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Author

Renling Hu

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#machine learning Jun 2025

LumiCharge: Spherical Harmonic Convolutional Networks for Atomic Charge Prediction in Drug Discovery.

This work proposes LumiCharge, a novel atomic charge prediction framework that incorporates high-order spherical harmonics convolutions and explicitly models multibody interactions, and demonstrates exceptional extrapolation capability and robustness across molecules of varying sizes, effectively overcoming the limitat...

Qun Su, Hui Zhang, Qiaolin Gou et al. · 2 citations
#computer vision Nov 2025

Improving the predictive performance of binding affinities and poses for protein–cyclic peptide complexes through fine-tuned MM/PBSA(GBSA)-based methods

Abstract Cyclic peptides represent a highly promising class of biopharmaceutical scaffolds. The screening of cyclic peptides against protein targets can be greatly facilitated using computational approaches, especially molecular docking. However, it remains a crucial challenge to accurately predict protein–cyclic pepti...

Huifeng Zhao, Jianxiang Huang, Gaoqi Weng et al. · 10 citations
#computer vision Open access Jul 2025

A scalable and quantum-accurate foundation model for biomolecular force fields via linearly tensorized quadrangle attention

LiTEN achieves state-of-the-art accuracy on standard benchmarks, consistently outperforming leading approaches in both precision and speed, and enables comprehensive modeling tasks, ranging from geometry optimization to free energy surface construction, with high computational efficiency for large biomolecules.

Qun Su, Kai Zhu, Qiaolin Gou et al. · 2 citations
#natural language process... Open access Apr 2026

LaMGen: LLM-based 3D molecular generation for multi-target drug design

This study introduces LaMGen, an LLM-powered framework that leverages large-scale protein-ligand data and rotation-aware molecular encoding to rapidly produce chemically plausible multi-target candidates, achieving strong zero-shot generalization, superior molecular quality, and robust performance across dual- and trip...

Qun Su, Qiaolin Gou, Hui Zhang et al. · 1 citation
#machine learning Open access Jun 2026

Targeting the intrinsically disordered AR-NTD through a machine learning-based enhanced sampling workflow

An integrated computational workflow that combines enhanced sampling techniques and machine learning collective variables to identify druggable conformations of the AR-NTD and elucidate the binding mechanism of its modulator, EPI-002 is introduced.

Kai Zhu, Huating Wang, Jin-Tu Zhang et al. · 0 citations

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