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#DeepGlycanSite predicts highly accurate carbohydrate-binding sites. #prediction

Highly accurate carbohydrate-binding site prediction with DeepGlycanSite

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  • Varki, A. Biological roles of glycans. Glycobiology 27, 3–49 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Varki, A. et al. Essentials of Glycobiology Ch. 4 (The Consortium of Glycobiology Editors, La Jolla, California, 2015).

  • Smith, B. A. H. & Bertozzi, C. R. The clinical impact of glycobiology: targeting selectins, Siglecs and mammalian glycans. Nat. Rev. Drug Discov. 20, 217–243 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tiralongo, J., Pegg, M. S. & von Itzstein, M. Effect of substrate aglycon on enzyme mechanism in the reaction of sialidase from influenza virus. Febs. Lett. 372, 148–150 (1995).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Chong, A. K., Pegg, M. S., Taylor, N. R. & von Itzstein, M. Evidence for a sialosyl cation transition-state complex in the reaction of sialidase from influenza virus. Eur. J. Biochem. 207, 335–343 (1992).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • von Itzstein, M. The war against influenza: discovery and development of sialidase inhibitors. Nat. Rev. Drug Discov. 6, 967–974 (2007).

    Article 

    Google Scholar
     

  • Bokor, É. et al. C-Glycopyranosyl arenes and hetarenes: synthetic methods and bioactivity focused on antidiabetic potential. Chem. Rev. 117, 1687–1764 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Ernst, B. & Magnani, J. L. From carbohydrate leads to glycomimetic drugs. Nat. Rev. Drug Discov. 8, 661–677 (2009).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Copoiu, L., Torres, P. H. M., Ascher, D. B., Blundell, T. L. & Malhotra, S. ProCarbDB: a database of carbohydrate-binding proteins. Nucleic Acids Res 48, D368–D375 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Griffin, M. E. & Hsieh-Wilson, L. C. Tools for mammalian glycoscience research. Cell 185, 2657–2677 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhao, J., Cao, Y. & Zhang, L. Exploring the computational methods for protein-ligand binding site prediction. Comput. Struct. Biotechnol. J. 18, 417–426 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ngan, C. H., Hall, D. R., Zerbe, B., Grove, L. E., Kozakov, D. & Vajda, S. FTSite: high accuracy detection of ligand binding sites on unbound protein structures. Bioinformatics 28, 286–287 (2012).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Le Guilloux, V., Schmidtke, P. & Tuffery, P. Fpocket: an open source platform for ligand pocket detection. BMC Bioinforma. 10, 168 (2009).

    Article 

    Google Scholar
     

  • Gattani, S., Mishra, A. & Hoque, M. T. StackCBPred: a stacking based prediction of protein-carbohydrate binding sites from sequence. Carbohydr. Res. 486, 107857 (2019).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Banno, M. et al. Development of a sugar-binding residue prediction system from protein sequences using support vector machine. Comput. Biol. Chem. 66, 36–43 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Taherzadeh, G., Zhou, Y. Q., Liew, A. W. C. & Yang, Y. D. Sequence-based prediction of protein-carbohydrate binding sites using support vector machines. J. Chem. Inf. Model. 56, 2115–2122 (2016).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • York, W. S. et al. GlyGen: computational and informatics resources for glycoscience. Glycobiology 30, 72–73 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Mariethoz, J. et al. Glycomics@ExPASy: bridging the gap. Mol. Cell. Proteom. 17, 2164–2176 (2018).

    Article 
    CAS 

    Google Scholar
     

  • Yamada, I. et al. The GlyCosmos portal: a unified and comprehensive web resource for the glycosciences. Nat. Methods 17, 649–650 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Berman, H., Henrick, K. & Nakamura, H. Announcing the worldwide Protein Data Bank. Nat. Struct. Biol. 10, 980 (2003).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Bonnardel, F. et al. UniLectin3D, a database of carbohydrate binding proteins with curated information on 3D structures and interacting ligands. Nucleic Acids Res 47, D1236–D1244 (2019).

    Article 
    PubMed 

    Google Scholar
     

  • Siva Shanmugam, N. R., Jino Blessy, J., Veluraja, K. & Michael Gromiha, M. ProCaff: protein-carbohydrate complex binding affinity database. Bioinformatics 36, 3615–3617 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Meng, X. Y., Zhang, H. X., Mezei, M. & Cui, M. Molecular docking: a powerful approach for structure-based drug discovery. Curr. Comput-Aid. Drug 7, 146–157 (2011).

    Article 
    CAS 

    Google Scholar
     

  • Lin, Z. et al. Evolutionary-scale prediction of atomic-level protein structure with a language model. Science 379, 1123–1130 (2023).

    Article 
    ADS 
    MathSciNet 
    CAS 
    PubMed 

    Google Scholar
     

  • Alenton, R. R., Koiwai, K., Miyaguchi, K., Kondo, H. & Hirono, I. Pathogen recognition of a novel C-type lectin from Marsupenaeus japonicus reveals the divergent sugar-binding specificity of QAP motif. Sci. Rep. 7, 45818 (2017).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Shen, D., Wang, L., Ji, J., Liu, Q. & An, C. Identification and characterization of C-type Lectins in Ostrinia furnacalis (Lepidoptera: Pyralidae). J. Insect Sci. 18, 24 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhao, L. et al. Identification of a carbohydrate recognition motif of purinergic receptors. Elife 12, e85449 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Xia, B. et al. Mapping the acetylamino and carboxyl groups on glycans by engineered α-hemolysin nanopores. J. Am. Chem. Soc. 145, 18812–18824 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Yao, G. et al. Direct identification of complex glycans via a highly sensitive engineered nanopore. J. Am. Chem. Soc. 146, 13356–13366 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Liang, R. et al. Polyvalent binding to carbohydrates immobilized on an insoluble resin. P. Natl Acad. Sci. Usa. 94, 10554–10559 (1997).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Kim, B. W., Hong, S. B., Kim, J. H., Kwon, D. H. & Song, H. K. Structural basis for recognition of autophagic receptor NDP52 by the sugar receptor galectin-8. Nat. Commun. 4, 1613 (2013).

    Article 
    ADS 
    PubMed 

    Google Scholar
     

  • Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Richard E., et al. Protein complex prediction with AlphaFold-Multimer. Preprint at https://doi.org/10.1101/2021.10.04.463034v1 (2022).

  • Aggarwal, R., Gupta, A., Chelur, V., Jawahar, C. V. & Priyakumar, U. D. DeepPocket: ligand binding site detection and segmentation using 3D convolutional neural networks. J. Chem. Inf. Model. 62, 5069–5079 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Krapp, L. F., Abriata, L. A., Cortes Rodriguez, F., Dal & Peraro, M. PeSTo: parameter-free geometric deep learning for accurate prediction of protein binding interfaces. Nat. Commun. 14, 2175 (2023).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Halgren, T. A. Identifying and characterizing binding sites and assessing druggability. J. Chem. Inf. Model. 49, 377–389 (2009).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Zhou, G. et al. Uni-Mol: a universal 3D molecular representation learning framework. In International Conference on Learning Representations (eds K., Rwanda) (Ithaca, NY. 2023).

  • Vamathevan, J. et al. Applications of machine learning in drug discovery and development. Nat. Rev. Drug Discov. 18, 463–477 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Boittier, E. D., Burns, J. M., Gandhi, N. S. & Ferro, V. GlycoTorch Vina: docking designed and tested for glycosaminoglycans. J. Chem. Inf. Model. 60, 6328–6343 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Trott, O. & Olson, A. J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 31, 455–461 (2010).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Corso, G., Stärk, H., Jing, B., Barzilay, R. & Jaakkola, T. Diffdock: Diffusion steps, twists, and turns for molecular docking. In International Conference on Learning Representations (eds K., Rwanda) https://doi.org/10.48550/arXiv.2210.01776 (Ithaca, NY. 2023).

  • Stark H., Ganea O. E., Pattanaik L., Barzilay R. & Jaakkola T. EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction. In Proceedings of Machine Learning Research (eds Baltimore, MD, USA) https://doi.org/10.48550/arXiv.2202.05146 (2022).

  • Breton, S. & Brown, D. Novel proinflammatory function of renal intercalated cells. Ann. Nutr. Metab. 72, 11–16 (2018). Suppl 2.

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Amison, R. T. et al. Lipopolysaccharide (LPS) induced pulmonary neutrophil recruitment and platelet activation is mediated via the P2Y1 and P2Y14 receptors in mice. Pulm. Pharmacol. Ther. 45, 62–68 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Moriwaki, K. et al. Deficiency of GMDS leads to escape from NK cell-mediated tumor surveillance through modulation of TRAIL signaling. Gastroenterology 137, 188–198 (2009).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Kizuka, Y. et al. An alkynyl-fucose halts hepatoma cell migration and invasion by inhibiting GDP-fucose-synthesizing enzyme FX, TSTA3. Cell Chem. Biol. 24, 1467–1478 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Schneider, M., Al-Shareffi, E. & Haltiwanger, R. S. Biological functions of fucose in mammals. Glycobiology 27, 601–618 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Carter, R. L. et al. Quantification of Gi-mediated inhibition of adenylyl cyclase activity reveals that UDP is a potent agonist of the human P2Y14 receptor. Mol. Pharmacol. 76, 1341–1348 (2009).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Varadi, M. et al. Alphafold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res 50, D439–D444 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Tsai, K. C. et al. Prediction of carbohydrate binding sites on protein surfaces with 3-dimensional probability density distributions of interacting atoms. Plos One 7, e40846 (2012).

  • Zhao, H. Y., Yang, Y. D., von Itzstein, M. & Zhou, Y. Q. Carbohydrate-binding protein identification by coupling structural similarity searching with binding affinity prediction. J. Comput. Chem. 35, 2177–2183 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Loris, R. Principles of structures of animal and plant lectins. Bba-Gen. Subj. 1572, 198–208 (2002).

    Article 
    CAS 

    Google Scholar
     

  • O’Reilly, M. K. et al. Bifunctional CD22 Ligands use multimeric immunoglobulins as protein scaffolds in assembly of immune complexes on B cells. J. Am. Chem. Soc. 130, 7736–7745 (2008).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Peng, W. & Paulson, J. C. CD22 ligands on a natural N-Glycan scaffold efficiently deliver toxins to B-Lymphoma cells. J. Am. Chem. Soc. 139, 12450–12458 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Liu, F. T. & Stowell, S. R. The role of galectins in immunity and infection. Nat. Rev. Immunol. 23, 479–494 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Marino, K. V., Cagnoni, A. J., Croci, D. O. & Rabinovich, G. A. Targeting galectin-driven regulatory circuits in cancer and fibrosis. Nat. Rev. Drug Discov. 22, 295–316 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Cecioni, S., Imberty, A. & Vidal, S. Glycomimetics versus multivalent glycoconjugates for the design of high affinity lectin ligands. Chem. Rev. 115, 525–561 (2015).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Yang, Z., Zeng, X., Zhao, Y. & Chen, R. AlphaFold2 and its applications in the fields of biology and medicine. Signal Transduct. Target. Ther. 8, 115 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • He, X., You, C., Jiang, H., Jiang, Y., Xu HE & Cheng, X. AlphaFold2 versus experimental structures: evaluation on G protein-coupled receptors. Acta Pharm. Sin. 44, 1–7 (2023).

    Article 
    CAS 

    Google Scholar
     

  • van Kempen, M. et al. Fast and accurate protein structure search with Foldseek. Nat. Biotechnol. 42, 243–246 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Yang, J., Anishchenko, I., Park, H., Peng, Z., Ovchinnikov, S. & Baker, D. Improved protein structure prediction using predicted interresidue orientations. Proc. Natl Acad. Sci. Usa. 117, 1496–1503 (2020).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Landrum, G. et al. rdkit/rdkit: 2022_09_5 (Q3 2022). Zenodo. https://doi.org/10.5281/zenodo.7671152 (2023).

  • Schütt K., Unke O. & Gastegger M. Equivariant message passing for the prediction of tensorial properties and molecular spectra. In International Conference on Machine Learning (eds Virtual) https://doi.org/10.48550/arXiv.2102.03150(2021).

  • Vinyals O., Bengio S. & Kudlur M. Order matters: sequence to sequence for sets. In International Conference on Learning Representations (eds San. J., Puerto. R). (Ithaca, NY. 2016).

  • Qin, R., Qiao, K., Wang, L., Zeng, L., Chen, J. & Yan, B. Weighted focal loss: an effective loss function to overcome unbalance problem of chest X-ray14. Iop. Conf. Ser.: Mater. Sci. Eng. 428, 012022 (2018).

    Article 

    Google Scholar
     

  • Frazier P. I. Bayesian optimization. Recent Advances in Optimization and Modeling of Contemporary Problems (INFORMS Tutorials in Operations Research, 2018).

  • Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Comput. Phys. 79, 926–935 (1983).

    CAS 

    Google Scholar
     

  • Wu, E. L. et al. CHARMM-GUI Membrane builder toward realistic biological membrane simulations. J. Comput. Chem. 35, 1997–2004 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Huang, J. et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods 14, 71–73 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Vanommeslaeghe, K. et al. CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J. Comput. Chem. 31, 671–690 (2010).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Salomon-Ferrer, R., Götz, A. W., Poole, D., Le Grand, S. & Walker, R. C. Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit Solvent Particle Mesh Ewald. J. Chem. Theory Comput. 9, 3878–3888 (2013).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Evans, D. J. & Holian, B. L. The Nose–Hoover thermostat. J. Chem. Phys. 83, 4069–4074 (1985).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 52, 7182–7190 (1981).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Ryckaert, J.-P., Ciccotti, G. & Berendsen, H. J. C. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J. Comput. Phys. 23, 327–341 (1977).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • Darden, T., York, D. & Pedersen, L. Particle mesh Ewald: An Nlog(N) method for Ewald sums in large systems. J. Chem. Phys. 98, 10089–10092 (1993).

    Article 
    ADS 
    CAS 

    Google Scholar
     

  • He, X. et al. Hinge region mediates signal transmission of luteinizing hormone and chorionic gonadotropin receptor. Comput. Struct. Biotechnol. J. 20, 6503–6511 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Liu, H. et al. Structural insights into ligand recognition and activation of the medium-chain fatty acid-sensing receptor GPR84. Nat. Commun. 14, 3271 (2023).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lu, S. et al. Activation pathway of a G protein-coupled receptor uncovers conformational intermediates as targets for allosteric drug design. Nat. Commun. 12, 4721 (2021).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhuang, Y. et al. Molecular recognition of morphine and fentanyl by the human μ-opioid receptor. Cell 185, 4361–4375 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Wang, S., Zhang, J., Wei, F., Li, W. & Wen, L. Facile synthesis of sugar nucleotides from common sugars by the cascade conversion strategy. J. Am. Chem. Soc. 144, 9980–9989 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • He, X. et al. Highly accurate carbohydrate-binding site prediction with DeepGlycanSite. Zenodo, https://doi.org/10.5281/zenodo.11201294. (2024).

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