6 papers
Towards Generalizable and Evidential Nuclear Magnetic Resonance-Based Molecular Structure Elucidation via Large Language Model Agent
Zheng Fang, Chen Yang, Yusen Tan +9
Nuclear Magnetic Resonance (NMR) spectroscopy is the gold standard for molecular structure elucidation, yet interpreting complex spectra for unknown molecules remains a bottleneck…
MemNovo: Look Back at the Spectrum for Balanced De Novo Peptide Sequencing from Mass Spectrometry
Dongxin Lyu, Jingbo Zhou, Hongxin Xiang +2
De novo peptide sequencing from tandem mass spectrometry is pivotal in proteomics, enabling identification of novel peptides without reference databases. While recent Transformer-b…
Refold: Refining Protein Inverse Folding with Efficient Structural Matching and Fusion
Yiran Zhu, Changxi Chi, Hongxin Xiang +3
Protein inverse folding aims to design an amino acid sequence that will fold into a given backbone structure, serving as a central task in protein design. Two main paradigms have b…
EDBench: Large-Scale Electron Density Data for Molecular Modeling
Hongxin Xiang, Ke Li, Mingquan Liu +7
Existing molecular machine learning force fields (MLFFs) generally focus on the learning of atoms, molecules, and simple quantum chemical properties (such as energy and force), but…
ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models
Zhuo Chen, Yizhen Zheng, Huan Yee Koh +4
Molecular Relational Learning (MRL) aims to understand interactions between molecular pairs, playing a critical role in advancing biochemical research. With the recent development…
FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning
Sizhe Liu, Jun Xia, Lecheng Zhang +8
Molecular relational learning (MRL) is crucial for understanding the interaction behaviors between molecular pairs, a critical aspect of drug discovery and development. However, th…