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Tsai YX, Chang NE, Reuter K, Chang HT, Yang TJ, von Bülow S, Sehrawat V, Zerrouki N, Tuffery M, Gecht M, Grothaus IL, Colombi Ciacchi L, Wang YS, Hsu MF, Khoo KH, Hummer G, Hsu STD, Hanus C, Sikora M. Rapid simulation of glycoprotein structures by grafting and steric exclusion of glycan conformer libraries. Cell 2024; 187:1296-1311.e26. [PMID: 38428397 DOI: 10.1016/j.cell.2024.01.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 10/18/2023] [Accepted: 01/22/2024] [Indexed: 03/03/2024]
Abstract
Most membrane proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, shielding potentially large fractions of protein surface. High glycan conformational freedom hinders complete structural elucidation of glycoproteins. Computer simulations may be used to model glycosylated proteins but require hundreds of thousands of computing hours on supercomputers, thus limiting routine use. Here, we describe GlycoSHIELD, a reductionist method that can be implemented on personal computers to graft realistic ensembles of glycan conformers onto static protein structures in minutes. Using molecular dynamics simulation, small-angle X-ray scattering, cryoelectron microscopy, and mass spectrometry, we show that this open-access toolkit provides enhanced models of glycoprotein structures. Focusing on N-cadherin, human coronavirus spike proteins, and gamma-aminobutyric acid receptors, we show that GlycoSHIELD can shed light on the impact of glycans on the conformation and activity of complex glycoproteins.
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Affiliation(s)
- Yu-Xi Tsai
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan; Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Ning-En Chang
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan; Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Klaus Reuter
- Max Planck Computing and Data Facility, 85748 Garching, Germany
| | - Hao-Ting Chang
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan; Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Tzu-Jing Yang
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan; Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Sören von Bülow
- Department of Theoretical Biophysics, Max Planck Institute for Biophysics, 60438 Frankfurt, Germany
| | - Vidhi Sehrawat
- Department of Theoretical Biophysics, Max Planck Institute for Biophysics, 60438 Frankfurt, Germany; Malopolska Centre of Biotechnology, Jagiellonian University, 31-007 Kraków, Poland
| | - Noémie Zerrouki
- Institute of Psychiatry and Neurosciences of Paris, Inserm UMR1266, Université Paris-Cité, 75014 Paris, France
| | - Matthieu Tuffery
- Institute of Psychiatry and Neurosciences of Paris, Inserm UMR1266, Université Paris-Cité, 75014 Paris, France
| | - Michael Gecht
- Department of Theoretical Biophysics, Max Planck Institute for Biophysics, 60438 Frankfurt, Germany
| | - Isabell Louise Grothaus
- Hybrid Materials Interfaces Group, Faculty of Production Engineering, Bremen Center for Computational Materials Science and MAPEX Center for Materials and Processes, University of Bremen, 28359 Bremen, Germany
| | - Lucio Colombi Ciacchi
- Hybrid Materials Interfaces Group, Faculty of Production Engineering, Bremen Center for Computational Materials Science and MAPEX Center for Materials and Processes, University of Bremen, 28359 Bremen, Germany
| | - Yong-Sheng Wang
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan; Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Min-Feng Hsu
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Kay-Hooi Khoo
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan; Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Gerhard Hummer
- Department of Theoretical Biophysics, Max Planck Institute for Biophysics, 60438 Frankfurt, Germany; Institute of Biophysics, Goethe University, 60438 Frankfurt, Germany
| | - Shang-Te Danny Hsu
- Institute of Biological Chemistry, Academia Sinica, Taipei 11529, Taiwan; Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan; International Institute for Sustainability with Knotted Chiral Meta Matter (WPI-SKCM(2)), Hiroshima University, Hiroshima 739-8526, Japan.
| | - Cyril Hanus
- Institute of Psychiatry and Neurosciences of Paris, Inserm UMR1266, Université Paris-Cité, 75014 Paris, France; GHU Psychiatrie et Neurosciences de Paris, 75014 Paris, France.
| | - Mateusz Sikora
- Department of Theoretical Biophysics, Max Planck Institute for Biophysics, 60438 Frankfurt, Germany; Malopolska Centre of Biotechnology, Jagiellonian University, 31-007 Kraków, Poland.
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Beck M, Covino R, Hänelt I, Müller-McNicoll M. Understanding the cell: Future views of structural biology. Cell 2024; 187:545-562. [PMID: 38306981 DOI: 10.1016/j.cell.2023.12.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/05/2023] [Accepted: 12/11/2023] [Indexed: 02/04/2024]
Abstract
Determining the structure and mechanisms of all individual functional modules of cells at high molecular detail has often been seen as equal to understanding how cells work. Recent technical advances have led to a flush of high-resolution structures of various macromolecular machines, but despite this wealth of detailed information, our understanding of cellular function remains incomplete. Here, we discuss present-day limitations of structural biology and highlight novel technologies that may enable us to analyze molecular functions directly inside cells. We predict that the progression toward structural cell biology will involve a shift toward conceptualizing a 4D virtual reality of cells using digital twins. These will capture cellular segments in a highly enriched molecular detail, include dynamic changes, and facilitate simulations of molecular processes, leading to novel and experimentally testable predictions. Transferring biological questions into algorithms that learn from the existing wealth of data and explore novel solutions may ultimately unveil how cells work.
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Affiliation(s)
- Martin Beck
- Max Planck Institute of Biophysics, Max-von-Laue-Straße 3, 60438 Frankfurt am Main, Germany; Goethe University Frankfurt, Frankfurt, Germany.
| | - Roberto Covino
- Frankfurt Institute for Advanced Studies, Ruth-Moufang-Straße 1, 60438 Frankfurt am Main, Germany.
| | - Inga Hänelt
- Goethe University Frankfurt, Frankfurt, Germany.
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Lennemann NJ, Corliss L, Maury W. Modification of N-Linked Glycan Sites in Viral Glycoproteins. Methods Mol Biol 2024; 2762:27-41. [PMID: 38315358 DOI: 10.1007/978-1-0716-3666-4_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Post-translational modification of proteins by the addition of sugar chains, or glycans, is a functionally important hallmark of proteins trafficked through the secretory system. These proteins are termed glycoproteins. Glycans are known to be important for initiating signaling through binding of cell surface receptors, facilitating protein folding, and maintaining protein stability. For pathogens, glycans can also mask vulnerable protein regions from neutralizing antibodies. Thus, there is a need to develop methods to decipher the role of specific glycans attached to proteins in order to understand their biological role. Here, we describe established methods for identifying glycosylated residues and understanding their role in protein synthesis and function using viral glycoproteins as a model.
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Affiliation(s)
- Nicholas J Lennemann
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, AL, USA.
| | - Lochlain Corliss
- Department of Microbiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Wendy Maury
- Department of Microbiology and Immunology, University of Iowa, Iowa City, IA, USA
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Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. Comparative Analysis of Conformational Dynamics and Systematic Characterization of Cryptic Pockets in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 Spike Complexes with the ACE2 Host Receptor: Confluence of Binding and Structural Plasticity in Mediating Networks of Conserved Allosteric Sites. Viruses 2023; 15:2073. [PMID: 37896850 PMCID: PMC10612107 DOI: 10.3390/v15102073] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/04/2023] [Accepted: 10/06/2023] [Indexed: 10/29/2023] Open
Abstract
In the current study, we explore coarse-grained simulations and atomistic molecular dynamics together with binding energetics scanning and cryptic pocket detection in a comparative examination of conformational landscapes and systematic characterization of allosteric binding sites in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 spike full-length trimer complexes with the host receptor ACE2. Microsecond simulations, Markov state models and mutational scanning of binding energies of the SARS-CoV-2 BA.2 and BA.2.75 receptor binding domain complexes revealed the increased thermodynamic stabilization of the BA.2.75 variant and significant dynamic differences between these Omicron variants. Molecular simulations of the SARS-CoV-2 Omicron spike full-length trimer complexes with the ACE2 receptor complemented atomistic studies and enabled an in-depth analysis of mutational and binding effects on conformational dynamic and functional adaptability of the Omicron variants. Despite considerable structural similarities, Omicron variants BA.2, BA.2.75 and XBB.1 can induce unique conformational dynamic signatures and specific distributions of the conformational states. Using conformational ensembles of the SARS-CoV-2 Omicron spike trimer complexes with ACE2, we conducted a comprehensive cryptic pocket screening to examine the role of Omicron mutations and ACE2 binding on the distribution and functional mechanisms of the emerging allosteric binding sites. This analysis captured all experimentally known allosteric sites and discovered networks of inter-connected and functionally relevant allosteric sites that are governed by variant-sensitive conformational adaptability of the SARS-CoV-2 spike structures. The results detailed how ACE2 binding and Omicron mutations in the BA.2, BA.2.75 and XBB.1 spike complexes modulate the distribution of conserved and druggable allosteric pockets harboring functionally important regions. The results are significant for understanding the functional roles of druggable cryptic pockets that can be used for allostery-mediated therapeutic intervention targeting conformational states of the Omicron variants.
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Affiliation(s)
- Mohammed Alshahrani
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Grace Gupta
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75275, USA; (S.X.); (P.T.)
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, TX 75275, USA; (S.X.); (P.T.)
| | - Gennady Verkhivker
- Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA; (M.A.); (G.G.)
- Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, USA
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