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He X, Zhao L, Tian Y, Li R, Chu Q, Gu Z, Zheng M, Wang Y, Li S, Jiang H, Jiang Y, Wen L, Wang D, Cheng X. Highly accurate carbohydrate-binding site prediction with DeepGlycanSite. Nat Commun 2024; 15:5163. [PMID: 38886381 PMCID: PMC11183243 DOI: 10.1038/s41467-024-49516-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 06/10/2024] [Indexed: 06/20/2024] Open
Abstract
As the most abundant organic substances in nature, carbohydrates are essential for life. Understanding how carbohydrates regulate proteins in the physiological and pathological processes presents opportunities to address crucial biological problems and develop new therapeutics. However, the diversity and complexity of carbohydrates pose a challenge in experimentally identifying the sites where carbohydrates bind to and act on proteins. Here, we introduce a deep learning model, DeepGlycanSite, capable of accurately predicting carbohydrate-binding sites on a given protein structure. Incorporating geometric and evolutionary features of proteins into a deep equivariant graph neural network with the transformer architecture, DeepGlycanSite remarkably outperforms previous state-of-the-art methods and effectively predicts binding sites for diverse carbohydrates. Integrating with a mutagenesis study, DeepGlycanSite reveals the guanosine-5'-diphosphate-sugar-recognition site of an important G-protein coupled receptor. These findings demonstrate DeepGlycanSite is invaluable for carbohydrate-binding site prediction and could provide insights into molecular mechanisms underlying carbohydrate-regulation of therapeutically important proteins.
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Affiliation(s)
- Xinheng He
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lifen Zhao
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Yinping Tian
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Rui Li
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
- School of Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Qinyu Chu
- School of Pharmaceutical Science and Technology, Hangzhou Institute of Advanced Study, Hangzhou, China
| | - Zhiyong Gu
- School of Pharmaceutical Science and Technology, Hangzhou Institute of Advanced Study, Hangzhou, China
| | - Mingyue Zheng
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
- School of Pharmaceutical Science and Technology, Hangzhou Institute of Advanced Study, Hangzhou, China
| | - Yusong Wang
- National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, China
| | - Shaoning Li
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Hualiang Jiang
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
- School of Pharmaceutical Science and Technology, Hangzhou Institute of Advanced Study, Hangzhou, China
- Lingang Laboratory, Shanghai, China
| | - Yi Jiang
- Lingang Laboratory, Shanghai, China
| | - Liuqing Wen
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
- University of Chinese Academy of Sciences, Beijing, China.
| | | | - Xi Cheng
- State Key Laboratory of Drug Research and State Key Laboratory of Chemical Biology, Carbohydrate-Based Drug Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China.
- University of Chinese Academy of Sciences, Beijing, China.
- School of Pharmaceutical Science and Technology, Hangzhou Institute of Advanced Study, Hangzhou, China.
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von Itzstein M. The war against influenza: discovery and development of sialidase inhibitors. Nat Rev Drug Discov 2007; 6:967-74. [PMID: 18049471 DOI: 10.1038/nrd2400] [Citation(s) in RCA: 498] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The threat of a major human influenza pandemic, in particular from highly aggressive strains such as avian H5N1, has emphasized the need for therapeutic strategies to combat these pathogens. At present, two inhibitors of sialidase (also known as neuraminidase), a viral enzyme that has a key role in the life cycle of influenza viruses, would be the mainstay of pharmacological strategies in the event of such a pandemic. This article provides a historical perspective on the discovery and development of these drugs--zanamivir and oseltamivir--and highlights the value of structure-based drug design in this process.
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Affiliation(s)
- Mark von Itzstein
- Institute for Glycomics, Gold Coast Campus, Griffith University, Queensland 4222, Australia.
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Achyuthan KE, Achyuthan AM. Comparative enzymology, biochemistry and pathophysiology of human exo-alpha-sialidases (neuraminidases). Comp Biochem Physiol B Biochem Mol Biol 2001; 129:29-64. [PMID: 11337249 DOI: 10.1016/s1096-4959(01)00372-4] [Citation(s) in RCA: 98] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
This review summarizes the current research on human exo-alpha-sialidase (sialidase, neuraminidase). Where appropriate, the properties of viral, bacterial, and human sialidases have been compared. Sialic acids are implicated in diverse physiological processes. Sialidases, as enzymes acting upon sialic acids, assume importance as well. Sialidases hydrolyze the terminal, non-reducing, sialic acid linkage in glycoproteins, glycolipids, gangliosides, polysaccharides, and synthetic molecules. Therefore, a variety of assays are available to measure sialidase activity. Human sialidase is present in several organs and cells. Its cellular distribution could be cytosolic, lysosomal, or in the membrane. Human sialidase occurs in a high molecular-mass complex with several other proteins, including cathepsin A and beta-galactosidase. Multi-protein complexation is important for the in vivo integrity and catalytic activity of the sialidase. However, multi-protein complexation, the occurrence of isoenzymes, diverse subcellular localization, thermal instability, and membrane association have all contributed to difficulties in purifying and characterizing human sialidases. Human sialidase isoenzymes have recently been cloned and sequenced. Even though crystal structures for the human sialidases are not available, the highly conserved regions of the sialidase from various organisms have facilitated molecular modeling of the human enzyme and raise interesting evolutionary questions. While the molecular mechanisms vary, genetic defects leading to human sialidase deficiency are closely associated with at least two well-known human diseases, namely sialidosis and galactosialidosis. No therapy is currently available for either disease. A thorough investigation of human sialidases is therefore crucial to human health.
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Affiliation(s)
- K E Achyuthan
- ZymeTx Inc., 800 Research Parkway # 100, Oklahoma City, OK 73104, USA.
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Ciccotosto S, Kiefel MJ, Abo S, Stewart W, Quelch K, von Itzstein M. Synthesis and evaluation of N-acetylneuraminic acid-based affinity matrices for the purification of sialic acid-recognizing proteins. Glycoconj J 1998; 15:663-9. [PMID: 9881772 DOI: 10.1023/a:1006932330367] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The synthesis of 2-S-(2-aminoethyl) 5-acetamido-3,5-dideoxy-2-thio-D-galacto-2-nonulopyranosidonic acid (1) has been successfully achieved from the precursors methyl 5-acetamido-4,7,8,9-tetra-O-acetyl-2-S-acetyl-3,5-dideoxy-2-thio-D-glyce ro-alpha-D-galacto-2-nonulopyranosonate (2) and 2-bromo-N-(tert-butoxycarbonyl)-ethylamine (5). Compounds 1 and 2 were coupled, via amino and thioglycosidic linkages, respectively, to epoxy-activated Sepharose 6B. The resultant affinity adsorbents have proved efficient in purifying the sialic acid-recognizing enzyme Vibrio cholerae sialidase, in a one-step process with yields in the order of 60%.
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Affiliation(s)
- S Ciccotosto
- Department of Medicinal Chemistry, Monash University (Parkville Campus), Victoria, Australia
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