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Karaca E, Prévost C, Sacquin-Mora S. Modeling the Dynamics of Protein–Protein Interfaces, How and Why? Molecules 2022; 27:molecules27061841. [PMID: 35335203 PMCID: PMC8950966 DOI: 10.3390/molecules27061841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 03/06/2022] [Accepted: 03/08/2022] [Indexed: 12/07/2022] Open
Abstract
Protein–protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein–protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein–protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein–protein interface.
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Affiliation(s)
- Ezgi Karaca
- Izmir Biomedicine and Genome Center, Izmir 35340, Turkey;
- Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir 35340, Turkey
| | - Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, 13 rue Pierre et Marie Curie, 75005 Paris, France;
- Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, 75006 Paris, France
- Correspondence:
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Petrotchenko EV, Borchers CH. Protein Chemistry Combined with Mass Spectrometry for Protein Structure Determination. Chem Rev 2021; 122:7488-7499. [PMID: 34968047 DOI: 10.1021/acs.chemrev.1c00302] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The advent of soft-ionization mass spectrometry for biomolecules has opened up new possibilities for the structural analysis of proteins. Combining protein chemistry methods with modern mass spectrometry has led to the emergence of the distinct field of structural proteomics. Multiple protein chemistry approaches, such as surface modification, limited proteolysis, hydrogen-deuterium exchange, and cross-linking, provide diverse and often orthogonal structural information on the protein systems studied. Combining experimental data from these various structural proteomics techniques provides a more comprehensive examination of the protein structure and increases confidence in the ultimate findings. Here, we review various types of experimental data from structural proteomics approaches with an emphasis on the use of multiple complementary mass spectrometric approaches to provide experimental constraints for the solving of protein structures.
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Affiliation(s)
- Evgeniy V Petrotchenko
- Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec H3T 1E2, Canada.,Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Christoph H Borchers
- Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec H3T 1E2, Canada.,Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 121205, Russia.,Gerald Bronfman Department of Oncology, Jewish General Hospital, McGill University, Montreal, Quebec H3T 1E2, Canada
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Graziadei A, Rappsilber J. Leveraging crosslinking mass spectrometry in structural and cell biology. Structure 2021; 30:37-54. [PMID: 34895473 DOI: 10.1016/j.str.2021.11.007] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 10/11/2021] [Accepted: 11/17/2021] [Indexed: 12/18/2022]
Abstract
Crosslinking mass spectrometry (crosslinking-MS) is a versatile tool providing structural insights into protein conformation and protein-protein interactions. Its medium-resolution residue-residue distance restraints have been used to validate protein structures proposed by other methods and have helped derive models of protein complexes by integrative structural biology approaches. The use of crosslinking-MS in integrative approaches is underpinned by progress in estimating error rates in crosslinking-MS data and in combining these data with other information. The flexible and high-throughput nature of crosslinking-MS has allowed it to complement the ongoing resolution revolution in electron microscopy by providing system-wide residue-residue distance restraints, especially for flexible regions or systems. Here, we review how crosslinking-MS information has been leveraged in structural model validation and integrative modeling. Crosslinking-MS has also been a key technology for cell biology studies and structural systems biology where, in conjunction with cryoelectron tomography, it can provide structural and mechanistic insights directly in situ.
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Affiliation(s)
- Andrea Graziadei
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Juri Rappsilber
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany; Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh EH9 3BF, UK.
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Abstract
Knowledge of protein structure is crucial to our understanding of biological function and is routinely used in drug discovery. High-resolution techniques to determine the three-dimensional atomic coordinates of proteins are available. However, such methods are frequently limited by experimental challenges such as sample quantity, target size, and efficiency. Structural mass spectrometry (MS) is a technique in which structural features of proteins are elucidated quickly and relatively easily. Computational techniques that convert sparse MS data into protein models that demonstrate agreement with the data are needed. This review features cutting-edge computational methods that predict protein structure from MS data such as chemical cross-linking, hydrogen-deuterium exchange, hydroxyl radical protein footprinting, limited proteolysis, ion mobility, and surface-induced dissociation. Additionally, we address future directions for protein structure prediction with sparse MS data. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Sarah E Biehn
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA;
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA;
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Integrative Structural Biology of Protein-RNA Complexes. Structure 2020; 28:6-28. [DOI: 10.1016/j.str.2019.11.017] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 11/17/2019] [Accepted: 11/27/2019] [Indexed: 12/16/2022]
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6
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Sarkar A, Sen S. A Comparative Analysis of the Molecular Interaction Techniques for In Silico Drug Design. Int J Pept Res Ther 2019. [DOI: 10.1007/s10989-019-09830-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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Vandermarliere E, Stes E, Gevaert K, Martens L. Resolution of protein structure by mass spectrometry. MASS SPECTROMETRY REVIEWS 2016; 35:653-665. [PMID: 25536908 DOI: 10.1002/mas.21450] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2014] [Accepted: 10/14/2014] [Indexed: 06/04/2023]
Abstract
Typically, mass spectrometry is used to identify the peptides present in a complex peptide mixture and subsequently the precursor proteins. As such, mass spectrometry focuses mainly on the primary structure, the (modified) amino acid sequence of peptides and proteins. In contrast, the three-dimensional structure of a protein is typically determined with protein X-ray crystallography or NMR. Despite the close relationship between these two aspects of protein studies (sequence and structure), mass spectrometry and structure determination are not frequently combined. Nevertheless, this combination of approaches, dubbed conformational proteomics, can offer insight into the function, working mechanism, and conformational status of a protein. In this review, we will discuss the developments at the intersection of mass spectrometry-based proteomics and protein structure determination and start from a brief overview of the classic approaches to identify protein structure along with their advantages and disadvantages. We will subsequently discuss the ability of mass spectrometry to overcome some of the hurdles of these classic methods. Finally, we will provide an outlook on the interplay of mass spectrometry and protein structure determination, and highlight several recent experiments in which mass spectrometry was successfully used to either aid or complement structure elucidation. © 2014 Wiley Periodicals, Inc. Mass Spec Rev 35:653-665, 2016.
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Affiliation(s)
- Elien Vandermarliere
- Department of Medical Protein Research, VIB, B-9000, Ghent, Belgium
- Department of Biochemistry, Ghent University, B- 9000, Ghent, Belgium
| | - Elisabeth Stes
- Department of Medical Protein Research, VIB, B-9000, Ghent, Belgium
- Department of Biochemistry, Ghent University, B- 9000, Ghent, Belgium
| | - Kris Gevaert
- Department of Medical Protein Research, VIB, B-9000, Ghent, Belgium
- Department of Biochemistry, Ghent University, B- 9000, Ghent, Belgium
| | - Lennart Martens
- Department of Medical Protein Research, VIB, B-9000, Ghent, Belgium.
- Department of Biochemistry, Ghent University, B- 9000, Ghent, Belgium.
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Spiliotopoulos D, Kastritis PL, Melquiond ASJ, Bonvin AMJJ, Musco G, Rocchia W, Spitaleri A. dMM-PBSA: A New HADDOCK Scoring Function for Protein-Peptide Docking. Front Mol Biosci 2016; 3:46. [PMID: 27630991 PMCID: PMC5006095 DOI: 10.3389/fmolb.2016.00046] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Accepted: 08/16/2016] [Indexed: 11/13/2022] Open
Abstract
Molecular-docking programs coupled with suitable scoring functions are now established and very useful tools enabling computational chemists to rapidly screen large chemical databases and thereby to identify promising candidate compounds for further experimental processing. In a broader scenario, predicting binding affinity is one of the most critical and challenging components of computer-aided structure-based drug design. The development of a molecular docking scoring function which in principle could combine both features, namely ranking putative poses and predicting complex affinity, would be of paramount importance. Here, we systematically investigated the performance of the MM-PBSA approach, using two different Poisson-Boltzmann solvers (APBS and DelPhi), in the currently rising field of protein-peptide interactions (PPIs), identifying the correct binding conformations of 19 different protein-peptide complexes and predicting their binding free energies. First, we scored the decoy structures from HADDOCK calculation via the MM-PBSA approach in order to assess the capability of retrieving near-native poses in the best-scoring clusters and of evaluating the corresponding free energies of binding. MM-PBSA behaves well in finding the poses corresponding to the lowest binding free energy, however the built-in HADDOCK score shows a better performance. In order to improve the MM-PBSA-based scoring function, we dampened the MM-PBSA solvation and coulombic terms by 0.2, as proposed in the HADDOCK score and LIE approaches. The new dampened MM-PBSA (dMM-PBSA) outperforms the original MM-PBSA and ranks the decoys structures as the HADDOCK score does. Second, we found a good correlation between the dMM-PBSA and HADDOCK scores for the near-native clusters of each system and the experimental binding energies, respectively. Therefore, we propose a new scoring function, dMM-PBSA, to be used together with the built-in HADDOCK score in the context of protein-peptide docking simulations.
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Affiliation(s)
| | - Panagiotis L Kastritis
- Faculty of Science - Chemistry, Bijvoet Center, Utrecht UniversityUtrecht, Netherlands; European Molecular Biology Laboratory HeidelbergHeidelberg, Germany
| | - Adrien S J Melquiond
- Faculty of Science - Chemistry, Bijvoet Center, Utrecht University Utrecht, Netherlands
| | | | - Giovanna Musco
- Biomolecular Nuclear Magnetic Resonance Unit, Ospedale S. Raffaele Milan, Italy
| | - Walter Rocchia
- CONCEPT Lab, Istituto Italiano di Tecnologia Genoa, Italy
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Marcoux J, Cianférani S. Towards integrative structural mass spectrometry: Benefits from hybrid approaches. Methods 2015; 89:4-12. [DOI: 10.1016/j.ymeth.2015.05.024] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Revised: 05/06/2015] [Accepted: 05/25/2015] [Indexed: 01/10/2023] Open
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10
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Vandermarliere E, Maddelein D, Hulstaert N, Stes E, Di Michele M, Gevaert K, Jacoby E, Brehmer D, Martens L. PepShell: Visualization of Conformational Proteomics Data. J Proteome Res 2015; 14:1987-90. [DOI: 10.1021/pr5012125] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Elien Vandermarliere
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
| | - Davy Maddelein
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
| | - Niels Hulstaert
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
| | - Elisabeth Stes
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
| | - Michela Di Michele
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
| | - Kris Gevaert
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
| | - Edgar Jacoby
- Oncology
Discovery, Janssen Research and Development, A Division of Janssen Pharmaceutica NV, Turnhoutseweg 30, B-2340 Beerse, Belgium
| | - Dirk Brehmer
- Oncology
Discovery, Janssen Research and Development, A Division of Janssen Pharmaceutica NV, Turnhoutseweg 30, B-2340 Beerse, Belgium
| | - Lennart Martens
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
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11
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Hennig J, Wang I, Sonntag M, Gabel F, Sattler M. Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex. JOURNAL OF BIOMOLECULAR NMR 2013; 56:17-30. [PMID: 23456097 DOI: 10.1007/s10858-013-9719-9] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2012] [Accepted: 02/19/2013] [Indexed: 05/12/2023]
Abstract
Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.
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Affiliation(s)
- Janosch Hennig
- Institute of Structural Biology, Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
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