. |
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+ | `design_seed` | Integer design seed used to generate the binder. |
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+ | `mpnn_variant` | ProteinMPNN variant index for the same design seed. |
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+ | `split` | Split assignment: `train`, `validation`, `test`, or `deleaked`. |
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+ | `paired_interface_cluster_id` | Paired target-side/binder-side interface cluster identifier used for leakage-controlled splitting. |
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+ | `cluster_member_type` | Cluster membership annotation for the validation and test splits. `cluster_rep` denotes the randomly selected representative used for one-per-cluster validation/test evaluation; `cluster_member` denotes other members of the same cluster. |
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+ | `structure_archive` | Relative path to the target-level `tar.gz` archive containing the structure files. |
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+ | `target_binder_complex_pdb_path` | Path inside the archive to the superimposed target-domain–binder complex PDB file. |
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+ | `binder_alone_pdb_path` | Path inside the archive to the binder-only PDB file. |
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+ | `target_alone_pdb_path` | Path inside the archive to the target-only PDB file. |
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+ ## Dataset Splits
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+ The dataset provides predefined train, validation, and test partitions. Complexes removed during leakage control are annotated as `deleaked` and are not part of the usable benchmark.
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+ | Split | Complexes | Share |
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+ |---|---:|---:|
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+ | train | 233,170 | 76.16% |
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+ | validation | 21,260 | 6.94% |
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+ | test | 19,777 | 6.46% |
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+ | deleaked | 31,939 | 10.43% |
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+ | total | 306,146 | 100.00% |
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+ | usable benchmark | 274,207 | 89.57% |
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+ The usable benchmark consists of the train, validation, and test partitions only.
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+ ## Split Construction
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+ Leakage was defined at the level of structural interface similarity, rather than by target identity, binder identity, sequence identity, or design metadata alone. This is important because designed complexes can share related binding epitopes or recurrent interface geometries even when their identifiers or sequences differ.
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+ The split was constructed using an interface-level procedure adapted from [PINDER](https://www.biorxiv.org/content/10.1101/2024.07.17.603980v4). Interface residues were defined as residues with at least one heavy backbone atom within 10 Å of the opposite chain. Target and binder chains were aligned all-vs-all with [Foldseek](https://www.nature.com/articles/s41587-023-01773-0). Alignments were retained for clustering only when the aligned region covered at least 50% of an interface residue set.
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+ The resulting interface-similarity graph was thresholded using the PINDER clustering threshold of 0.70, and weighted asynchronous label propagation was used to assign chain-interface cluster labels. Each complex was assigned to a paired-interface cluster defined by its target-side and binder-side interface cluster identifiers. Train, validation, and test assignment was performed at the paired-interface-cluster level.
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+ After holdout clusters were selected, PINDER’s depth-2 transitive deleaking logic was applied using the deleaking threshold of 0.55. Candidate training complexes connected to validation or test complexes through one or two interface-similarity graph edges were assigned to the `deleaked` partition and excluded from the usable benchmark.
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+ ## Redundancy Audit
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+ As an independent audit, we assessed whether ProteinMPNN sister variants derived from the same binder backbone on the same target domain were assigned to the same paired-interface cluster. ProteinMPNN grouping was not used as input to the clustering algorithm.
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+ Among 120,609 multi-member backbone groups, 120,082 were contained within a single paired-interface cluster, whereas 527 were split across multiple clusters. 99.56% of multi-member backbone groups were captured by the paired-interface clustering procedure.
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+ ## Intended Use
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+ The predefined split should be used for benchmark comparisons at the interface level. The validation split is intended for model selection and hyperparameter tuning. The test split should be reserved for final evaluation.
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+ Users should not randomly repartition the dataset for benchmark claims, because random or label-based splits may place structurally related interfaces in both training and evaluation partitions.
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+ ## Citation
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+ If you use this dataset, please cite our publication
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+ ## Acknowledgments
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+ We thank the authors of the following methods, datasets and tools, on which Bindome is built:
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+ - [BindCraft](https://www.nature.com/articles/s41586-025-09429-6)
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+ - [ColabDesign](https://github.com/sokrypton/ColabDesign)
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+ - [AlphaFold2](https://www.nature.com/articles/s41586-021-03819-2)
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+ - [AlphaFold-Multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v2)
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+ - [ProteinMPNN](https://www.science.org/doi/10.1126/science.add2187)
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+ - [Foldseek](https://www.nature.com/articles/s41587-023-01773-0)
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+ - [PINDER](https://www.biorxiv.org/content/10.1101/2024.07.17.603980v4)