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Saar KL, Scrutton RM, Bloznelyte K, Morgunov AS, Good LL, Lee AA, Teichmann SA, Knowles TPJ. Protein Condensate Atlas from predictive models of heteromolecular condensate composition. Nat Commun 2024; 15:5418. [PMID: 38987300 PMCID: PMC11237133 DOI: 10.1038/s41467-024-48496-7] [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: 06/17/2023] [Accepted: 05/02/2024] [Indexed: 07/12/2024] Open
Abstract
Biomolecular condensates help cells organise their content in space and time. Cells harbour a variety of condensate types with diverse composition and many are likely yet to be discovered. Here, we develop a methodology to predict the composition of biomolecular condensates. We first analyse available proteomics data of cellular condensates and find that the biophysical features that determine protein localisation into condensates differ from known drivers of homotypic phase separation processes, with charge mediated protein-RNA and hydrophobicity mediated protein-protein interactions playing a key role in the former process. We then develop a machine learning model that links protein sequence to its propensity to localise into heteromolecular condensates. We apply the model across the proteome and find many of the top-ranked targets outside the original training data to localise into condensates as confirmed by orthogonal immunohistochemical staining imaging. Finally, we segment the condensation-prone proteome into condensate types based on an overlap with biomolecular interaction profiles to generate a Protein Condensate Atlas. Several condensate clusters within the Atlas closely match the composition of experimentally characterised condensates or regions within them, suggesting that the Atlas can be valuable for identifying additional components within known condensate systems and discovering previously uncharacterised condensates.
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Affiliation(s)
- Kadi L Saar
- Transition Bio Ltd, Cambridge, UK.
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.
| | - Rob M Scrutton
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
- Department of Chemistry, University of Oxford, Oxford, OX1 3TA, UK
| | | | - Alexey S Morgunov
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| | - Lydia L Good
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
- Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Alpha A Lee
- Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, CB3 0HE, UK
| | - Sarah A Teichmann
- Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, CB3 0HE, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Tuomas P J Knowles
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.
- Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, CB3 0HE, UK.
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2
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Manning MC, Holcomb RE, Payne RW, Stillahn JM, Connolly BD, Katayama DS, Liu H, Matsuura JE, Murphy BM, Henry CS, Crommelin DJA. Stability of Protein Pharmaceuticals: Recent Advances. Pharm Res 2024; 41:1301-1367. [PMID: 38937372 DOI: 10.1007/s11095-024-03726-x] [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: 03/25/2024] [Accepted: 06/03/2024] [Indexed: 06/29/2024]
Abstract
There have been significant advances in the formulation and stabilization of proteins in the liquid state over the past years since our previous review. Our mechanistic understanding of protein-excipient interactions has increased, allowing one to develop formulations in a more rational fashion. The field has moved towards more complex and challenging formulations, such as high concentration formulations to allow for subcutaneous administration and co-formulation. While much of the published work has focused on mAbs, the principles appear to apply to any therapeutic protein, although mAbs clearly have some distinctive features. In this review, we first discuss chemical degradation reactions. This is followed by a section on physical instability issues. Then, more specific topics are addressed: instability induced by interactions with interfaces, predictive methods for physical stability and interplay between chemical and physical instability. The final parts are devoted to discussions how all the above impacts (co-)formulation strategies, in particular for high protein concentration solutions.'
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Affiliation(s)
- Mark Cornell Manning
- Legacy BioDesign LLC, Johnstown, CO, USA.
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA.
| | - Ryan E Holcomb
- Legacy BioDesign LLC, Johnstown, CO, USA
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA
| | - Robert W Payne
- Legacy BioDesign LLC, Johnstown, CO, USA
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA
| | - Joshua M Stillahn
- Legacy BioDesign LLC, Johnstown, CO, USA
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA
| | | | | | | | | | | | - Charles S Henry
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA
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Fuxreiter M. Context-dependent, fuzzy protein interactions: Towards sequence-based insights. Curr Opin Struct Biol 2024; 87:102834. [PMID: 38759297 DOI: 10.1016/j.sbi.2024.102834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/11/2024] [Accepted: 04/22/2024] [Indexed: 05/19/2024]
Abstract
Predicting protein interactions in the cellular environment still remains a challenge in the AlphaFold era. Protein interactions, similarly to their structures, sample a continuum from ordered to disordered states, with specific partners in many bound configurations. A multiplicity of binding modes (MBM) enables transition between these states under different cellular conditions. This review focuses on how the cellular environment affects protein interactions, highlighting the molecular mechanisms, biophysical origin, and sequence-based principles of context-dependent, fuzzy interactions. It summarises experimental and computational approaches to address the challenge of interaction heterogeneity and its contribution to a wide range of biological functions. These insights will help in understanding complex cellular processes, involving conversions between protein assembly states, such as from liquid-like droplet state to the amyloid state.
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Affiliation(s)
- Monika Fuxreiter
- Department of Biomedical Sciences, University of Padova, Padova, Italy; Department of Physics and Astronomy, University of Padova, Padova, Italy.
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4
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Hou S, Hu J, Yu Z, Li D, Liu C, Zhang Y. Machine learning predictor PSPire screens for phase-separating proteins lacking intrinsically disordered regions. Nat Commun 2024; 15:2147. [PMID: 38459060 PMCID: PMC10923898 DOI: 10.1038/s41467-024-46445-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 02/28/2024] [Indexed: 03/10/2024] Open
Abstract
The burgeoning comprehension of protein phase separation (PS) has ushered in a wealth of bioinformatics tools for the prediction of phase-separating proteins (PSPs). These tools often skew towards PSPs with a high content of intrinsically disordered regions (IDRs), thus frequently undervaluing potential PSPs without IDRs. Nonetheless, PS is not only steered by IDRs but also by the structured modular domains and interactions that aren't necessarily reflected in amino acid sequences. In this work, we introduce PSPire, a machine learning predictor that incorporates both residue-level and structure-level features for the precise prediction of PSPs. Compared to current PSP predictors, PSPire shows a notable improvement in identifying PSPs without IDRs, which underscores the crucial role of non-IDR, structure-based characteristics in multivalent interactions throughout the PS process. Additionally, our biological validation experiments substantiate the predictive capacity of PSPire, with 9 out of 11 chosen candidate PSPs confirmed to form condensates within cells.
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Affiliation(s)
- Shuang Hou
- State Key Laboratory of Cardiology and Medical Innovation Center, Institute for Regenerative Medicine, Department of Neurosurgery, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jiaojiao Hu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032, China
| | - Zhaowei Yu
- State Key Laboratory of Cardiology and Medical Innovation Center, Institute for Regenerative Medicine, Department of Neurosurgery, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Dan Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, 200240, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Cong Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032, China.
| | - Yong Zhang
- State Key Laboratory of Cardiology and Medical Innovation Center, Institute for Regenerative Medicine, Department of Neurosurgery, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
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Shang B, Li C, Zhang X. How intrinsically disordered proteins order plant gene silencing. Trends Genet 2024; 40:260-275. [PMID: 38296708 PMCID: PMC10932933 DOI: 10.1016/j.tig.2023.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 12/25/2023] [Accepted: 12/29/2023] [Indexed: 02/02/2024]
Abstract
Intrinsically disordered proteins (IDPs) and proteins with intrinsically disordered regions (IDRs) possess low sequence complexity of amino acids and display non-globular tertiary structures. They can act as scaffolds, form regulatory hubs, or trigger biomolecular condensation to control diverse aspects of biology. Emerging evidence has recently implicated critical roles of IDPs and IDR-contained proteins in nuclear transcription and cytoplasmic post-transcriptional processes, among other molecular functions. We here summarize the concepts and organizing principles of IDPs. We then illustrate recent progress in understanding the roles of key IDPs in machineries that regulate transcriptional and post-transcriptional gene silencing (PTGS) in plants, aiming at highlighting new modes of action of IDPs in controlling biological processes.
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Affiliation(s)
- Baoshuan Shang
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization (Henan University), State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA
| | - Changhao Li
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA
| | - Xiuren Zhang
- Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843, USA; Department of Biology, Texas A&M University, College Station, TX 77843, USA.
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Rinauro DJ, Chiti F, Vendruscolo M, Limbocker R. Misfolded protein oligomers: mechanisms of formation, cytotoxic effects, and pharmacological approaches against protein misfolding diseases. Mol Neurodegener 2024; 19:20. [PMID: 38378578 PMCID: PMC10877934 DOI: 10.1186/s13024-023-00651-2] [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: 03/02/2023] [Accepted: 08/17/2023] [Indexed: 02/22/2024] Open
Abstract
The conversion of native peptides and proteins into amyloid aggregates is a hallmark of over 50 human disorders, including Alzheimer's and Parkinson's diseases. Increasing evidence implicates misfolded protein oligomers produced during the amyloid formation process as the primary cytotoxic agents in many of these devastating conditions. In this review, we analyze the processes by which oligomers are formed, their structures, physicochemical properties, population dynamics, and the mechanisms of their cytotoxicity. We then focus on drug discovery strategies that target the formation of oligomers and their ability to disrupt cell physiology and trigger degenerative processes.
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Affiliation(s)
- Dillon J Rinauro
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
| | - Fabrizio Chiti
- Section of Biochemistry, Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50134, Florence, Italy
| | - Michele Vendruscolo
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.
| | - Ryan Limbocker
- Department of Chemistry and Life Science, United States Military Academy, West Point, NY, 10996, USA.
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Wake N, Weng SL, Zheng T, Wang SH, Kirilenko V, Mittal J, Fawzi NL. Expanding the molecular grammar of polar residues and arginine in FUS prion-like domain phase separation and aggregation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.15.580391. [PMID: 38405719 PMCID: PMC10888811 DOI: 10.1101/2024.02.15.580391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
A molecular grammar governing low-complexity prion-like domains phase separation (PS) has been proposed based on mutagenesis experiments that identified tyrosine and arginine as primary drivers of phase separation via aromatic-aromatic and aromatic-arginine interactions. Here we show that additional residues make direct favorable contacts that contribute to phase separation, highlighting the need to account for these contributions in PS theories and models. We find that tyrosine and arginine make important contacts beyond only tyrosine-tyrosine and tyrosine-arginine, including arginine-arginine contacts. Among polar residues, glutamine in particular contributes to phase separation with sequence/position-specificity, making contacts with both tyrosine and arginine as well as other residues, both before phase separation and in condensed phases. For glycine, its flexibility, not its small solvation volume, favors phase separation by allowing favorable contacts between other residues and inhibits the liquid-to-solid (LST) transition. Polar residue types also make sequence-specific contributions to aggregation that go beyond simple rules, which for serine positions is linked to formation of an amyloid-core structure by the FUS low-complexity domain. Hence, here we propose a revised molecular grammar expanding the role of arginine and polar residues in prion-like domain protein phase separation and aggregation.
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Affiliation(s)
- Noah Wake
- Therapeutic Sciences Graduate Program, Brown University, Providence, RI 02912
| | - Shuo-Lin Weng
- Department of Chemistry, Texas A&M University, College Station, TX 77843
| | - Tongyin Zheng
- Department of Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, RI 02912
| | - Szu-Huan Wang
- Department of Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, RI 02912
| | - Valentin Kirilenko
- Department of Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, RI 02912
| | - Jeetain Mittal
- Department of Chemistry, Texas A&M University, College Station, TX 77843
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX 77843
- Interdisciplinary Graduate Program in Genetics and Genomics, Texas A&M University, College Station, TX 77843
| | - Nicolas L Fawzi
- Department of Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, RI 02912
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