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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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Henkel A, Oberthür D. A snapshot love story: what serial crystallography has done and will do for us. Acta Crystallogr D Struct Biol 2024; 80:563-579. [PMID: 38984902 PMCID: PMC11301758 DOI: 10.1107/s2059798324005588] [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: 02/29/2024] [Accepted: 06/11/2024] [Indexed: 07/11/2024] Open
Abstract
Serial crystallography, born from groundbreaking experiments at the Linac Coherent Light Source in 2009, has evolved into a pivotal technique in structural biology. Initially pioneered at X-ray free-electron laser facilities, it has now expanded to synchrotron-radiation facilities globally, with dedicated experimental stations enhancing its accessibility. This review gives an overview of current developments in serial crystallography, emphasizing recent results in time-resolved crystallography, and discussing challenges and shortcomings.
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Affiliation(s)
- Alessandra Henkel
- Center for Free-Electron Laser Science CFELDeutsches Elektronen-Synchrotron DESYNotkestr. 8522607HamburgGermany
| | - Dominik Oberthür
- Center for Free-Electron Laser Science CFELDeutsches Elektronen-Synchrotron DESYNotkestr. 8522607HamburgGermany
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Wankowicz SA, Fraser JS. Comprehensive encoding of conformational and compositional protein structural ensembles through the mmCIF data structure. IUCRJ 2024; 11:494-501. [PMID: 38958015 PMCID: PMC11220883 DOI: 10.1107/s2052252524005098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 05/29/2024] [Indexed: 07/04/2024]
Abstract
In the folded state, biomolecules exchange between multiple conformational states crucial for their function. However, most structural models derived from experiments and computational predictions only encode a single state. To represent biomolecules accurately, we must move towards modeling and predicting structural ensembles. Information about structural ensembles exists within experimental data from X-ray crystallography and cryo-electron microscopy. Although new tools are available to detect conformational and compositional heterogeneity within these ensembles, the legacy PDB data structure does not robustly encapsulate this complexity. We propose modifications to the macromolecular crystallographic information file (mmCIF) to improve the representation and interrelation of conformational and compositional heterogeneity. These modifications will enable the capture of macromolecular ensembles in a human and machine-interpretable way, potentially catalyzing breakthroughs for ensemble-function predictions, analogous to the achievements of AlphaFold with single-structure prediction.
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Affiliation(s)
- Stephanie A. Wankowicz
- Department of Bioengineering and Therapeutic ScienceUniversity of CaliforniaSan FranciscoCA94117USA
| | - James S. Fraser
- Department of Bioengineering and Therapeutic ScienceUniversity of CaliforniaSan FranciscoCA94117USA
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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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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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