Index-Predict the ADMET of peptides

Key features

Data mining for over 10 years

Utilizing a decade of accumulated expertise to extract meaningful biological insights.

Database with 36,000+ entries

Massive curated entries ensure a reliable foundation for peptide ADMET evaluation.

Covering 29 Key Properties of ADMET

In-depth coverage across Absorption, Distribution, Metabolism, Excretion, and Toxicity.

Supports Cyclic, Linear, Natural and Modified Peptides

Direct input of molecular structures allows it to go beyond a limited range of modification types.

Support for Cell Lines, Organs, and Species

Cross-species predictive modeling ensures wide applicability in biomedical research.

State-of-the-art AI algorithms

Harnessing cutting-edge artificial intelligence to enhance prediction accuracy and speed.

Quick start

Physicochemical Properties

Collaboration

For additional quota, batch prediction, or commercial collaboration, please contact: jiedong@csu.edu.cn

Data and Privacy Statement

PepADMET does not permanently store user-uploaded files or input data. All inputs are only temporarily cached for processing and are deleted after completion.

Each user can only view their own submission records after login; no other users can access them. The server does not retain submitted data, ensuring confidentiality and privacy protection.

Please cite

If you find pepADMET helpful for your research, please cite the following publications:

2026

pepADMET: A Novel Computational Platform For Systematic ADMET Evaluation of Peptides.

Tan, X., Liu, Q., Zhou, M., Fang, Y., Ouyang, D., Zeng, W., & Dong, J. Journal of Chemical Information and Modeling. https://doi.org/10.1021/acs.jcim.5c02518.

2024

Introducing enzymatic cleavage features and transfer learning realizes accurate peptide half-life prediction across species and organs.

Tan, X., Liu, Q., Fang, Y., Yang, S., Chen, F., Wang, J., ... Dong J & Zeng, W. (2024). Briefings in Bioinformatics, 25(4), bbae350.