insitro/kindel
KinDEL is a large DNA-encoded library dataset containing two kinase targets (DDR1 and MAPK14) for benchmarking machine learning models.
This dataset provides a large collection of DNA-encoded library (DEL) screening results for two kinase targets: DDR1 and MAPK14. It takes raw molecular data, including SMILES strings and sequence counts, and provides structured training and held-out test sets, complete with experimental binding measurements (Kd values). Medicinal chemists and cheminformaticians can use this to develop and benchmark machine learning models for predicting small molecule-protein interactions.
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Use this if you are a medicinal chemist or data scientist working on drug discovery and need to train or evaluate machine learning models that predict how well small molecules bind to kinase targets based on DEL screening data.
Not ideal if you are looking for experimental results for non-kinase targets or are not focused on developing or benchmarking machine learning models for drug discovery.
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Python
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Last pushed
Sep 02, 2025
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