# ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support

*PRI Rank #3 · Topics and Trends in Most Cited Computational Drug Discovery Methods Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/computational-drug-discovery-methods/2026/rank-3*

| Field | Value |
| --- | --- |
| Rank | #3 |
| 18m citations | 446 |
| Journal | Nucleic Acids Research |
| Year | 2024 |
| DOI | 10.1093/nar/gkae236 |
| Corresponding authors | Tingjun Hou |
| Institution | Central South University, China |

**Ranking page:** [Topics and Trends in Most Cited Computational Drug Discovery Methods Papers, Class of 2026](https://pri.pepkio.com/top-papers/computational-drug-discovery-methods/2026)

**Paper link:** [10.1093/nar/gkae236](https://doi.org/10.1093/nar/gkae236)

## Topics

ADMET · ADMET · Physicochemical properties · medicinal chemistry · D-MPNN · Directed message-passing neural networks · Molecular descriptors · API functionality · uncertainty estimates · Drug discovery · absorption · distribution · metabolism · excretion · Toxicity prediction · Web server · candidate compound selection · Pharmacokinetics · In silico prediction

## Cite this ranking

```
Pepkio Research Index (PRI). Topics and Trends in Most Cited Computational Drug Discovery Methods Papers, Class of 2026. https://pri.pepkio.com/top-papers/computational-drug-discovery-methods/2026. Accessed 2026-07-22.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459
```