KLSD: A Curated Kinase–Ligand Database Mapping Selectivity Landscapes and Polypharmacology
Herein, we present a database, KLSD, which is a curated resource of 787 213 small-molecule kinase inhibitors annotated with 1.8 M quantitative activity records across 428 human kinases, emphasizing selectivity and polypharmacology. Moreover, we introduce a dual-task ensemble that simultaneously regresses pAct and computes selectivity scores. The core is a multibranch residual multilayer perceptron (MLP) whose branches are kinase-specific; this is augmented by SVM, RF, XGBoost, CNN, GCN, GAT, RGCN and VAE-enhanced graph nets. Continuous potency labels replace categorical classes to improve resolution. Benchmarked on the JAK family (JAK1/2/3, TYK2), the ensemble achieves classification accuracies of ≥0.84 for each kinase and 0.98 overall, demonstrating strong generalizability. KLSD and models are freely available at http://ai.njucm.edu.cn:8080.
Authors
- Chang Li (ORCID: https://orcid.org/0000-0002-3267-1859)
- Shanliang Sun
- Xufeng Lang (ORCID: https://orcid.org/0000-0002-4767-9482)
- YiHua SONG
- Hongyan Li (ORCID: https://orcid.org/0000-0002-1158-5871)
- Yuqian Yuan
- Zuojian Zhou
- Xuebin Qiao
- Muzi Liang
- Ye Yang
Institutions
- Nanjing University of Chinese Medicine (CN)
- Nanjing Normal University (CN)
- Henan University of Traditional Chinese Medicine (CN)
- Holistic Management International (US)
- Centre de Recherche en Informatique (FR)
- Epidemic Intelligence Service (US)
- Integrative Medicine Institute (US)
- Hong Kong Metropolitan University (HK)
Publication Details
- Journal
- ACS Omega
- Published
- 2026-02-23
- DOI
- https://doi.org/10.1021/acsomega.5c11061
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00