PbsNRs: Predict the Potential Binders and Scaffolds for Nuclear Receptors

Overview

Journal Brief Bioinform

Publisher Oxford University Press

Date 2025 Jan 11

PMID 39798999

Authors

Genhui Zheng

Dingfeng Wu

Xiuxia Wei

Dongpo Xu

Tiantian Mao

Deyu Yan

Wenhao Han

Xiaoxiao Shang

Zikun Chen

Jingxuan Qiu

Kailin Tang

Zhiwei Cao

Tianyi Qiu

Affiliations

Soon will be listed here.

Abstract

Nuclear receptors (NRs) are a class of essential proteins that regulate the expression of specific genes and are associated with multiple diseases. In silico methods for prescreening potential NR binders with predictive binding ability are highly desired for NR-related drug development but are rarely reported. Here, we present the PbsNRs (Predicting binders and scaffolds for Nuclear Receptors), a user-friendly web server designed to predict the potential NR binders and scaffolds through proteochemometric modeling. The utility of PbsNRs was systemically evaluated using both chemical compounds and natural products. Results indicated that PbsNRs achieved a good prediction performance for chemical compounds on internal (ROC-AUC = 0.906, where ROC is Receiver-Operating Characteristic curve and AUC is the Area Under the Curve) and external (ROC-AUC = 0.783) datasets, outperforming both compound-ligand interaction tools and NR-specific predictors. PbsNRs also successfully identified bioactive chemical scaffolds for NRs by screening massive natural products. Moreover, the predicted bioactive and inactive natural products for NR2B1 were experimentally validated using biosensors. PbsNRs not only aids in screening potential therapeutic NR binders but also helps discover the essential molecular scaffold and guide the drug discovery for multiple NR-related diseases. The PbsNRs web server is available at http://pbsnrs.badd-cao.net.

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