Work

An interpretable framework applying protein words to predict protein–small molecule complementary pairing rules

Year: 2026

Type: article

Abstract: , SARS-CoV-2 main protease. Notably, PWScore captures complementary interaction information, yielding superior enrichment performance when integrated with these established methods. Structural analysis of protein-ligand complexes indicates that learned word-fragment rules are significantly enriched near ligand-binding pockets, despite training without explicit structural guidance. By extracting and applying complementary pairing rules, PWRules provides an interpretable framework for drug discovery.

Source: Chemical Science

DOI: 10.1039/d6sc03365b

Authors: Jingke Chen, Jingrui Zhong, Tazneen Hossain Tani, Zidong Su, Xiaochun Zhang, Boxue Tian

Institutions: State Key Laboratory of Molecular Oncology, Tsinghua University

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Drug Discovery

Field: Pharmacology, Toxicology and Pharmaceutics

Domain: Life Sciences

Open Access status: diamond

Funders: Beijing Frontier Research Center for Biological Structure, Tsinghua University, Tsinghua University, Natural Science Foundation of Beijing Municipality, Peking University

Awards: G1985939484, G2776483416, G4383563372, G7179776169, G7497020886