Academic Journal
Molecular Graph-Based Deep Learning Algorithm Facilitates an Imaging-Based Strategy for Rapid Discovery of Small Molecules Modulating Biomolecular Condensates
| العنوان: | Molecular Graph-Based Deep Learning Algorithm Facilitates an Imaging-Based Strategy for Rapid Discovery of Small Molecules Modulating Biomolecular Condensates |
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| المؤلفون: | Peng Gao, Qi Zhang, Devin Keely, Don W. Cleveland, Yihong Ye, Wei Zheng, Min Shen, Haiyang Yu |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Biochemistry, Medicine, Genetics, Pharmacology, Biotechnology, Sociology, Space Science, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Information Systems not elsewhere classified, undergoes phase transition, spatial information extraction, normal splicing function, identify small molecules, abnormal subcellular loci, graph convolutional network, based methods restrict, promote biomolecular condensates, based compound screens, binding protein 43, biomolecular condensates, molecular graph, essential protein, compound screen, based strategy, based screen, tar dna, taken together, screening scale |
| الوصف: | Biomolecular condensates are proposed to cause diseases, such as cancer and neurodegeneration, by concentrating proteins at abnormal subcellular loci. Imaging-based compound screens have been used to identify small molecules that reverse or promote biomolecular condensates. However, limitations of conventional imaging-based methods restrict the screening scale. Here, we used a graph convolutional network (GCN)-based computational approach and identified small molecule candidates that reduce the nuclear liquid–liquid phase separation of TAR DNA-binding protein 43 (TDP-43), an essential protein that undergoes phase transition in neurodegenerative diseases. We demonstrated that the GCN-based deep learning algorithm is suitable for spatial information extraction from the molecular graph. Thus, this is a promising method to identify small molecule candidates with novel scaffolds. Furthermore, we validated that these candidates do not affect the normal splicing function of TDP-43. Taken together, a combination of an imaging-based screen and a GCN-based deep learning method dramatically improves the speed and accuracy of the compound screen for biomolecular condensates. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| Relation: | https://figshare.com/articles/journal_contribution/Molecular_Graph-Based_Deep_Learning_Algorithm_Facilitates_an_Imaging-Based_Strategy_for_Rapid_Discovery_of_Small_Molecules_Modulating_Biomolecular_Condensates/24525400 |
| DOI: | 10.1021/acs.jmedchem.3c00490.s001 |
| الاتاحة: | https://doi.org/10.1021/acs.jmedchem.3c00490.s001 https://figshare.com/articles/journal_contribution/Molecular_Graph-Based_Deep_Learning_Algorithm_Facilitates_an_Imaging-Based_Strategy_for_Rapid_Discovery_of_Small_Molecules_Modulating_Biomolecular_Condensates/24525400 |
| Rights: | CC BY-NC 4.0 |
| رقم الانضمام: | edsbas.66501FC9 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1021/acs.jmedchem.3c00490.s001 |
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