1
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Perez S, Makshakova O, Angulo J, Bedini E, Bisio A, de Paz JL, Fadda E, Guerrini M, Hricovini M, Hricovini M, Lisacek F, Nieto PM, Pagel K, Paiardi G, Richter R, Samsonov SA, Vivès RR, Nikitovic D, Ricard Blum S. Glycosaminoglycans: What Remains To Be Deciphered? JACS AU 2023; 3:628-656. [PMID: 37006755 PMCID: PMC10052243 DOI: 10.1021/jacsau.2c00569] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 06/19/2023]
Abstract
Glycosaminoglycans (GAGs) are complex polysaccharides exhibiting a vast structural diversity and fulfilling various functions mediated by thousands of interactions in the extracellular matrix, at the cell surface, and within the cells where they have been detected in the nucleus. It is known that the chemical groups attached to GAGs and GAG conformations comprise "glycocodes" that are not yet fully deciphered. The molecular context also matters for GAG structures and functions, and the influence of the structure and functions of the proteoglycan core proteins on sulfated GAGs and vice versa warrants further investigation. The lack of dedicated bioinformatic tools for mining GAG data sets contributes to a partial characterization of the structural and functional landscape and interactions of GAGs. These pending issues will benefit from the development of new approaches reviewed here, namely (i) the synthesis of GAG oligosaccharides to build large and diverse GAG libraries, (ii) GAG analysis and sequencing by mass spectrometry (e.g., ion mobility-mass spectrometry), gas-phase infrared spectroscopy, recognition tunnelling nanopores, and molecular modeling to identify bioactive GAG sequences, biophysical methods to investigate binding interfaces, and to expand our knowledge and understanding of glycocodes governing GAG molecular recognition, and (iii) artificial intelligence for in-depth investigation of GAGomic data sets and their integration with proteomics.
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Affiliation(s)
- Serge Perez
- Centre
de Recherche sur les Macromolecules, Vegetales,
University of Grenoble-Alpes, Centre National de la Recherche Scientifique, Grenoble F-38041 France
| | - Olga Makshakova
- FRC
Kazan Scientific Center of Russian Academy of Sciences, Kazan Institute of Biochemistry and Biophysics, Kazan 420111, Russia
| | - Jesus Angulo
- Insituto
de Investigaciones Quimicas, CIC Cartuja, CSIC and Universidad de Sevilla, Sevilla, SP 41092, Spain
| | - Emiliano Bedini
- Department
of Chemical Sciences, University of Naples
Federico II, Naples,I-80126, Italy
| | - Antonella Bisio
- Istituto
di Richerche Chimiche e Biochimiche, G. Ronzoni, Milan I-20133, Italy
| | - Jose Luis de Paz
- Insituto
de Investigaciones Quimicas, CIC Cartuja, CSIC and Universidad de Sevilla, Sevilla, SP 41092, Spain
| | - Elisa Fadda
- Department
of Chemistry and Hamilton Institute, Maynooth
University, Maynooth W23 F2H6, Ireland
| | - Marco Guerrini
- Istituto
di Richerche Chimiche e Biochimiche, G. Ronzoni, Milan I-20133, Italy
| | - Michal Hricovini
- Institute
of Chemistry, Slovak Academy of Sciences, Bratislava SK-845 38, Slovakia
| | - Milos Hricovini
- Institute
of Chemistry, Slovak Academy of Sciences, Bratislava SK-845 38, Slovakia
| | - Frederique Lisacek
- Computer
Science Department & Section of Biology, University of Geneva & Swiss Institue of Bioinformatics, Geneva CH-1227, Switzerland
| | - Pedro M. Nieto
- Insituto
de Investigaciones Quimicas, CIC Cartuja, CSIC and Universidad de Sevilla, Sevilla, SP 41092, Spain
| | - Kevin Pagel
- Institut
für Chemie und Biochemie Organische Chemie, Freie Universität Berlin, Berlin 14195, Germany
| | - Giulia Paiardi
- Molecular
and Cellular Modeling Group, Heidelberg Institute for Theoretical
Studies, Heidelberg University, Heidelberg 69118, Germany
| | - Ralf Richter
- School
of Biomedical Sciences, Faculty of Biological Sciences, School of
Physics and Astronomy, Faculty of Engineering and Physical Sciences,
Astbury Centre for Structural Molecular Biology and Bragg Centre for
Materials Research, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Sergey A. Samsonov
- Department
of Theoretical Chemistry, Faculty of Chemistry, University of Gdansk, Gdsank 80-309, Poland
| | - Romain R. Vivès
- Univ.
Grenoble Alpes, CNRS, CEA, IBS, Grenoble F-38044, France
| | - Dragana Nikitovic
- School
of Histology-Embriology, Medical School, University of Crete, Heraklion 71003, Greece
| | - Sylvie Ricard Blum
- University
Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry,
UMR 5246, Villeurbanne F 69622 Cedex, France
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2
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Joshi RP, Schultz KJ, Wilson JW, Kruel A, Varikoti RA, Kombala CJ, Kneller DW, Galanie S, Phillips G, Zhang Q, Coates L, Parvathareddy J, Surendranathan S, Kong Y, Clyde A, Ramanathan A, Jonsson CB, Brandvold KR, Zhou M, Head MS, Kovalevsky A, Kumar N. AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2. J Chem Inf Model 2023; 63:1438-1453. [PMID: 36808989 PMCID: PMC9969887 DOI: 10.1021/acs.jcim.2c01377] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Indexed: 02/23/2023]
Abstract
Direct-acting antivirals for the treatment of the COVID-19 pandemic caused by the SARS-CoV-2 virus are needed to complement vaccination efforts. Given the ongoing emergence of new variants, automated experimentation, and active learning based fast workflows for antiviral lead discovery remain critical to our ability to address the pandemic's evolution in a timely manner. While several such pipelines have been introduced to discover candidates with noncovalent interactions with the main protease (Mpro), here we developed a closed-loop artificial intelligence pipeline to design electrophilic warhead-based covalent candidates. This work introduces a deep learning-assisted automated computational workflow to introduce linkers and an electrophilic "warhead" to design covalent candidates and incorporates cutting-edge experimental techniques for validation. Using this process, promising candidates in the library were screened, and several potential hits were identified and tested experimentally using native mass spectrometry and fluorescence resonance energy transfer (FRET)-based screening assays. We identified four chloroacetamide-based covalent inhibitors of Mpro with micromolar affinities (KI of 5.27 μM) using our pipeline. Experimentally resolved binding modes for each compound were determined using room-temperature X-ray crystallography, which is consistent with the predicted poses. The induced conformational changes based on molecular dynamics simulations further suggest that the dynamics may be an important factor to further improve selectivity, thereby effectively lowering KI and reducing toxicity. These results demonstrate the utility of our modular and data-driven approach for potent and selective covalent inhibitor discovery and provide a platform to apply it to other emerging targets.
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Affiliation(s)
- Rajendra P. Joshi
- Earth and Biological Sciences Directorate,
Pacific Northwest National Laboratory, Richland, Washington
99352, United States
| | - Katherine J. Schultz
- Earth and Biological Sciences Directorate,
Pacific Northwest National Laboratory, Richland, Washington
99352, United States
| | - Jesse William Wilson
- Earth and Biological Sciences Directorate,
Pacific Northwest National Laboratory, Richland, Washington
99352, United States
| | - Agustin Kruel
- Earth and Biological Sciences Directorate,
Pacific Northwest National Laboratory, Richland, Washington
99352, United States
| | - Rohith Anand Varikoti
- Earth and Biological Sciences Directorate,
Pacific Northwest National Laboratory, Richland, Washington
99352, United States
| | - Chathuri J. Kombala
- Elson S. Floyd College of Medicine, Department of
Nutrition and Exercise Physiology, Washington State University,
Spokane, Washington 99202, United States
| | - Daniel W. Kneller
- Neutron Scattering Division, Oak Ridge
National Laboratory, Oak Ridge, Tennessee 37831, United
States
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
| | - Stephanie Galanie
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
- Biosciences Division, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37831, United
States
- Department of Process Research and Development,
Merck & Co., Inc., 126 E. Lincoln Avenue, Rahway, New
Jersey 07065, United States
| | - Gwyndalyn Phillips
- Neutron Scattering Division, Oak Ridge
National Laboratory, Oak Ridge, Tennessee 37831, United
States
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
| | - Qiu Zhang
- Neutron Scattering Division, Oak Ridge
National Laboratory, Oak Ridge, Tennessee 37831, United
States
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
| | - Leighton Coates
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
- Second Target Station, Oak Ridge National
Laboratory, Oak Ridge, Tennessee 37831, United
States
| | - Jyothi Parvathareddy
- Regional Biocontainment Laboratory, The
University of Tennessee Health Science Center, Memphis, Tennessee 38105,
United States
| | - Surekha Surendranathan
- Regional Biocontainment Laboratory, The
University of Tennessee Health Science Center, Memphis, Tennessee 38105,
United States
| | - Ying Kong
- Regional Biocontainment Laboratory, The
University of Tennessee Health Science Center, Memphis, Tennessee 38105,
United States
| | - Austin Clyde
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
- Data Science and Learning Division,
Argonne National Laboratory, Lemont, Illinois 60439,
United States
| | - Arvind Ramanathan
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
- Data Science and Learning Division,
Argonne National Laboratory, Lemont, Illinois 60439,
United States
| | - Colleen B. Jonsson
- Regional Biocontainment Laboratory, The
University of Tennessee Health Science Center, Memphis, Tennessee 38105,
United States
- Institute for the Study of Host-Pathogen Systems,
University of Tennessee Health Science Center, Memphis,
Tennessee 38103, United States
- Department of Microbiology, Immunology and
Biochemistry, University of Tennessee Health Science Center,
Memphis, Tennessee 38103, United States
| | - Kristoffer R. Brandvold
- Earth and Biological Sciences Directorate,
Pacific Northwest National Laboratory, Richland, Washington
99352, United States
- Elson S. Floyd College of Medicine, Department of
Nutrition and Exercise Physiology, Washington State University,
Spokane, Washington 99202, United States
| | - Mowei Zhou
- Earth and Biological Sciences Directorate,
Pacific Northwest National Laboratory, Richland, Washington
99352, United States
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
| | - Martha S. Head
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
- Joint Institute for Biological Sciences,
Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831,
United States
- Center for Research Acceleration by Digital
Innovation, Amgen Research, Thousand Oaks, California 91320,
United States
| | - Andrey Kovalevsky
- Neutron Scattering Division, Oak Ridge
National Laboratory, Oak Ridge, Tennessee 37831, United
States
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
| | - Neeraj Kumar
- Earth and Biological Sciences Directorate,
Pacific Northwest National Laboratory, Richland, Washington
99352, United States
- National Virtual Biotechnology Laboratory,
US Department of Energy, Washington, District of Columbia
20585, United States
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3
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Quintana JI, Atxabal U, Unione L, Ardá A, Jiménez-Barbero J. Exploring multivalent carbohydrate-protein interactions by NMR. Chem Soc Rev 2023; 52:1591-1613. [PMID: 36753338 PMCID: PMC9987413 DOI: 10.1039/d2cs00983h] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Indexed: 02/09/2023]
Abstract
Nuclear Magnetic Resonance (NMR) has been widely employed to assess diverse features of glycan-protein molecular recognition events. Different types of qualitative and quantitative information at different degrees of resolution and complexity can be extracted from the proper application of the available NMR-techniques. In fact, affinity, structural, kinetic, conformational, and dynamic characteristics of the binding process are available. Nevertheless, except in particular cases, the affinity of lectin-sugar interactions is weak, mostly at the low mM range. This feature is overcome in biological processes by using multivalency, thus augmenting the strength of the binding. However, the application of NMR methods to monitor multivalent lectin-glycan interactions is intrinsically challenging. It is well known that when large macromolecular complexes are formed, the NMR signals disappear from the NMR spectrum, due to the existence of fast transverse relaxation, related to the large size and exchange features. Indeed, at the heart of the molecular recognition event, the associated free-bound chemical exchange process for both partners takes place in a particular timescale. Thus, these factors have to be considered and overcome. In this review article, we have distinguished, in a subjective manner, the existence of multivalent presentations in the glycan or in the lectin. From the glycan perspective, we have also considered whether multiple epitopes of a given ligand are presented in the same linear chain of a saccharide (i.e., poly-LacNAc oligosaccharides) or decorating different arms of a multiantennae scaffold, either natural (as in multiantennae N-glycans) or synthetic (of dendrimer or polymer nature). From the lectin perspective, the presence of an individual binding site at every monomer of a multimeric lectin may also have key consequences for the binding event at different levels of complexity.
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Affiliation(s)
- Jon I Quintana
- CICbioGUNE, Basque Research & Technology Alliance (BRTA), Bizkaia Technology Park, Building 800, 48160 Derio, Bizkaia, Spain.
| | - Unai Atxabal
- CICbioGUNE, Basque Research & Technology Alliance (BRTA), Bizkaia Technology Park, Building 800, 48160 Derio, Bizkaia, Spain.
| | - Luca Unione
- CICbioGUNE, Basque Research & Technology Alliance (BRTA), Bizkaia Technology Park, Building 800, 48160 Derio, Bizkaia, Spain.
- Ikerbasque, Basque Foundation for Science, Plaza Euskadi 5, 48009 Bilbao, Bizkaia, Spain
| | - Ana Ardá
- CICbioGUNE, Basque Research & Technology Alliance (BRTA), Bizkaia Technology Park, Building 800, 48160 Derio, Bizkaia, Spain.
- Ikerbasque, Basque Foundation for Science, Plaza Euskadi 5, 48009 Bilbao, Bizkaia, Spain
| | - Jesús Jiménez-Barbero
- CICbioGUNE, Basque Research & Technology Alliance (BRTA), Bizkaia Technology Park, Building 800, 48160 Derio, Bizkaia, Spain.
- Ikerbasque, Basque Foundation for Science, Plaza Euskadi 5, 48009 Bilbao, Bizkaia, Spain
- Department of Organic Chemistry, II Faculty of Science and Technology, EHU-UPV, 48940 Leioa, Spain
- Centro de Investigación Biomédica En Red de Enfermedades Respiratorias, Madrid, Spain
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4
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Gerothanassis IP. Ligand-observed in-tube NMR in natural products research: A review on enzymatic biotransformations, protein-ligand interactions, and in-cell NMR spectroscopy. ARAB J CHEM 2023. [DOI: 10.1016/j.arabjc.2022.104536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
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5
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Inter-Ligand STD NMR: An Efficient 1D NMR Approach to Probe Relative Orientation of Ligands in a Multi-Subsite Protein Binding Pocket. Pharmaceuticals (Basel) 2022; 15:ph15081030. [PMID: 36015178 PMCID: PMC9415034 DOI: 10.3390/ph15081030] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 08/12/2022] [Accepted: 08/19/2022] [Indexed: 11/27/2022] Open
Abstract
In recent years, Saturation Transfer Difference NMR (STD NMR) has been proven to be a powerful and versatile ligand-based NMR technique to elucidate crucial aspects in the investigation of protein-ligand complexes. Novel STD NMR approaches relying on “multi-frequency” irradiation have enabled us to even elucidate specific ligand-amino acid interactions and explore the binding of fragments in previously unknown binding subsites. Exploring multi-subsite protein binding pockets is especially important in Fragment Based Drug Discovery (FBDD) to design leads of increased specificity and efficacy. We hereby propose a novel multi-frequency STD NMR approach based on direct irradiation of one of the ligands in a multi-ligand binding process, to probe the vicinity and explore the relative orientation of fragments in adjacent binding sub-sites, which we called Inter-Ligand STD NMR (IL-STD NMR). We proved its applicability on (i) a standard protein-ligand system commonly used for ligand-observed NMR benchmarking: Naproxen as bound to Bovine Serum Albumin, and (ii) the biologically relevant system of Cholera Toxin Subunit B and two inhibitors adjacently bound within the GM1 binding site. Relative to Inter-Ligand NOE (ILOE), the current state-of-the-art methodology to probe relative orientations of adjacent ligands, IL-STD NMR requires about one tenth of the experimental time and protein consumption, making it a competitive methodology with the potential to be applied in the pharmaceutical industries.
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6
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Di Carluccio C, Forgione MC, Martini S, Berti F, Molinaro A, Marchetti R, Silipo A. Investigation of protein-ligand complexes by ligand-based NMR methods. Carbohydr Res 2021; 503:108313. [PMID: 33865181 DOI: 10.1016/j.carres.2021.108313] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/31/2021] [Accepted: 04/06/2021] [Indexed: 11/20/2022]
Abstract
Molecular recognition is at the base of all biological events and its knowledge at atomic level is pivotal in the development of new drug design approaches. NMR spectroscopy is one of the most widely used technique to detect and characterize transient ligand-receptor interactions in solution. In particular, ligand-based NMR approaches, including NOE-based NMR techniques, diffusion experiments and relaxation methods, are excellent tools to investigate how ligands interact with their receptors. Here we describe the key structural information that can be achieved on binding processes thanks to the combined used of advanced NMR and computational methods. Saturation Transfer Difference NMR (STD-NMR), WaterLOGSY, diffusion- and relaxation-based experiments, together with tr-NOE techniques allow, indeed, to investigate the ligand behavior when bound to a receptor, determining, among others, the epitope map of the ligand and its bioactive conformation. The combination of these NMR techniques with computational methods, including docking, molecular dynamics and CORCEMA-ST analysis, permits to define and validate an accurate 3D model of protein-ligand complexes.
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Affiliation(s)
- Cristina Di Carluccio
- Dipartimento di Scienze Chimiche, Complesso Universitario Monte Sant'Angelo, Università di Napoli Federico II, Via Cintia 4, I-80126, Napoli, Italy
| | - Maria Concetta Forgione
- Dipartimento di Scienze Chimiche, Complesso Universitario Monte Sant'Angelo, Università di Napoli Federico II, Via Cintia 4, I-80126, Napoli, Italy; GSK, Via Fiorentina 1, 53100, Siena, Italy
| | | | | | - Antonio Molinaro
- Dipartimento di Scienze Chimiche, Complesso Universitario Monte Sant'Angelo, Università di Napoli Federico II, Via Cintia 4, I-80126, Napoli, Italy
| | - Roberta Marchetti
- Dipartimento di Scienze Chimiche, Complesso Universitario Monte Sant'Angelo, Università di Napoli Federico II, Via Cintia 4, I-80126, Napoli, Italy.
| | - Alba Silipo
- Dipartimento di Scienze Chimiche, Complesso Universitario Monte Sant'Angelo, Università di Napoli Federico II, Via Cintia 4, I-80126, Napoli, Italy; CNR, Institute for Polymers, Composites and Biomaterials, IPCB ss, Catania, Italy.
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