{"url":"/dataset/bindingdb","name":"BindingDB","full_name":"The Binding Database","description_markdown":"BindingDB is a public, web-accessible database of measured binding affinities, focusing chiefly on the interactions of protein considered to be drug-targets with small, drug-like molecules. As of May 27, 2022, BindingDB contains 41,296 Entries, each with a DOI, containing 2,519,702 binding data for 8,810 protein targets and 1,080,101 small molecules. There are 5,988 protein-ligand crystal structures with BindingDB affinity measurements for proteins with 100% sequence identity, and 11,442 crystal structures allowing proteins to 85% sequence identity.You can also use BindingDB data through the Registry of Open Data on AWS: https://registry.opendata.aws/binding-db. This dataset using the split by TransformerCPI(doi.org/10.1093/bioinformatics/btaa524)","description_withheld":null,"homepage":"https://www.bindingdb.org/bind/index.jsp","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Drug Discovery","url":"/task/drug-discovery","datasets_with_task":"/datasets/task/drug-discovery"}],"languages":[],"variants":["BindingDB","BindingDB IC50"],"data_loaders":[],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/drug-discovery-on-bindingdb","task":"Drug Discovery","dataset_variant":"BindingDB","rows":4,"metrics":["AUC"],"first_row_in_archive_order":{"model":"AttentionSiteDTI","paper":"/paper/attentionsitedti-an-interpretable-graph-based","metrics":{"AUC":"0.9717"},"code_links":[{"title":"yazdanimehdi/AttentionSiteDTI","url":"https://github.com/yazdanimehdi/AttentionSiteDTI"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/drug-discovery-on-bindingdb-ic50","task":"Drug Discovery","dataset_variant":"BindingDB IC50","rows":2,"metrics":["Pearson Correlation","RMSE"],"first_row_in_archive_order":{"model":"DeepDTA","paper":"/paper/deepdta-deep-drug-target-binding-affinity","metrics":{"Pearson Correlation":"0.848","RMSE":"0.782"},"code_links":[{"title":"kexinhuang12345/DeepPurpose","url":"https://github.com/kexinhuang12345/DeepPurpose"},{"title":"hkmztrk/DeepDTA","url":"https://github.com/hkmztrk/DeepDTA"},{"title":"Yindong-Zhang/GraphConvolutionDrugTargetInteration","url":"https://github.com/Yindong-Zhang/GraphConvolutionDrugTargetInteration"},{"title":"CAVED123/DeepPurpose","url":"https://github.com/CAVED123/DeepPurpose"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/attentionsitedti-an-interpretable-graph-based","title":"AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification","date":"2022-07-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/an-adaptive-graph-learning-method-for","title":"An adaptive graph learning method for automated molecular interactions and properties predictions","date":"2022-06-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/drug-target-affinity-prediction-using-graph","title":"Drug–target affinity prediction using graph neural network and contact maps","date":"2020-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/transformercpi-improving-compound-protein","title":"TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments","date":"2020-05-19","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/deepaffinity-interpretable-deep-learning-of","title":"DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks","date":"2018-06-20","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/deepdta-deep-drug-target-binding-affinity","title":"DeepDTA: Deep Drug-Target Binding Affinity Prediction","date":"2018-01-30","rows_on_this_dataset":1,"code_links":4,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}