1
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Badonyi M, Marsh JA. Hallmarks and evolutionary drivers of cotranslational protein complex assembly. FEBS J 2023. [PMID: 37202910 DOI: 10.1111/febs.16869] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/11/2023] [Accepted: 05/18/2023] [Indexed: 05/20/2023]
Abstract
Recent discoveries have highlighted the prevalence of cotranslational assembly in proteomes, revealing a range of mechanisms that enables the assembly of protein complex subunits on the ribosome. Structural analyses have uncovered emergent properties that may inherently control whether a subunit undergoes cotranslational assembly. However, the evolutionary paths that have yielded such complexes over an extended timescale remain largely unclear. In this review, we reflect on historical experiments that contributed to the field, including breakthroughs that have made possible the proteome-wide detection of cotranslational assembly, and the technical challenges yet to be overcome. We introduce a simple framework that encapsulates the hallmarks of cotranslational assembly and discuss how results from new experiments are shaping our view of the mechanistic, structural and evolutionary factors driving the phenomenon.
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Affiliation(s)
- Mihaly Badonyi
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Joseph A Marsh
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
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2
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Prévost C, Sacquin-Mora S. Moving pictures: Reassessing docking experiments with a dynamic view of protein interfaces. Proteins 2021; 89:1315-1323. [PMID: 34038009 DOI: 10.1002/prot.26152] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/22/2021] [Accepted: 05/19/2021] [Indexed: 11/06/2022]
Abstract
The modeling of protein assemblies at the atomic level remains a central issue in structural biology, as protein interactions play a key role in numerous cellular processes. This problem is traditionally addressed using docking tools, where the quality of the models is based on their similarity to a single reference experimental structure. However, using a static reference does not take into account the dynamic quality of the protein interface. Here, we used all-atom classical Molecular Dynamics simulations to investigate the stability of the reference interface for three complexes that previously served as targets in the CAPRI competition. For each one of these targets, we also ran MD simulations for ten models that are distributed over the High, Medium and Acceptable accuracy categories. To assess the quality of these models from a dynamic perspective, we set up new criteria which take into account the stability of the reference experimental protein interface. We show that, when the protein interfaces are allowed to evolve along time, the original ranking based on the static CAPRI criteria no longer holds as over 50% of the docking models undergo a category change (which can be either toward a better or a lower accuracy group) when reassessing their quality using dynamic information.
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Affiliation(s)
- Chantal Prévost
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, Paris, France.,Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, Paris, France
| | - Sophie Sacquin-Mora
- CNRS, Laboratoire de Biochimie Théorique, UPR9080, Université de Paris, Paris, France.,Institut de Biologie Physico-Chimique, Fondation Edmond de Rothschild, PSL Research University, Paris, France
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3
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Laniado J, Meador K, Yeates TO. A fragment-based protein interface design algorithm for symmetric assemblies. Protein Eng Des Sel 2021; 34:6269139. [PMID: 33955480 DOI: 10.1093/protein/gzab008] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 03/08/2021] [Indexed: 11/13/2022] Open
Abstract
Theoretical and experimental advances in protein engineering have led to the creation of precisely defined, novel protein assemblies of great size and complexity, with diverse applications. One powerful approach involves designing a new attachment or binding interface between two simpler symmetric oligomeric protein components. The required methods of design, which present both similarities and key differences compared to problems in protein docking, remain challenging and are not yet routine. With the aim of more fully enabling this emerging area of protein material engineering, we developed a computer program, nanohedra, to introduce two key advances. First, we encoded in the program the construction rules (i.e. the search space parameters) that underlie all possible symmetric material constructions. Second, we developed algorithms for rapidly identifying favorable docking/interface arrangements based on tabulations of empirical patterns of known protein fragment-pair associations. As a result, the candidate poses that nanohedra generates for subsequent amino acid interface design appear highly native-like (at the protein backbone level), while simultaneously conforming to the exacting requirements for symmetry-based assembly. A retrospective computational analysis of successful vs failed experimental studies supports the expectation that this should improve the success rate for this challenging area of protein engineering.
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Affiliation(s)
- Joshua Laniado
- UCLA Molecular Biology Institute, Los Angeles, CA 90095, USA
| | - Kyle Meador
- UCLA Department of Chemistry and Biochemistry, Los Angeles, CA 90095, USA
| | - Todd O Yeates
- UCLA Molecular Biology Institute, Los Angeles, CA 90095, USA.,UCLA Department of Chemistry and Biochemistry, Los Angeles, CA 90095, USA.,UCLA DOE Institute for Genomics and Proteomics, Los Angeles, CA 90095, USA
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4
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Padariya M, Sznarkowska A, Kote S, Gómez-Herranz M, Mikac S, Pilch M, Alfaro J, Fahraeus R, Hupp T, Kalathiya U. Functional Interfaces, Biological Pathways, and Regulations of Interferon-Related DNA Damage Resistance Signature (IRDS) Genes. Biomolecules 2021; 11:622. [PMID: 33922087 DOI: 10.3390/biom11050622] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/15/2021] [Accepted: 04/20/2021] [Indexed: 12/14/2022] Open
Abstract
Interferon (IFN)-related DNA damage resistant signature (IRDS) genes are a subgroup of interferon-stimulated genes (ISGs) found upregulated in different cancer types, which promotes resistance to DNA damaging chemotherapy and radiotherapy. Along with briefly discussing IFNs and signalling in this review, we highlighted how different IRDS genes are affected by viruses. On the contrary, different strategies adopted to suppress a set of IRDS genes (STAT1, IRF7, OAS family, and BST2) to induce (chemo- and radiotherapy) sensitivity were deliberated. Significant biological pathways that comprise these genes were classified, along with their frequently associated genes (IFIT1/3, IFITM1, IRF7, ISG15, MX1/2 and OAS1/3/L). Major upstream regulators from the IRDS genes were identified, and different IFN types regulating these genes were outlined. Functional interfaces of IRDS proteins with DNA/RNA/ATP/GTP/NADP biomolecules featured a well-defined pharmacophore model for STAT1/IRF7-dsDNA and OAS1/OAS3/IFIH1-dsRNA complexes, as well as for the genes binding to GDP or NADP+. The Lys amino acid was found commonly interacting with the ATP phosphate group from OAS1/EIF2AK2/IFIH1 genes. Considering the premise that targeting IRDS genes mediated resistance offers an efficient strategy to resensitize tumour cells and enhances the outcome of anti-cancer treatment, this review can add some novel insights to the field.
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5
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Ruiz-Blanco YB, Ávila-Barrientos LP, Hernández-García E, Antunes A, Agüero-Chapin G, García-Hernández E. Engineering protein fragments via evolutionary and protein-protein interaction algorithms: de novo design of peptide inhibitors for F O F 1 -ATP synthase. FEBS Lett 2020; 595:183-194. [PMID: 33151544 DOI: 10.1002/1873-3468.13988] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 10/23/2020] [Accepted: 10/30/2020] [Indexed: 11/08/2022]
Abstract
Enzyme subunit interfaces have remarkable potential in drug design as both target and scaffold for their own inhibitors. We show an evolution-driven strategy for the de novo design of peptide inhibitors targeting interfaces of the Escherichia coli FoF1-ATP synthase as a case study. The evolutionary algorithm ROSE was applied to generate diversity-oriented peptide libraries by engineering peptide fragments from ATP synthase interfaces. The resulting peptides were scored with PPI-Detect, a sequence-based predictor of protein-protein interactions. Two selected peptides were confirmed by in vitro inhibition and binding tests. The proposed methodology can be widely applied to design peptides targeting relevant interfaces of enzymatic complexes.
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Affiliation(s)
| | | | | | - Agostinho Antunes
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Terminal de Cruzeiros do Porto de Leixões, Portugal.,Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Portugal
| | - Guillermin Agüero-Chapin
- CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Terminal de Cruzeiros do Porto de Leixões, Portugal.,Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Portugal
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6
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Guzenko D, Lafita A, Monastyrskyy B, Kryshtafovych A, Duarte JM. Assessment of protein assembly prediction in CASP13. Proteins 2019; 87:1190-1199. [PMID: 31374138 DOI: 10.1002/prot.25795] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/11/2019] [Accepted: 07/27/2019] [Indexed: 01/08/2023]
Abstract
We present the assembly category assessment in the 13th edition of the CASP community-wide experiment. For the second time, protein assemblies constitute an independent assessment category. Compared to the last edition we see a clear uptake in participation, more oligomeric targets released, and consistent, albeit modest, improvement of the predictions quality. Looking at the tertiary structure predictions, we observe that ignoring the oligomeric state of the targets hinders modeling success. We also note that some contact prediction groups successfully predicted homomeric interfacial contacts, though it appears that these predictions were not used for assembly modeling. Homology modeling with sizeable human intervention appears to form the basis of the assembly prediction techniques in this round of CASP. Future developments should see more integrated approaches where subunits are modeled in the context of the assemblies they form.
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Affiliation(s)
- Dmytro Guzenko
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, La Jolla, California
| | - Aleix Lafita
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
| | - Bohdan Monastyrskyy
- Protein Structure Prediction Center, Genome and Biomedical Sciences Facilities, University of California, Davis, California, USA
| | - Andriy Kryshtafovych
- Protein Structure Prediction Center, Genome and Biomedical Sciences Facilities, University of California, Davis, California, USA
| | - Jose M Duarte
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, La Jolla, California
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7
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Gaines JC, Acebes S, Virrueta A, Butler M, Regan L, O'Hern CS. Comparing side chain packing in soluble proteins, protein- protein interfaces, and transmembrane proteins. Proteins 2018; 86:581-591. [PMID: 29427530 PMCID: PMC5912992 DOI: 10.1002/prot.25479] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Revised: 01/23/2018] [Accepted: 02/06/2018] [Indexed: 12/26/2022]
Abstract
We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins.
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Affiliation(s)
- J C Gaines
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, 06520
- Integrated Graduate Program in Physical and Engineering Biology (IGPPEB), Yale University, New Haven, Connecticut, 06520
| | - S Acebes
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut, 06520
| | - A Virrueta
- Integrated Graduate Program in Physical and Engineering Biology (IGPPEB), Yale University, New Haven, Connecticut, 06520
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut, 06520
| | - M Butler
- Department of Physics and Astronomy, University of Southern California, Los Angeles, California, 90007
| | - L Regan
- Integrated Graduate Program in Physical and Engineering Biology (IGPPEB), Yale University, New Haven, Connecticut, 06520
- Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, Connecticut, 06520
- Department of Chemistry, Yale University, New Haven, Connecticut, 06520
| | - C S O'Hern
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, 06520
- Integrated Graduate Program in Physical and Engineering Biology (IGPPEB), Yale University, New Haven, Connecticut, 06520
- Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut, 06520
- Department of Physics, Yale University, New Haven, Connecticut, 06520
- Department of Applied Physics, Yale University, New Haven, Connecticut, 06520
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8
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Park H, Kim D, Ovchinnikov S, Baker D, DiMaio F. Automatic structure prediction of oligomeric assemblies using Robetta in CASP12. Proteins 2018; 86 Suppl 1:283-291. [PMID: 28913931 PMCID: PMC6019630 DOI: 10.1002/prot.25387] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2017] [Revised: 09/01/2017] [Accepted: 09/11/2017] [Indexed: 12/15/2022]
Abstract
Many naturally occurring protein systems function primarily as symmetric assemblies. Prediction of the quaternary structure of these assemblies is an important biological problem. This article describes automated tools we have developed for predicting the structures of symmetric protein assemblies in the Robetta structure prediction server. We assess the performance of this pipeline on a set of targets from the recent CASP12/CAPRI blind quaternary structure prediction experiment. Our approach successfully predicted 5 of 7 symmetric assemblies in this challenge, and was assessed as the best participating server group, and 1 of only 2 groups (human or server) with 2 predictions judged as high quality by the assessors. We also assess the method on a broader set of 22 natively symmetric CASP12 targets, where we show that oligomeric modeling can improve the accuracy of monomeric structure determination, particularly in highly intertwined oligomers.
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Affiliation(s)
- Hahnbeom Park
- Department of Biochemistry, University of Washington, Seattle 98195, Washington
- Institute for Protein Design, University of Washington, Seattle 98195, Washington
| | - David Kim
- Institute for Protein Design, University of Washington, Seattle 98195, Washington
- Howard Hughes Medical Institute, University of Washington, Seattle 98195, Washington
| | - Sergey Ovchinnikov
- Department of Biochemistry, University of Washington, Seattle 98195, Washington
- Institute for Protein Design, University of Washington, Seattle 98195, Washington
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle 98195, Washington
- Institute for Protein Design, University of Washington, Seattle 98195, Washington
- Howard Hughes Medical Institute, University of Washington, Seattle 98195, Washington
| | - Frank DiMaio
- Department of Biochemistry, University of Washington, Seattle 98195, Washington
- Institute for Protein Design, University of Washington, Seattle 98195, Washington
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9
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Lafita A, Bliven S, Kryshtafovych A, Bertoni M, Monastyrskyy B, Duarte JM, Schwede T, Capitani G. Assessment of protein assembly prediction in CASP12. Proteins 2017; 86 Suppl 1:247-256. [PMID: 29071742 DOI: 10.1002/prot.25408] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Revised: 10/04/2017] [Accepted: 10/24/2017] [Indexed: 01/01/2023]
Abstract
We present the results of the first independent assessment of protein assemblies in CASP. A total of 1624 oligomeric models were submitted by 108 predictor groups for the 30 oligomeric targets in the CASP12 edition. We evaluated the accuracy of oligomeric predictions by comparison to their reference structures at the interface patch and residue contact levels. We find that interface patches are more reliably predicted than the specific residue contacts. Whereas none of the 15 hard oligomeric targets have successful predictions for the residue contacts at the interface, six have models with resemblance in the interface patch. Successful predictions of interface patch and contacts exist for all targets suitable for homology modeling, with at least one group improving over the best available template for each target. However, the participation in protein assembly prediction is low and uneven. Three human groups are closely ranked at the top by overall performance, but a server outperforms all other predictors for targets suitable for homology modeling. The state of the art of protein assembly prediction methods is in development and has apparent room for improvement, especially for assemblies without templates.
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Affiliation(s)
- Aleix Lafita
- Laboratory of Biomolecular Research, Paul Scherrer Institute, Villigen, PSI, 5232, Switzerland.,Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland
| | - Spencer Bliven
- Laboratory of Biomolecular Research, Paul Scherrer Institute, Villigen, PSI, 5232, Switzerland.,National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, 20894
| | | | - Martino Bertoni
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, Basel, 4056, Switzerland.,SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | | | - Jose M Duarte
- RCSB Protein Data Bank, San Diego Supercomputing Center, UC San Diego, San Diego
| | - Torsten Schwede
- Biozentrum, University of Basel, Klingelbergstrasse 50/70, Basel, 4056, Switzerland.,SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Guido Capitani
- Laboratory of Biomolecular Research, Paul Scherrer Institute, Villigen, PSI, 5232, Switzerland.,Department of Biology, ETH Zurich, Zurich, 8093, Switzerland
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10
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Plach MG, Semmelmann F, Busch F, Busch M, Heizinger L, Wysocki VH, Merkl R, Sterner R. Evolutionary diversification of protein-protein interactions by interface add-ons. Proc Natl Acad Sci U S A 2017; 114:E8333-42. [PMID: 28923934 DOI: 10.1073/pnas.1707335114] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein-protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein-protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein-protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein-protein interactions.
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11
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Pechmann S, Levy ED, Tartaglia GG, Vendruscolo M. Physicochemical principles that regulate the competition between functional and dysfunctional association of proteins. Proc Natl Acad Sci U S A 2009; 106:10159-64. [PMID: 19502422 PMCID: PMC2700930 DOI: 10.1073/pnas.0812414106] [Citation(s) in RCA: 124] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2008] [Indexed: 01/31/2023] Open
Abstract
To maintain protein homeostasis, a variety of quality control mechanisms, such as the unfolded protein response and the heat shock response, enable proteins to fold and to assemble into functional complexes while avoiding the formation of aberrant and potentially harmful aggregates. We show here that a complementary contribution to the regulation of the interactions between proteins is provided by the physicochemical properties of their amino acid sequences. The results of a systematic analysis of the protein-protein complexes in the Protein Data Bank (PDB) show that interface regions are more prone to aggregate than other surface regions, indicating that many of the interactions that promote the formation of functional complexes, including hydrophobic and electrostatic forces, can potentially also cause abnormal intermolecular association. We also show, however, that aggregation-prone interfaces are prevented from triggering uncontrolled assembly by being stabilized into their functional conformations by disulfide bonds and salt bridges. These results indicate that functional and dysfunctional association of proteins are promoted by similar forces but also that they are closely regulated by the presence of specific interactions that stabilize native states.
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Affiliation(s)
- Sebastian Pechmann
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom; and
| | - Emmanuel D. Levy
- Laboratory of Molecular Biology, Medical Research Council, Hills Road, Cambridge CB2 0QH, United Kingdom
| | - Gian Gaetano Tartaglia
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom; and
| | - Michele Vendruscolo
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom; and
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12
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Abstract
Biological complexes typically exhibit intermolecular interfaces of high shape complementarity. Many computational docking approaches use this surface complementarity as a guide in the search for predicting the structures of protein-protein complexes. Proteins often undergo conformational changes to create a highly complementary interface when associating. These conformational changes are a major cause of failure for automated docking procedures when predicting binding modes between proteins using their unbound conformations. Low resolution surfaces in which high frequency geometric details are omitted have been used to address this problem. These smoothed, or blurred, surfaces are expected to minimize the differences between free and bound structures, especially those that are due to side chain conformations or small backbone deviations. Despite the fact that this approach has been used in many docking protocols, there has yet to be a systematic study of the effects of such surface smoothing on the shape complementarity of the resulting interfaces. Here we investigate this question by computing shape complementarity of a set of 66 protein-protein complexes represented by multiresolution blurred surfaces. Complexed and unbound structures are available for these protein-protein complexes. They are a subset of complexes from a nonredundant docking benchmark selected for rigidity (i.e. the proteins undergo limited conformational changes between their bound and unbound states). In this work, we construct the surfaces by isocontouring a density map obtained by accumulating the densities of Gaussian functions placed at all atom centers of the molecule. The smoothness or resolution is specified by a Gaussian fall-off coefficient, termed "blobbyness." Shape complementarity is quantified using a histogram of the shortest distances between two proteins' surface mesh vertices for both the crystallographic complexes and the complexes built using the protein structures in their unbound conformation. The histograms calculated for the bound complex structures demonstrate that medium resolution smoothing (blobbyness = -0.9) can reproduce about 88% of the shape complementarity of atomic resolution surfaces. Complexes formed from the free component structures show a partial loss of shape complementarity (more overlaps and gaps) with the atomic resolution surfaces. For surfaces smoothed to low resolution (blobbyness = -0.3), we find more consistency of shape complementarity between the complexed and free cases. To further reduce bad contacts without significantly impacting the good contacts we introduce another blurred surface, in which the Gaussian densities of flexible atoms are reduced. From these results we discuss the use of shape complementarity in protein-protein docking.
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Affiliation(s)
- Qing Zhang
- Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, mail MB-5, La Jolla, CA 92037
| | - Michel Sanner
- Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, mail MB-5, La Jolla, CA 92037
| | - Arthur J. Olson
- Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, mail MB-5, La Jolla, CA 92037
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13
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Abstract
Prism (protein interactions by structural matching) is a system that employs a novel prediction algorithm for protein-protein interactions. It adopts a bottom-up approach that combines structure and sequence conservation in protein interfaces. The algorithm seeks possible binary interactions between proteins through structure similarity and evolutionary conservation of known interfaces. It is composed of a database containing protein interface structures derived from the Protein Data Bank (PDB) and predicted protein-protein interactions. It also provides related information about the proteins and an interactive protein interface viewer. In the current version, 3799 structurally nonredundant interfaces are used to predict the interactions among 6170 proteins. A substantial number of interactions are verified in two publicly available interaction databases (DIP and BIND). As the verified interactions demonstrate the suitability of our approach, unverified ones may point to undiscovered interactions. Prism can be accessed through a user-friendly website (http://prism.ccbb.ku.edu.tr) and it will be updated regularly as new protein structures become available in the PDB. Users may browse through the nonredundant dataset of representative interfaces on which the prediction algorithm depends, retrieve the list of structures similar to these interfaces, or see the results of interaction predictions for a particular protein. Another service provided is the interactive prediction. This is done by running the algorithm for the user input structures.
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14
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Keskin O, Tsai CJ, Wolfson H, Nussinov R. A new, structurally nonredundant, diverse data set of protein- protein interfaces and its implications. Protein Sci 2004; 13:1043-55. [PMID: 15044734 PMCID: PMC2280042 DOI: 10.1110/ps.03484604] [Citation(s) in RCA: 144] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2003] [Revised: 12/23/2003] [Accepted: 01/09/2004] [Indexed: 10/26/2022]
Abstract
Here, we present a diverse, structurally nonredundant data set of two-chain protein-protein interfaces derived from the PDB. Using a sequence order-independent structural comparison algorithm and hierarchical clustering, 3799 interface clusters are obtained. These yield 103 clusters with at least five nonhomologous members. We divide the clusters into three types. In Type I clusters, the global structures of the chains from which the interfaces are derived are also similar. This cluster type is expected because, in general, related proteins associate in similar ways. In Type II, the interfaces are similar; however, remarkably, the overall structures and functions of the chains are different. The functional spectrum is broad, from enzymes/inhibitors to immunoglobulins and toxins. The fact that structurally different monomers associate in similar ways, suggests "good" binding architectures. This observation extends a paradigm in protein science: It has been well known that proteins with similar structures may have different functions. Here, we show that it extends to interfaces. In Type III clusters, only one side of the interface is similar across the cluster. This structurally nonredundant data set provides rich data for studies of protein-protein interactions and recognition, cellular networks and drug design. In particular, it may be useful in addressing the difficult question of what are the favorable ways for proteins to interact. (The data set is available at http://protein3d.ncifcrf.gov/~keskino/ and http://home.ku.edu.tr/~okeskin/INTERFACE/INTERFACES.html.)
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Affiliation(s)
- Ozlem Keskin
- NCI-Frederick, Building 469, Room 151, Frederick, MD 21702, USA
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