1
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Gavalda-Garcia J, Bickel D, Roca-Martinez J, Raimondi D, Orlando G, Vranken W. Data-driven probabilistic definition of the low energy conformational states of protein residues. NAR Genom Bioinform 2024; 6:lqae082. [PMID: 38984065 PMCID: PMC11231583 DOI: 10.1093/nargab/lqae082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 06/14/2024] [Accepted: 06/26/2024] [Indexed: 07/11/2024] Open
Abstract
Protein dynamics and related conformational changes are essential for their function but difficult to characterise and interpret. Amino acids in a protein behave according to their local energy landscape, which is determined by their local structural context and environmental conditions. The lowest energy state for a given residue can correspond to sharply defined conformations, e.g. in a stable helix, or can cover a wide range of conformations, e.g. in intrinsically disordered regions. A good definition of such low energy states is therefore important to describe the behaviour of a residue and how it changes with its environment. We propose a data-driven probabilistic definition of six low energy conformational states typically accessible for amino acid residues in proteins. This definition is based on solution NMR information of 1322 proteins through a combined analysis of structure ensembles with interpreted chemical shifts. We further introduce a conformational state variability parameter that captures, based on an ensemble of protein structures from molecular dynamics or other methods, how often a residue moves between these conformational states. The approach enables a different perspective on the local conformational behaviour of proteins that is complementary to their static interpretation from single structure models.
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Affiliation(s)
- Jose Gavalda-Garcia
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
| | - David Bickel
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
| | - Joel Roca-Martinez
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
| | | | | | - Wim Vranken
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium
- Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium
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2
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Porter LL, Artsimovitch I, Ramírez-Sarmiento CA. Metamorphic proteins and how to find them. Curr Opin Struct Biol 2024; 86:102807. [PMID: 38537533 PMCID: PMC11102287 DOI: 10.1016/j.sbi.2024.102807] [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: 02/01/2024] [Revised: 03/05/2024] [Accepted: 03/06/2024] [Indexed: 04/04/2024]
Abstract
In the last two decades, our existing notion that most foldable proteins have a unique native state has been challenged by the discovery of metamorphic proteins, which reversibly interconvert between multiple, sometimes highly dissimilar, native states. As the number of known metamorphic proteins increases, several computational and experimental strategies have emerged for gaining insights about their refolding processes and identifying unknown metamorphic proteins amongst the known proteome. In this review, we describe the current advances in biophysically and functionally ascertaining the structural interconversions of metamorphic proteins and how coevolution can be harnessed to identify novel metamorphic proteins from sequence information. We also discuss the challenges and ongoing efforts in using artificial intelligence-based protein structure prediction methods to discover metamorphic proteins and predict their corresponding three-dimensional structures.
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Affiliation(s)
- Lauren L Porter
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA; Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Irina Artsimovitch
- Department of Microbiology and Center for RNA Biology, The Ohio State University, Columbus, OH 43210, USA.
| | - César A Ramírez-Sarmiento
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile; ANID, Millennium Science Initiative Program, Millennium Institute for Integrative Biology (iBio), Santiago 833150, Chile.
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3
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Jose AM. Heritable epigenetic changes are constrained by the dynamics of regulatory architectures. eLife 2024; 12:RP92093. [PMID: 38717010 PMCID: PMC11078544 DOI: 10.7554/elife.92093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2024] Open
Abstract
Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here, I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors, and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode Caenorhabditis elegans. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.
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4
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Ellaway JIJ, Anyango S, Nair S, Zaki HA, Nadzirin N, Powell HR, Gutmanas A, Varadi M, Velankar S. Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies. STRUCTURAL DYNAMICS (MELVILLE, N.Y.) 2024; 11:034701. [PMID: 38774441 PMCID: PMC11106648 DOI: 10.1063/4.0000251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 05/08/2024] [Indexed: 05/24/2024]
Abstract
Studying protein dynamics and conformational heterogeneity is crucial for understanding biomolecular systems and treating disease. Despite the deposition of over 215 000 macromolecular structures in the Protein Data Bank and the advent of AI-based structure prediction tools such as AlphaFold2, RoseTTAFold, and ESMFold, static representations are typically produced, which fail to fully capture macromolecular motion. Here, we discuss the importance of integrating experimental structures with computational clustering to explore the conformational landscapes that manifest protein function. We describe the method developed by the Protein Data Bank in Europe - Knowledge Base to identify distinct conformational states, demonstrate the resource's primary use cases, through examples, and discuss the need for further efforts to annotate protein conformations with functional information. Such initiatives will be crucial in unlocking the potential of protein dynamics data, expediting drug discovery research, and deepening our understanding of macromolecular mechanisms.
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Affiliation(s)
- Joseph I. J. Ellaway
- Protein Data Bank in Europe, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Stephen Anyango
- Protein Data Bank in Europe, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Sreenath Nair
- Protein Data Bank in Europe, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Hossam A. Zaki
- The Warren Alpert Medical School of Brown University, Providence, Rhode Island 02903, USA
| | - Nurul Nadzirin
- Protein Data Bank in Europe, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Harold R. Powell
- Imperial College London, Department of Life Sciences, London, United Kingdom
| | - Aleksandras Gutmanas
- WaveBreak Therapeutics Ltd., Clarendon House, Clarendon Road, Cambridge, United Kingdom
| | - Mihaly Varadi
- Protein Data Bank in Europe, European Bioinformatics Institute, Hinxton, United Kingdom
| | - Sameer Velankar
- Protein Data Bank in Europe, European Bioinformatics Institute, Hinxton, United Kingdom
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5
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Xie T, Huang J. Can Protein Structure Prediction Methods Capture Alternative Conformations of Membrane Transporters? J Chem Inf Model 2024; 64:3524-3536. [PMID: 38564295 DOI: 10.1021/acs.jcim.3c01936] [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: 04/04/2024]
Abstract
Understanding the conformational dynamics of proteins, such as the inward-facing (IF) and outward-facing (OF) transition observed in transporters, is vital for elucidating their functional mechanisms. Despite significant advances in protein structure prediction (PSP) over the past three decades, most efforts have been focused on single-state prediction, leaving multistate or alternative conformation prediction (ACP) relatively unexplored. This discrepancy has led to the development of highly accurate PSP methods such as AlphaFold, yet their capabilities for ACP remain limited. To investigate the performance of current PSP methods in ACP, we curated a data set, named IOMemP, consisting of 32 experimentally determined high-resolution IF and OF structures of 16 membrane proteins with substantial conformational changes. We benchmarked 12 representative PSP methods, along with two recent multistate methods based on AlphaFold, against this data set. Our findings reveal a remarkably consistent preference for specific states across various PSP methods. We elucidated how coevolution information in MSAs influences state preference. Moreover, we showed that AlphaFold, when excluding coevolution information, estimated similar energies between the experimental IF and OF conformations, indicating that the energy model learned by AlphaFold is not biased toward any particular state. Our IOMemP data set and benchmark results are anticipated to advance the development of robust ACP methods.
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Affiliation(s)
- Tengyu Xie
- College of Life Science, Zhejiang University, HangZhou Zhejiang 310058, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, HangZhou Zhejiang 310024, China
- Westlake AI Therapeutics Lab, Westlake Laboratory of Life Sciences and Biomedicine, HangZhou Zhejiang 310024, China
| | - Jing Huang
- College of Life Science, Zhejiang University, HangZhou Zhejiang 310058, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, HangZhou Zhejiang 310024, China
- Westlake AI Therapeutics Lab, Westlake Laboratory of Life Sciences and Biomedicine, HangZhou Zhejiang 310024, China
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6
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Monteiro da Silva G, Cui JY, Dalgarno DC, Lisi GP, Rubenstein BM. High-throughput prediction of protein conformational distributions with subsampled AlphaFold2. Nat Commun 2024; 15:2464. [PMID: 38538622 PMCID: PMC10973385 DOI: 10.1038/s41467-024-46715-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 02/28/2024] [Indexed: 04/12/2024] Open
Abstract
This paper presents an innovative approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins' ground state conformations and is limited in its ability to predict conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments. We tested our method against nuclear magnetic resonance experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted changes in their relative state populations with more than 80% accuracy. Our subsampling approach worked best when used to qualitatively predict the effects of mutations or evolution on the conformational landscape and well-populated states of proteins. It thus offers a fast and cost-effective way to predict the relative populations of protein conformations at even single-point mutation resolution, making it a useful tool for pharmacology, analysis of experimental results, and predicting evolution.
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Affiliation(s)
| | - Jennifer Y Cui
- Brown University Department of Molecular and Cell Biology and Biochemistry, Providence, RI, USA
| | | | - George P Lisi
- Brown University Department of Molecular and Cell Biology and Biochemistry, Providence, RI, USA
- Brown University Department of Chemistry, Providence, RI, USA
| | - Brenda M Rubenstein
- Brown University Department of Molecular and Cell Biology and Biochemistry, Providence, RI, USA.
- Brown University Department of Chemistry, Providence, RI, USA.
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7
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Montrose K, Lac DT, Burnetti AJ, Tong K, Bozdag GO, Hukkanen M, Ratcliff WC, Saarikangas J. Proteostatic tuning underpins the evolution of novel multicellular traits. SCIENCE ADVANCES 2024; 10:eadn2706. [PMID: 38457507 PMCID: PMC10923498 DOI: 10.1126/sciadv.adn2706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 02/06/2024] [Indexed: 03/10/2024]
Abstract
The evolution of multicellularity paved the way for the origin of complex life on Earth, but little is known about the mechanistic basis of early multicellular evolution. Here, we examine the molecular basis of multicellular adaptation in the multicellularity long-term evolution experiment (MuLTEE). We demonstrate that cellular elongation, a key adaptation underpinning increased biophysical toughness and organismal size, is convergently driven by down-regulation of the chaperone Hsp90. Mechanistically, Hsp90-mediated morphogenesis operates by destabilizing the cyclin-dependent kinase Cdc28, resulting in delayed mitosis and prolonged polarized growth. Reinstatement of Hsp90 or Cdc28 expression resulted in shortened cells that formed smaller groups with reduced multicellular fitness. Together, our results show how ancient protein folding systems can be tuned to drive rapid evolution at a new level of biological individuality by revealing novel developmental phenotypes.
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Affiliation(s)
- Kristopher Montrose
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, Helsinki, Finland
- Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | - Dung T. Lac
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Anthony J. Burnetti
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Kai Tong
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, Helsinki, Finland
- Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
- Interdisciplinary Graduate Program in Quantitative Biosciences (QBioS), Georgia Institute of Technology, Atlanta, GA, USA
| | - G. Ozan Bozdag
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Mikaela Hukkanen
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, Helsinki, Finland
- Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | - William C. Ratcliff
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Juha Saarikangas
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, Helsinki, Finland
- Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland
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8
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Fesenko I, Sahakyan H, Shabalina SA, Koonin EV. The Cryptic Bacterial Microproteome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.17.580829. [PMID: 38903115 PMCID: PMC11188072 DOI: 10.1101/2024.02.17.580829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Microproteins encoded by small open reading frames (smORFs) comprise the "dark matter" of proteomes. Although functional microproteins were identified in diverse organisms from all three domains of life, bacterial smORFs remain poorly characterized. In this comprehensive study of intergenic smORFs (ismORFs, 15-70 codons) in 5,668 bacterial genomes of the family Enterobacteriaceae, we identified 67,297 clusters of ismORFs subject to purifying selection. The ismORFs mainly code for hydrophobic, potentially transmembrane, unstructured, or minimally structured microproteins. Using AlphaFold Multimer, we predicted interactions of some of the predicted microproteins encoded by transcribed ismORFs with proteins encoded by neighboring genes, revealing the potential of microproteins to regulate the activity of various proteins, particularly, under stress. We compiled a catalog of predicted microprotein families with different levels of evidence from synteny analysis, structure prediction, and transcription and translation data. This study offers a resource for investigation of biological functions of microproteins.
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Affiliation(s)
- Igor Fesenko
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Harutyun Sahakyan
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Svetlana A. Shabalina
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Eugene V. Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
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9
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Montrose K, Lac DT, Burnetti AJ, Tong K, Ozan Bozdag G, Hukkanen M, Ratcliff WC, Saarikangas J. Proteostatic tuning underpins the evolution of novel multicellular traits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.31.543183. [PMID: 37333256 PMCID: PMC10274739 DOI: 10.1101/2023.05.31.543183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
The evolution of multicellularity paved the way for the origin of complex life on Earth, but little is known about the mechanistic basis of early multicellular evolution. Here, we examine the molecular basis of multicellular adaptation in the Multicellularity Long Term Evolution Experiment (MuLTEE). We demonstrate that cellular elongation, a key adaptation underpinning increased biophysical toughness and organismal size, is convergently driven by downregulation of the chaperone Hsp90. Mechanistically, Hsp90-mediated morphogenesis operates by destabilizing the cyclin-dependent kinase Cdc28, resulting in delayed mitosis and prolonged polarized growth. Reinstatement of Hsp90 or Cdc28 expression resulted in shortened cells that formed smaller groups with reduced multicellular fitness. Together, our results show how ancient protein folding systems can be tuned to drive rapid evolution at a new level of biological individuality by revealing novel developmental phenotypes.
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Affiliation(s)
- Kristopher Montrose
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki
- Faculty of Biological and Environmental Sciences, University of Helsinki
| | - Dung T. Lac
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Anthony J. Burnetti
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Kai Tong
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki
- Faculty of Biological and Environmental Sciences, University of Helsinki
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
- Interdisciplinary Graduate Program in Quantitative Biosciences (QBioS)
| | - G. Ozan Bozdag
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Mikaela Hukkanen
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki
- Faculty of Biological and Environmental Sciences, University of Helsinki
| | - William C. Ratcliff
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Juha Saarikangas
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki
- Faculty of Biological and Environmental Sciences, University of Helsinki
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10
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Schafer JW, Chakravarty D, Chen EA, Porter LL. Sequence clustering confounds AlphaFold2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.05.574434. [PMID: 38313252 PMCID: PMC10836070 DOI: 10.1101/2024.01.05.574434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Though typically associated with a single folded state, some globular proteins remodel their secondary and/or tertiary structures in response to cellular stimuli. AlphaFold21 (AF2) readily generates one dominant protein structure for these fold-switching (a.k.a. metamorphic) proteins2, but it often fails to predict their alternative experimentally observed structures3,4. Wayment-Steele, et al. steered AF2 to predict alternative structures of a few metamorphic proteins using a method they call AF-cluster5. However, their Paper lacks some essential controls needed to assess AF-cluster's reliability. We find that these controls show AF-cluster to be a poor predictor of metamorphic proteins. First, closer examination of the Paper's results reveals that random sequence sampling outperforms sequence clustering, challenging the claim that AF-cluster works by "deconvolving conflicting sets of couplings." Further, we observe that AF-cluster mistakes some single-folding KaiB homologs for fold switchers, a critical flaw bound to mislead users. Finally, proper error analysis reveals that AF-cluster predicts many correct structures with low confidence and some experimentally unobserved conformations with confidences similar to experimentally observed ones. For these reasons, we suggest using ColabFold6-based random sequence sampling7-augmented by other predictive approaches-as a more accurate and less computationally intense alternative to AF-cluster.
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Affiliation(s)
- Joseph W. Schafer
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Devlina Chakravarty
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Ethan A. Chen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Lauren L. Porter
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
- Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892
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11
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Wayment-Steele HK, Ojoawo A, Otten R, Apitz JM, Pitsawong W, Hömberger M, Ovchinnikov S, Colwell L, Kern D. Predicting multiple conformations via sequence clustering and AlphaFold2. Nature 2024; 625:832-839. [PMID: 37956700 PMCID: PMC10808063 DOI: 10.1038/s41586-023-06832-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 11/03/2023] [Indexed: 11/15/2023]
Abstract
AlphaFold2 (ref. 1) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein's biological function often depends on multiple conformational substates2, and disease-causing point mutations often cause population changes within these substates3,4. We demonstrate that clustering a multiple-sequence alignment by sequence similarity enables AlphaFold2 to sample alternative states of known metamorphic proteins with high confidence. Using this method, named AF-Cluster, we investigated the evolutionary distribution of predicted structures for the metamorphic protein KaiB5 and found that predictions of both conformations were distributed in clusters across the KaiB family. We used nuclear magnetic resonance spectroscopy to confirm an AF-Cluster prediction: a cyanobacteria KaiB variant is stabilized in the opposite state compared with the more widely studied variant. To test AF-Cluster's sensitivity to point mutations, we designed and experimentally verified a set of three mutations predicted to flip KaiB from Rhodobacter sphaeroides from the ground to the fold-switched state. Finally, screening for alternative states in protein families without known fold switching identified a putative alternative state for the oxidoreductase Mpt53 in Mycobacterium tuberculosis. Further development of such bioinformatic methods in tandem with experiments will probably have a considerable impact on predicting protein energy landscapes, essential for illuminating biological function.
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Affiliation(s)
- Hannah K Wayment-Steele
- Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA
| | - Adedolapo Ojoawo
- Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA
| | - Renee Otten
- Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA
- Treeline Biosciences, Watertown, MA, USA
| | - Julia M Apitz
- Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA
| | - Warintra Pitsawong
- Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA
- Biomolecular Discovery, Relay Therapeutics, Cambridge, MA, USA
| | - Marc Hömberger
- Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA
- Treeline Biosciences, Watertown, MA, USA
| | | | - Lucy Colwell
- Google Research, Cambridge, MA, USA
- Cambridge University, Cambridge, UK
| | - Dorothee Kern
- Department of Biochemistry, Brandeis University and Howard Hughes Medical Institute, Waltham, MA, USA.
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12
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da Silva GM, Cui JY, Dalgarno DC, Lisi GP, Rubenstein BM. Predicting Relative Populations of Protein Conformations without a Physics Engine Using AlphaFold 2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.25.550545. [PMID: 37546747 PMCID: PMC10402055 DOI: 10.1101/2023.07.25.550545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
This paper presents a novel approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins' ground state conformations and is limited in its ability to predict conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments. We tested our method against NMR experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted changes in their relative state populations with more than 80% accuracy. Our subsampling approach worked best when used to qualitatively predict the effects of mutations or evolution on the conformational landscape and well-populated states of proteins. It thus offers a fast and cost-effective way to predict the relative populations of protein conformations at even single-point mutation resolution, making it a useful tool for pharmacology, NMR analysis, and evolution.
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Affiliation(s)
- Gabriel Monteiro da Silva
- Brown University Department of Molecular Biology, Cell Biology, and Biochemistry, Providence, RI, USA
| | - Jennifer Y Cui
- Brown University Department of Molecular Biology, Cell Biology, and Biochemistry, Providence, RI, USA
| | | | - George P Lisi
- Brown University Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University Department of Chemistry, Providence, RI, USA
| | - Brenda M Rubenstein
- Brown University Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University Department of Chemistry, Providence, RI, USA
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13
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Chakravarty D, Schafer JW, Chen EA, Thole JR, Porter LL. AlphaFold2 has more to learn about protein energy landscapes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.12.571380. [PMID: 38168383 PMCID: PMC10760193 DOI: 10.1101/2023.12.12.571380] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Recent work suggests that AlphaFold2 (AF2)-a deep learning-based model that can accurately infer protein structure from sequence-may discern important features of folded protein energy landscapes, defined by the diversity and frequency of different conformations in the folded state. Here, we test the limits of its predictive power on fold-switching proteins, which assume two structures with regions of distinct secondary and/or tertiary structure. Using several implementations of AF2, including two published enhanced sampling approaches, we generated >280,000 models of 93 fold-switching proteins whose experimentally determined conformations were likely in AF2's training set. Combining all models, AF2 predicted fold switching with a modest success rate of ~25%, indicating that it does not readily sample both experimentally characterized conformations of most fold switchers. Further, AF2's confidence metrics selected against models consistent with experimentally determined fold-switching conformations in favor of inconsistent models. Accordingly, these confidence metrics-though suggested to evaluate protein energetics reliably-did not discriminate between low and high energy states of fold-switching proteins. We then evaluated AF2's performance on seven fold-switching proteins outside of its training set, generating >159,000 models in total. Fold switching was accurately predicted in one of seven targets with moderate confidence. Further, AF2 demonstrated no ability to predict alternative conformations of two newly discovered targets without homologs in the set of 93 fold switchers. These results indicate that AF2 has more to learn about the underlying energetics of protein ensembles and highlight the need for further developments of methods that readily predict multiple protein conformations.
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Affiliation(s)
- Devlina Chakravarty
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Joseph W. Schafer
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Ethan A. Chen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Joseph R. Thole
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
- Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892
| | - Lauren L. Porter
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
- Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892
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14
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Jose AM. Heritable epigenetic changes are constrained by the dynamics of regulatory architectures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.544138. [PMID: 37333369 PMCID: PMC10274868 DOI: 10.1101/2023.06.07.544138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Such stable changes can (1) alter steady-state levels while preserving the architecture, (2) induce different architectures that persist for many generations, or (3) collapse the entire architecture. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that the evolution of mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of regulatory architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode C. elegans, which range from permanent silencing to recovery from silencing within a few generations and subsequent resistance to silencing. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.
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15
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Chen EA, Porter LL. SSDraw: Software for generating comparative protein secondary structure diagrams. Protein Sci 2023; 32:e4836. [PMID: 37953705 PMCID: PMC10680343 DOI: 10.1002/pro.4836] [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: 08/25/2023] [Revised: 10/18/2023] [Accepted: 11/08/2023] [Indexed: 11/14/2023]
Abstract
The program SSDraw generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. Diagrams of homologous proteins can be registered according to an input multiple sequence alignment. Linear visualization allows the user to stack registered diagrams, facilitating comparison of secondary structure and other properties among homologous proteins. SSDraw can be used to compare secondary structures of homologous proteins with both conserved and divergent folds. It can also generate one secondary structure diagram from an input protein structure of interest. The source code can be downloaded (https://github.com/ncbi/SSDraw) and run locally for rapid structure generation, while a Google Colab notebook allows easy use.
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Affiliation(s)
- Ethan A. Chen
- National Center for Biotechnology Information, National Library of MedicineNational Institutes of HealthBethesdaMarylandUSA
| | - Lauren L. Porter
- National Center for Biotechnology Information, National Library of MedicineNational Institutes of HealthBethesdaMarylandUSA
- Biochemistry and Biophysics Center, National Heart, Lung, and Blood InstituteNational Institutes of HealthBethesdaMarylandUSA
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16
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Porter LL, Chakravarty D, Schafer JW, Chen EA. ColabFold predicts alternative protein structures from single sequences, coevolution unnecessary for AF-cluster. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.21.567977. [PMID: 38076792 PMCID: PMC10705582 DOI: 10.1101/2023.11.21.567977] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
Though typically associated with a single folded state, globular proteins are dynamic and often assume alternative or transient structures important for their functions1,2. Wayment-Steele, et al. steered ColabFold3 to predict alternative structures of several proteins using a method they call AF-cluster4. They propose that AF-cluster "enables ColabFold to sample alternate states of known metamorphic proteins with high confidence" by first clustering multiple sequence alignments (MSAs) in a way that "deconvolves" coevolutionary information specific to different conformations and then using these clusters as input for ColabFold. Contrary to this Coevolution Assumption, clustered MSAs are not needed to make these predictions. Rather, these alternative structures can be predicted from single sequences and/or sequence similarity, indicating that coevolutionary information is unnecessary for predictive success and may not be used at all. These results suggest that AF-cluster's predictive scope is likely limited to sequences with distinct-yet-homologous structures within ColabFold's training set.
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Affiliation(s)
- Lauren L. Porter
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
- Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892
| | - Devlina Chakravarty
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Joseph W. Schafer
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Ethan A. Chen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
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17
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Martin NS, Ahnert SE. The Boltzmann distributions of molecular structures predict likely changes through random mutations. Biophys J 2023; 122:4467-4475. [PMID: 37897043 PMCID: PMC10698324 DOI: 10.1016/j.bpj.2023.10.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 08/19/2023] [Accepted: 10/20/2023] [Indexed: 10/29/2023] Open
Abstract
New folded molecular structures can only evolve after arising through mutations. This aspect is modeled using genotype-phenotype maps, which connect sequence changes through mutations to changes in molecular structures. Previous work has shown that the likelihood of appearing through mutations can differ by orders of magnitude from structure to structure and that this can affect the outcomes of evolutionary processes. Thus, we focus on the phenotypic mutation probabilities φqp, i.e., the likelihood that a random mutation changes structure p into structure q. For both RNA secondary structures and the HP protein model, we show that a simple biophysical principle can explain and predict how this likelihood depends on the new structure q: φqp is high if sequences that fold into p as the minimum-free-energy structure are likely to have q as an alternative structure with high Boltzmann frequency. This generalizes the existing concept of plastogenetic congruence from individual sequences to the entire neutral spaces of structures. Our result helps us understand why some structural changes are more likely than others, may be useful for estimating these likelihoods via sampling and makes a connection to alternative structures with high Boltzmann frequency, which could be relevant in evolutionary processes.
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Affiliation(s)
- Nora S Martin
- Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, United Kingdom; Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom; Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom.
| | - Sebastian E Ahnert
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom; The Alan Turing Institute, London, United Kingdom
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18
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Chen EA, Porter LL. SSDraw: software for generating comparative protein secondary structure diagrams. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.25.554905. [PMID: 37786684 PMCID: PMC10541582 DOI: 10.1101/2023.08.25.554905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
The program SSDraw generates publication-quality protein secondary structure diagrams from three-dimensional protein structures. To depict relationships between secondary structure and other protein features, diagrams can be colored by conservation score, B-factor, or custom scoring. Diagrams of homologous proteins can be registered according to an input multiple sequence alignment. Linear visualization allows the user to stack registered diagrams, facilitating comparison of secondary structure and other properties among homologous proteins. SSDraw can be used to compare secondary structures of homologous proteins with both conserved and divergent folds. It can also generate one secondary structure diagram from an input protein structure of interest. The source code can be downloaded (https://github.com/ethanchen1301/SSDraw) and run locally for rapid structure generation, while a Google Colab notebook allows easy use.
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Affiliation(s)
- Ethan A. Chen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
| | - Lauren L. Porter
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894
- Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892
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19
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Paukštytė J, López Cabezas RM, Feng Y, Tong K, Schnyder D, Elomaa E, Gregorova P, Doudin M, Särkkä M, Sarameri J, Lippi A, Vihinen H, Juutila J, Nieminen A, Törönen P, Holm L, Jokitalo E, Krisko A, Huiskonen J, Sarin LP, Hietakangas V, Picotti P, Barral Y, Saarikangas J. Global analysis of aging-related protein structural changes uncovers enzyme-polymerization-based control of longevity. Mol Cell 2023; 83:3360-3376.e11. [PMID: 37699397 DOI: 10.1016/j.molcel.2023.08.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 05/18/2023] [Accepted: 08/11/2023] [Indexed: 09/14/2023]
Abstract
Aging is associated with progressive phenotypic changes. Virtually all cellular phenotypes are produced by proteins, and their structural alterations can lead to age-related diseases. However, we still lack comprehensive knowledge of proteins undergoing structural-functional changes during cellular aging and their contributions to age-related phenotypes. Here, we conducted proteome-wide analysis of early age-related protein structural changes in budding yeast using limited proteolysis-mass spectrometry (LiP-MS). The results, compiled in online ProtAge catalog, unraveled age-related functional changes in regulators of translation, protein folding, and amino acid metabolism. Mechanistically, we found that folded glutamate synthase Glt1 polymerizes into supramolecular self-assemblies during aging, causing breakdown of cellular amino acid homeostasis. Inhibiting Glt1 polymerization by mutating the polymerization interface restored amino acid levels in aged cells, attenuated mitochondrial dysfunction, and led to lifespan extension. Altogether, this comprehensive map of protein structural changes enables identifying mechanisms of age-related phenotypes and offers opportunities for their reversal.
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Affiliation(s)
- Jurgita Paukštytė
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, 00790 Helsinki, Finland; Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland
| | - Rosa María López Cabezas
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, 00790 Helsinki, Finland; Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland
| | - Yuehan Feng
- Institute of Biochemistry, ETH Zurich, 8093 Zurich, Switzerland
| | - Kai Tong
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, 00790 Helsinki, Finland; Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA; Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | | | - Ellinoora Elomaa
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, 00790 Helsinki, Finland; Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland
| | - Pavlina Gregorova
- Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland
| | - Matteo Doudin
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, 00790 Helsinki, Finland; Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland
| | - Meeri Särkkä
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, 00790 Helsinki, Finland; Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland
| | - Jesse Sarameri
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, 00790 Helsinki, Finland; Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland
| | - Alice Lippi
- Department of Experimental Neurodegeneration, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Helena Vihinen
- Institute of Biotechnology, HiLIFE, University of Helsinki, 00790 Helsinki, Finland
| | - Juhana Juutila
- Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland; Institute of Biotechnology, HiLIFE, University of Helsinki, 00790 Helsinki, Finland
| | - Anni Nieminen
- Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland; Institute of Biotechnology, HiLIFE, University of Helsinki, 00790 Helsinki, Finland
| | - Petri Törönen
- Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland; Institute of Biotechnology, HiLIFE, University of Helsinki, 00790 Helsinki, Finland
| | - Liisa Holm
- Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland; Institute of Biotechnology, HiLIFE, University of Helsinki, 00790 Helsinki, Finland
| | - Eija Jokitalo
- Institute of Biotechnology, HiLIFE, University of Helsinki, 00790 Helsinki, Finland
| | - Anita Krisko
- Department of Experimental Neurodegeneration, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Juha Huiskonen
- Institute of Biotechnology, HiLIFE, University of Helsinki, 00790 Helsinki, Finland
| | - L Peter Sarin
- Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland
| | - Ville Hietakangas
- Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland; Institute of Biotechnology, HiLIFE, University of Helsinki, 00790 Helsinki, Finland
| | - Paola Picotti
- Institute of Biochemistry, ETH Zurich, 8093 Zurich, Switzerland; Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland
| | - Yves Barral
- Institute of Biochemistry, ETH Zurich, 8093 Zurich, Switzerland
| | - Juha Saarikangas
- Helsinki Institute of Life Science, HiLIFE, University of Helsinki, 00790 Helsinki, Finland; Faculty of Biological and Environmental Sciences, University of Helsinki, 00790 Helsinki, Finland.
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20
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Bazmi S, Seifi B, Wallin S. Simulations of a protein fold switch reveal crowding-induced population shifts driven by disordered regions. Commun Chem 2023; 6:191. [PMID: 37689829 PMCID: PMC10492864 DOI: 10.1038/s42004-023-00995-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 08/24/2023] [Indexed: 09/11/2023] Open
Abstract
Macromolecular crowding effects on globular proteins, which usually adopt a single stable fold, have been widely studied. However, little is known about crowding effects on fold-switching proteins, which reversibly switch between distinct folds. Here we study the mutationally driven switch between the folds of GA and GB, the two 56-amino acid binding domains of protein G, using a structure-based dual-basin model. We show that, in the absence of crowders, the fold populations PA and PB can be controlled by the strengths of contacts in the two folds, κA and κB. A population balance, PA ≈ PB, is obtained for κB/κA = 0.92. The resulting model protein is subject to crowding at different packing fractions, ϕc. We find that crowding increases the GB population and reduces the GA population, reaching PB/PA ≈ 4 at ϕc = 0.44. We analyze the ϕc-dependence of the crowding-induced GA-to-GB switch using scaled particle theory, which provides a qualitative, but not quantitative, fit of our data, suggesting effects beyond a spherical description of the folds. We show that the terminal regions of the protein chain, which are intrinsically disordered only in GA, play a dominant role in the response of the fold switch to crowding effects.
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Affiliation(s)
- Saman Bazmi
- Department of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's, NL, A1B 3X7, Canada
| | - Bahman Seifi
- Department of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's, NL, A1B 3X7, Canada
| | - Stefan Wallin
- Department of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's, NL, A1B 3X7, Canada.
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21
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Schafer JW, Porter LL. Evolutionary selection of proteins with two folds. Nat Commun 2023; 14:5478. [PMID: 37673981 PMCID: PMC10482954 DOI: 10.1038/s41467-023-41237-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 08/24/2023] [Indexed: 09/08/2023] Open
Abstract
Although most globular proteins fold into a single stable structure, an increasing number have been shown to remodel their secondary and tertiary structures in response to cellular stimuli. State-of-the-art algorithms predict that these fold-switching proteins adopt only one stable structure, missing their functionally critical alternative folds. Why these algorithms predict a single fold is unclear, but all of them infer protein structure from coevolved amino acid pairs. Here, we hypothesize that coevolutionary signatures are being missed. Suspecting that single-fold variants could be masking these signatures, we developed an approach, called Alternative Contact Enhancement (ACE), to search both highly diverse protein superfamilies-composed of single-fold and fold-switching variants-and protein subfamilies with more fold-switching variants. ACE successfully revealed coevolution of amino acid pairs uniquely corresponding to both conformations of 56/56 fold-switching proteins from distinct families. Then, we used ACE-derived contacts to (1) predict two experimentally consistent conformations of a candidate protein with unsolved structure and (2) develop a blind prediction pipeline for fold-switching proteins. The discovery of widespread dual-fold coevolution indicates that fold-switching sequences have been preserved by natural selection, implying that their functionalities provide evolutionary advantage and paving the way for predictions of diverse protein structures from single sequences.
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Affiliation(s)
- Joseph W Schafer
- National Library of Medicine, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Lauren L Porter
- National Library of Medicine, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, 20894, USA.
- National Heart, Lung, and Blood Institute, Biochemistry and Biophysics Center, National Institutes of Health, Bethesda, MD, 20892, USA.
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22
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Porter LL. Fluid protein fold space and its implications. Bioessays 2023; 45:e2300057. [PMID: 37431685 PMCID: PMC10529699 DOI: 10.1002/bies.202300057] [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: 03/30/2023] [Revised: 06/21/2023] [Accepted: 06/23/2023] [Indexed: 07/12/2023]
Abstract
Fold-switching proteins, which remodel their secondary and tertiary structures in response to cellular stimuli, suggest a new view of protein fold space. For decades, experimental evidence has indicated that protein fold space is discrete: dissimilar folds are encoded by dissimilar amino acid sequences. Challenging this assumption, fold-switching proteins interconnect discrete groups of dissimilar protein folds, making protein fold space fluid. Three recent observations support the concept of fluid fold space: (1) some amino acid sequences interconvert between folds with distinct secondary structures, (2) some naturally occurring sequences have switched folds by stepwise mutation, and (3) fold switching is evolutionarily selected and likely confers advantage. These observations indicate that minor amino acid sequence modifications can transform protein structure and function. Consequently, proteomic structural and functional diversity may be expanded by alternative splicing, small nucleotide polymorphisms, post-translational modifications, and modified translation rates.
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Affiliation(s)
- Lauren L. Porter
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
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23
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Banavar JR, Giacometti A, Hoang TX, Maritan A, Škrbić T. A geometrical framework for thinking about proteins. Proteins 2023. [PMID: 37565735 DOI: 10.1002/prot.26567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 07/16/2023] [Accepted: 07/21/2023] [Indexed: 08/12/2023]
Abstract
We present a model, based on symmetry and geometry, for proteins. Using elementary ideas from mathematics and physics, we derive the geometries of discrete helices and sheets. We postulate a compatible solvent-mediated emergent pairwise attraction that assembles these building blocks, while respecting their individual symmetries. Instead of seeking to mimic the complexity of proteins, we look for a simple abstraction of reality that yet captures the essence of proteins. We employ analytic calculations and detailed Monte Carlo simulations to explore some consequences of our theory. The predictions of our approach are in accord with experimental data. Our framework provides a rationalization for understanding the common characteristics of proteins. Our results show that the free energy landscape of a globular protein is pre-sculpted at the backbone level, sequences and functionalities evolve in the fixed backdrop of the folds determined by geometry and symmetry, and that protein structures are unique in being simultaneously characterized by stability, diversity, and sensitivity.
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Affiliation(s)
- Jayanth R Banavar
- Department of Physics and Institute for Fundamental Science, University of Oregon, Eugene, Oregon, USA
| | - Achille Giacometti
- Ca' Foscari University of Venice, Department of Molecular Sciences and Nanosystems, Venice, Italy
- European Centre for Living Technology (ECLT), Venice, Italy
| | - Trinh X Hoang
- Vietnam Academy of Science and Technology, Institute of Physics, Hanoi, Vietnam
| | - Amos Maritan
- University of Padua, Department of Physics and Astronomy, Padua, Italy
| | - Tatjana Škrbić
- Department of Physics and Institute for Fundamental Science, University of Oregon, Eugene, Oregon, USA
- Ca' Foscari University of Venice, Department of Molecular Sciences and Nanosystems, Venice, Italy
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24
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García-Galindo P, Ahnert SE, Martin NS. The non-deterministic genotype-phenotype map of RNA secondary structure. J R Soc Interface 2023; 20:20230132. [PMID: 37608711 PMCID: PMC10445035 DOI: 10.1098/rsif.2023.0132] [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: 03/08/2023] [Accepted: 08/01/2023] [Indexed: 08/24/2023] Open
Abstract
Selection and variation are both key aspects in the evolutionary process. Previous research on the mapping between molecular sequence (genotype) and molecular fold (phenotype) has shown the presence of several structural properties in different biological contexts, implying that these might be universal in evolutionary spaces. The deterministic genotype-phenotype (GP) map that links short RNA sequences to minimum free energy secondary structures has been studied extensively because of its computational tractability and biologically realistic nature. However, this mapping ignores the phenotypic plasticity of RNA. We define a GP map that incorporates non-deterministic (ND) phenotypes, and take RNA as a case study; we use the Boltzmann probability distribution of folded structures and examine the structural properties of ND GP maps for RNA sequences of length 12 and coarse-grained RNA structures of length 30 (RNAshapes30). A framework is presented to study robustness, evolvability and neutral spaces in the ND map. This framework is validated by demonstrating close correspondence between the ND quantities and sample averages of their deterministic counterparts. When using the ND framework we observe the same structural properties as in the deterministic GP map, such as bias, negative correlation between genotypic robustness and evolvability, and positive correlation between phenotypic robustness and evolvability.
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Affiliation(s)
- Paula García-Galindo
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK
| | - Sebastian E. Ahnert
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK
- The Alan Turing Institute, 96 Euston Road, London NW1 2DB, UK
| | - Nora S. Martin
- Rudolf Peierls Centre for Theoretical Physics, Beecroft Building, Parks Road, Oxford OX1 3PU, UK
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25
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Dishman AF, Volkman BF. Metamorphic protein folding as evolutionary adaptation. Trends Biochem Sci 2023; 48:665-672. [PMID: 37270322 PMCID: PMC10526677 DOI: 10.1016/j.tibs.2023.05.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/12/2023] [Accepted: 05/04/2023] [Indexed: 06/05/2023]
Abstract
Metamorphic proteins switch reversibly between multiple distinct, stable structures, often with different functions. It was previously hypothesized that metamorphic proteins arose as intermediates in the evolution of a new fold - rare and transient exceptions to the 'one sequence, one fold' paradigm. However, as described herein, mounting evidence suggests that metamorphic folding is an adaptive feature, preserved and optimized over evolutionary time as exemplified by the NusG family and the chemokine XCL1. Analysis of extant protein families and resurrected protein ancestors demonstrates that large regions of sequence space are compatible with metamorphic folding. As a category that enhances biological fitness, metamorphic proteins are likely to employ fold switching to perform important biological functions and may be more common than previously thought.
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Affiliation(s)
- Acacia F Dishman
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Medical Scientist Training Program, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Brian F Volkman
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA; Program in Chemical Biology, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
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26
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Jeffery CJ. Current successes and remaining challenges in protein function prediction. FRONTIERS IN BIOINFORMATICS 2023; 3:1222182. [PMID: 37576715 PMCID: PMC10415035 DOI: 10.3389/fbinf.2023.1222182] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 07/03/2023] [Indexed: 08/15/2023] Open
Abstract
In recent years, improvements in protein function prediction methods have led to increased success in annotating protein sequences. However, the functions of over 30% of protein-coding genes remain unknown for many sequenced genomes. Protein functions vary widely, from catalyzing chemical reactions to binding DNA or RNA or forming structures in the cell, and some types of functions are challenging to predict due to the physical features associated with those functions. Other complications in understanding protein functions arise due to the fact that many proteins have more than one function or very small differences in sequence or structure that correspond to different functions. We will discuss some of the recent developments in predicting protein functions and some of the remaining challenges.
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Affiliation(s)
- Constance J. Jeffery
- Department of Biological Sciences, University of Illinois at Chicago, Chicago, IL, United States
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27
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Kulkarni P, Salgia R, Rangarajan G. Intrinsically disordered proteins and conformational noise: The hypothesis a decade later. iScience 2023; 26:107109. [PMID: 37408690 PMCID: PMC10319216 DOI: 10.1016/j.isci.2023.107109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2023] Open
Abstract
Phenotypic plasticity is the ability of individual genotypes to produce different phenotypes in response to environmental perturbations. We previously postulated how conformational noise emanating from conformational dynamics of intrinsically disordered proteins (IDPs) which is distinct from transcriptional noise, can contribute to phenotypic switching by rewiring the cellular protein interaction network. Since most transcription factors are IDPs, we posited that conformational noise is an integral component of transcriptional noise implying that IDPs may amplify total noise in the system either stochastically or in response to environmental changes. Here, we review progress in elucidating the details of the hypothesis. We highlight empirical evidence supporting the hypothesis, discuss conceptual advances that underscore its fundamental importance and implications, and identify areas for future investigations.
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Affiliation(s)
- Prakash Kulkarni
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA
- Department of Systems Biology, City of Hope National Medical Center, Duarte, CA, USA
| | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA
| | - Govindan Rangarajan
- Department of Mathematics, Indian Institute of Science, Bangalore 560012, India
- Center for Neuroscience, Indian Institute of Science, Bangalore 560012, India
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28
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Zhang N, Guan W, Cui S, Ai N. Crowded environments tune the fold-switching in metamorphic proteins. Commun Chem 2023; 6:117. [PMID: 37291449 PMCID: PMC10250422 DOI: 10.1038/s42004-023-00909-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 05/22/2023] [Indexed: 06/10/2023] Open
Abstract
Metamorphic proteins such as circadian clock protein KaiB and human chemokine XCL1 play vital roles in regulating biological processes, including gene expression, circadian clock and innate immune responses, and perform distinct functions in living cell by switching different structures in response to cellular environment stimuli. However, it is unclear how complex and crowded intracellular environments affect conformational rearrangement of metamorphic proteins. Here, the kinetics and thermodynamics of two well-characterized metamorphic proteins, circadian clock protein KaiB and human chemokine XCL1, were quantified in physiologically relevant environments by using NMR spectroscopy, indicating that crowded agents shift equilibrium towards the inactive form (ground-state KaiB and Ltn10-like state XCL1) without disturbing the corresponding structures, and crowded agents have predominantly impact on the exchange rate of XCL1 that switches folds on timescales of seconds, but have slightly impact on the exchange rate of KaiB that switches folds on timescales of hours. Our data shed light on how metamorphic proteins can respond immediately to the changed crowded intracellular conditions that induced by environmental cues and then execute different functions in living cell, and it also enhances our understanding of how environments enrich the sequence-structure-function paradigm.
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Affiliation(s)
- Ning Zhang
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China.
- Shandong Energy Institute, Qingdao, 266101, China.
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China.
| | - Wenyan Guan
- Materials and Biomaterials Science and Engineering, University of California, Merced, CA, 95343, USA
| | - Shouqi Cui
- Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Nana Ai
- Materials and Biomaterials Science and Engineering, University of California, Merced, CA, 95343, USA
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29
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Chakravarty D, Sreenivasan S, Swint-Kruse L, Porter LL. Identification of a covert evolutionary pathway between two protein folds. Nat Commun 2023; 14:3177. [PMID: 37264049 DOI: 10.1038/s41467-023-38519-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 05/03/2023] [Indexed: 06/03/2023] Open
Abstract
Although homologous protein sequences are expected to adopt similar structures, some amino acid substitutions can interconvert α-helices and β-sheets. Such fold switching may have occurred over evolutionary history, but supporting evidence has been limited by the: (1) abundance and diversity of sequenced genes, (2) quantity of experimentally determined protein structures, and (3) assumptions underlying the statistical methods used to infer homology. Here, we overcome these barriers by applying multiple statistical methods to a family of ~600,000 bacterial response regulator proteins. We find that their homologous DNA-binding subunits assume divergent structures: helix-turn-helix versus α-helix + β-sheet (winged helix). Phylogenetic analyses, ancestral sequence reconstruction, and AlphaFold2 models indicate that amino acid substitutions facilitated a switch from helix-turn-helix into winged helix. This structural transformation likely expanded DNA-binding specificity. Our approach uncovers an evolutionary pathway between two protein folds and provides a methodology to identify secondary structure switching in other protein families.
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Affiliation(s)
- Devlina Chakravarty
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Shwetha Sreenivasan
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, KS, 66160, USA
| | - Liskin Swint-Kruse
- Department of Biochemistry and Molecular Biology, The University of Kansas Medical Center, Kansas City, KS, 66160, USA
| | - Lauren L Porter
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
- Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
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30
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Serebryany E, Zhao VY, Park K, Bitran A, Trauger SA, Budnik B, Shakhnovich EI. Systematic conformation-to-phenotype mapping via limited deep sequencing of proteins. Mol Cell 2023; 83:1936-1952.e7. [PMID: 37267908 PMCID: PMC10281453 DOI: 10.1016/j.molcel.2023.05.006] [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: 04/12/2022] [Revised: 01/29/2023] [Accepted: 05/03/2023] [Indexed: 06/04/2023]
Abstract
Non-native conformations drive protein-misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.
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Affiliation(s)
- Eugene Serebryany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.
| | - Victor Y Zhao
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Kibum Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Amir Bitran
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
| | - Sunia A Trauger
- Center for Mass Spectrometry, Harvard University, Cambridge, MA 02138, USA
| | - Bogdan Budnik
- Center for Mass Spectrometry, Harvard University, Cambridge, MA 02138, USA
| | - Eugene I Shakhnovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.
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31
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Gupta MN, Uversky VN. Moonlighting enzymes: when cellular context defines specificity. Cell Mol Life Sci 2023; 80:130. [PMID: 37093283 PMCID: PMC11073002 DOI: 10.1007/s00018-023-04781-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/13/2023] [Accepted: 04/15/2023] [Indexed: 04/25/2023]
Abstract
It is not often realized that the absolute protein specificity is an exception rather than a rule. Two major kinds of protein multi-specificities are promiscuity and moonlighting. This review discusses the idea of enzyme specificity and then focusses on moonlighting. Some important examples of protein moonlighting, such as crystallins, ceruloplasmin, metallothioniens, macrophage migration inhibitory factor, and enzymes of carbohydrate metabolism are discussed. How protein plasticity and intrinsic disorder enable the removing the distinction between enzymes and other biologically active proteins are outlined. Finally, information on important roles of moonlighting in human diseases is updated.
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Affiliation(s)
- Munishwar Nath Gupta
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India
| | - Vladimir N Uversky
- Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd., MDC07, Tampa, FL, 33612-4799, USA.
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32
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Chakravarty D, Schafer JW, Porter LL. Distinguishing features of fold-switching proteins. Protein Sci 2023; 32:e4596. [PMID: 36782353 PMCID: PMC9951197 DOI: 10.1002/pro.4596] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/30/2023] [Accepted: 02/09/2023] [Indexed: 02/15/2023]
Abstract
Though many folded proteins assume one stable structure that performs one function, a small-but-increasing number remodel their secondary and tertiary structures and change their functions in response to cellular stimuli. These fold-switching proteins regulate biological processes and are associated with autoimmune dysfunction, severe acute respiratory syndrome coronavirus-2 infection, and more. Despite their biological importance, it is difficult to computationally predict fold switching. With the aim of advancing computational prediction and experimental characterization of fold switchers, this review discusses several features that distinguish fold-switching proteins from their single-fold and intrinsically disordered counterparts. First, the isolated structures of fold switchers are less stable and more heterogeneous than single folders but more stable and less heterogeneous than intrinsically disordered proteins (IDPs). Second, the sequences of single fold, fold switching, and intrinsically disordered proteins can evolve at distinct rates. Third, proteins from these three classes are best predicted using different computational techniques. Finally, late-breaking results suggest that single folders, fold switchers, and IDPs have distinct patterns of residue-residue coevolution. The review closes by discussing high-throughput and medium-throughput experimental approaches that might be used to identify new fold-switching proteins.
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Affiliation(s)
- Devlina Chakravarty
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesdaMarylandUSA
| | - Joseph W. Schafer
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesdaMarylandUSA
| | - Lauren L. Porter
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthBethesdaMarylandUSA
- Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute, National Institutes of HealthBethesdaMarylandUSA
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33
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Chaudhari AS, Chatterjee A, Domingos CAO, Andrikopoulos PC, Liu Y, Andersson I, Schneider B, Lórenz-Fonfría VA, Fuertes G. Genetically encoded non-canonical amino acids reveal asynchronous dark reversion of chromophore, backbone and side-chains in EL222. Protein Sci 2023; 32:e4590. [PMID: 36764820 PMCID: PMC10019195 DOI: 10.1002/pro.4590] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/01/2023] [Accepted: 02/06/2023] [Indexed: 02/12/2023]
Abstract
Photoreceptors containing the light-oxygen-voltage (LOV) domain elicit biological responses upon excitation of their flavin mononucleotide (FMN) chromophore by blue light. The mechanism and kinetics of dark-state recovery are not well understood. Here we incorporated the non-canonical amino acid p-cyanophenylalanine (CNF) by genetic code expansion technology at forty-five positions of the bacterial transcription factor EL222. Screening of light-induced changes in infrared (IR) absorption frequency, electric field and hydration of the nitrile groups identified residues CNF31 and CNF35 as reporters of monomer/oligomer and caged/decaged equilibria, respectively. Time-resolved multi-probe UV/Visible and IR spectroscopy experiments of the lit-to-dark transition revealed four dynamical events. Predominantly, rearrangements around the A'α helix interface (CNF31 and CNF35) precede FMN-cysteinyl adduct scission, folding of α-helices (amide bands), and relaxation of residue CNF151. This study illustrates the importance of characterizing all parts of a protein and suggests a key role for the N-terminal A'α extension of the LOV domain in controlling EL222 photocycle length. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Aditya S Chaudhari
- Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic.,Faculty of Science, Charles University, Prague, Czech Republic
| | - Aditi Chatterjee
- Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic.,Faculty of Science, Charles University, Prague, Czech Republic
| | - Catarina A O Domingos
- Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic.,Escola Superior de Tecnologia do Barreiro, Instituto Politécnico de Setúbal, Lavradio, Portugal
| | | | - Yingliang Liu
- Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic
| | - Inger Andersson
- Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic.,Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Bohdan Schneider
- Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic
| | | | - Gustavo Fuertes
- Institute of Biotechnology of the Czech Academy of Sciences, Vestec, Czech Republic
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34
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Sykes J, Holland BR, Charleston MA. A review of visualisations of protein fold networks and their relationship with sequence and function. Biol Rev Camb Philos Soc 2023; 98:243-262. [PMID: 36210328 PMCID: PMC10092621 DOI: 10.1111/brv.12905] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 09/08/2022] [Accepted: 09/09/2022] [Indexed: 01/12/2023]
Abstract
Proteins form arguably the most significant link between genotype and phenotype. Understanding the relationship between protein sequence and structure, and applying this knowledge to predict function, is difficult. One way to investigate these relationships is by considering the space of protein folds and how one might move from fold to fold through similarity, or potential evolutionary relationships. The many individual characterisations of fold space presented in the literature can tell us a lot about how well the current Protein Data Bank represents protein fold space, how convergence and divergence may affect protein evolution, how proteins affect the whole of which they are part, and how proteins themselves function. A synthesis of these different approaches and viewpoints seems the most likely way to further our knowledge of protein structure evolution and thus, facilitate improved protein structure design and prediction.
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Affiliation(s)
- Janan Sykes
- School of Natural Sciences, University of Tasmania, Private Bag 37, Hobart, Tasmania, 7001, Australia
| | - Barbara R Holland
- School of Natural Sciences, University of Tasmania, Private Bag 37, Hobart, Tasmania, 7001, Australia
| | - Michael A Charleston
- School of Natural Sciences, University of Tasmania, Private Bag 37, Hobart, Tasmania, 7001, Australia
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35
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Serebryany E, Zhao VY, Park K, Bitran A, Trauger SA, Budnik B, Shakhnovich EI. Systematic conformation-to-phenotype mapping via limited deep-sequencing of proteins. ARXIV 2023:2204.06159. [PMID: 36776823 PMCID: PMC9915745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
Non-native conformations drive protein misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well-suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.
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Affiliation(s)
- Eugene Serebryany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | - Victor Y. Zhao
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | - Kibum Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | - Amir Bitran
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA
| | | | - Bogdan Budnik
- Center for Mass Spectrometry, Harvard University, Cambridge, MA
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36
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Ruan B, He Y, Chen Y, Choi EJ, Chen Y, Motabar D, Solomon T, Simmerman R, Kauffman T, Gallagher DT, Orban J, Bryan PN. Design and characterization of a protein fold switching network. Nat Commun 2023; 14:431. [PMID: 36702827 PMCID: PMC9879998 DOI: 10.1038/s41467-023-36065-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 01/13/2023] [Indexed: 01/27/2023] Open
Abstract
To better understand how amino acid sequence encodes protein structure, we engineered mutational pathways that connect three common folds (3α, β-grasp, and α/β-plait). The structures of proteins at high sequence-identity intersections in the pathways (nodes) were determined using NMR spectroscopy and analyzed for stability and function. To generate nodes, the amino acid sequence encoding a smaller fold is embedded in the structure of an ~50% larger fold and a new sequence compatible with two sets of native interactions is designed. This generates protein pairs with a 3α or β-grasp fold in the smaller form but an α/β-plait fold in the larger form. Further, embedding smaller antagonistic folds creates critical states in the larger folds such that single amino acid substitutions can switch both their fold and function. The results help explain the underlying ambiguity in the protein folding code and show that new protein structures can evolve via abrupt fold switching.
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Affiliation(s)
- Biao Ruan
- Potomac Affinity Proteins, 11305 Dunleith Pl, North Potomac, MD, 20878, USA
| | - Yanan He
- Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA
| | - Yingwei Chen
- Potomac Affinity Proteins, 11305 Dunleith Pl, North Potomac, MD, 20878, USA
| | - Eun Jung Choi
- Potomac Affinity Proteins, 11305 Dunleith Pl, North Potomac, MD, 20878, USA
| | - Yihong Chen
- Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA
| | - Dana Motabar
- Potomac Affinity Proteins, 11305 Dunleith Pl, North Potomac, MD, 20878, USA.,Department of Bioengineering, University of Maryland, College Park, MD, 20742, USA
| | - Tsega Solomon
- Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA.,Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, 20742, USA
| | - Richard Simmerman
- Potomac Affinity Proteins, 11305 Dunleith Pl, North Potomac, MD, 20878, USA
| | - Thomas Kauffman
- Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA.,Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, 20742, USA
| | - D Travis Gallagher
- Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA.,National Institute of Standards and Technology and the University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA
| | - John Orban
- Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA. .,Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, 20742, USA.
| | - Philip N Bryan
- Potomac Affinity Proteins, 11305 Dunleith Pl, North Potomac, MD, 20878, USA. .,Institute for Bioscience and Biotechnology Research, University of Maryland, 9600 Gudelsky Drive, Rockville, MD, 20850, USA.
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37
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Reversible switching between two common protein folds in a designed system using only temperature. Proc Natl Acad Sci U S A 2023; 120:e2215418120. [PMID: 36669114 PMCID: PMC9942840 DOI: 10.1073/pnas.2215418120] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Naturally occurring metamorphic proteins have the ability to interconvert from one folded state to another through either a limited set of mutations or by way of a change in the local environment. Here, we show in a designed system that it is possible to switch reversibly between two of the most common monomeric folds employing only temperature changes. We demonstrate that a latent 3α state can be unmasked from an α/β-plait topology with a single V90T amino acid substitution, populating both forms simultaneously. The equilibrium between these two states exhibits temperature dependence, such that the 3α state is predominant (>90%) at 5 °C, while the α/β-plait fold is the major species (>90%) at 30 °C. We describe the structure and dynamics of these topologies, how mutational changes affect the temperature dependence, and the energetics and kinetics of interconversion. Additionally, we demonstrate how ligand-binding function can be tightly regulated by large amplitude changes in protein structure over a relatively narrow temperature range that is relevant to biology. The 3α/αβ switch thus represents a potentially useful approach for designing proteins that alter their fold topologies in response to environmental triggers. It may also serve as a model for computational studies of temperature-dependent protein stability and fold switching.
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38
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Schafer JW, Porter LL. Evolutionary selection of proteins with two folds. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.18.524637. [PMID: 36789442 PMCID: PMC9928049 DOI: 10.1101/2023.01.18.524637] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Although most globular proteins fold into a single stable structure 1 , an increasing number have been shown to remodel their secondary and tertiary structures in response to cellular stimuli 2 . State-of-the-art algorithms 3-5 predict that these fold-switching proteins assume only one stable structure 6,7 , missing their functionally critical alternative folds. Why these algorithms predict a single fold is unclear, but all of them infer protein structure from coevolved amino acid pairs. Here, we hypothesize that coevolutionary signatures are being missed. Suspecting that over-represented single-fold sequences may be masking these signatures, we developed an approach to search both highly diverse protein superfamilies-composed of single-fold and fold-switching variants-and protein subfamilies with more fold-switching variants. This approach successfully revealed coevolution of amino acid pairs uniquely corresponding to both conformations of 56/58 fold-switching proteins from distinct families. Then, using a set of coevolved amino acid pairs predicted by our approach, we successfully biased AlphaFold2 5 to predict two experimentally consistent conformations of a candidate protein with unsolved structure. The discovery of widespread dual-fold coevolution indicates that fold-switching sequences have been preserved by natural selection, implying that their functionalities provide evolutionary advantage and paving the way for predictions of diverse protein structures from single sequences.
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Affiliation(s)
- Joseph W. Schafer
- National Library of Medicine, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA
| | - Lauren L. Porter
- National Library of Medicine, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA
- National Heart, Lung, and Blood Institute, Biochemistry and Biophysics Center, National Institutes of Health, Bethesda, MD 20892, USA
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39
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Chen SJ, Hassan M, Jernigan RL, Jia K, Kihara D, Kloczkowski A, Kotelnikov S, Kozakov D, Liang J, Liwo A, Matysiak S, Meller J, Micheletti C, Mitchell JC, Mondal S, Nussinov R, Okazaki KI, Padhorny D, Skolnick J, Sosnick TR, Stan G, Vakser I, Zou X, Rose GD. Opinion: Protein folds vs. protein folding: Differing questions, different challenges. Proc Natl Acad Sci U S A 2023; 120:e2214423119. [PMID: 36580595 PMCID: PMC9910419 DOI: 10.1073/pnas.2214423119] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Affiliation(s)
- Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, MO65211
| | - Mubashir Hassan
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children’s Hospital, Columbus, OH43205
| | - Robert L. Jernigan
- Bioinformatics and Computational Biology Program and Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA50011
| | - Kejue Jia
- Bioinformatics and Computational Biology Program and Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology Iowa State University, Ames, IA50011
| | - Daisuke Kihara
- Department of Biological Sciences, Department of Computer Science Purdue University, West Lafayette, IN79075
| | - Andrzej Kloczkowski
- Department of Pediatrics, The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children’s Hospital, The Ohio State University, Columbus, OH43205
| | - Sergei Kotelnikov
- Department of Applied Mathematics and Statistics, Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
| | - Dima Kozakov
- Frey Family Foundation, Department of Applied Mathematics and Statistics, Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
| | - Jie Liang
- Richard and Loan Hill Dept of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL60607
| | - Adam Liwo
- Faculty of Chemistry, University of Gdansk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, Gdansk80-308, Poland
| | - Silvina Matysiak
- Fischell Department of Bioengineering, University of Maryland, College Park, MD20742
| | - Jarek Meller
- University of Cincinnati & Cincinnati Children’s Hospital Medical Center, Cincinnati, OH45229
| | - Cristian Micheletti
- SISSA - International School for Advanced Studies, Via Bonomea 265, TriesteI-34136, Italy
| | | | | | - Ruth Nussinov
- Computational Structural Biology Section, National Laboratory for Cancer Research in the Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD21702
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv69978, Israel
| | - Kei-ichi Okazaki
- Research Center for Computational Science, Institute for Molecular Science, Okazaki, Aichi444-8585, Japan
| | - Dzmitry Padhorny
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
| | - Jeffrey Skolnick
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA30332
| | - Tobin R. Sosnick
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL60637
| | - George Stan
- Department of Chemistry, University of Cincinnati, Cincinnati, OH45221
| | - Ilya Vakser
- Computational Biology Program and Center for Computational Biology, Department of Molecular Biosciences, The University of Kansas, Lawrence, KS66045
| | - Xiaoqin Zou
- Department of Physics and Astronomy, Department of Biochemistry, Dalton Cardiovascular Research Center, Institute for Data Science and Informatics, University of Missouri, Columbia, MO65211
| | - George D. Rose
- Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD21218
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40
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Jin X, Sun X, Chai Y, Bai Y, Li Y, Hao T, Qi J, Song H, Wong CCL, Gao GF. Structural characterization of SARS-CoV-2 dimeric ORF9b reveals potential fold-switching trigger mechanism. SCIENCE CHINA. LIFE SCIENCES 2023; 66:152-164. [PMID: 36184694 PMCID: PMC9527070 DOI: 10.1007/s11427-022-2168-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 07/20/2022] [Indexed: 11/06/2022]
Abstract
The constant emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants indicates the evolution and adaptation of the virus. Enhanced innate immune evasion through increased expression of viral antagonist proteins, including ORF9b, contributes to the improved transmission of the Alpha variant; hence, more attention should be paid to these viral proteins. ORF9b is an accessory protein that suppresses innate immunity via a monomer conformation by binding to Tom70. Here, we solved the dimeric structure of SARS-CoV-2 ORF9b with a long hydrophobic tunnel containing a lipid molecule that is crucial for the dimeric conformation and determined the specific lipid ligands as monoglycerides by conducting a liquid chromatography with tandem mass spectrometry analysis, suggesting an important role in the viral life cycle. Notably, a long intertwined loop accessible for host factor binding was observed in the structure. Eight phosphorylated residues in ORF9b were identified, and residues S50 and S53 were found to contribute to the stabilization of dimeric ORF9b. Additionally, we proposed a model of multifunctional ORF9b with a distinct conformation, suggesting that ORF9b is a fold-switching protein, while both lipids and phosphorylation contribute to the switching. Specifically, the ORF9b monomer interacts with Tom70 to suppress the innate immune response, whereas the ORF9b dimer binds to the membrane involving mature virion assembly. Our results provide a better understanding of the multiple functions of ORF9b.
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Affiliation(s)
- Xiyue Jin
- grid.59053.3a0000000121679639School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027 China ,grid.9227.e0000000119573309CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 China
| | - Xue Sun
- grid.11135.370000 0001 2256 9319Peking University First Hospital, Peking University, Beijing, 100034 China ,grid.11135.370000 0001 2256 9319Center for Precision Medicine Multi-Omics Research, Peking University Health Science Center, Peking University, Beijing, 100191 China
| | - Yan Chai
- grid.9227.e0000000119573309CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 China
| | - Yu Bai
- grid.9227.e0000000119573309CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Ying Li
- grid.9227.e0000000119573309CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Tianjiao Hao
- grid.9227.e0000000119573309CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Jianxun Qi
- grid.9227.e0000000119573309CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Hao Song
- grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, 100049 China ,grid.9227.e0000000119573309Research Network of Immunity and Health (RNIH), Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101 China
| | - Catherine C. L. Wong
- grid.11135.370000 0001 2256 9319Peking University First Hospital, Peking University, Beijing, 100034 China ,grid.11135.370000 0001 2256 9319Center for Precision Medicine Multi-Omics Research, Peking University Health Science Center, Peking University, Beijing, 100191 China ,grid.11135.370000 0001 2256 9319Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871 China ,grid.11135.370000 0001 2256 9319School of Basic Medical Sciences, Peking University Health Science Center, Peking University, Beijing, 100191 China
| | - George F. Gao
- grid.59053.3a0000000121679639School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230027 China ,grid.9227.e0000000119573309CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101 China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, Beijing, 100049 China ,grid.9227.e0000000119573309Research Network of Immunity and Health (RNIH), Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101 China
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Abstract
Mechanisms of emergence and divergence of protein folds pose central questions in biological sciences. Incremental mutation and stepwise adaptation explain relationships between topologically similar protein folds. However, the universe of folds is diverse and riotous, suggesting more potent and creative forces are at play. Sequence and structure similarity are observed between distinct folds, indicating that proteins with distinct folds may share common ancestry. We found evidence of common ancestry between three distinct β-barrel folds: Scr kinase family homology (SH3), oligonucleotide/oligosaccharide-binding (OB), and cradle loop barrel (CLB). The data suggest a mechanism of fold evolution that interconverts SH3, OB, and CLB. This mechanism, which we call creative destruction, can be generalized to explain many examples of fold evolution including circular permutation. In creative destruction, an open reading frame duplicates or otherwise merges with another to produce a fused polypeptide. A merger forces two ancestral domains into a new sequence and spatial context. The fused polypeptide can explore folding landscapes that are inaccessible to either of the independent ancestral domains. However, the folding landscapes of the fused polypeptide are not fully independent of those of the ancestral domains. Creative destruction is thus partially conservative; a daughter fold inherits some motifs from ancestral folds. After merger and refolding, adaptive processes such as mutation and loss of extraneous segments optimize the new daughter fold. This model has application in disease states characterized by genetic instability. Fused proteins observed in cancer cells are likely to experience remodeled folding landscapes and realize altered folds, conferring new or altered functions.
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42
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Marie V, Gordon M. Understanding the co-evolutionary molecular mechanisms of resistance in the HIV-1 Gag and protease. J Biomol Struct Dyn 2022; 40:10852-10861. [PMID: 34253143 DOI: 10.1080/07391102.2021.1950569] [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] [Indexed: 01/29/2023]
Abstract
Due to high human immunodeficiency virus type 1 (HIV-1) subtype C infections coupled with increasing antiretroviral treatment failure, the elucidation of complex drug resistance mutational patterns arising through protein co-evolution is required. Despite the inclusion of potent protease inhibitors Lopinavir (LPV) and Darunavir (DRV) in second- and third-line therapies, many patients still fail treatment due to the accumulation of mutations in protease (PR) and recently, Gag. To understand the co-evolutionary molecular mechanisms of resistance in the HIV-1 PR and Gag, we performed 100 ns molecular dynamic simulations on multidrug resistant PR's when bound to LPV, DRV or a mutated A431V NC|p1 Gag cleavage site (CS). Here we showed that distinct changes in PR's active site, flap and elbow regions due to several PR resistance mutations (L10F, M46I, I54V, L76V, V82A) were found to alter LPV and DRV drug binding. However, binding was significantly exacerbated when the mutant PRs were bound to the NC|p1 Gag CS. Although A431V was shown to coordinate several residues in PR, the L76V PR mutation was found to have a significant role in substrate recognition. Consequently, a greater binding affinity was observed when the mutated substrate was bound to an L76V-inclusive PR mutant (Gbind: -62.46 ± 5.75 kcal/mol) than without (Gbind: -50.34 ± 6.28 kcal/mol). These data showed that the co-selection of resistance mutations in the enzyme and substrate can simultaneously constrict regions in PR's active site whilst flexing the flaps to allow flexible movement of the substrate and multiple, complex mechanisms of resistance to occur. Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Veronna Marie
- KwaZulu-Natal Research Innovation & Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, DurbanSouth Africa
| | - Michelle Gordon
- KwaZulu-Natal Research Innovation & Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, DurbanSouth Africa
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43
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Pillai AS, Hochberg GK, Thornton JW. Simple mechanisms for the evolution of protein complexity. Protein Sci 2022; 31:e4449. [PMID: 36107026 PMCID: PMC9601886 DOI: 10.1002/pro.4449] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 09/01/2022] [Accepted: 09/10/2022] [Indexed: 01/26/2023]
Abstract
Proteins are tiny models of biological complexity: specific interactions among their many amino acids cause proteins to fold into elaborate structures, assemble with other proteins into higher-order complexes, and change their functions and structures upon binding other molecules. These complex features are classically thought to evolve via long and gradual trajectories driven by persistent natural selection. But a growing body of evidence from biochemistry, protein engineering, and molecular evolution shows that naturally occurring proteins often exist at or near the genetic edge of multimerization, allostery, and even new folds, so just one or a few mutations can trigger acquisition of these properties. These sudden transitions can occur because many of the physical properties that underlie these features are present in simpler proteins as fortuitous by-products of their architecture. Moreover, complex features of proteins can be encoded by huge arrays of sequences, so they are accessible from many different starting points via many possible paths. Because the bridges to these features are both short and numerous, random chance can join selection as a key factor in explaining the evolution of molecular complexity.
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Affiliation(s)
- Arvind S. Pillai
- Department of Ecology and EvolutionUniversity of ChicagoChicagoIllinoisUSA
- Institute for Protein DesignUniversity of WashingtonSeattleWAUSA
| | - Georg K.A. Hochberg
- Max Planck Institute for Terrestrial MicrobiologyMarburgGermany
- Department of Chemistry, Center for Synthetic MicrobiologyPhilipps University MarburgMarburgGermany
| | - Joseph W. Thornton
- Department of Ecology and EvolutionUniversity of ChicagoChicagoIllinoisUSA
- Departments of Human Genetics and Ecology and EvolutionUniversity of ChicagoChicagoIllinoisUSA
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44
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Artsimovitch I, Ramírez-Sarmiento CA. Metamorphic proteins under a computational microscope: Lessons from a fold-switching RfaH protein. Comput Struct Biotechnol J 2022; 20:5824-5837. [PMID: 36382197 PMCID: PMC9630627 DOI: 10.1016/j.csbj.2022.10.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 10/18/2022] [Accepted: 10/18/2022] [Indexed: 11/28/2022] Open
Abstract
Metamorphic proteins constitute unexpected paradigms of the protein folding problem, as their sequences encode two alternative folds, which reversibly interconvert within biologically relevant timescales to trigger different cellular responses. Once considered a rare aberration, metamorphism may be common among proteins that must respond to rapidly changing environments, exemplified by NusG-like proteins, the only transcription factors present in every domain of life. RfaH, a specialized paralog of bacterial NusG, undergoes an all-α to all-β domain switch to activate expression of virulence and conjugation genes in many animal and plant pathogens and is the quintessential example of a metamorphic protein. The dramatic nature of RfaH structural transformation and the richness of its evolutionary history makes for an excellent model for studying how metamorphic proteins switch folds. Here, we summarize the structural and functional evidence that sparked the discovery of RfaH as a metamorphic protein, the experimental and computational approaches that enabled the description of the molecular mechanism and refolding pathways of its structural interconversion, and the ongoing efforts to find signatures and general properties to ultimately describe the protein metamorphome.
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Affiliation(s)
- Irina Artsimovitch
- Department of Microbiology and The Center for RNA Biology, The Ohio State University, Columbus, OH, USA
| | - César A. Ramírez-Sarmiento
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile
- ANID, Millennium Science Initiative Program, Millennium Institute for Integrative Biology (iBio), Santiago, Chile
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45
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Many dissimilar NusG protein domains switch between α-helix and β-sheet folds. Nat Commun 2022; 13:3802. [PMID: 35778397 PMCID: PMC9247905 DOI: 10.1038/s41467-022-31532-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 06/17/2022] [Indexed: 11/16/2022] Open
Abstract
Folded proteins are assumed to be built upon fixed scaffolds of secondary structure, α-helices and β-sheets. Experimentally determined structures of >58,000 non-redundant proteins support this assumption, though it has recently been challenged by ~100 fold-switching proteins. Though ostensibly rare, these proteins raise the question of how many uncharacterized proteins have shapeshifting–rather than fixed–secondary structures. Here, we use a comparative sequence-based approach to predict fold switching in the universally conserved NusG transcription factor family, one member of which has a 50-residue regulatory subunit experimentally shown to switch between α-helical and β-sheet folds. Our approach predicts that 24% of sequences in this family undergo similar α-helix ⇌ β-sheet transitions. While these predictions cannot be reproduced by other state-of-the-art computational methods, they are confirmed by circular dichroism and nuclear magnetic resonance spectroscopy for 10 out of 10 sequence-diverse variants. This work suggests that fold switching may be a pervasive mechanism of transcriptional regulation in all kingdoms of life. Folded proteins are composed of secondary structures, α-helices and β-sheets, that are generally assumed to be stable. Here, the authors combine computational prediction with experimental validation to show that many sequence-diverse NusG protein domains switch completely from α-helix to β-sheet folds.
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46
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Galaz‐Davison P, Ferreiro DU, Ramírez‐Sarmiento CA. Coevolution-derived native and non-native contacts determine the emergence of a novel fold in a universally conserved family of transcription factors. Protein Sci 2022; 31:e4337. [PMID: 35634768 PMCID: PMC9123645 DOI: 10.1002/pro.4337] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/18/2022] [Accepted: 05/03/2022] [Indexed: 11/07/2022]
Abstract
The NusG protein family is structurally and functionally conserved in all domains of life. Its members directly bind RNA polymerases and regulate transcription processivity and termination. RfaH, a divergent sub-family in its evolutionary history, is known for displaying distinct features than those in NusG proteins, which allows them to regulate the expression of virulence factors in enterobacteria in a DNA sequence-dependent manner. A striking feature is its structural interconversion between an active fold, which is the canonical NusG three-dimensional structure, and an autoinhibited fold, which is distinctively novel. How this novel fold is encoded within RfaH sequence to encode a metamorphic protein remains elusive. In this work, we used publicly available genomic RfaH protein sequences to construct a complete multiple sequence alignment, which was further augmented with metagenomic sequences and curated by predicting their secondary structure propensities using JPred. Coevolving pairs of residues were calculated from these sequences using plmDCA and GREMLIN, which allowed us to detect the enrichment of key metamorphic contacts after sequence filtering. Finally, we combined our coevolutionary predictions with molecular dynamics to demonstrate that these interactions are sufficient to predict the structures of both native folds, where coevolutionary-derived non-native contacts may play a key role in achieving the compact RfaH novel fold. All in all, emergent coevolutionary signals found within RfaH sequences encode the autoinhibited and active folds of this protein, shedding light on the key interactions responsible for the action of this metamorphic protein.
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Affiliation(s)
- Pablo Galaz‐Davison
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological SciencesPontificia Universidad Católica de ChileSantiagoChile
- ANID—Millennium Science Initiative Program—Millennium Institute for Integrative Biology (iBio)SantiagoChile
| | - Diego U. Ferreiro
- Protein Physiology Lab, Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales (IQUIBICEN‐CONICET)Universidad de Buenos AiresBuenos AiresArgentina
| | - César A. Ramírez‐Sarmiento
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological SciencesPontificia Universidad Católica de ChileSantiagoChile
- ANID—Millennium Science Initiative Program—Millennium Institute for Integrative Biology (iBio)SantiagoChile
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47
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Dishman AF, Volkman BF. Design and discovery of metamorphic proteins. Curr Opin Struct Biol 2022; 74:102380. [PMID: 35561475 PMCID: PMC9664977 DOI: 10.1016/j.sbi.2022.102380] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/14/2022] [Accepted: 03/16/2022] [Indexed: 11/03/2022]
Abstract
Metamorphic proteins are single amino acid sequences that reversibly interconvert between multiple, dramatically different native structures, often with distinct functions. Since the discovery of the first metamorphic proteins in the early 2000s, several additional metamorphic proteins have been identified, and it was suggested that up to 4% of proteins in the PDB may switch folds. Metamorphic proteins have been found to share common features such as marginal thermostability and inconsistencies in predicted secondary structures. Outstanding challenges in the field include the search for more metamorphic proteins and the design of new proteins that switch folds. Identification of novel metamorphic proteins in nature will improve therapeutic targeting of fold-switching proteins involved in human pathology and will enhance the design of protein-based therapies. Designed fold switching proteins have applications as biosensors, molecular switches, molecular machines, and self-assembling systems.
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Affiliation(s)
- Acacia F Dishman
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA; Medical Scientist Training Program, Medical College of Wisconsin, Milwaukee, WI, USA. https://twitter.com/@cacidish
| | - Brian F Volkman
- Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA.
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48
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Chakravarty D, Porter LL. AlphaFold2
fails to predict protein fold switching. Protein Sci 2022; 31:e4353. [DOI: 10.1002/pro.4353] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/05/2022] [Accepted: 05/07/2022] [Indexed: 12/15/2022]
Affiliation(s)
- Devlina Chakravarty
- National Library of Medicine, National Center for Biotechnology Information National Institutes of Health Bethesda Maryland USA
| | - Lauren L. Porter
- National Library of Medicine, National Center for Biotechnology Information National Institutes of Health Bethesda Maryland USA
- National Heart, Lung, and Blood Institute, Biochemistry and Biophysics Center National Institutes of Health Bethesda Maryland USA
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49
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Boi L. A reappraisal of the form: function problem-theory and phenomenology. Theory Biosci 2022; 141:73-103. [PMID: 35471494 DOI: 10.1007/s12064-022-00368-8] [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: 08/03/2021] [Accepted: 03/11/2022] [Indexed: 11/26/2022]
Abstract
This paper is aimed at demonstrating that some geometrical and topological transformations and operations serve not only as promoters of many specific genetic and cellular events in multicellular living organisms, but also as initiators of the organization and regulation of their functions. Thus, changes in the form and structure of macromolecular and cellular systems must be directly associated to their functions. There are specific classes of enzymes that manipulate the geometry and topology of complex DNA-protein structures, and thereby they perform many important cellular processes, including segregation of daughter chromosomes, gene regulation, and DNA repair. We argue that form has an organizing power, hence a causal action, in the sense that it enables to induce functional events during different biological processes, at the supramolecular, cellular, and organismal levels of organization. Clearly, topological forms must be matched with specific kinetic and dynamical parameters to have a functional effectiveness in living systems. This effectiveness is remarkably apparent, to give an example, in the regulation of the genome functions and in cell activity. In more general terms, we try to show that the conformational plasticity of biological systems depends on different kinds of topological manipulations performed by specific families of enzymes. In doing so, they catalyze all those spatial and dynamical changes of biological structures that are suitable for the functions to be acted by the organism.
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Affiliation(s)
- Luciano Boi
- École des Hautes Études en Sciences Sociales, Centre de Mathématiques (CAMS), 54, bd Raspail, 75006, Paris, France.
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50
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Chow WY, De Paëpe G, Hediger S. Biomolecular and Biological Applications of Solid-State NMR with Dynamic Nuclear Polarization Enhancement. Chem Rev 2022; 122:9795-9847. [PMID: 35446555 DOI: 10.1021/acs.chemrev.1c01043] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Solid-state NMR spectroscopy (ssNMR) with magic-angle spinning (MAS) enables the investigation of biological systems within their native context, such as lipid membranes, viral capsid assemblies, and cells. However, such ambitious investigations often suffer from low sensitivity due to the presence of significant amounts of other molecular species, which reduces the effective concentration of the biomolecule or interaction of interest. Certain investigations requiring the detection of very low concentration species remain unfeasible even with increasing experimental time for signal averaging. By applying dynamic nuclear polarization (DNP) to overcome the sensitivity challenge, the experimental time required can be reduced by orders of magnitude, broadening the feasible scope of applications for biological solid-state NMR. In this review, we outline strategies commonly adopted for biological applications of DNP, indicate ongoing challenges, and present a comprehensive overview of biological investigations where MAS-DNP has led to unique insights.
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Affiliation(s)
- Wing Ying Chow
- Univ. Grenoble Alpes, CEA, CNRS, Interdisciplinary Research Institute of Grenoble (IRIG), Modeling and Exploration of Materials Laboratory (MEM), 38054 Grenoble, France.,Univ. Grenoble Alpes, CEA, CNRS, Inst. Biol. Struct. IBS, 38044 Grenoble, France
| | - Gaël De Paëpe
- Univ. Grenoble Alpes, CEA, CNRS, Interdisciplinary Research Institute of Grenoble (IRIG), Modeling and Exploration of Materials Laboratory (MEM), 38054 Grenoble, France
| | - Sabine Hediger
- Univ. Grenoble Alpes, CEA, CNRS, Interdisciplinary Research Institute of Grenoble (IRIG), Modeling and Exploration of Materials Laboratory (MEM), 38054 Grenoble, France
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