FraGAT
FraGAT, a Fragment-oriented Multi-scale Graph Attention Network, enhances molecular property prediction by incorporating the hierarchical structures of molecules, which existing graph-based models have largely overlooked. Recognizing the crucial role of functional groups within molecules in determining their physio-chemical properties and binding affinities, FraGAT represents molecules through graph fragments containing or constituting functional groups. This approach allows for a more nuanced and accurate prediction of molecular properties.
The development of FraGAT is underpinned by a novel definition of molecule graph fragments aimed at capturing the essential functional groups relevant to molecular properties.
Topic
Molecular modelling;Chemistry;Molecular biology;Small molecules
Detail
Operation: Molecular docking;Small molecule design;Network analysis;Phasing
Software interface: Library
Language: Python
License: Not stated
Cost: Free of charge
Version name: -
Credit: National Key Research and Development Program of China, National Natural Science Foundation of China.
Input: -
Output: -
Contact: Shuigeng Zhou sgzhou@fudan.edu.cn
Collection: -
Maturity: -
Publications
- FraGAT: a fragment-oriented multi-scale graph attention model for molecular property prediction.
- Zhang Z, et al. FraGAT: a fragment-oriented multi-scale graph attention model for molecular property prediction. FraGAT: a fragment-oriented multi-scale graph attention model for molecular property prediction. 2021; 37:2981-2987. doi: 10.1093/bioinformatics/btab195
- https://doi.org/10.1093/BIOINFORMATICS/BTAB195
- PMID: 33769437
- PMC: PMC8479684
Download and documentation
Documentation: https://github.com/ZiqiaoZhang/FraGAT/blob/master/readme.md
Home page: https://github.com/ZiqiaoZhang/FraGAT
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