TY - JOUR
T1 - DeepCYP: an integrated deep learning web server for the holistic “pathway-site product” prediction of CYP450 metabolism
AU - Zhou, Yiling
AU - Yang, Sen
AU - Wang, Xiaoli
AU - He, Yuanhang
AU - Tian, Yao
AU - Yi, Jiacai
AU - Wang, Yikun
AU - Deng, Youchao
AU - Jiang, Dejun
AU - Cao, Dongsheng
N1 - This work was financially supported by the National Natural Science Foundation of China (82221002, 22220102001, 22173118, 22307112, 82304316, 82404746), National Science and Technology Major Project of the Ministry of Science and Technology of China (2023ZD0507104), Innovative Drug Research and Development National Science and Technology Major Project (NO.2025ZD1802302), and Young Scientists Fund of Natural Science Foundation of Hunan Province of China (2024JJ6554, 2025JJ60651). Open access publication charges were funded by the National Natural Science Foundation of China (82221002).
Publisher Copyright:
The Author(s) 2026. Published by Oxford University Press
PY - 2026/7/7
Y1 - 2026/7/7
N2 - CYP450 (cytochrome P450)-mediated drug metabolism is a critical determinant of pharmacokinetics and clinical safety, making comprehensive metabolic profiling essential for rational drug discovery. Here, we present DeepCYP (https://deepcyp.scbdd.com), a freely accessible deep-learning web server for end-to-end CYP450 metabolic profiling. Trained on an expanded dataset and a mechanism-based reaction rule library, DeepCYP uses a multi-task graph neural network (GNN) combined with multi-scale descriptors. Operating directly on 2D molecular graphs, this architecture bridges the entire "pathway-site-product" continuum across nine major CYP isoforms (CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4) within a unified pipeline. Benchmarking demonstrates that DeepCYP outperforms established tools, including FAME3, SMARTCyp, and BioTransformer 3.0, improving Top-1 and Top-2 ranking metrics by over 10%. Furthermore, the server supports high-throughput batch processing, capable of evaluating ~280 molecules per minute. DeepCYP also enhances interpretability through an interactive visualization interface, featuring susceptibility radar charts and dynamic transformation tables. By translating abstract predictions into biological insights, DeepCYP provides a practical tool to accelerate lead optimization and mitigate toxicity risks.
AB - CYP450 (cytochrome P450)-mediated drug metabolism is a critical determinant of pharmacokinetics and clinical safety, making comprehensive metabolic profiling essential for rational drug discovery. Here, we present DeepCYP (https://deepcyp.scbdd.com), a freely accessible deep-learning web server for end-to-end CYP450 metabolic profiling. Trained on an expanded dataset and a mechanism-based reaction rule library, DeepCYP uses a multi-task graph neural network (GNN) combined with multi-scale descriptors. Operating directly on 2D molecular graphs, this architecture bridges the entire "pathway-site-product" continuum across nine major CYP isoforms (CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4) within a unified pipeline. Benchmarking demonstrates that DeepCYP outperforms established tools, including FAME3, SMARTCyp, and BioTransformer 3.0, improving Top-1 and Top-2 ranking metrics by over 10%. Furthermore, the server supports high-throughput batch processing, capable of evaluating ~280 molecules per minute. DeepCYP also enhances interpretability through an interactive visualization interface, featuring susceptibility radar charts and dynamic transformation tables. By translating abstract predictions into biological insights, DeepCYP provides a practical tool to accelerate lead optimization and mitigate toxicity risks.
UR - https://www.scopus.com/pages/publications/105044169357
U2 - 10.1093/nar/gkag478
DO - 10.1093/nar/gkag478
M3 - Journal article
C2 - 42152517
SN - 0305-1048
VL - 54
SP - W22–W32
JO - Nucleic Acids Research
JF - Nucleic Acids Research
IS - W1
ER -