1
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Thomasen FE, Skaalum T, Kumar A, Srinivasan S, Vanni S, Lindorff-Larsen K. Rescaling protein-protein interactions improves Martini 3 for flexible proteins in solution. Nat Commun 2024; 15:6645. [PMID: 39103332 DOI: 10.1038/s41467-024-50647-9] [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: 05/29/2023] [Accepted: 07/15/2024] [Indexed: 08/07/2024] Open
Abstract
Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is difficult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the 'symmetry' between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.
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Affiliation(s)
- F Emil Thomasen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark.
| | - Tórur Skaalum
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark
| | - Ashutosh Kumar
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Swiss National Center for Competence in Research (NCCR) Bio-inspired Materials, University of Fribourg, Chemin des Verdiers 4, CH-1700, Fribourg, Switzerland
| | | | - Stefano Vanni
- Department of Biology, University of Fribourg, Fribourg, Switzerland.
- Swiss National Center for Competence in Research (NCCR) Bio-inspired Materials, University of Fribourg, Chemin des Verdiers 4, CH-1700, Fribourg, Switzerland.
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200, Copenhagen N, Denmark.
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2
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Hutchins CM, Gorfe AA. From disorder comes function: Regulation of small GTPase function by intrinsically disordered lipidated membrane anchor. Curr Opin Struct Biol 2024; 87:102869. [PMID: 38943706 PMCID: PMC11283958 DOI: 10.1016/j.sbi.2024.102869] [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: 04/15/2024] [Revised: 05/23/2024] [Accepted: 06/04/2024] [Indexed: 07/01/2024]
Abstract
The intrinsically disordered, lipid-modified membrane anchor of small GTPases is emerging as a critical modulator of function through its ability to sort lipids in a conformation-dependent manner. We reviewed recent computational and experimental studies that have begun to shed light on the sequence-ensemble-function relationship in this unique class of lipidated intrinsically disordered regions (LIDRs).
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Affiliation(s)
- Chase M Hutchins
- Department of Integrative Biology and Pharmacology, McGovern Medical School, University of Texas Health Science Center at Houston, 6431 Fannin St., Houston, TX 77030, USA; Biochemistry and Cell Biology Program & Therapeutics and Pharmacology Program, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, 6431 Fannin St., Houston, TX 77030, USA. https://twitter.com/chasedsims
| | - Alemayehu A Gorfe
- Department of Integrative Biology and Pharmacology, McGovern Medical School, University of Texas Health Science Center at Houston, 6431 Fannin St., Houston, TX 77030, USA; Biochemistry and Cell Biology Program & Therapeutics and Pharmacology Program, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, 6431 Fannin St., Houston, TX 77030, USA.
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3
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Brown CM, Marrink SJ. Modeling membranes in situ. Curr Opin Struct Biol 2024; 87:102837. [PMID: 38744147 DOI: 10.1016/j.sbi.2024.102837] [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: 12/22/2023] [Revised: 03/26/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024]
Abstract
Molecular dynamics simulations of cellular membranes have come a long way-from simple model lipid bilayers to multicomponent systems capturing the crowded and complex nature of real cell membranes. In this opinionated minireview, we discuss the current challenge to simulate the dynamics of membranes in their native environment, in situ, with the prospect of reaching the level of whole cells and cell organelles using an integrative modeling framework.
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Affiliation(s)
- Chelsea M Brown
- Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, the Netherlands. https://twitter.com/chelseabrowncg
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, the Netherlands. s.j.marrinkrug.nl
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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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Holehouse AS, Kragelund BB. The molecular basis for cellular function of intrinsically disordered protein regions. Nat Rev Mol Cell Biol 2024; 25:187-211. [PMID: 37957331 DOI: 10.1038/s41580-023-00673-0] [Citation(s) in RCA: 48] [Impact Index Per Article: 48.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/26/2023] [Indexed: 11/15/2023]
Abstract
Intrinsically disordered protein regions exist in a collection of dynamic interconverting conformations that lack a stable 3D structure. These regions are structurally heterogeneous, ubiquitous and found across all kingdoms of life. Despite the absence of a defined 3D structure, disordered regions are essential for cellular processes ranging from transcriptional control and cell signalling to subcellular organization. Through their conformational malleability and adaptability, disordered regions extend the repertoire of macromolecular interactions and are readily tunable by their structural and chemical context, making them ideal responders to regulatory cues. Recent work has led to major advances in understanding the link between protein sequence and conformational behaviour in disordered regions, yet the link between sequence and molecular function is less well defined. Here we consider the biochemical and biophysical foundations that underlie how and why disordered regions can engage in productive cellular functions, provide examples of emerging concepts and discuss how protein disorder contributes to intracellular information processing and regulation of cellular function.
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Affiliation(s)
- Alex S Holehouse
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St Louis, MO, USA.
- Center for Biomolecular Condensates, Washington University in St Louis, St Louis, MO, USA.
| | - Birthe B Kragelund
- REPIN, Structural Biology and NMR Laboratory, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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6
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Brooks CL, MacKerell AD, Post CB, Nilsson L. Biomolecular dynamics in the 21st century. Biochim Biophys Acta Gen Subj 2024; 1868:130534. [PMID: 38065235 PMCID: PMC10842176 DOI: 10.1016/j.bbagen.2023.130534] [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: 09/26/2023] [Revised: 11/28/2023] [Accepted: 11/29/2023] [Indexed: 01/03/2024]
Abstract
The relevance of motions in biological macromolecules has been clear since the early structural analyses of proteins by X-ray crystallography. Computer simulations have been applied to provide a deeper understanding of the dynamics of biological macromolecules since 1976, and are now a standard tool in many labs working on the structure and function of biomolecules. In this mini-review we highlight some areas of current interest and active development for simulations, in particular all-atom molecular dynamics simulations.
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Affiliation(s)
- Charles L Brooks
- University of Michigan, Department of Chemistry, Ann Arbor, MI 48109, USA.
| | | | - Carol B Post
- Purdue University, Department of Medicinal Chemistry and Molecular Pharmacology, West Lafayette, IN 47907-2091, USA.
| | - Lennart Nilsson
- Karolinska Institutet, Department of Biosciences and Nutrition, SE-14183 Huddinge, Sweden.
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7
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Tesei G, Trolle AI, Jonsson N, Betz J, Knudsen FE, Pesce F, Johansson KE, Lindorff-Larsen K. Conformational ensembles of the human intrinsically disordered proteome. Nature 2024; 626:897-904. [PMID: 38297118 DOI: 10.1038/s41586-023-07004-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 12/19/2023] [Indexed: 02/02/2024]
Abstract
Intrinsically disordered proteins and regions (collectively, IDRs) are pervasive across proteomes in all kingdoms of life, help to shape biological functions and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures and defy conventional sequence-structure-function relationships1. Developments in protein science have made it possible to predict the three-dimensional structures of folded proteins at the proteome scale2. By contrast, there is a lack of knowledge about the conformational properties of IDRs, partly because the sequences of disordered proteins are poorly conserved and also because only a few of these proteins have been characterized experimentally. The inability to predict structural properties of IDRs across the proteome has limited our understanding of the functional roles of IDRs and how evolution shapes them. As a supplement to previous structural studies of individual IDRs3, we developed an efficient molecular model to generate conformational ensembles of IDRs and thereby to predict their conformational properties from sequences4,5. Here we use this model to simulate nearly all of the IDRs in the human proteome. Examining conformational ensembles of 28,058 IDRs, we show how chain compaction is correlated with cellular function and localization. We provide insights into how sequence features relate to chain compaction and, using a machine-learning model trained on our simulation data, show the conservation of conformational properties across orthologues. Our results recapitulate observations from previous studies of individual protein systems and exemplify how to link-at the proteome scale-conformational ensembles with cellular function and localization, amino acid sequence, evolutionary conservation and disease variants. Our freely available database of conformational properties will encourage further experimental investigation and enable the generation of hypotheses about the biological roles and evolution of IDRs.
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Affiliation(s)
- Giulio Tesei
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Anna Ida Trolle
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Nicolas Jonsson
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Johannes Betz
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Frederik E Knudsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Francesco Pesce
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kristoffer E Johansson
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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8
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Ghosh C, Nagpal S, Muñoz V. Molecular simulations integrated with experiments for probing the interaction dynamics and binding mechanisms of intrinsically disordered proteins. Curr Opin Struct Biol 2024; 84:102756. [PMID: 38118365 PMCID: PMC11242915 DOI: 10.1016/j.sbi.2023.102756] [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: 10/08/2023] [Revised: 11/28/2023] [Accepted: 11/29/2023] [Indexed: 12/22/2023]
Abstract
Intrinsically disordered proteins (IDPs) exploit their plasticity to deploy a rich panoply of soft interactions and binding phenomena. Advances in tailoring molecular simulations for IDPs combined with experimental cross-validation offer an atomistic view of the mechanisms that control IDP binding, function, and dysfunction. The emerging theme is that unbound IDPs autonomously form transient local structures and self-interactions that determine their binding behavior. Recent results have shed light on whether and how IDPs fold, stay disordered or drive condensation upon binding; how they achieve binding specificity and select among competing partners. The disorder-binding paradigm is now being proactively used by researchers to target IDPs for rational drug design and engineer molecular responsive elements for biosensing applications.
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Affiliation(s)
- Catherine Ghosh
- NSF-CREST Center for Cellular and Biomolecular Machines (CCBM), University of California at Merced, Merced, 95343 CA, USA; Department of Bioengineering, University of California at Merced, Merced, 95343 CA, USA. https://twitter.com/cat_ghosh
| | - Suhani Nagpal
- NSF-CREST Center for Cellular and Biomolecular Machines (CCBM), University of California at Merced, Merced, 95343 CA, USA; Department of Bioengineering, University of California at Merced, Merced, 95343 CA, USA; OpenEye, Cadence Molecular Sciences, Boston, 02114 MA, USA
| | - Victor Muñoz
- NSF-CREST Center for Cellular and Biomolecular Machines (CCBM), University of California at Merced, Merced, 95343 CA, USA; Department of Bioengineering, University of California at Merced, Merced, 95343 CA, USA.
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9
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Heller G, Shukla VK, Figueiredo AM, Hansen DF. Picosecond Dynamics of a Small Molecule in Its Bound State with an Intrinsically Disordered Protein. J Am Chem Soc 2024; 146:2319-2324. [PMID: 38251829 PMCID: PMC10835725 DOI: 10.1021/jacs.3c11614] [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: 10/18/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/23/2024]
Abstract
Intrinsically disordered proteins (IDPs) are highly dynamic biomolecules that rapidly interconvert among many structural conformations. These dynamic biomolecules are involved in cancers, neurodegeneration, cardiovascular illnesses, and viral infections. Despite their enormous therapeutic potential, IDPs have generally been considered undruggable because of their lack of classical long-lived binding pockets for small molecules. Currently, only a few instances are known where small molecules have been observed to interact with IDPs, and this situation is further exacerbated by the limited sensitivity of experimental techniques to detect such binding events. Here, using experimental nuclear magnetic resonance (NMR) spectroscopy 19F transverse spin-relaxation measurements, we discovered that a small molecule, 5-fluoroindole, interacts with the disordered domains of non-structural protein 5A from hepatitis C virus with a Kd of 260 ± 110 μM. Our analysis also allowed us to determine the rotational correlation times (τc) for the free and bound states of 5-fluoroindole. In the free state, we observed a rotational correlation time of 27.0 ± 1.3 ps, whereas in the bound state, τc only increased to 46 ± 10 ps. Our findings imply that it is possible for small molecules to engage with IDPs in exceptionally dynamic ways, in sharp contrast to the rigid binding modes typically exhibited when small molecules bind to well-defined binding pockets within structured proteins.
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Affiliation(s)
- Gabriella
T. Heller
- Department of Structural
and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, U.K.
| | - Vaibhav Kumar Shukla
- Department of Structural
and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, U.K.
| | - Angelo Miguel Figueiredo
- Department of Structural
and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, U.K.
| | - D. Flemming Hansen
- Department of Structural
and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, U.K.
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10
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Versini R, Sritharan S, Aykac Fas B, Tubiana T, Aimeur SZ, Henri J, Erard M, Nüsse O, Andreani J, Baaden M, Fuchs P, Galochkina T, Chatzigoulas A, Cournia Z, Santuz H, Sacquin-Mora S, Taly A. A Perspective on the Prospective Use of AI in Protein Structure Prediction. J Chem Inf Model 2024; 64:26-41. [PMID: 38124369 DOI: 10.1021/acs.jcim.3c01361] [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: 12/23/2023]
Abstract
AlphaFold2 (AF2) and RoseTTaFold (RF) have revolutionized structural biology, serving as highly reliable and effective methods for predicting protein structures. This article explores their impact and limitations, focusing on their integration into experimental pipelines and their application in diverse protein classes, including membrane proteins, intrinsically disordered proteins (IDPs), and oligomers. In experimental pipelines, AF2 models help X-ray crystallography in resolving the phase problem, while complementarity with mass spectrometry and NMR data enhances structure determination and protein flexibility prediction. Predicting the structure of membrane proteins remains challenging for both AF2 and RF due to difficulties in capturing conformational ensembles and interactions with the membrane. Improvements in incorporating membrane-specific features and predicting the structural effect of mutations are crucial. For intrinsically disordered proteins, AF2's confidence score (pLDDT) serves as a competitive disorder predictor, but integrative approaches including molecular dynamics (MD) simulations or hydrophobic cluster analyses are advocated for accurate dynamics representation. AF2 and RF show promising results for oligomeric models, outperforming traditional docking methods, with AlphaFold-Multimer showing improved performance. However, some caveats remain in particular for membrane proteins. Real-life examples demonstrate AF2's predictive capabilities in unknown protein structures, but models should be evaluated for their agreement with experimental data. Furthermore, AF2 models can be used complementarily with MD simulations. In this Perspective, we propose a "wish list" for improving deep-learning-based protein folding prediction models, including using experimental data as constraints and modifying models with binding partners or post-translational modifications. Additionally, a meta-tool for ranking and suggesting composite models is suggested, driving future advancements in this rapidly evolving field.
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Affiliation(s)
- Raphaelle Versini
- Laboratoire de Biochimie Théorique, CNRS (UPR9080), Université Paris Cité, F-75005 Paris, France
| | - Sujith Sritharan
- Laboratoire de Biochimie Théorique, CNRS (UPR9080), Université Paris Cité, F-75005 Paris, France
| | - Burcu Aykac Fas
- Laboratoire de Biochimie Théorique, CNRS (UPR9080), Université Paris Cité, F-75005 Paris, France
| | - Thibault Tubiana
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France
| | - Sana Zineb Aimeur
- Université Paris-Saclay, CNRS, Institut de Chimie Physique, 91405 Orsay, France
| | - Julien Henri
- Sorbonne Université, CNRS, Laboratoire de Biologie, Computationnelle et Quantitative UMR 7238, Institut de Biologie Paris-Seine, 4 Place Jussieu, F-75005 Paris, France
| | - Marie Erard
- Université Paris-Saclay, CNRS, Institut de Chimie Physique, 91405 Orsay, France
| | - Oliver Nüsse
- Université Paris-Saclay, CNRS, Institut de Chimie Physique, 91405 Orsay, France
| | - Jessica Andreani
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91198 Gif-sur-Yvette, France
| | - Marc Baaden
- Laboratoire de Biochimie Théorique, CNRS (UPR9080), Université Paris Cité, F-75005 Paris, France
| | - Patrick Fuchs
- Sorbonne Université, École Normale Supérieure, PSL University, CNRS, Laboratoire des Biomolécules, LBM, 75005 Paris, France
- Université de Paris, UFR Sciences du Vivant, 75013 Paris, France
| | - Tatiana Galochkina
- Université Paris Cité and Université des Antilles and Université de la Réunion, INSERM, BIGR, F-75014 Paris, France
| | - Alexios Chatzigoulas
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
- Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, 15784 Athens, Greece
| | - Zoe Cournia
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
- Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, 15784 Athens, Greece
| | - Hubert Santuz
- Laboratoire de Biochimie Théorique, CNRS (UPR9080), Université Paris Cité, F-75005 Paris, France
| | - Sophie Sacquin-Mora
- Laboratoire de Biochimie Théorique, CNRS (UPR9080), Université Paris Cité, F-75005 Paris, France
| | - Antoine Taly
- Laboratoire de Biochimie Théorique, CNRS (UPR9080), Université Paris Cité, F-75005 Paris, France
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11
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Patel KN, Chavda D, Manna M. Molecular Docking of Intrinsically Disordered Proteins: Challenges and Strategies. Methods Mol Biol 2024; 2780:165-201. [PMID: 38987470 DOI: 10.1007/978-1-0716-3985-6_11] [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] [Indexed: 07/12/2024]
Abstract
Intrinsically disordered proteins (IDPs) are a novel class of proteins that have established a significant importance and attention within a very short period of time. These proteins are essentially characterized by their inherent structural disorder, encoded mainly by their amino acid sequences. The profound abundance of IDPs and intrinsically disordered regions (IDRs) in the biological world delineates their deep-rooted functionality. IDPs and IDRs convey such extensive functionality through their unique dynamic nature, which enables them to carry out huge number of multifaceted biomolecular interactions and make them "interaction hub" of the cellular systems. Additionally, with such widespread functions, their misfunctioning is also intimately associated with multiple diseases. Thus, understanding the dynamic heterogeneity of various IDPs along with their interactions with respective binding partners is an important field with immense potentials in biomolecular research. In this context, molecular docking-based computational approaches have proven to be remarkable in case of ordered proteins. Molecular docking methods essentially model the biomolecular interactions in both structural and energetic terms and use this information to characterize the putative interactions between the two participant molecules. However, direct applications of the conventional docking methods to study IDPs are largely limited by their structural heterogeneity and demands for unique IDP-centric strategies. Thus, in this chapter, we have presented an overview of current methodologies for successful docking operations involving IDPs and IDRs. These specialized methods majorly include the ensemble-based and fragment-based approaches with their own benefits and limitations. More recently, artificial intelligence and machine learning-assisted approaches are also used to significantly reduce the complexity and computational burden associated with various docking applications. Thus, this chapter aims to provide a comprehensive summary of major challenges and recent advancements of molecular docking approaches in the IDP field for their better utilization and greater applicability.Asp (D).
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Affiliation(s)
- Keyur N Patel
- Applied Phycology and Biotechnology Division, CSIR Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Dhruvil Chavda
- Applied Phycology and Biotechnology Division, CSIR Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Moutusi Manna
- Applied Phycology and Biotechnology Division, CSIR Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India.
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India.
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12
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Sementa D, Dave D, Fisher RS, Wang T, Elbaum-Garfinkle S, Ulijn RV. Sequence-Tunable Phase Behavior and Intrinsic Fluorescence in Dynamically Interacting Peptides. Angew Chem Int Ed Engl 2023; 62:e202311479. [PMID: 37934145 DOI: 10.1002/anie.202311479] [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: 08/09/2023] [Revised: 10/31/2023] [Accepted: 11/06/2023] [Indexed: 11/08/2023]
Abstract
A conceptual framework towards understanding biological condensed phases is emerging, derived from biological, biomimetic, and synthetic sequences. However, de novo peptide condensate design remains a challenge due to an incomplete understanding of the structural and interactive complexity. We designed peptide modules based on a simple repeat motif composed of tripeptide spacers (GSG, SGS, GLG) interspersed with adhesive amino acids (R/H and Y). We show, using sequence editing and a combination of computation and experiment, that n→π* interactions in GLG backbones are a dominant factor in providing sufficient backbone structure, which in turn regulates the water interface, collectively promoting liquid droplet formation. Moreover, these R(GLG)Y and H(GLG)Y condensates unexpectedly display sequence-dependent emission that is a consequence of their non-covalent network interactions, and readily observable by confocal microscopy.
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Affiliation(s)
- Deborah Sementa
- Advanced Science Research Center (ASRC) at the Graduate Center, City University of New York (CUNY), 85 St Nicholas Terrace, New York, NY 10031, USA
| | - Dhwanit Dave
- Advanced Science Research Center (ASRC) at the Graduate Center, City University of New York (CUNY), 85 St Nicholas Terrace, New York, NY 10031, USA
- Ph.D. Programs in Biochemistry and Chemistry, The Graduate Center of the City University of New York, 365 Fifth Avenue, New York, NY 10016, USA
- Department of Chemistry, Hunter College, City University of New York (CUNY), 695 Park Avenue, New York, NY 10065, USA
| | - Rachel S Fisher
- Advanced Science Research Center (ASRC) at the Graduate Center, City University of New York (CUNY), 85 St Nicholas Terrace, New York, NY 10031, USA
| | - Tong Wang
- Advanced Science Research Center (ASRC) at the Graduate Center, City University of New York (CUNY), 85 St Nicholas Terrace, New York, NY 10031, USA
| | - Shana Elbaum-Garfinkle
- Advanced Science Research Center (ASRC) at the Graduate Center, City University of New York (CUNY), 85 St Nicholas Terrace, New York, NY 10031, USA
| | - Rein V Ulijn
- Advanced Science Research Center (ASRC) at the Graduate Center, City University of New York (CUNY), 85 St Nicholas Terrace, New York, NY 10031, USA
- Ph.D. Programs in Biochemistry and Chemistry, The Graduate Center of the City University of New York, 365 Fifth Avenue, New York, NY 10016, USA
- Department of Chemistry, Hunter College, City University of New York (CUNY), 695 Park Avenue, New York, NY 10065, USA
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13
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Nussinov R, Liu Y, Zhang W, Jang H. Cell phenotypes can be predicted from propensities of protein conformations. Curr Opin Struct Biol 2023; 83:102722. [PMID: 37871498 PMCID: PMC10841533 DOI: 10.1016/j.sbi.2023.102722] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 10/25/2023]
Abstract
Proteins exist as dynamic conformational ensembles. Here we suggest that the propensities of the conformations can be predictors of cell function. The conformational states that the molecules preferentially visit can be viewed as phenotypic determinants, and their mutations work by altering the relative propensities, thus the cell phenotype. Our examples include (i) inactive state variants harboring cancer driver mutations that present active state-like conformational features, as in K-Ras4BG12V compared to other K-Ras4BG12X mutations; (ii) mutants of the same protein presenting vastly different phenotypic and clinical profiles: cancer and neurodevelopmental disorders; (iii) alterations in the occupancies of the conformational (sub)states influencing enzyme reactivity. Thus, protein conformational propensities can determine cell fate. They can also suggest the allosteric drugs efficiency.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA; Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel; Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA.
| | - Yonglan Liu
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
| | - Wengang Zhang
- Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA; Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
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14
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Amith W, Dutagaci B. Complex Conformational Space of the RNA Polymerase II C-Terminal Domain upon Phosphorylation. J Phys Chem B 2023; 127:9223-9235. [PMID: 37870995 PMCID: PMC10626582 DOI: 10.1021/acs.jpcb.3c02655] [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: 04/21/2023] [Revised: 10/03/2023] [Indexed: 10/25/2023]
Abstract
Intrinsically disordered proteins (IDPs) have been closely studied during the past decade due to their importance in many biological processes. The disordered nature of this group of proteins makes it difficult to observe its full span of the conformational space using either experimental or computational studies. In this article, we explored the conformational space of the C-terminal domain (CTD) of RNA polymerase II (Pol II), which is also an intrinsically disordered low complexity domain, using enhanced sampling methods. We provided a detailed conformational analysis of model systems of CTD with different lengths; first with the last 44 residues of the human CTD sequence and finally the CTD model with 2-heptapeptide repeating units. We then investigated the effects of phosphorylation on CTD conformations by performing simulations at different phosphorylated states. We obtained broad conformational spaces in nonphosphorylated CTD models, and phosphorylation has complex effects on the conformations of the CTD. These complex effects depend on the length of the CTD, spacing between the multiple phosphorylation sites, ion coordination, and interactions with the nearby residues.
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Affiliation(s)
- Weththasinghage
D. Amith
- Department of Molecular and
Cell Biology, University of California,
Merced, Merced, California 95343, United States
| | - Bercem Dutagaci
- Department of Molecular and
Cell Biology, University of California,
Merced, Merced, California 95343, United States
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15
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Forsberg Z, Stepnov AA, Tesei G, Wang Y, Buchinger E, Kristiansen SK, Aachmann FL, Arleth L, Eijsink VGH, Lindorff-Larsen K, Courtade G. The effect of linker conformation on performance and stability of a two-domain lytic polysaccharide monooxygenase. J Biol Chem 2023; 299:105262. [PMID: 37734553 PMCID: PMC10598543 DOI: 10.1016/j.jbc.2023.105262] [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: 06/23/2023] [Revised: 09/05/2023] [Accepted: 09/14/2023] [Indexed: 09/23/2023] Open
Abstract
A considerable number of lytic polysaccharide monooxygenases (LPMOs) and other carbohydrate-active enzymes are modular, with catalytic domains being tethered to additional domains, such as carbohydrate-binding modules, by flexible linkers. While such linkers may affect the structure, function, and stability of the enzyme, their roles remain largely enigmatic, as do the reasons for natural variation in length and sequence. Here, we have explored linker functionality using the two-domain cellulose-active ScLPMO10C from Streptomyces coelicolor as a model system. In addition to investigating the WT enzyme, we engineered three linker variants to address the impact of both length and sequence and characterized these using small-angle X-ray scattering, NMR, molecular dynamics simulations, and functional assays. The resulting data revealed that, in the case of ScLPMO10C, linker length is the main determinant of linker conformation and enzyme performance. Both the WT and a serine-rich variant, which have the same linker length, demonstrated better performance compared with those with either a shorter linker or a longer linker. A highlight of our findings was the substantial thermostability observed in the serine-rich variant. Importantly, the linker affects thermal unfolding behavior and enzyme stability. In particular, unfolding studies show that the two domains unfold independently when mixed, whereas the full-length enzyme shows one cooperative unfolding transition, meaning that the impact of linkers in biomass-processing enzymes is more complex than mere structural tethering.
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Affiliation(s)
- Zarah Forsberg
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Ås, Norway.
| | - Anton A Stepnov
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Ås, Norway
| | - Giulio Tesei
- Structural Biology and NMR Laboratory, Department of Biology, Linderstrøm-Lang Centre for Protein Science, University of Copenhagen, Copenhagen, Denmark
| | - Yong Wang
- Structural Biology and NMR Laboratory, Department of Biology, Linderstrøm-Lang Centre for Protein Science, University of Copenhagen, Copenhagen, Denmark; College of Life Sciences, Zhejiang University, Hangzhou, China
| | - Edith Buchinger
- Vectron Biosolutions AS, Trondheim, Norway; Department of Biotechnology and Food Science, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Sandra K Kristiansen
- Department of Biotechnology and Food Science, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Finn L Aachmann
- Department of Biotechnology and Food Science, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Lise Arleth
- X-ray and Neutron Science, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
| | - Vincent G H Eijsink
- Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Ås, Norway
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, Department of Biology, Linderstrøm-Lang Centre for Protein Science, University of Copenhagen, Copenhagen, Denmark
| | - Gaston Courtade
- Department of Biotechnology and Food Science, NTNU Norwegian University of Science and Technology, Trondheim, Norway.
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16
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Pesce F, Bremer A, Tesei G, Hopkins JB, Grace CR, Mittag T, Lindorff-Larsen K. Design of intrinsically disordered protein variants with diverse structural properties. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.22.563461. [PMID: 37961110 PMCID: PMC10634714 DOI: 10.1101/2023.10.22.563461] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Intrinsically disordered proteins (IDPs) perform a wide range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Designing IDPs with specific structural or functional properties has, however, been difficult, in part because determining accurate conformational ensembles of IDPs generally requires a combination of computational modelling and experiments. Motivated by recent advancements in efficient physics-based models for simulations of IDPs, we have developed a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs with different levels of compaction and that vary more than 100 fold in their propensity to undergo phase separation, even while keeping a fixed amino acid composition. We experimentally tested designs of variants of the low-complexity domain of hnRNPA1 and find high accuracy in our computational predictions, both in terms of single-chain compaction and propensity to undergo phase separation. We analyze the sequence features that determine changes in compaction and propensity to phase separate and find an overall good agreement with previous findings for naturally occurring sequences. Our general, physics-based method enables the design of disordered sequences with specified conformational properties. Our algorithm thus expands the toolbox for protein design to include also the most flexible proteins and will enable the design of proteins whose functions exploit the many properties afforded by protein disorder.
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Affiliation(s)
- Francesco Pesce
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Anne Bremer
- Department of Structural Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Giulio Tesei
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Jesse B. Hopkins
- BioCAT, Department of Physics, Illinois Institute of Technology, Chicago, IL, USA
| | - Christy R. Grace
- Department of Structural Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Tanja Mittag
- Department of Structural Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory, The Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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17
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Schneider T, Sawade K, Berner F, Peter C, Kovermann M. Specifying conformational heterogeneity of multi-domain proteins at atomic resolution. Structure 2023; 31:1259-1274.e10. [PMID: 37557171 DOI: 10.1016/j.str.2023.07.008] [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: 03/03/2023] [Revised: 06/02/2023] [Accepted: 07/14/2023] [Indexed: 08/11/2023]
Abstract
The conformational landscape of multi-domain proteins is inherently linked to their specific functions. This also holds for polyubiquitin chains that are assembled by two or more ubiquitin domains connected by a flexible linker thus showing a large interdomain mobility. However, molecular recognition and signal transduction are associated with particular conformational substates that are populated in solution. Here, we apply high-resolution NMR spectroscopy in combination with dual-scale MD simulations to explore the conformational space of K6-, K29-, and K33-linked diubiquitin molecules. The conformational ensembles are evaluated utilizing a paramagnetic cosolute reporting on solvent exposure plus a set of complementary NMR parameters. This approach unravels a conformational heterogeneity of diubiquitins and explains the diversity of structural models that have been determined for K6-, K29-, and K33-linked diubiquitins in free and ligand-bound states so far. We propose a general application of the approach developed here to demystify multi-domain proteins occurring in nature.
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Affiliation(s)
- Tobias Schneider
- Department of Chemistry, University of Konstanz, 78457 Konstanz, Germany; Konstanz Research School Chemical Biology, University of Konstanz, 78457 Konstanz, Germany
| | - Kevin Sawade
- Department of Chemistry, University of Konstanz, 78457 Konstanz, Germany; Graduate School Chemistry, University of Konstanz, 78457 Konstanz, Germany
| | - Frederic Berner
- Department of Chemistry, University of Konstanz, 78457 Konstanz, Germany; Konstanz Research School Chemical Biology, University of Konstanz, 78457 Konstanz, Germany
| | - Christine Peter
- Department of Chemistry, University of Konstanz, 78457 Konstanz, Germany; Konstanz Research School Chemical Biology, University of Konstanz, 78457 Konstanz, Germany
| | - Michael Kovermann
- Department of Chemistry, University of Konstanz, 78457 Konstanz, Germany; Konstanz Research School Chemical Biology, University of Konstanz, 78457 Konstanz, Germany.
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18
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Abdollahi H, Prestegard JH, Valafar H. Computational modeling multiple conformational states of proteins with residual dipolar coupling data. Curr Opin Struct Biol 2023; 82:102655. [PMID: 37454402 DOI: 10.1016/j.sbi.2023.102655] [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: 03/21/2023] [Revised: 06/06/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023]
Abstract
Solution nuclear magnetic resonance spectroscopy provides unique opportunities to study the structure and dynamics of biomolecules in aqueous environments. While spin relaxation methods are well recognized for their ability to probe timescales of motion, residual dipolar couplings (RDCs) provide access to amplitudes and directions of motion, characteristics that are important to the function of these molecules. Although observed in the 1960s, the acquisition and computational analysis of RDCs has gained significant momentum in recent years, and particularly applications to motion in proteins have become more numerous. This trend may well continue as RDCs can easily leverage structures produced by new computational methods (e.g., AlphaFold) to produce functional descriptions. In this report, we provide examples and a summary of the ways that RDCs have been used to confirm the existence of internal dynamics, characterize the type of dynamics, and recover atomic-scale structural ensembles that define the full range of conformational sampling.
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Affiliation(s)
- Hamed Abdollahi
- Department of Computer Science and Engineering, University of South Carolina, 29201, Columbia, SC, USA.
| | - James H Prestegard
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.
| | - Homayoun Valafar
- Department of Computer Science and Engineering, University of South Carolina, 29201, Columbia, SC, USA.
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19
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Chao TH, Rekhi S, Mittal J, Tabor DP. Data-Driven Models for Predicting Intrinsically Disordered Protein Polymer Physics Directly from Composition or Sequence. MOLECULAR SYSTEMS DESIGN & ENGINEERING 2023; 8:1146-1155. [PMID: 38222029 PMCID: PMC10786636 DOI: 10.1039/d3me00053b] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
The molecular-level understanding of intrinsically disordered proteins is challenging due to experimental characterization difficulties. Computational understanding of IDPs also requires fundamental advances, as the leading tools for predicting protein folding (e.g., AlphaFold), typically fail to describe the structural ensembles of IDPs. The focus of this paper is to 1) develop new representations for intrinsically disordered proteins and 2) pair these representations with classical machine learning and deep learning models to predict the radius of gyration and derived scaling exponent of IDPs. Here, we build a new physically-motivated feature called the bag of amino acid interactions representation, which encodes pairwise interactions explicitly into the representation. This feature essentially counts and weights all possible non-bonded interactions in a sequence and thus is, in principle, compatible with arbitrary sequence lengths. To see how well this new feature performs, both categorical and physically-motivated featurization techniques are tested on a computational dataset containing 10,000 sequences simulated at the coarse-grained level. The results indicate that this new feature outperforms the other purely categorical and physically-motivated features and possesses solid extrapolation capabilities. For future use, this feature can potentially provide physical insights into amino acid interactions, including their temperature dependence, and be applied to other protein spaces.
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Affiliation(s)
- Tzu-Hsuan Chao
- Department of Chemistry, Texas A&M University, PO Box 30012, College Station, TX 77842-3012, USA
| | - Shiv Rekhi
- Department of Chemistry, Texas A&M University, PO Box 30012, College Station, TX 77842-3012, USA
| | - Jeetain Mittal
- Department of Chemistry, Texas A&M University, PO Box 30012, College Station, TX 77842-3012, USA
| | - Daniel P Tabor
- Department of Chemistry, Texas A&M University, PO Box 30012, College Station, TX 77842-3012, USA
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20
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Michaelis M, Cupellini L, Mensch C, Perry CC, Delle Piane M, Colombi Ciacchi L. Tidying up the conformational ensemble of a disordered peptide by computational prediction of spectroscopic fingerprints. Chem Sci 2023; 14:8483-8496. [PMID: 37592980 PMCID: PMC10430726 DOI: 10.1039/d3sc02202a] [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: 05/01/2023] [Accepted: 07/15/2023] [Indexed: 08/19/2023] Open
Abstract
The most advanced structure prediction methods are powerless in exploring the conformational ensemble of disordered peptides and proteins and for this reason the "protein folding problem" remains unsolved. We present a novel methodology that enables the accurate prediction of spectroscopic fingerprints (circular dichroism, infrared, Raman, and Raman optical activity), and by this allows for "tidying up" the conformational ensembles of disordered peptides and disordered regions in proteins. This concept is elaborated for and applied to a dodecapeptide, whose spectroscopic fingerprint is measured and theoretically predicted by means of enhanced-sampling molecular dynamics coupled with quantum mechanical calculations. Following this approach, we demonstrate that peptides lacking a clear propensity for ordered secondary-structure motifs are not randomly, but only conditionally disordered. This means that their conformational landscape, or phase-space, can be well represented by a basis-set of conformers including about 10 to 100 structures. The implications of this finding have profound consequences both for the interpretation of experimental electronic and vibrational spectral features of peptides in solution and for the theoretical prediction of these features using accurate and computationally expensive techniques. The here-derived methods and conclusions are expected to fundamentally impact the rationalization of so-far elusive structure-spectra relationships for disordered peptides and proteins, towards improved and versatile structure prediction methods.
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Affiliation(s)
- Monika Michaelis
- Hybrid Materials Interfaces Group, Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, University of Bremen Am Fallturm 1 Bremen 28359 Germany
- Biomolecular and Materials Interface Research Group, Interdisciplinary Biomedical Research Centre, School of Science and Technology, Nottingham Trent University Clifton Lane Nottingham NG11 8NS UK
| | - Lorenzo Cupellini
- Dipartimento di Chimica e Chimica Industriale, University of Pisa Via G. Moruzzi 13 Pisa I-56124 Italy
| | - Carl Mensch
- Molecular Spectroscopy Research Group, Department of Chemistry, University of Antwerp Groenenborgerlaan 171 Antwerp 2020 Belgium
| | - Carole C Perry
- Biomolecular and Materials Interface Research Group, Interdisciplinary Biomedical Research Centre, School of Science and Technology, Nottingham Trent University Clifton Lane Nottingham NG11 8NS UK
| | - Massimo Delle Piane
- Hybrid Materials Interfaces Group, Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, University of Bremen Am Fallturm 1 Bremen 28359 Germany
- Department of Applied Science and Technology, Politecnico di Torino Corso Duca degli Abruzzi 24 Torino 10129 Italy
| | - Lucio Colombi Ciacchi
- Hybrid Materials Interfaces Group, Faculty of Production Engineering, Bremen Center for Computational Materials Science, Center for Environmental Research and Sustainable Technology (UFT), and MAPEX Center for Materials and Processes, University of Bremen Am Fallturm 1 Bremen 28359 Germany
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21
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Mondal A, Lenz S, MacCallum JL, Perez A. Hybrid computational methods combining experimental information with molecular dynamics. Curr Opin Struct Biol 2023; 81:102609. [PMID: 37224642 DOI: 10.1016/j.sbi.2023.102609] [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: 02/05/2023] [Revised: 04/12/2023] [Accepted: 04/23/2023] [Indexed: 05/26/2023]
Abstract
A goal of structural biology is to understand how macromolecules carry out their biological roles by identifying their metastable states, mechanisms of action, pathways leading to conformational changes, and the thermodynamic and kinetic relationships between those states. Integrative modeling brings structural insights into systems where traditional structure determination approaches cannot help. We focus on the synergies and challenges of integrative modeling combining experimental data with molecular dynamics simulations.
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Affiliation(s)
- Arup Mondal
- Quantum Theory Project, Department of Chemistry, University of Florida, Leigh, UK. https://twitter.com/@amondal_chem
| | - Stefan Lenz
- Department of Chemistry, University of Calgary, 2500 University Drive, Canada
| | - Justin L MacCallum
- Department of Chemistry, University of Calgary, 2500 University Drive, Canada. https://twitter.com/@jlmaccal
| | - Alberto Perez
- Quantum Theory Project, Department of Chemistry, University of Florida, Leigh, UK.
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22
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Hiranyakorn M, Yagi-Utsumi M, Yanaka S, Ohtsuka N, Momiyama N, Satoh T, Kato K. Mutational and Environmental Effects on the Dynamic Conformational Distributions of Lys48-Linked Ubiquitin Chains. Int J Mol Sci 2023; 24:ijms24076075. [PMID: 37047047 PMCID: PMC10094362 DOI: 10.3390/ijms24076075] [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: 02/24/2023] [Revised: 03/18/2023] [Accepted: 03/20/2023] [Indexed: 04/14/2023] Open
Abstract
In multidomain proteins, individual domains connected by flexible linkers are dynamically rearranged upon ligand binding and sensing changes in environmental factors, such as pH and temperature. Here, we characterize dynamic domain rearrangements of Lys48-linked ubiquitin (Ub) chains as models of multidomain proteins in which molecular surfaces mediating intermolecular interactions are involved in intramolecular domain-domain interactions. Using NMR and other biophysical techniques, we characterized dynamic conformational interconversions of diUb between open and closed states regarding solvent exposure of the hydrophobic surfaces of each Ub unit, which serve as binding sites for various Ub-interacting proteins. We found that the hydrophobic Ub-Ub interaction in diUb was reinforced by cysteine substitution of Lys48 of the distal Ub unit because of interaction between the cysteinyl thiol group and the C-terminal segment of the proximal Ub unit. In contrast, the replacement of the isopeptide linker with an artificial ethylenamine linker minimally affected the conformational distributions. Furthermore, we demonstrated that the mutational modification allosterically impacted the exposure of the most distal Ub unit in triUb. Thus, the conformational interconversion of Ub chains offers a unique design framework in Ub-based protein engineering not only for developing biosensing probes but also for allowing new opportunities for the allosteric regulation of multidomain proteins.
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Affiliation(s)
- Methanee Hiranyakorn
- Department of Functional Molecular Science, School of Physical Science, The Graduate University for Advanced Studies, SOKENDAI, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
| | - Maho Yagi-Utsumi
- Department of Functional Molecular Science, School of Physical Science, The Graduate University for Advanced Studies, SOKENDAI, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuho-ku, Nagoya 467-8603, Japan
| | - Saeko Yanaka
- Department of Functional Molecular Science, School of Physical Science, The Graduate University for Advanced Studies, SOKENDAI, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuho-ku, Nagoya 467-8603, Japan
| | - Naoya Ohtsuka
- Department of Functional Molecular Science, School of Physical Science, The Graduate University for Advanced Studies, SOKENDAI, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
| | - Norie Momiyama
- Department of Functional Molecular Science, School of Physical Science, The Graduate University for Advanced Studies, SOKENDAI, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
| | - Tadashi Satoh
- Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuho-ku, Nagoya 467-8603, Japan
| | - Koichi Kato
- Department of Functional Molecular Science, School of Physical Science, The Graduate University for Advanced Studies, SOKENDAI, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Institute for Molecular Science (IMS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5-1 Higashiyama, Myodaiji, Okazaki 444-8787, Japan
- Graduate School of Pharmaceutical Sciences, Nagoya City University, 3-1 Tanabe-dori, Mizuho-ku, Nagoya 467-8603, Japan
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23
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Thomasen FE, Cuneo MJ, Mittag T, Lindorff-Larsen K. Conformational and oligomeric states of SPOP from small-angle X-ray scattering and molecular dynamics simulations. eLife 2023; 12:e84147. [PMID: 36856266 PMCID: PMC9998093 DOI: 10.7554/elife.84147] [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: 10/12/2022] [Accepted: 02/20/2023] [Indexed: 03/02/2023] Open
Abstract
Speckle-type POZ protein (SPOP) is a substrate adaptor in the ubiquitin proteasome system, and plays important roles in cell-cycle control, development, and cancer pathogenesis. SPOP forms linear higher-order oligomers following an isodesmic self-association model. Oligomerization is essential for SPOP's multivalent interactions with substrates, which facilitate phase separation and localization to biomolecular condensates. Structural characterization of SPOP in its oligomeric state and in solution is, however, challenging due to the inherent conformational and compositional heterogeneity of the oligomeric species. Here, we develop an approach to simultaneously and self-consistently characterize the conformational ensemble and the distribution of oligomeric states of SPOP by combining small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations. We build initial conformational ensembles of SPOP oligomers using coarse-grained molecular dynamics simulations, and use a Bayesian/maximum entropy approach to refine the ensembles, along with the distribution of oligomeric states, against a concentration series of SAXS experiments. Our results suggest that SPOP oligomers behave as rigid, helical structures in solution, and that a flexible linker region allows SPOP's substrate-binding domains to extend away from the core of the oligomers. Additionally, our results are in good agreement with previous characterization of the isodesmic self-association of SPOP. In the future, the approach presented here can be extended to other systems to simultaneously characterize structural heterogeneity and self-assembly.
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Affiliation(s)
- F Emil Thomasen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of CopenhagenCopenhagenDenmark
| | - Matthew J Cuneo
- Department of Structural Biology, St. Jude Children’s Research HospitalMemphisUnited States
| | - Tanja Mittag
- Department of Structural Biology, St. Jude Children’s Research HospitalMemphisUnited States
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of CopenhagenCopenhagenDenmark
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24
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Janson G, Valdes-Garcia G, Heo L, Feig M. Direct generation of protein conformational ensembles via machine learning. Nat Commun 2023; 14:774. [PMID: 36774359 PMCID: PMC9922302 DOI: 10.1038/s41467-023-36443-x] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Accepted: 02/01/2023] [Indexed: 02/13/2023] Open
Abstract
Dynamics and conformational sampling are essential for linking protein structure to biological function. While challenging to probe experimentally, computer simulations are widely used to describe protein dynamics, but at significant computational costs that continue to limit the systems that can be studied. Here, we demonstrate that machine learning can be trained with simulation data to directly generate physically realistic conformational ensembles of proteins without the need for any sampling and at negligible computational cost. As a proof-of-principle we train a generative adversarial network based on a transformer architecture with self-attention on coarse-grained simulations of intrinsically disordered peptides. The resulting model, idpGAN, can predict sequence-dependent coarse-grained ensembles for sequences that are not present in the training set demonstrating that transferability can be achieved beyond the limited training data. We also retrain idpGAN on atomistic simulation data to show that the approach can be extended in principle to higher-resolution conformational ensemble generation.
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Affiliation(s)
- Giacomo Janson
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Gilberto Valdes-Garcia
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Lim Heo
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Michael Feig
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA.
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25
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Illuminating Intrinsically Disordered Proteins with Integrative Structural Biology. Biomolecules 2023; 13:biom13010124. [PMID: 36671509 PMCID: PMC9856150 DOI: 10.3390/biom13010124] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/01/2023] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
Intense study of intrinsically disordered proteins (IDPs) did not begin in earnest until the late 1990s when a few groups, working independently, convinced the community that these 'weird' proteins could have important functions. Over the past two decades, it has become clear that IDPs play critical roles in a multitude of biological phenomena with prominent examples including coordination in signaling hubs, enabling gene regulation, and regulating ion channels, just to name a few. One contributing factor that delayed appreciation of IDP functional significance is the experimental difficulty in characterizing their dynamic conformations. The combined application of multiple methods, termed integrative structural biology, has emerged as an essential approach to understanding IDP phenomena. Here, we review some of the recent applications of the integrative structural biology philosophy to study IDPs.
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26
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Intrinsically Disordered Proteins: An Overview. Int J Mol Sci 2022; 23:ijms232214050. [PMID: 36430530 PMCID: PMC9693201 DOI: 10.3390/ijms232214050] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 11/16/2022] Open
Abstract
Many proteins and protein segments cannot attain a single stable three-dimensional structure under physiological conditions; instead, they adopt multiple interconverting conformational states. Such intrinsically disordered proteins or protein segments are highly abundant across proteomes, and are involved in various effector functions. This review focuses on different aspects of disordered proteins and disordered protein regions, which form the basis of the so-called "Disorder-function paradigm" of proteins. Additionally, various experimental approaches and computational tools used for characterizing disordered regions in proteins are discussed. Finally, the role of disordered proteins in diseases and their utility as potential drug targets are explored.
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27
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Delhommel F, Martínez-Lumbreras S, Sattler M. Combining NMR, SAXS and SANS to characterize the structure and dynamics of protein complexes. Methods Enzymol 2022; 678:263-297. [PMID: 36641211 DOI: 10.1016/bs.mie.2022.09.020] [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: 11/05/2022]
Abstract
Understanding the structure and dynamics of biological macromolecules is essential to decipher the molecular mechanisms that underlie cellular functions. The description of structure and conformational dynamics often requires the integration of complementary techniques. In this review, we highlight the utility of combining nuclear magnetic resonance (NMR) spectroscopy with small angle scattering (SAS) to characterize these challenging biomolecular systems. NMR can assess the structure and conformational dynamics of multidomain proteins, RNAs and biomolecular complexes. It can efficiently provide information on interaction surfaces, long-distance restraints and relative domain orientations at residue-level resolution. Such information can be readily combined with high-resolution structural data available on subcomponents of biomolecular assemblies. Moreover, NMR is a powerful tool to characterize the dynamics of biomolecules on a wide range of timescales, from nanoseconds to seconds. On the other hand, SAS approaches provide global information on the size and shape of biomolecules and on the ensemble of all conformations present in solution. Therefore, NMR and SAS provide complementary data that are uniquely suited to investigate dynamic biomolecular assemblies. Here, we briefly review the type of data that can be obtained by both techniques and describe different approaches that can be used to combine them to characterize biomolecular assemblies. We then provide guidelines on which experiments are best suited depending on the type of system studied, ranging from fully rigid complexes, dynamic structures that interconvert between defined conformations and systems with very high structural heterogeneity.
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Affiliation(s)
- Florent Delhommel
- Institute of Structural Biology, Helmholtz Zentrum München, Neuherberg, Germany; Bavarian NMR Center, Department of Chemistry, Technical University of Munich, Garching, Germany
| | - Santiago Martínez-Lumbreras
- Institute of Structural Biology, Helmholtz Zentrum München, Neuherberg, Germany; Bavarian NMR Center, Department of Chemistry, Technical University of Munich, Garching, Germany
| | - Michael Sattler
- Institute of Structural Biology, Helmholtz Zentrum München, Neuherberg, Germany; Bavarian NMR Center, Department of Chemistry, Technical University of Munich, Garching, Germany.
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28
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Khan SH, Braet SM, Koehler SJ, Elacqua E, Anand GS, Okafor CD. Ligand-induced shifts in conformational ensembles that describe transcriptional activation. eLife 2022; 11:80140. [PMID: 36222302 PMCID: PMC9555869 DOI: 10.7554/elife.80140] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 09/14/2022] [Indexed: 11/15/2022] Open
Abstract
Nuclear receptors function as ligand-regulated transcription factors whose ability to regulate diverse physiological processes is closely linked with conformational changes induced upon ligand binding. Understanding how conformational populations of nuclear receptors are shifted by various ligands could illuminate strategies for the design of synthetic modulators to regulate specific transcriptional programs. Here, we investigate ligand-induced conformational changes using a reconstructed, ancestral nuclear receptor. By making substitutions at a key position, we engineer receptor variants with altered ligand specificities. We combine cellular and biophysical experiments to characterize transcriptional activity, as well as elucidate mechanisms underlying altered transcription in receptor variants. We then use atomistic molecular dynamics (MD) simulations with enhanced sampling to generate ensembles of wildtype and engineered receptors in combination with multiple ligands, followed by conformational analysis and correlation of MD-based predictions with functional ligand profiles. We determine that conformational ensembles accurately describe ligand responses based on observed population shifts. These studies provide a platform which will allow structural characterization of physiologically-relevant conformational ensembles, as well as provide the ability to design and predict transcriptional responses in novel ligands.
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Affiliation(s)
- Sabab Hasan Khan
- Department of Biochemistry and Molecular Biology, Pennsylvania State University
| | - Sean M Braet
- Department of Chemistry, Pennsylvania State University
| | | | | | | | - C Denise Okafor
- Department of Biochemistry and Molecular Biology, Pennsylvania State University
- Department of Chemistry, Pennsylvania State University
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29
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Rizuan A, Jovic N, Phan TM, Kim YC, Mittal J. Developing Bonded Potentials for a Coarse-Grained Model of Intrinsically Disordered Proteins. J Chem Inf Model 2022; 62:4474-4485. [PMID: 36066390 PMCID: PMC10165611 DOI: 10.1021/acs.jcim.2c00450] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Recent advances in residue-level coarse-grained (CG) computational models have enabled molecular-level insights into biological condensates of intrinsically disordered proteins (IDPs), shedding light on the sequence determinants of their phase separation. The existing CG models that treat protein chains as flexible molecules connected via harmonic bonds cannot populate common secondary-structure elements. Here, we present a CG dihedral angle potential between four neighboring beads centered at Cα atoms to faithfully capture the transient helical structures of IDPs. In order to parameterize and validate our new model, we propose Cα-based helix assignment rules based on dihedral angles that succeed in reproducing the atomistic helicity results of a polyalanine peptide and folded proteins. We then introduce sequence-dependent dihedral angle potential parameters (εd) and use experimentally available helical propensities of naturally occurring 20 amino acids to find their optimal values. The single-chain helical propensities from the CG simulations for commonly studied prion-like IDPs are in excellent agreement with the NMR-based α-helix fraction, demonstrating that the new HPS-SS model can accurately produce structural features of IDPs. Furthermore, this model can be easily implemented for large-scale assembly simulations due to its simplicity.
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Affiliation(s)
- Azamat Rizuan
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
| | - Nina Jovic
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
| | - Tien M Phan
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
| | - Young C Kim
- Center for Materials Physics and Technology, Naval Research Laboratory, Washington, District of Columbia 20375, United States
| | - Jeetain Mittal
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States
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30
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Characterisation of HOIP RBR E3 ligase conformational dynamics using integrative modelling. Sci Rep 2022; 12:15201. [PMID: 36076045 PMCID: PMC9458678 DOI: 10.1038/s41598-022-18890-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 08/22/2022] [Indexed: 11/29/2022] Open
Abstract
Multidomain proteins composed of individual domains connected by flexible linkers pose a challenge for structural studies due to their intrinsic conformational dynamics. Integrated modelling approaches provide a means to characterise protein flexibility by combining experimental measurements with molecular simulations. In this study, we characterise the conformational dynamics of the catalytic RBR domain of the E3 ubiquitin ligase HOIP, which regulates immune and inflammatory signalling pathways. Specifically, we combine small angle X-ray scattering experiments and molecular dynamics simulations to generate weighted conformational ensembles of the HOIP RBR domain using two different approaches based on maximum parsimony and maximum entropy principles. Both methods provide optimised ensembles that are instrumental in rationalising observed differences between SAXS-based solution studies and available crystal structures and highlight the importance of interdomain linker flexibility.
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31
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Teixeira JMC, Liu ZH, Namini A, Li J, Vernon RM, Krzeminski M, Shamandy AA, Zhang O, Haghighatlari M, Yu L, Head-Gordon T, Forman-Kay JD. IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States. J Phys Chem A 2022; 126:5985-6003. [PMID: 36030416 PMCID: PMC9465686 DOI: 10.1021/acs.jpca.2c03726] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
![]()
The power of structural information for informing biological
mechanisms
is clear for stable folded macromolecules, but similar structure–function
insight is more difficult to obtain for highly dynamic systems such
as intrinsically disordered proteins (IDPs) which must be described
as structural ensembles. Here, we present IDPConformerGenerator, a
flexible, modular open-source software platform for generating large
and diverse ensembles of disordered protein states that builds conformers
that obey geometric, steric, and other physical restraints on the
input sequence. IDPConformerGenerator samples backbone phi (φ),
psi (ψ), and omega (ω) torsion angles of relevant sequence
fragments from loops and secondary structure elements extracted from
folded protein structures in the RCSB Protein Data Bank and builds
side chains from robust Monte Carlo algorithms using expanded rotamer
libraries. IDPConformerGenerator has many user-defined options enabling
variable fractional sampling of secondary structures, supports Bayesian
models for assessing the agreement of IDP ensembles for consistency
with experimental data, and introduces a machine learning approach
to transform between internal and Cartesian coordinates with reduced
error. IDPConformerGenerator will facilitate the characterization
of disordered proteins to ultimately provide structural insights into
these states that have key biological functions.
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Affiliation(s)
- João M. C. Teixeira
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Zi Hao Liu
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Ashley Namini
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | | | - Robert M. Vernon
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Mickaël Krzeminski
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Alaa A. Shamandy
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Computer Science, University of Toronto, Toronto, Ontario M5S 2E4, Canada
| | | | | | | | | | - Julie D. Forman-Kay
- Molecular Medicine Program, Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 1A8, Canada
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32
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Abramova A, Glagolev M, Vasilevskaya V. Structured globules with twisted arrangement of helical blocks: Computer simulation. POLYMER 2022. [DOI: 10.1016/j.polymer.2022.124974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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33
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Thomasen FE, Pesce F, Roesgaard MA, Tesei G, Lindorff-Larsen K. Improving Martini 3 for Disordered and Multidomain Proteins. J Chem Theory Comput 2022; 18:2033-2041. [PMID: 35377637 DOI: 10.1021/acs.jctc.1c01042] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Coarse-grained molecular dynamics simulations are a useful tool to determine conformational ensembles of proteins. Here, we show that the coarse-grained force field Martini 3 underestimates the global dimensions of intrinsically disordered proteins (IDPs) and multidomain proteins when compared with small-angle X-ray scattering (SAXS) data and that increasing the strength of protein-water interactions favors more expanded conformations. We find that increasing the strength of interactions between protein and water by ca. 10% results in improved agreement with the SAXS data for IDPs and multidomain proteins. We also show that this correction results in a more accurate description of self-association of IDPs and folded proteins and better agreement with paramagnetic relaxation enhancement data for most IDPs. While simulations with this revised force field still show deviations to experiments for some systems, our results suggest that it is overall a substantial improvement for coarse-grained simulations of soluble proteins.
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Affiliation(s)
- F Emil Thomasen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Francesco Pesce
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Mette Ahrensback Roesgaard
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Giulio Tesei
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Kresten Lindorff-Larsen
- Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
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34
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Karamanos TK, Kalverda AP, Radford SE. Generating Ensembles of Dynamic Misfolding Proteins. Front Neurosci 2022; 16:881534. [PMID: 35431773 PMCID: PMC9008329 DOI: 10.3389/fnins.2022.881534] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 03/08/2022] [Indexed: 01/09/2023] Open
Abstract
The early stages of protein misfolding and aggregation involve disordered and partially folded protein conformers that contain a high degree of dynamic disorder. These dynamic species may undergo large-scale intra-molecular motions of intrinsically disordered protein (IDP) precursors, or flexible, low affinity inter-molecular binding in oligomeric assemblies. In both cases, generating atomic level visualization of the interconverting species that captures the conformations explored and their physico-chemical properties remains hugely challenging. How specific sub-ensembles of conformers that are on-pathway to aggregation into amyloid can be identified from their aggregation-resilient counterparts within these large heterogenous pools of rapidly moving molecules represents an additional level of complexity. Here, we describe current experimental and computational approaches designed to capture the dynamic nature of the early stages of protein misfolding and aggregation, and discuss potential challenges in describing these species because of the ensemble averaging of experimental restraints that arise from motions on the millisecond timescale. We give a perspective of how machine learning methods can be used to extract aggregation-relevant sub-ensembles and provide two examples of such an approach in which specific interactions of defined species within the dynamic ensembles of α-synuclein (αSyn) and β2-microgloblulin (β2m) can be captured and investigated.
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Affiliation(s)
- Theodoros K. Karamanos
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
| | | | - Sheena E. Radford
- Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
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