1
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McCarthy WJ, Thomas SE, Olaleye T, Boland JA, Floto RA, Williams G, Blundell TL, Coyne AG, Abell C. A Fragment-Based Competitive 19F LB-NMR Platform For Hotspot-Directed Ligand Profiling. Angew Chem Int Ed Engl 2024; 63:e202406846. [PMID: 38896426 DOI: 10.1002/anie.202406846] [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: 04/10/2024] [Revised: 06/19/2024] [Accepted: 06/19/2024] [Indexed: 06/21/2024]
Abstract
Ligand binding hotspots are regions of protein surfaces that form particularly favourable interactions with small molecule pharmacophores. Targeting interactions with these hotspots maximises the efficiency of ligand binding. Existing methods are capable of identifying hotspots but often lack assays to quantify ligand binding and direct elaboration at these sites. Herein, we describe a fragment-based competitive 19F Ligand Based NMR (LB-NMR) screening platform that enables routine, quantitative ligand profiling focused at ligand-binding hotspots. As a proof of concept, the method was applied to 4'-phosphopantetheine adenylyltransferase (PPAT) from Mycobacterium abscessus (Mabs). X-ray crystallographic characterisation of the hits from a 960-member fragment screen identified three ligand-binding hotspots across the PPAT active site. From the fragment hits a collection of 19F reporter candidates were designed and synthesised. By rigorous prioritisation and use of optimisation workflows, a single 19F reporter molecule was generated for each hotspot. Profiling the binding of a set of structurally characterised ligands by competitive 19F LB-NMR with this suite of 19F reporters recapitulated the binding affinity and site ID assignments made by ITC and X-ray crystallography. This quantitative mapping of ligand binding events at hotspot level resolution establishes the utility of the fragment-based competitive 19F LB-NMR screening platform for hotspot-directed ligand profiling.
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Affiliation(s)
- William J McCarthy
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK, CB2 1EW
- Present Address: Molecular Structure of Cell Signalling Laboratory, The Francis Crick Institute, 1 Midland Road, London, UK, NW1 1AT
| | - Sherine E Thomas
- Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, UK, CB2 1GA
- Present Address: Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge, UK, CB2 1PD
| | - Tayo Olaleye
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK, CB2 1EW
| | - Jennifer A Boland
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK, CB2 1EW
| | - R Andres Floto
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK, CB2 0QH
- VPD Heart Lung Research Institute, Department of Medicine, University of Cambridge, Cambridge, UK, CB2 0BB
| | - Glyn Williams
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK, CB2 1EW
| | - Tom L Blundell
- Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, UK, CB2 1GA
- VPD Heart Lung Research Institute, Department of Medicine, University of Cambridge, Cambridge, UK, CB2 0BB
| | - Anthony G Coyne
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK, CB2 1EW
| | - Chris Abell
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK, CB2 1EW
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2
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Mehlman T, Ginn HM, Keedy DA. An expanded trove of fragment-bound structures for the allosteric enzyme PTP1B from computational reanalysis of large-scale crystallographic data. Structure 2024; 32:1231-1238.e4. [PMID: 38861991 PMCID: PMC11316629 DOI: 10.1016/j.str.2024.05.010] [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: 01/13/2024] [Revised: 04/15/2024] [Accepted: 05/15/2024] [Indexed: 06/13/2024]
Abstract
Due to their low binding affinities, detecting small-molecule fragments bound to protein structures from crystallographic datasets has been a challenge. Here, we report a trove of 65 new fragment hits for PTP1B, an "undruggable" therapeutic target enzyme for diabetes and cancer. These structures were obtained from computational analysis of data from a large crystallographic screen, demonstrating the power of this approach to elucidate many (∼50% more) "hidden" ligand-bound states of proteins. Our new structures include a fragment hit found in a novel binding site in PTP1B with a unique location relative to the active site, one that links adjacent allosteric sites, and, perhaps most strikingly, a fragment that induces long-range allosteric protein conformational responses. Altogether, our research highlights the utility of computational analysis of crystallographic data, makes publicly available dozens of new ligand-bound structures of a high-value drug target, and identifies novel aspects of ligandability and allostery in PTP1B.
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Affiliation(s)
- Tamar Mehlman
- Structural Biology Initiative, CUNY Advanced Science Research Center, New York, NY 10031, USA; PhD Program in Biochemistry, CUNY Graduate Center, New York, NY 10016, USA
| | - Helen M Ginn
- Center for Free-Electron Laser Science CFEL, Deutsches Elektronen-Synchrotron DESY, Hamburg, Germany; Institute for Nanostructure and Solid State Physics, Universität Hamburg, Hamburg, Germany; Division of Life Sciences, Diamond Light Source Ltd, Harwell Science and Innovation Campus, Didcot, UK
| | - Daniel A Keedy
- Structural Biology Initiative, CUNY Advanced Science Research Center, New York, NY 10031, USA; Department of Chemistry and Biochemistry, City College of New York, New York, NY 10031, USA; PhD Programs in Biochemistry, Biology, & Chemistry, CUNY Graduate Center, New York, NY 10016, USA.
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3
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Dalwani S, Metz A, Huschmann FU, Weiss MS, Wierenga RK, Venkatesan R. Crystallographic fragment-binding studies of the Mycobacterium tuberculosis trifunctional enzyme suggest binding pockets for the tails of the acyl-CoA substrates at its active sites and a potential substrate-channeling path between them. Acta Crystallogr D Struct Biol 2024; 80:605-619. [PMID: 39012716 DOI: 10.1107/s2059798324006557] [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: 01/12/2024] [Accepted: 07/03/2024] [Indexed: 07/18/2024] Open
Abstract
The Mycobacterium tuberculosis trifunctional enzyme (MtTFE) is an α2β2 tetrameric enzyme in which the α-chain harbors the 2E-enoyl-CoA hydratase (ECH) and 3S-hydroxyacyl-CoA dehydrogenase (HAD) active sites, and the β-chain provides the 3-ketoacyl-CoA thiolase (KAT) active site. Linear, medium-chain and long-chain 2E-enoyl-CoA molecules are the preferred substrates of MtTFE. Previous crystallographic binding and modeling studies identified binding sites for the acyl-CoA substrates at the three active sites, as well as the NAD binding pocket at the HAD active site. These studies also identified three additional CoA binding sites on the surface of MtTFE that are different from the active sites. It has been proposed that one of these additional sites could be of functional relevance for the substrate channeling (by surface crawling) of reaction intermediates between the three active sites. Here, 226 fragments were screened in a crystallographic fragment-binding study of MtTFE crystals, resulting in the structures of 16 MtTFE-fragment complexes. Analysis of the 121 fragment-binding events shows that the ECH active site is the `binding hotspot' for the tested fragments, with 41 binding events. The mode of binding of the fragments bound at the active sites provides additional insight into how the long-chain acyl moiety of the substrates can be accommodated at their proposed binding pockets. In addition, the 20 fragment-binding events between the active sites identify potential transient binding sites of reaction intermediates relevant to the possible channeling of substrates between these active sites. These results provide a basis for further studies to understand the functional relevance of the latter binding sites and to identify substrates for which channeling is crucial.
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Affiliation(s)
- Subhadra Dalwani
- Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland
| | - Alexander Metz
- Department of Pharmaceutical Chemistry, Philipps-University Marburg, Marburg, Germany
| | - Franziska U Huschmann
- Department of Pharmaceutical Chemistry, Philipps-University Marburg, Marburg, Germany
| | - Manfred S Weiss
- Macromolecular Crystallography, Helmholtz-Zentrum Berlin, Berlin, Germany
| | - Rik K Wierenga
- Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland
| | - Rajaram Venkatesan
- Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland
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4
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Ray Chaudhuri N, Ghosh Dastidar S. Adaptive Workflows of Machine Learning Illuminate the Sequential Operation Mechanism of the TAK1's Allosteric Network. Biochemistry 2024; 63:1474-1492. [PMID: 38743619 DOI: 10.1021/acs.biochem.3c00643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Allostery is a fundamental mechanism driving biomolecular processes that holds significant therapeutic concern. Our study rigorously investigates how two distinct machine-learning algorithms uniquely classify two already close-to-active DFG-in states of TAK1, differing just by the presence or absence of its allosteric activator TAB1, from an ensemble mixture of conformations (obtained from 2.4 μs molecular dynamics (MD) simulations). The novelty, however, lies in understanding the deeper algorithmic potentials to systematically derive a diverse set of differential residue connectivity features that reconstruct the essential mechanistic architecture for TAK1-TAB1 allostery in such a close-to-active biochemical scenario. While the recursive, random forest-based workflow displays the potential of conducting discretized, hierarchical derivation of allosteric features, a multilayer perceptron-based approach gains considerable efficacy in revealing fluid connected patterns of features when hybridized with mutual information scoring. Interestingly, both pipelines benchmark similar directions of functional conformational changes for TAK1's activation. The findings significantly advance the depth of mechanistic understanding by highlighting crucial activation signatures along a directed C-lobe → activation loop → ATP pocket channel of information flow, including (1) the αF-αE biterminal alignments and (2) the "catalytic" drift of the activation loop toward kinase active site. Besides, some novel allosteric hotspots (K253, Y206, N189, etc.) are further recognized as TAB1 sensors, transducers, and responders, including a benchmark E70 mutation site, precisely mapping the important structural segments for sequential allosteric execution. Hence, our work demonstrates how to navigate through greater structural depths and dimensions of dynamic allosteric machineries just by leveraging standard ML methods in suitable streamlined workflows adaptive to the specific system and objectives.
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Affiliation(s)
- Nibedita Ray Chaudhuri
- Biological Sciences, Bose Institute, EN 80, Sector V, Bidhan Nagar, Kolkata 700091, India
| | - Shubhra Ghosh Dastidar
- Biological Sciences, Bose Institute, EN 80, Sector V, Bidhan Nagar, Kolkata 700091, India
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5
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Stachowski TR, Fischer M. FLEXR GUI: a graphical user interface for multi-conformer modeling of proteins. J Appl Crystallogr 2024; 57:580-586. [PMID: 38596743 PMCID: PMC11001397 DOI: 10.1107/s1600576724001523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 02/14/2024] [Indexed: 04/11/2024] Open
Abstract
Proteins are well known 'shapeshifters' which change conformation to function. In crystallography, multiple conformational states are often present within the crystal and the resulting electron-density map. Yet, explicitly incorporating alternative states into models to disentangle multi-conformer ensembles is challenging. We previously reported the tool FLEXR, which, within a few minutes, automatically separates conformational signal from noise and builds the corresponding, often missing, structural features into a multi-conformer model. To make the method widely accessible for routine multi-conformer building as part of the computational toolkit for macromolecular crystallography, we present a graphical user interface (GUI) for FLEXR, designed as a plugin for Coot 1. The GUI implementation seamlessly connects FLEXR models with the existing suite of validation and modeling tools available in Coot. We envision that FLEXR will aid crystallographers by increasing access to a multi-conformer modeling method that will ultimately lead to a better representation of protein conformational heterogeneity in the Protein Data Bank. In turn, deeper insights into the protein conformational landscape may inform biology or provide new opportunities for ligand design. The code is open source and freely available on GitHub at https://github.com/TheFischerLab/FLEXR-GUI.
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Affiliation(s)
- Timothy R. Stachowski
- Department of Chemical Biology and Therapeutics, St Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Marcus Fischer
- Department of Chemical Biology and Therapeutics, St Jude Children’s Research Hospital, Memphis, TN 38105, USA
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6
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Mehlman T(S, Ginn HM, Keedy DA. An expanded view of ligandability in the allosteric enzyme PTP1B from computational reanalysis of large-scale crystallographic data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.05.574428. [PMID: 38260327 PMCID: PMC10802458 DOI: 10.1101/2024.01.05.574428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The recent advent of crystallographic small-molecule fragment screening presents the opportunity to obtain unprecedented numbers of ligand-bound protein crystal structures from a single high-throughput experiment, mapping ligandability across protein surfaces and identifying useful chemical footholds for structure-based drug design. However, due to the low binding affinities of most fragments, detecting bound fragments from crystallographic datasets has been a challenge. Here we report a trove of 65 new fragment hits across 59 new liganded crystal structures for PTP1B, an "undruggable" therapeutic target enzyme for diabetes and cancer. These structures were obtained from computational analysis of data from a large crystallographic screen, demonstrating the power of this approach to elucidate many (~50% more) "hidden" ligand-bound states of proteins. Our new structures include a fragment hit found in a novel binding site in PTP1B with a unique location relative to the active site, one that validates another new binding site recently identified by simulations, one that links adjacent allosteric sites, and, perhaps most strikingly, a fragment that induces long-range allosteric protein conformational responses via a previously unreported intramolecular conduit. Altogether, our research highlights the utility of computational analysis of crystallographic data, makes publicly available dozens of new ligand-bound structures of a high-value drug target, and identifies novel aspects of ligandability and allostery in PTP1B.
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Affiliation(s)
- Tamar (Skaist) Mehlman
- Structural Biology Initiative, CUNY Advanced Science Research Center, New York, NY 10031
- PhD Program in Biochemistry, CUNY Graduate Center, New York, NY 10016
| | - Helen M. Ginn
- Center for Free-Electron Laser Science CFEL, Deutsches Elektronen-Synchrotron DESY, Hamburg, Germany
- Institute for Nanostructure and Solid State Physics, Universität Hamburg, Hamburg, Germany
- Division of Life Sciences, Diamond Light Source Ltd, Harwell Science and Innovation Campus, Didcot, UK
| | - Daniel A. Keedy
- Structural Biology Initiative, CUNY Advanced Science Research Center, New York, NY 10031
- Department of Chemistry and Biochemistry, City College of New York, New York, NY 10031
- PhD Programs in Biochemistry, Biology, & Chemistry, CUNY Graduate Center, New York, NY 10016
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7
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Du S, Wankowicz SA, Yabukarski F, Doukov T, Herschlag D, Fraser JS. Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction data. Methods Enzymol 2023; 688:223-254. [PMID: 37748828 PMCID: PMC10637719 DOI: 10.1016/bs.mie.2023.06.009] [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] [Indexed: 09/27/2023]
Abstract
Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363 K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.
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Affiliation(s)
- Siyuan Du
- Department of Biochemistry, Stanford University, Stanford, CA, United States; Department of Chemistry, Stanford University, Stanford, CA, United States
| | - Stephanie A Wankowicz
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, United States
| | - Filip Yabukarski
- Department of Biochemistry, Stanford University, Stanford, CA, United States; Bristol-Myers Squibb, San Diego, CA, United States
| | - Tzanko Doukov
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA, United States
| | - Daniel Herschlag
- Department of Biochemistry, Stanford University, Stanford, CA, United States; Department of Chemical Engineering, Stanford University, Stanford, CA, United States; Stanford ChEM-H, Stanford University, Stanford, CA, United States
| | - James S Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, United States; Quantitative Biosciences Institute, University of California, San Francisco, CA, United States.
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8
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Mathy CJP, Kortemme T. Emerging maps of allosteric regulation in cellular networks. Curr Opin Struct Biol 2023; 80:102602. [PMID: 37150039 PMCID: PMC10960510 DOI: 10.1016/j.sbi.2023.102602] [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: 12/29/2022] [Revised: 03/24/2023] [Accepted: 04/04/2023] [Indexed: 05/09/2023]
Abstract
Allosteric regulation is classically defined as action at a distance, where a perturbation outside of a protein active site affects function. While this definition has motivated many studies of allosteric mechanisms at the level of protein structure, translating these insights to the allosteric regulation of entire cellular processes - and their crosstalk - has received less attention, despite the broad importance of allostery for cellular regulation foreseen by Jacob and Monod. Here, we revisit an evolutionary model for the widespread emergence of allosteric regulation in colocalized proteins, describe supporting evidence, and discuss emerging advances in mapping allostery in cellular networks that link precise and often allosteric perturbations at the molecular level to functional changes at the pathway and systems levels.
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Affiliation(s)
- Christopher J P Mathy
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94158, USA; Quantitative Biosciences Institute, University of California, San Francisco, CA, 94158, USA; The UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, CA, 94158, USA.
| | - Tanja Kortemme
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94158, USA; Quantitative Biosciences Institute, University of California, San Francisco, CA, 94158, USA; The UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, CA, 94158, USA; Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
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9
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Du S, Wankowicz SA, Yabukarski F, Doukov T, Herschlag D, Fraser JS. Refinement of Multiconformer Ensemble Models from Multi-temperature X-ray Diffraction Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.05.539620. [PMID: 37205593 PMCID: PMC10187334 DOI: 10.1101/2023.05.05.539620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.
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Affiliation(s)
- Siyuan Du
- Department of Biochemistry, Stanford University, Stanford, California 94305, United States
- Department of Chemistry, Stanford University, Stanford, California 94305, United States
| | - Stephanie A. Wankowicz
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, United States
| | - Filip Yabukarski
- Department of Biochemistry, Stanford University, Stanford, California 94305, United States
- Bristol-Myers Squibb, San Diego, California 92121, United States
| | - Tzanko Doukov
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, California 94025, United States
| | - Daniel Herschlag
- Department of Biochemistry, Stanford University, Stanford, California 94305, United States
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
- Stanford ChEM-H, Stanford University, Stanford, California 94305, United States
| | - James S. Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California 94143, United States
- Quantitative Biosciences Institute, University of California, San Francisco, California 94143, United States
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10
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Skaist Mehlman T, Biel JT, Azeem SM, Nelson ER, Hossain S, Dunnett L, Paterson NG, Douangamath A, Talon R, Axford D, Orins H, von Delft F, Keedy DA. Room-temperature crystallography reveals altered binding of small-molecule fragments to PTP1B. eLife 2023; 12:84632. [PMID: 36881464 PMCID: PMC9991056 DOI: 10.7554/elife.84632] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 02/12/2023] [Indexed: 03/08/2023] Open
Abstract
Much of our current understanding of how small-molecule ligands interact with proteins stems from X-ray crystal structures determined at cryogenic (cryo) temperature. For proteins alone, room-temperature (RT) crystallography can reveal previously hidden, biologically relevant alternate conformations. However, less is understood about how RT crystallography may impact the conformational landscapes of protein-ligand complexes. Previously, we showed that small-molecule fragments cluster in putative allosteric sites using a cryo crystallographic screen of the therapeutic target PTP1B (Keedy et al., 2018). Here, we have performed two RT crystallographic screens of PTP1B using many of the same fragments, representing the largest RT crystallographic screens of a diverse library of ligands to date, and enabling a direct interrogation of the effect of data collection temperature on protein-ligand interactions. We show that at RT, fewer ligands bind, and often more weakly - but with a variety of temperature-dependent differences, including unique binding poses, changes in solvation, new binding sites, and distinct protein allosteric conformational responses. Overall, this work suggests that the vast body of existing cryo-temperature protein-ligand structures may provide an incomplete picture, and highlights the potential of RT crystallography to help complete this picture by revealing distinct conformational modes of protein-ligand systems. Our results may inspire future use of RT crystallography to interrogate the roles of protein-ligand conformational ensembles in biological function.
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Affiliation(s)
- Tamar Skaist Mehlman
- Structural Biology Initiative, CUNY Advanced Science Research CenterNew YorkUnited States
- PhD Program in Biochemistry, CUNY Graduate CenterNew YorkUnited States
| | - Justin T Biel
- Department of Bioengineering and Therapeutic Sciences, University of California, San FranciscoSan FranciscoUnited States
| | - Syeda Maryam Azeem
- Structural Biology Initiative, CUNY Advanced Science Research CenterNew YorkUnited States
| | | | - Sakib Hossain
- Structural Biology Initiative, CUNY Advanced Science Research CenterNew YorkUnited States
| | - Louise Dunnett
- Diamond Light SourceDidcotUnited Kingdom
- Research Complex at Harwell, Harwell Science and Innovation CampusDidcotUnited Kingdom
| | | | - Alice Douangamath
- Diamond Light SourceDidcotUnited Kingdom
- Research Complex at Harwell, Harwell Science and Innovation CampusDidcotUnited Kingdom
| | | | | | - Helen Orins
- Structural Biology Initiative, CUNY Advanced Science Research CenterNew YorkUnited States
| | - Frank von Delft
- Diamond Light SourceDidcotUnited Kingdom
- Research Complex at Harwell, Harwell Science and Innovation CampusDidcotUnited Kingdom
- Centre for Medicines Discovery, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
- Department of Biochemistry, University of JohannesburgJohannesburgSouth Africa
| | - Daniel A Keedy
- Structural Biology Initiative, CUNY Advanced Science Research CenterNew YorkUnited States
- Department of Chemistry and Biochemistry, City College of New YorkNew YorkUnited States
- PhD Programs in Biochemistry, Biology, and Chemistry, CUNY Graduate CenterNew YorkUnited States
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11
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Hough MA, Prischi F, Worrall JAR. Perspective: Structure determination of protein-ligand complexes at room temperature using X-ray diffraction approaches. Front Mol Biosci 2023; 10:1113762. [PMID: 36756363 PMCID: PMC9899996 DOI: 10.3389/fmolb.2023.1113762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 01/12/2023] [Indexed: 01/24/2023] Open
Abstract
The interaction between macromolecular proteins and small molecule ligands is an essential component of cellular function. Such ligands may include enzyme substrates, molecules involved in cellular signalling or pharmaceutical drugs. Together with biophysical techniques used to assess the thermodynamic and kinetic properties of ligand binding to proteins, methodology to determine high-resolution structures that enable atomic level interactions between protein and ligand(s) to be directly visualised is required. Whilst such structural approaches are well established with high throughput X-ray crystallography routinely used in the pharmaceutical sector, they provide only a static view of the complex. Recent advances in X-ray structural biology methods offer several new possibilities that can examine protein-ligand complexes at ambient temperature rather than under cryogenic conditions, enable transient binding sites and interactions to be characterised using time-resolved approaches and combine spectroscopic measurements from the same crystal that the structures themselves are determined. This Perspective reviews several recent developments in these areas and discusses new possibilities for applications of these advanced methodologies to transform our understanding of protein-ligand interactions.
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Affiliation(s)
- Michael A. Hough
- School of Life Sciences, University of Essex, Colchester, United Kingdom
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot, United Kingdom
| | - Filippo Prischi
- School of Life Sciences, University of Essex, Colchester, United Kingdom
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12
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Mühlethaler T, Milanos L, Ortega JA, Blum TB, Gioia D, Roy B, Prota AE, Cavalli A, Steinmetz MO. Rational Design of a Novel Tubulin Inhibitor with a Unique Mechanism of Action. Angew Chem Int Ed Engl 2022; 61:e202204052. [PMID: 35404502 PMCID: PMC9324959 DOI: 10.1002/anie.202204052] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Indexed: 11/16/2022]
Abstract
In this study, we capitalized on our previously performed crystallographic fragment screen and developed the antitubulin small molecule Todalam with only two rounds of straightforward chemical synthesis. Todalam binds to a novel tubulin site, disrupts microtubule networks in cells, arrests cells in G2/M, induces cell death, and synergizes with vinblastine. The compound destabilizes microtubules by acting as a molecular plug that sterically inhibits the curved-to-straight conformational switch in the α-tubulin subunit, and by sequestering tubulin dimers into assembly incompetent oligomers. Our results describe for the first time the generation of a fully rationally designed small molecule tubulin inhibitor from a fragment, which displays a unique molecular mechanism of action. They thus demonstrate the usefulness of tubulin-binding fragments as valuable starting points for innovative antitubulin drug and chemical probe discovery campaigns.
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Affiliation(s)
- Tobias Mühlethaler
- Laboratory of Biomolecular ResearchDepartment of Biology and ChemistryPaul Scherrer Institut5232Villigen PSISwitzerland
| | - Lampros Milanos
- Computational & Chemical BiologyIstituto Italiano di Tecnologiavia Morego 3016163GenovaItaly
| | - Jose Antonio Ortega
- Computational & Chemical BiologyIstituto Italiano di Tecnologiavia Morego 3016163GenovaItaly
| | - Thorsten B. Blum
- Laboratory of Biomolecular ResearchDepartment of Biology and ChemistryPaul Scherrer Institut5232Villigen PSISwitzerland
| | - Dario Gioia
- Computational & Chemical BiologyIstituto Italiano di Tecnologiavia Morego 3016163GenovaItaly
| | - Bibhas Roy
- Laboratory of Nanoscale BiologyDepartment of Biology and ChemistryPaul Scherrer Institut5232Villigen PSISwitzerland
| | - Andrea E. Prota
- Laboratory of Biomolecular ResearchDepartment of Biology and ChemistryPaul Scherrer Institut5232Villigen PSISwitzerland
| | - Andrea Cavalli
- Computational & Chemical BiologyIstituto Italiano di Tecnologiavia Morego 3016163GenovaItaly
- Department of Pharmacy and BiotechnologyAlma Mater StudiorumUniversity of Bolognavia Belmeloro 640126BolognaItaly
| | - Michel O. Steinmetz
- Laboratory of Biomolecular ResearchDepartment of Biology and ChemistryPaul Scherrer Institut5232Villigen PSISwitzerland
- University of Basel, Biozentrum4056BaselSwitzerland
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13
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Mühlethaler T, Milanos L, Ortega JA, Blum TB, Gioia D, Roy B, Prota AE, Cavalli A, Steinmetz MO. Rational Design of a Novel Tubulin Inhibitor with a Unique Mechanism of Action. Angew Chem Int Ed Engl 2022. [DOI: 10.1002/ange.202204052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Tobias Mühlethaler
- Laboratory of Biomolecular Research Department of Biology and Chemistry Paul Scherrer Institut 5232 Villigen PSI Switzerland
| | - Lampros Milanos
- Computational & Chemical Biology Istituto Italiano di Tecnologia via Morego 30 16163 Genova Italy
| | - Jose Antonio Ortega
- Computational & Chemical Biology Istituto Italiano di Tecnologia via Morego 30 16163 Genova Italy
| | - Thorsten B. Blum
- Laboratory of Biomolecular Research Department of Biology and Chemistry Paul Scherrer Institut 5232 Villigen PSI Switzerland
| | - Dario Gioia
- Computational & Chemical Biology Istituto Italiano di Tecnologia via Morego 30 16163 Genova Italy
| | - Bibhas Roy
- Laboratory of Nanoscale Biology Department of Biology and Chemistry Paul Scherrer Institut 5232 Villigen PSI Switzerland
| | - Andrea E. Prota
- Laboratory of Biomolecular Research Department of Biology and Chemistry Paul Scherrer Institut 5232 Villigen PSI Switzerland
| | - Andrea Cavalli
- Computational & Chemical Biology Istituto Italiano di Tecnologia via Morego 30 16163 Genova Italy
- Department of Pharmacy and Biotechnology Alma Mater Studiorum University of Bologna via Belmeloro 6 40126 Bologna Italy
| | - Michel O. Steinmetz
- Laboratory of Biomolecular Research Department of Biology and Chemistry Paul Scherrer Institut 5232 Villigen PSI Switzerland
- University of Basel, Biozentrum 4056 Basel Switzerland
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14
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Nussinov R, Zhang M, Maloney R, Tsai C, Yavuz BR, Tuncbag N, Jang H. Mechanism of activation and the rewired network: New drug design concepts. Med Res Rev 2022; 42:770-799. [PMID: 34693559 PMCID: PMC8837674 DOI: 10.1002/med.21863] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 07/06/2021] [Accepted: 10/07/2021] [Indexed: 12/13/2022]
Abstract
Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer ImmunometabolismNational Cancer InstituteFrederickMarylandUSA
- Department of Human Molecular Genetics and Biochemistry, Sackler School of MedicineTel Aviv UniversityTel AvivIsrael
| | - Mingzhen Zhang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer ImmunometabolismNational Cancer InstituteFrederickMarylandUSA
| | - Ryan Maloney
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer ImmunometabolismNational Cancer InstituteFrederickMarylandUSA
| | - Chung‐Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer ImmunometabolismNational Cancer InstituteFrederickMarylandUSA
| | - Bengi Ruken Yavuz
- Department of Health Informatics, Graduate School of InformaticsMiddle East Technical UniversityAnkaraTurkey
| | - Nurcan Tuncbag
- Department of Health Informatics, Graduate School of InformaticsMiddle East Technical UniversityAnkaraTurkey
- Department of Chemical and Biological Engineering, College of EngineeringKoc UniversityIstanbulTurkey
- Koc University Research Center for Translational Medicine, School of MedicineKoc UniversityIstanbulTurkey
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer ImmunometabolismNational Cancer InstituteFrederickMarylandUSA
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15
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Spatial-thermodynamic understanding of stabilization mechanism using computational approaches and molecular-level elucidation of the mechanism of crystal transformation in polymorphic irbesartan nanosuspensions. Int J Pharm 2022; 612:121350. [PMID: 34896564 DOI: 10.1016/j.ijpharm.2021.121350] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/19/2021] [Accepted: 12/01/2021] [Indexed: 11/22/2022]
Abstract
Irbesartan polymorphisms possess low solubility properties, nanosuspensions represent a method for improving the dissolution. Stabilizers are significant constituents of nanosuspensions. Herein we presented computational research on screening stabilizers and exploring stabilization mechanisms. The crystal transformation mechanism was also investigated. Soluplus-P407 and TPGS-HPMCE5 were screened by spatial conformation and thermodynamic energy analyses. The prepared nanosuspensions improved the dissolution properties of bulk drugs at pH 1.2, 4.5, 6.8. The nanosuspensions stabilization mechanism was analyzed by Molecular docking, Molecular dynamics simulations, Fourier transform infrared spectroscopy and Raman spectroscopy. It might be relate to the decreased enthalpy and Gibbs free energy which were determined by the synergy of external and internal energy factors. The X-ray powder diffraction, differential scanning calorimetry, scanning electron microscopy and transmission electron microscopy showed the crystal structures. The irbesartan B form was transformed in a Soluplus-P407-B/TPGS-HPMCE5-B physical mixture, but not in an SDS (-OH free)-B physical mixture. The intra-proton transfer induced by -OH on the stabilizer might be the transformation mechanism.
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16
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Schuller M, Correy GJ, Gahbauer S, Fearon D, Wu T, Díaz RE, Young ID, Carvalho Martins L, Smith DH, Schulze-Gahmen U, Owens TW, Deshpande I, Merz GE, Thwin AC, Biel JT, Peters JK, Moritz M, Herrera N, Kratochvil HT, Aimon A, Bennett JM, Brandao Neto J, Cohen AE, Dias A, Douangamath A, Dunnett L, Fedorov O, Ferla MP, Fuchs MR, Gorrie-Stone TJ, Holton JM, Johnson MG, Krojer T, Meigs G, Powell AJ, Rack JGM, Rangel VL, Russi S, Skyner RE, Smith CA, Soares AS, Wierman JL, Zhu K, O'Brien P, Jura N, Ashworth A, Irwin JJ, Thompson MC, Gestwicki JE, von Delft F, Shoichet BK, Fraser JS, Ahel I. Fragment binding to the Nsp3 macrodomain of SARS-CoV-2 identified through crystallographic screening and computational docking. SCIENCE ADVANCES 2021; 7:eabf8711. [PMID: 33853786 PMCID: PMC8046379 DOI: 10.1126/sciadv.abf8711] [Citation(s) in RCA: 90] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 02/24/2021] [Indexed: 05/19/2023]
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) macrodomain within the nonstructural protein 3 counteracts host-mediated antiviral adenosine diphosphate-ribosylation signaling. This enzyme is a promising antiviral target because catalytic mutations render viruses nonpathogenic. Here, we report a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. Crystallographic screening of 2533 diverse fragments resulted in 214 unique macrodomain-binders. An additional 60 molecules were selected from docking more than 20 million fragments, of which 20 were crystallographically confirmed. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Several fragment hits were confirmed by solution binding using three biophysical techniques (differential scanning fluorimetry, homogeneous time-resolved fluorescence, and isothermal titration calorimetry). The 234 fragment structures explore a wide range of chemotypes and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors.
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Affiliation(s)
- Marion Schuller
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK
| | - Galen J Correy
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Stefan Gahbauer
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA
| | - Daren Fearon
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - Taiasean Wu
- Institute for Neurodegenerative Disease, University of California San Francisco, San Francisco, CA 94158, USA
- Chemistry and Chemical Biology Graduate Program, University of California San Francisco, San Francisco, CA 94158, USA
| | - Roberto Efraín Díaz
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
- Tetrad Graduate Program, University of California San Francisco, San Francisco, CA 94158, USA
| | - Iris D Young
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Luan Carvalho Martins
- Biochemistry Department, Institute for Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Dominique H Smith
- Helen Diller Family Comprehensive Cancer, University of California San Francisco, San Francisco, CA 94158, USA
| | - Ursula Schulze-Gahmen
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Tristan W Owens
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Ishan Deshpande
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Gregory E Merz
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Aye C Thwin
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Justin T Biel
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jessica K Peters
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Michelle Moritz
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Nadia Herrera
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Huong T Kratochvil
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, San Francisco, CA 94158, USA
| | - Anthony Aimon
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - James M Bennett
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington OX3 7DQ, UK
| | - Jose Brandao Neto
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - Aina E Cohen
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Alexandre Dias
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - Alice Douangamath
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - Louise Dunnett
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - Oleg Fedorov
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington OX3 7DQ, UK
| | - Matteo P Ferla
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - Martin R Fuchs
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - Tyler J Gorrie-Stone
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - James M Holton
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | | | - Tobias Krojer
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
| | - George Meigs
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Ailsa J Powell
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | | | - Victor L Rangel
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
- School of Pharmaceutical Sciences of Ribeirao Preto, University of Sao Paulo, São Paulo, Brazil
| | - Silvia Russi
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Rachael E Skyner
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - Clyde A Smith
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Alexei S Soares
- Photon Sciences, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - Jennifer L Wierman
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Kang Zhu
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK
| | - Peter O'Brien
- Department of Chemistry, University of York, Heslington, York YO10 5DD, UK
| | - Natalia Jura
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Alan Ashworth
- Helen Diller Family Comprehensive Cancer, University of California San Francisco, San Francisco, CA 94158, USA
| | - John J Irwin
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA
| | - Michael C Thompson
- Department of Chemistry and Biochemistry, University of California Merced, Merced, CA 95343, USA
| | - Jason E Gestwicki
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA
- Institute for Neurodegenerative Disease, University of California San Francisco, San Francisco, CA 94158, USA
| | - Frank von Delft
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, UK.
- Department of Biochemistry, University of Johannesburg, Auckland Park 2006, South Africa
- Research Complex at Harwell, Harwell Science and Innovation Campus, Didcot, OX11 0FA UK
| | - Brian K Shoichet
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA 94158, USA.
| | - James S Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA.
| | - Ivan Ahel
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK.
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17
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Schuller M, Correy GJ, Gahbauer S, Fearon D, Wu T, Díaz RE, Young ID, Martins LC, Smith DH, Schulze-Gahmen U, Owens TW, Deshpande I, Merz GE, Thwin AC, Biel JT, Peters JK, Moritz M, Herrera N, Kratochvil HT, Aimon A, Bennett JM, Neto JB, Cohen AE, Dias A, Douangamath A, Dunnett L, Fedorov O, Ferla MP, Fuchs M, Gorrie-Stone TJ, Holton JM, Johnson MG, Krojer T, Meigs G, Powell AJ, Rangel VL, Russi S, Skyner RE, Smith CA, Soares AS, Wierman JL, Zhu K, Jura N, Ashworth A, Irwin J, Thompson MC, Gestwicki JE, von Delft F, Shoichet BK, Fraser JS, Ahel I. Fragment Binding to the Nsp3 Macrodomain of SARS-CoV-2 Identified Through Crystallographic Screening and Computational Docking. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2020:2020.11.24.393405. [PMID: 33269349 PMCID: PMC7709169 DOI: 10.1101/2020.11.24.393405] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The SARS-CoV-2 macrodomain (Mac1) within the non-structural protein 3 (Nsp3) counteracts host-mediated antiviral ADP-ribosylation signalling. This enzyme is a promising antiviral target because catalytic mutations render viruses non-pathogenic. Here, we report a massive crystallographic screening and computational docking effort, identifying new chemical matter primarily targeting the active site of the macrodomain. Crystallographic screening of diverse fragment libraries resulted in 214 unique macrodomain-binding fragments, out of 2,683 screened. An additional 60 molecules were selected from docking over 20 million fragments, of which 20 were crystallographically confirmed. X-ray data collection to ultra-high resolution and at physiological temperature enabled assessment of the conformational heterogeneity around the active site. Several crystallographic and docking fragment hits were validated for solution binding using three biophysical techniques (DSF, HTRF, ITC). Overall, the 234 fragment structures presented explore a wide range of chemotypes and provide starting points for development of potent SARS-CoV-2 macrodomain inhibitors.
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Affiliation(s)
- Marion Schuller
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK
| | - Galen J. Correy
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, USA
| | - Stefan Gahbauer
- Department of Pharmaceutical Chemistry, University of California San Francisco San Francisco, CA, USA
| | - Daren Fearon
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Taiasean Wu
- Institute for Neurodegenerative Disease, University of California San Francisco, CA, USA
- Chemistry and Chemical Biology Graduate Program, University of California San Francisco, CA, USA
| | - Roberto Efraín Díaz
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, USA
- Tetrad Graduate Program, University of California San Francisco, CA, USA
| | - Iris D. Young
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, USA
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Luan Carvalho Martins
- Biochemistry Department, Institute for Biological Sciences, Federal University of Minas Gerais. Belo Horizonte, Brazil
| | - Dominique H. Smith
- Helen Diller Family Comprehensive Cancer, University of California San Francisco, CA, USA
| | - Ursula Schulze-Gahmen
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Tristan W. Owens
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Ishan Deshpande
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Gregory E. Merz
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Aye C. Thwin
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Justin T. Biel
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Jessica K. Peters
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Michelle Moritz
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Nadia Herrera
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Huong T. Kratochvil
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - QCRG Structural Biology Consortium
- Quantitative Biosciences Institute (QBI) Coronavirus Research Group Structural Biology Consortium, University of California San Francisco, CA, USA
| | - Anthony Aimon
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - James M. Bennett
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
| | - Jose Brandao Neto
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Aina E. Cohen
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Alexandre Dias
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Alice Douangamath
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Louise Dunnett
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Oleg Fedorov
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
| | - Matteo P. Ferla
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - Martin Fuchs
- National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY, USA
| | - Tyler J. Gorrie-Stone
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - James M. Holton
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
- Department of Biochemistry and Biophysics, University of California San Francisco, CA, USA
- Department of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | - Tobias Krojer
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
| | - George Meigs
- Department of Biochemistry and Biophysics, University of California San Francisco, CA, USA
- Department of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Ailsa J. Powell
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | | | - Victor L Rangel
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
- School of Pharmaceutical Sciences of Ribeirao Preto, University of Sao Paulo, São Paulo, Brazil
| | - Silvia Russi
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Rachael E. Skyner
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Clyde A. Smith
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | | | - Jennifer L. Wierman
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Center, Menlo Park, CA 94025, USA
| | - Kang Zhu
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK
| | - Natalia Jura
- Department of Cellular and Molecular Pharmacology, University of California San Francisco, CA, USA
| | - Alan Ashworth
- Helen Diller Family Comprehensive Cancer, University of California San Francisco, CA, USA
| | - John Irwin
- Department of Pharmaceutical Chemistry, University of California San Francisco San Francisco, CA, USA
| | - Michael C. Thompson
- Department of Chemistry and Chemical Biology, University of California Merced, CA, USA
| | - Jason E. Gestwicki
- Department of Pharmaceutical Chemistry, University of California San Francisco San Francisco, CA, USA
- Institute for Neurodegenerative Disease, University of California San Francisco, CA, USA
| | - Frank von Delft
- Diamond Light Source Ltd., Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
- Centre for Medicines Discovery, University of Oxford, South Parks Road, Headington, OX3 7DQ, UK
- Structural Genomics Consortium, University of Oxford, Old Road Campus, Roosevelt Drive, Headington OX3 7DQ, UK
- Department of Biochemistry, University of Johannesburg, Auckland Park, 2006, South Africa
| | - Brian K. Shoichet
- Department of Pharmaceutical Chemistry, University of California San Francisco San Francisco, CA, USA
| | - James S. Fraser
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, CA, USA
| | - Ivan Ahel
- Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford OX1 3RE, UK
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