Update README.md

README.md

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----
-license: mit
----
+---
+license: cc-by-4.0
+tags:
+- ai4science
+- aidd
+- virtual_screening
+pretty_name: GenomeScreen
+---
+
+
+[![image/png](https://cdn-uploads.huggingface.co/production/uploads/635247ab507b679c3c5b7801/kTQ67Q-a6Whi6XzMvqHvC.png)](https://drug-the-whole-genome.yanyanlan.com/)
+
+# GenomeScreen  
+The first comprehensive genome-wide virtual screening dataset for human proteins.
+
+## Dataset Details  
+
+### Dataset Description  
+**GenomeScreen** represents the largest and most comprehensive virtual screening dataset ever created, containing over **2 million potential drug hits** targeting **>20,000 binding pockets** across **~10,000 human proteins** predicted by AlphaFold2. This dataset was generated through an unprecedented **10 trillion protein-ligand scoring operations**, covering nearly half of the human genome.
+
+Key features:
+- Screened **500+ million drug-like molecules** from ZINC and Enamine REAL databases
+- Completed in just **24 hours** on 8×A100 GPUs using DrugCLIP technology
+- Includes **diverse chemical clusters** selected via CADD pipeline
+- Covers **all major human protein families**
+
+- **Curated by:** Yinjun Jia, Bowen Gao, Jiaxin Tan, Jiqing Zheng, Xin Hong, et al. (Tsinghua University)
+- **Hosted at:** [Drug-The-Whole-Genome Portal](https://drug-the-whole-genome.yanyanlan.com)
+- **Language(s):** Structured scientific data (PDB, SMILES, docking grids)
+- **License:** CC-BY 4.0
+
+### Dataset Sources  
+- **Repository:** [GitHub - THU-ATOM/Drug-The-Whole-Genome](https://github.com/THU-ATOM/Drug-The-Whole-Genome)
+- **Paper:** Jia et al., *Deep contrastive learning enables genome-wide virtual screening* ([bioRxiv 2024.09.02.610777](https://www.biorxiv.org/content/10.1101/2024.09.02.610777))
+- **Data Portal:** [Genome Screening Results](https://drug-the-whole-genome.yanyanlan.com)
+
+---
+
+## Uses  
+
+### Direct Use  
+- **Hit Identification:** Rapid discovery of lead compounds for novel targets
+- **Target Druggability:** Assess ligandability of human proteins at scale
+- **Method Benchmarking:** Test docking/scoring algorithms against gold-standard data
+- **AI Training:** Train foundation models for structure-based drug design
+
+### Out-of-Scope Use  
+- **Clinical Decision Making:** Requires experimental validation
+- **Absolute Affinity Prediction:** Scores reflect relative rankings only
+- **Non-human Applications:** Focused exclusively on human proteome
+
+---
+
+## Dataset Structure  
+
+### Files and Formats  
+```
+|- target_protein/
+  |- pocket_1/
+    |- refined_structure.pdb.gz # Processed AlphaFold2 structure
+    |- docking_grid.in # Pre-computed grid coordinates
+    |- top_molecules.csv # Ranked hits with DrugCLIP scores
+    |- clustered_hits/ # Chemically diverse subsets
+    |- cluster_representatives.csv
+  |- pocket_2/
+```
+
+
+### Key Contents  
+- **Protein Structures:** Processed AlphaFold2 predictions with defined pockets
+- **Docking Grids:** Pre-computed binding site coordinates (x,y,z)
+- **Ranked Hits:** Top molecules with SMILES, DrugCLIP scores, and poses
+- **Cluster Representatives:** Diverse subsets for hit expansion
+
+---
+
+### Statistics  
+| Metric                     | Value               |
+|----------------------------|---------------------|
+| Proteins Screened          | ~10,000            |
+| Binding Pockets            | >20,000            |
+| Molecules Screened          | 500+ million       |
+| Scoring Operations          | >10 trillion       |
+| Potential Hits Identified  | 2+ million         |
+| GPU Hours                  | 192 (8×A100×24h)   |
+
+---
+
+## Citation  
+
+**BibTeX:**  
+```bibtex
+@article{Jia2024GenomeScreen,
+  title={Deep contrastive learning enables genome-wide virtual screening},
+  author={Jia, Yinjun and Gao, Bowen and Tan, Jiaxin and Zheng, Jiqing and Hong, Xin and Zhu, Wenyu and Tan, Haichuan and Xiao, Yuan and Tan, Liping and Cai, Hongyi and Huang, Yanwen and Deng, Zhiheng and Jin, Yue and Yuan, Yafei and Tian, Jiekang and He, Wei and Ma, Weiying and Zhang, Yaqin and Yan, Chuangye and Liu, Lei and Zhang, Wei and Lan, Yanyan},
+  journal={bioRxiv},
+  year={2024},
+  doi={10.1101/2024.09.02.610777},
+  url={https://www.biorxiv.org/content/10.1101/2024.09.02.610777}
+}
+```
+
+## Contact
+
+For dataset access and inquiries:
+
+- **Data Portal:** https://drug-the-whole-genome.yanyanlan.com
+- **Correspondence:** lanyanyan@air.tsinghua.edu.cn
+- **Technical Support:** github.com/THU-ATOM/Drug-The-Whole-Genome/issues