1
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Puławski W, Koliński A, Koliński M. Multiscale modeling of protofilament structures: A case study on insulin amyloid aggregates. Int J Biol Macromol 2024; 285:138382. [PMID: 39638203 DOI: 10.1016/j.ijbiomac.2024.138382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2024] [Revised: 11/29/2024] [Accepted: 12/02/2024] [Indexed: 12/07/2024]
Abstract
Under certain conditions, proteins may undergo misfolding and form long insoluble aggregates called amyloid fibrils. The presence of these aggregates is often associated with various diseases. The molecular mechanisms governing the aggregation process are yet to be fully understood. The self-assembly of amyloid protofilaments occurs over extended time frames, making the simulation of such events problematic. In this work, we describe a pipeline for multiscale modeling protofilament structures. In the first stage, the self-assembly of short fibrillar oligomers occurs during coarse-grained docking simulations of multiple copies of aggregating peptides. Subsequently, symmetry criteria are used to select the highest-ranked oligomer structures. Selected models are then reconstructed to an all-atom representation and used for the assembly of longer protofilaments. Models are optimized using molecular dynamics. Final structures are selected using various scoring protocols. We evaluated this modeling procedure through the test prediction of insulin amyloid protofilaments whose experimental structures have been published recently. The resulting insulin protofilament models closely resemble the experimental structures. This work provides a proof of concept for the proposed modeling procedure aiming to predict amyloid protofilament structures that exhibit in-register and parallel arrangement of β-sheets based solely on the amino acid sequence of aggregating peptides.
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Affiliation(s)
- Wojciech Puławski
- Bioinformatics Laboratory, Mossakowski Medical Research Institute, Polish Academy of Sciences, Pawińskiego 5, 02-106 Warsaw, Poland.
| | - Andrzej Koliński
- Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
| | - Michał Koliński
- Bioinformatics Laboratory, Mossakowski Medical Research Institute, Polish Academy of Sciences, Pawińskiego 5, 02-106 Warsaw, Poland.
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2
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Sarma S, Sudarshan TR, Nguyen V, Robang AS, Xiao X, Le JV, Helmicki ME, Paravastu AK, Hall CK. Design of parallel 𝛽-sheet nanofibrils using Monte Carlo search, coarse-grained simulations, and experimental testing. Protein Sci 2024; 33:e5102. [PMID: 39037281 PMCID: PMC11261811 DOI: 10.1002/pro.5102] [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: 11/10/2023] [Revised: 06/20/2024] [Accepted: 06/22/2024] [Indexed: 07/23/2024]
Abstract
Peptide self-assembly into amyloid fibrils provides numerous applications in drug delivery and biomedical engineering applications. We augment our previously-established computational screening technique along with experimental biophysical characterization to discover 7-mer peptides that self-assemble into "parallel β-sheets", that is, β-sheets with N-terminus-to-C-terminus 𝛽-strand vectors oriented in parallel. To accomplish the desired β-strand organization, we applied the PepAD amino acid sequence design software to the Class-1 cross-β spine defined by Sawaya et al. This molecular configuration includes two layers of parallel β-sheets stacked such that N-terminus-to-C-terminus vectors are oriented antiparallel for molecules on adjacent β-sheets. The first cohort of PepAD identified peptides were examined for their fibrillation behavior in DMD/PRIME20 simulations, and the top performing sequence was selected as a prototype for a subsequent round of sequence refinement. The two rounds of design resulted in a library of eight 7-mer peptides. In DMD/PRIME20 simulations, five of these peptides spontaneously formed fibril-like structures with a predominantly parallel 𝛽-sheet arrangement, two formed fibril-like structure with <50% in parallel 𝛽-sheet arrangement and one remained a random coil. Among the eight candidate peptides produced by PepAD and DMD/PRIME20, five were synthesized and purified. All five assembled into amyloid fibrils composed of parallel β-sheets based on Fourier transform infrared spectroscopy, circular dichroism, electron microscopy, and thioflavin-T fluorescence spectroscopy measurements.
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Affiliation(s)
- Sudeep Sarma
- Department of Chemical and Biomolecular EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Tarunya Rao Sudarshan
- Department of Chemical and Biomolecular EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Van Nguyen
- Department of Chemical and Biomolecular EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
| | - Alicia S. Robang
- Department of Chemical and Biomolecular EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Xingqing Xiao
- Department of Chemical and Biomolecular EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
- Present address:
Department of Chemistry, School of Chemistry and Chemical EngineeringHainan UniversityHaikou CityHainan ProvincePeople's Republic of China
| | - Justin V. Le
- Department of Chemical and Biomolecular EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Michael E. Helmicki
- Department of Chemical and Biomolecular EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Anant K. Paravastu
- Department of Chemical and Biomolecular EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
| | - Carol K. Hall
- Department of Chemical and Biomolecular EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
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3
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Ghosh D, Biswas A, Radhakrishna M. Advanced computational approaches to understand protein aggregation. BIOPHYSICS REVIEWS 2024; 5:021302. [PMID: 38681860 PMCID: PMC11045254 DOI: 10.1063/5.0180691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 03/18/2024] [Indexed: 05/01/2024]
Abstract
Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.
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Affiliation(s)
- Deepshikha Ghosh
- Department of Biological Sciences and Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
| | - Anushka Biswas
- Department of Chemical Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
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4
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Wang Y, Stebe KJ, de la Fuente-Nunez C, Radhakrishnan R. Computational Design of Peptides for Biomaterials Applications. ACS APPLIED BIO MATERIALS 2024; 7:617-625. [PMID: 36971822 PMCID: PMC11190638 DOI: 10.1021/acsabm.2c01023] [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] [Indexed: 03/29/2023]
Abstract
Computer-aided molecular design and protein engineering emerge as promising and active subjects in bioengineering and biotechnological applications. On one hand, due to the advancing computing power in the past decade, modeling toolkits and force fields have been put to use for accurate multiscale modeling of biomolecules including lipid, protein, carbohydrate, and nucleic acids. On the other hand, machine learning emerges as a revolutionary data analysis tool that promises to leverage physicochemical properties and structural information obtained from modeling in order to build quantitative protein structure-function relationships. We review recent computational works that utilize state-of-the-art computational methods to engineer peptides and proteins for various emerging biomedical, antimicrobial, and antifreeze applications. We also discuss challenges and possible future directions toward developing a roadmap for efficient biomolecular design and engineering.
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Affiliation(s)
- Yiming Wang
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Kathleen J Stebe
- Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Cesar de la Fuente-Nunez
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Machine Biology Group, Department of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
| | - Ravi Radhakrishnan
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
- Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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5
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Jones SJ, Perez A. Molecular Modeling of Self-Assembling Peptides. ACS APPLIED BIO MATERIALS 2024; 7:543-552. [PMID: 36795608 DOI: 10.1021/acsabm.2c00921] [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: 02/17/2023]
Abstract
Peptide epitopes mediate as many as 40% of protein-protein interactions and fulfill signaling, inhibition, and activation roles within the cell. Beyond protein recognition, some peptides can self- or coassemble into stable hydrogels, making them a readily available source of biomaterials. While these 3D assemblies are routinely characterized at the fiber level, there are missing atomistic details about the assembly scaffold. Such atomistic detail can be useful in the rational design of more stable scaffold structures and with improved accessibility to functional motifs. Computational approaches can in principle reduce the experimental cost of such an endeavor by predicting the assembly scaffold and identifying novel sequences that adopt said structure. Yet, inaccuracies in physical models and inefficient sampling have limited atomistic studies to short (two or three amino acid) peptides. Given recent developments in machine learning and advances in sampling strategies, we revisit the suitability of physical models for this task. We use the MELD (Modeling Employing Limited Data) approach to drive self-assembly in combination with generic data in cases where conventional MD is unsuccessful. Finally, despite recent developments in machine learning algorithms for protein structure and sequence predictions, we find the algorithms are not yet suited for studying the assembly of short peptides.
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Affiliation(s)
- Stephen J Jones
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, Florida 32611, United States
| | - Alberto Perez
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, Florida 32611, United States
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6
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Min J, Rong X, Zhang J, Su R, Wang Y, Qi W. Computational Design of Peptide Assemblies. J Chem Theory Comput 2024; 20:532-550. [PMID: 38206800 DOI: 10.1021/acs.jctc.3c01054] [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: 01/13/2024]
Abstract
With the ongoing development of peptide self-assembling materials, there is growing interest in exploring novel functional peptide sequences. From short peptides to long polypeptides, as the functionality increases, the sequence space is also expanding exponentially. Consequently, attempting to explore all functional sequences comprehensively through experience and experiments alone has become impractical. By utilizing computational methods, especially artificial intelligence enhanced molecular dynamics (MD) simulation and de novo peptide design, there has been a significant expansion in the exploration of sequence space. Through these methods, a variety of supramolecular functional materials, including fibers, two-dimensional arrays, nanocages, etc., have been designed by meticulously controlling the inter- and intramolecular interactions. In this review, we first provide a brief overview of the current main computational methods and then focus on the computational design methods for various self-assembled peptide materials. Additionally, we introduce some representative protein self-assemblies to offer guidance for the design of self-assembling peptides.
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Affiliation(s)
- Jiwei Min
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, P. R. China
| | - Xi Rong
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, P. R. China
| | - Jiaxing Zhang
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, P. R. China
| | - Rongxin Su
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, P. R. China
- Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, P. R. China
- Tianjin Key Laboratory of Membrane Science and Desalination Technology, Tianjin 300072, P. R. China
| | - Yuefei Wang
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, P. R. China
- Tianjin Key Laboratory of Membrane Science and Desalination Technology, Tianjin 300072, P. R. China
| | - Wei Qi
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, P. R. China
- Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, P. R. China
- Tianjin Key Laboratory of Membrane Science and Desalination Technology, Tianjin 300072, P. R. China
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7
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Liu R, Dong X, Seroski DT, Soto Morales B, Wong KM, Robang AS, Melgar L, Angelini TE, Paravastu AK, Hall CK, Hudalla GA. Side-Chain Chemistry Governs Hierarchical Order of Charge-Complementary β-sheet Peptide Coassemblies. Angew Chem Int Ed Engl 2023; 62:e202314531. [PMID: 37931093 PMCID: PMC10841972 DOI: 10.1002/anie.202314531] [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: 09/27/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/08/2023]
Abstract
Self-assembly of proteinaceous biomolecules into functional materials with ordered structures that span length scales is common in nature yet remains a challenge with designer peptides under ambient conditions. This report demonstrates how charged side-chain chemistry affects the hierarchical co-assembly of a family of charge-complementary β-sheet-forming peptide pairs known as CATCH(X+/Y-) at physiologic pH and ionic strength in water. In a concentration-dependent manner, the CATCH(6K+) (Ac-KQKFKFKFKQK-Am) and CATCH(6D-) (Ac-DQDFDFDFDQD-Am) pair formed either β-sheet-rich microspheres or β-sheet-rich gels with a micron-scale plate-like morphology, which were not observed with other CATCH(X+/Y-) pairs. This hierarchical order was disrupted by replacing D with E, which increased fibril twisting. Replacing K with R, or mutating the N- and C-terminal amino acids in CATCH(6K+) and CATCH(6D-) to Qs, increased observed co-assembly kinetics, which also disrupted hierarchical order. Due to the ambient assembly conditions, active CATCH(6K+)-green fluorescent protein fusions could be incorporated into the β-sheet plates and microspheres formed by the CATCH(6K+/6D-) pair, demonstrating the potential to endow functionality.
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Affiliation(s)
- Renjie Liu
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL-32611, USA
| | - Xin Dong
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC-27695, USA
| | - Dillon T Seroski
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL-32611, USA
| | - Bethsymarie Soto Morales
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL-32611, USA
| | - Kong M Wong
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA-30332, USA
| | - Alicia S Robang
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA-30332, USA
| | - Lucas Melgar
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL-32611, USA
| | - Thomas E Angelini
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL-32611, USA
| | - Anant K Paravastu
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA-30332, USA
| | - Carol K Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC-27695, USA
| | - Gregory A Hudalla
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL-32611, USA
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8
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Dong XY, Liu R, Seroski DT, Hudalla GA, Hall CK. Programming co-assembled peptide nanofiber morphology via anionic amino acid type: Insights from molecular dynamics simulations. PLoS Comput Biol 2023; 19:e1011685. [PMID: 38048311 PMCID: PMC10729967 DOI: 10.1371/journal.pcbi.1011685] [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: 06/13/2023] [Revised: 12/19/2023] [Accepted: 11/13/2023] [Indexed: 12/06/2023] Open
Abstract
Co-assembling peptides can be crafted into supramolecular biomaterials for use in biotechnological applications, such as cell culture scaffolds, drug delivery, biosensors, and tissue engineering. Peptide co-assembly refers to the spontaneous organization of two different peptides into a supramolecular architecture. Here we use molecular dynamics simulations to quantify the effect of anionic amino acid type on co-assembly dynamics and nanofiber structure in binary CATCH(+/-) peptide systems. CATCH peptide sequences follow a general pattern: CQCFCFCFCQC, where all C's are either a positively charged or a negatively charged amino acid. Specifically, we investigate the effect of substituting aspartic acid residues for the glutamic acid residues in the established CATCH(6E-) molecule, while keeping CATCH(6K+) unchanged. Our results show that structures consisting of CATCH(6K+) and CATCH(6D-) form flatter β-sheets, have stronger interactions between charged residues on opposing β-sheet faces, and have slower co-assembly kinetics than structures consisting of CATCH(6K+) and CATCH(6E-). Knowledge of the effect of sidechain type on assembly dynamics and fibrillar structure can help guide the development of advanced biomaterials and grant insight into sequence-to-structure relationships.
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Affiliation(s)
- Xin Y. Dong
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Renjie Liu
- Department of Biomedical Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Dillon T. Seroski
- Department of Biomedical Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Gregory A. Hudalla
- Department of Biomedical Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, United States of America
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9
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Pretti E, Shell MS. Mapping the configurational landscape and aggregation phase behavior of the tau protein fragment PHF6. Proc Natl Acad Sci U S A 2023; 120:e2309995120. [PMID: 37983502 PMCID: PMC10691331 DOI: 10.1073/pnas.2309995120] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 10/17/2023] [Indexed: 11/22/2023] Open
Abstract
The PHF6 (Val-Gln-Ile-Val-Tyr-Lys) motif, found in all isoforms of the microtubule-associated protein tau, forms an integral part of ordered cores of amyloid fibrils formed in tauopathies and is thought to play a fundamental role in tau aggregation. Because PHF6 as an isolated hexapeptide assembles into ordered fibrils on its own, it is investigated as a minimal model for insight into the initial stages of aggregation of larger tau fragments. Even for this small peptide, however, the large length and time scales associated with fibrillization pose challenges for simulation studies of its dynamic assembly, equilibrium configurational landscape, and phase behavior. Here, we develop an accurate, bottom-up coarse-grained model of PHF6 for large-scale simulations of its aggregation, which we use to uncover molecular interactions and thermodynamic driving forces governing its assembly. The model, not trained on any explicit information about fibrillar structure, predicts coexistence of formed fibrils with monomers in solution, and we calculate a putative equilibrium phase diagram in concentration-temperature space. We also characterize the configurational and free energetic landscape of PHF6 oligomers. Importantly, we demonstrate with a model of heparin that this widely studied cofactor enhances the aggregation propensity of PHF6 by ordering monomers during nucleation and remaining associated with growing fibrils, consistent with experimentally characterized heparin-tau interactions. Overall, this effort provides detailed molecular insight into PHF6 aggregation thermodynamics and pathways and, furthermore, demonstrates the potential of modern multiscale modeling techniques to produce predictive models of amyloidogenic peptides simultaneously capturing sequence-specific effects and emergent aggregate structures.
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Affiliation(s)
- Evan Pretti
- Department of Chemical Engineering, University of California, Santa Barbara, CA93106-5080
| | - M. Scott Shell
- Department of Chemical Engineering, University of California, Santa Barbara, CA93106-5080
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10
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Laurent H, Hughes MDG, Walko M, Brockwell DJ, Mahmoudi N, Youngs TGA, Headen TF, Dougan L. Visualization of Self-Assembly and Hydration of a β-Hairpin through Integrated Small and Wide-Angle Neutron Scattering. Biomacromolecules 2023; 24:4869-4879. [PMID: 37874935 PMCID: PMC10646990 DOI: 10.1021/acs.biomac.3c00583] [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: 06/14/2023] [Revised: 10/03/2023] [Indexed: 10/26/2023]
Abstract
Fundamental understanding of the structure and assembly of nanoscale building blocks is crucial for the development of novel biomaterials with defined architectures and function. However, accessing self-consistent structural information across multiple length scales is challenging. This limits opportunities to exploit atomic scale interactions to achieve emergent macroscale properties. In this work we present an integrative small- and wide-angle neutron scattering approach coupled with computational modeling to reveal the multiscale structure of hierarchically self-assembled β hairpins in aqueous solution across 4 orders of magnitude in length scale from 0.1 Å to 300 nm. Our results demonstrate the power of this self-consistent cross-length scale approach and allows us to model both the large-scale self-assembly and small-scale hairpin hydration of the model β hairpin CLN025. Using this combination of techniques, we map the hydrophobic/hydrophilic character of this model self-assembled biomolecular surface with atomic resolution. These results have important implications for the multiscale investigation of aqueous peptides and proteins, for the prediction of ligand binding and molecular associations for drug design, and for understanding the self-assembly of peptides and proteins for functional biomaterials.
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Affiliation(s)
- Harrison Laurent
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
| | - Matt D. G. Hughes
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
| | - Martin Walko
- School
of Chemistry, University of Leeds, Leeds, United
Kingdom, LS2 9JT
| | - David J. Brockwell
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
| | - Najet Mahmoudi
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Tristan G. A. Youngs
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Thomas F. Headen
- ISIS
Neutron and Muon Source, Rutherford Appleton
Laboratory, Harwell Oxford, Didcot, United Kingdom, OX11 0QX
| | - Lorna Dougan
- School
of Physics and Astronomy, University of
Leeds, Leeds, United Kingdom, LS2
9JT
- Astbury
Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom LS2
9JT
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11
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Szała-Mendyk B, Phan TM, Mohanty P, Mittal J. Challenges in studying the liquid-to-solid phase transitions of proteins using computer simulations. Curr Opin Chem Biol 2023; 75:102333. [PMID: 37267850 PMCID: PMC10527940 DOI: 10.1016/j.cbpa.2023.102333] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 04/24/2023] [Accepted: 04/30/2023] [Indexed: 06/04/2023]
Abstract
"Membraneless organelles," also referred to as biomolecular condensates, perform a variety of cellular functions and their dysregulation is implicated in cancer and neurodegeneration. In the last two decades, liquid-liquid phase separation (LLPS) of intrinsically disordered and multidomain proteins has emerged as a plausible mechanism underlying the formation of various biomolecular condensates. Further, the occurrence of liquid-to-solid transitions within liquid-like condensates may give rise to amyloid structures, implying a biophysical link between phase separation and protein aggregation. Despite significant advances, uncovering the microscopic details of liquid-to-solid phase transitions using experiments remains a considerable challenge and presents an exciting opportunity for the development of computational models which provide valuable, complementary insights into the underlying phenomenon. In this review, we first highlight recent biophysical studies which provide new insights into the molecular mechanisms underlying liquid-to-solid (fibril) phase transitions of folded, disordered and multi-domain proteins. Next, we summarize the range of computational models used to study protein aggregation and phase separation. Finally, we discuss recent computational approaches which attempt to capture the underlying physics of liquid-to-solid transitions along with their merits and shortcomings.
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Affiliation(s)
- Beata Szała-Mendyk
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, TAMU 3127, College Station, 77843, Texas, United States.
| | - Tien Minh Phan
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, TAMU 3127, College Station, 77843, Texas, United States.
| | - Priyesh Mohanty
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, TAMU 3127, College Station, 77843, Texas, United States.
| | - Jeetain Mittal
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, TAMU 3127, College Station, 77843, Texas, United States; Department of Chemistry, Texas A&M University, TAMU 3255, College Station, 77843, Texas, United States; Interdisciplinary Graduate Program in Genetics and Genomics, Texas A&M University, TAMU 3255, College Station, 77843, Texas, United States.
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12
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Puławski W, Koliński A, Koliński M. Integrative modeling of diverse protein-peptide systems using CABS-dock. PLoS Comput Biol 2023; 19:e1011275. [PMID: 37405984 DOI: 10.1371/journal.pcbi.1011275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 06/15/2023] [Indexed: 07/07/2023] Open
Abstract
The CABS model can be applied to a wide range of protein-protein and protein-peptide molecular modeling tasks, such as simulating folding pathways, predicting structures, docking, and analyzing the structural dynamics of molecular complexes. In this work, we use the CABS-dock tool in two diverse modeling tasks: 1) predicting the structures of amyloid protofilaments and 2) identifying cleavage sites in the peptide substrates of proteolytic enzymes. In the first case, simulations of the simultaneous docking of amyloidogenic peptides indicated that the CABS model can accurately predict the structures of amyloid protofilaments which have an in-register parallel architecture. Scoring based on a combination of symmetry criteria and estimated interaction energy values for bound monomers enables the identification of protofilament models that closely match their experimental structures for 5 out of 6 analyzed systems. For the second task, it has been shown that CABS-dock coarse-grained docking simulations can be used to identify the positions of cleavage sites in the peptide substrates of proteolytic enzymes. The cleavage site position was correctly identified for 12 out of 15 analyzed peptides. When combined with sequence-based methods, these docking simulations may lead to an efficient way of predicting cleavage sites in degraded proteins. The method also provides the atomic structures of enzyme-substrate complexes, which can give insights into enzyme-substrate interactions that are crucial for the design of new potent inhibitors.
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Affiliation(s)
- Wojciech Puławski
- Bioinformatics Laboratory, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland
| | | | - Michał Koliński
- Bioinformatics Laboratory, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland
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13
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Safaeian Laein S, Katouzian I, Mozafari MR, Farnudiyan-Habibi A, Akbarbaglu Z, Shadan MR, Sarabandi K. Biological and thermodynamic stabilization of lipid-based delivery systems through natural biopolymers; controlled release and molecular dynamics simulations. Crit Rev Food Sci Nutr 2023; 64:7728-7747. [PMID: 36950963 DOI: 10.1080/10408398.2023.2191281] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
Nowadays, the use of lipid-based nanocarriers for the targeted and controlled delivery of a variety of hydrophobic and hydrophilic bioactive-compounds and drugs has increased significantly. However, challenges such as thermodynamic instability, oxidation, and degradation of lipid membranes, as well as the unintended release of loaded compounds, have limited the use of these systems in the food and pharmaceutical industries. Therefore, the present study reviews the latest achievements in evaluating the characteristics, production methods, challenges, functional, and biological stabilization strategies of lipid-based carriers (including changes in formulation composition, structural modification, membrane-rigidity, and finally monolayer or multilayer coating with biopolymers) in different conditions, as well as molecular dynamics simulations. The scientists' findings indicate the effect of natural biopolymers (such as chitosan, calcium alginate, pectin, dextran, xanthan, caseins, gelatin, whey-proteins, zein, and etc.) in modifying the external structure of lipid-based carriers, improving thermodynamic stability and resistance of membranes to physicochemical and mechanical tensions. However, depending on the type of bioactive compound as well as the design and production goals of the delivery-system, selecting the appropriate biopolymer has a significant impact on the stability of vesicles and maintaining the bioaccessibility of the loaded-compounds due to the stresses caused by the storage-conditions, formulation, processing and gastrointestinal tract.
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Affiliation(s)
- Sara Safaeian Laein
- Department of Food Hygiene and Aquaculture, Faculty of Veterinary Medicine, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Iman Katouzian
- Australasian Nanoscience and Nanotechnology Initiative (ANNI), Clayton, Victoria, Australia
| | - M R Mozafari
- Australasian Nanoscience and Nanotechnology Initiative (ANNI), Clayton, Victoria, Australia
| | - Amir Farnudiyan-Habibi
- Department of Pharmaceutical Biomaterials, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran
- Nano-Encapsulation in the Food, Nutraceutical, and Pharmaceutical Industries Group (NFNPIG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Zahra Akbarbaglu
- Department of Food Science, College of Agriculture, University of Tabriz, Tabriz, Iran
| | - Mohammad Reza Shadan
- Clinical Immunology Research Center, Zahedan University of Medical Sciences, Zahedan, Iran
- Department of Food science and technology, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran
| | - Khashayar Sarabandi
- Department of Food science and technology, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran
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14
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Xiao X, Robang AS, Sarma S, Le JV, Helmicki ME, Lambert MJ, Guerrero-Ferreira R, Arboleda-Echavarria J, Paravastu AK, Hall CK. Sequence patterns and signatures: Computational and experimental discovery of amyloid-forming peptides. PNAS NEXUS 2022; 1:pgac263. [PMID: 36712347 PMCID: PMC9802472 DOI: 10.1093/pnasnexus/pgac263] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 11/22/2022] [Indexed: 11/27/2022]
Abstract
Screening amino acid sequence space via experiments to discover peptides that self-assemble into amyloid fibrils is challenging. We have developed a computational peptide assembly design (PepAD) algorithm that enables the discovery of amyloid-forming peptides. Discontinuous molecular dynamics (DMD) simulation with the PRIME20 force field combined with the FoldAmyloid tool is used to examine the fibrilization kinetics of PepAD-generated peptides. PepAD screening of ∼10,000 7-mer peptides resulted in twelve top-scoring peptides with two distinct hydration properties. Our studies revealed that eight of the twelve in silico discovered peptides spontaneously form amyloid fibrils in the DMD simulations and that all eight have at least five residues that the FoldAmyloid tool classifies as being aggregation-prone. Based on these observations, we re-examined the PepAD-generated peptides in the sequence pool returned by PepAD and extracted five sequence patterns as well as associated sequence signatures for the 7-mer amyloid-forming peptides. Experimental results from Fourier transform infrared spectroscopy (FTIR), thioflavin T (ThT) fluorescence, circular dichroism (CD), and transmission electron microscopy (TEM) indicate that all the peptides predicted to assemble in silico assemble into antiparallel β-sheet nanofibers in a concentration-dependent manner. This is the first attempt to use a computational approach to search for amyloid-forming peptides based on customized settings. Our efforts facilitate the identification of β-sheet-based self-assembling peptides, and contribute insights towards answering a fundamental scientific question: "What does it take, sequence-wise, for a peptide to self-assemble?".
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Affiliation(s)
| | | | | | - Justin V Le
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Michael E Helmicki
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Matthew J Lambert
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Ricardo Guerrero-Ferreira
- Robert P. Apkarian Integrated Electron Microscopy Core, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Johana Arboleda-Echavarria
- Robert P. Apkarian Integrated Electron Microscopy Core, Emory University School of Medicine, Atlanta, GA 30322, USA
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15
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Böker A, Paul W. Thermodynamics and Conformations of Single Polyalanine, Polyserine, and Polyglutamine Chains within the PRIME20 Model. J Phys Chem B 2022; 126:7286-7297. [DOI: 10.1021/acs.jpcb.2c04360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Arne Böker
- Institut für Physik, Martin Luther-Universität Halle-Wittenberg, von Seckendorff Platz 1, 06120 Halle, Germany
| | - Wolfgang Paul
- Institut für Physik, Martin Luther-Universität Halle-Wittenberg, von Seckendorff Platz 1, 06120 Halle, Germany
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16
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Zhang Y, Wang Y, Xia F, Cao Z, Xu X. Accurate and Efficient Estimation of Lennard-Jones Interactions for Coarse-Grained Particles via a Potential Matching Method. J Chem Theory Comput 2022; 18:4879-4890. [PMID: 35838523 DOI: 10.1021/acs.jctc.2c00513] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The Lennard-Jones (LJ) energy functions are commonly used to describe the nonbonded interactions in bulk coarse-grained (CG) models, which contribute significantly to the stabilization of a local binding configuration or a self-assembly system. In many cases, systematic development of the LJ interaction parameters in a CG model requires a comprehensive sampling of the objective molecules at the all-atom (AA) level, which is therefore extremely time-consuming for large systems. Inspired by the concept of electrostatic potential (ESP), we define the LJ static potential (LJSP), by which the embedding potential energy surface can be constructed analytically. A semianalytic approach, namely, the LJSP matching method, is developed here to derive the CG parameters by minimizing the LJSP difference between the AA and the CG models, which provides a universal way to derive the CG LJ parameters from the AA models without doing presampling. The LJSP matching method is successful not only in deriving the LJ interaction energy landscape in the CG models for proteins, lipids, and DNA but also in reproducing the critical properties such as intermediate structures and enthalpy contributions as exemplified in simulating the self-assembly process of the dipalmitoylphosphatidylcholine (DPPC) lipids.
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Affiliation(s)
- Yuwei Zhang
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Departments of Chemistry, Fudan University, Shanghai 200433, China
| | - Yunchu Wang
- LSEC, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
| | - Fei Xia
- School of Chemistry and Molecular Engineering, NYU-ECNU Center for Computational Chemistry at NYU Shanghai, East China Normal University, Shanghai 200062, China
| | - Zexing Cao
- State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemistry Engineering, Xiamen University, Xiamen 361005, China
| | - Xin Xu
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Departments of Chemistry, Fudan University, Shanghai 200433, China
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17
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Cai X, Han W. Development of a Hybrid-Resolution Force Field for Peptide Self-Assembly Simulations: Optimizing Peptide-Peptide and Peptide-Solvent Interactions. J Chem Inf Model 2022; 62:2744-2760. [PMID: 35561002 DOI: 10.1021/acs.jcim.2c00066] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Atomic descriptions of peptide self-assembly are crucial to an understanding of disease-related peptide aggregation and the design of peptide-assembled materials. Obtaining these descriptions through computer simulation is challenging because current force fields, which were not designed for this process and are often unable to describe correctly peptide self-assembly behavior and the sequence dependence. Here, we developed a framework using dipeptide aggregation as a model system to improve force fields for simulations of self-assembly. Aggregation-related structural properties were designed and used to guide the optimization of peptide-peptide and peptide-solvent interactions. With this framework, we developed a self-assembly force field, termed PACE-ASM, by reoptimizing a hybrid-resolution force field that was originally developed for folding simulation. With its applicability in folding simulations, the new PACE was used to simulate the self-assembly of two disease-related short peptides, Aβ16-21 and PHF6, into β-sheet-rich cross-β amyloids. These simulations reproduced the crystal structures of Aβ16-21 and PHF6 amyloids at near-atomic resolution and captured the difference in packing orientations between the two sequences, a task which is challenging even with all-atom force fields. Apart from cross-β amyloids, the self-assembly of emerging helix-rich cross-α amyloids by another peptide PSMα3 can also be correctly described with the new PACE, manifesting the versatility of the force field. We demonstrated that the ability of the PACE-ASM to model peptide self-assembly is based largely on its improved description of peptide-peptide and peptide-solvent interactions. This was achieved with our optimization framework that can readily identify and address the deficiency in describing these interactions.
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Affiliation(s)
- Xiang Cai
- State Key Laboratory of Chemical Oncogenomics, Guangdong Provincial Key Laboratory of Chemical Genomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Wei Han
- State Key Laboratory of Chemical Oncogenomics, Guangdong Provincial Key Laboratory of Chemical Genomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen 518055, China.,Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China
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18
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Kawamoto S, Liu H, Miyazaki Y, Seo S, Dixit M, DeVane R, MacDermaid C, Fiorin G, Klein ML, Shinoda W. SPICA Force Field for Proteins and Peptides. J Chem Theory Comput 2022; 18:3204-3217. [PMID: 35413197 DOI: 10.1021/acs.jctc.1c01207] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A coarse-grained (CG) model for peptides and proteins was developed as an extension of the Surface Property fItting Coarse grAined (SPICA) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulations with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. An elastic network model was adopted to maintain the secondary structure within a single chain. The side-chain analogues reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable association free energy (potential of mean force) in water compared to those from AA MD. A series of peptides/proteins adsorbed onto or penetrated into the membrane simulated by the CG MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins as comparable to those in the orientations of proteins in membranes (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated the good performance of the SPICA FF.
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Affiliation(s)
- Shuhei Kawamoto
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Huihui Liu
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Yusuke Miyazaki
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan
| | - Sangjae Seo
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Korea Institute of Science and Technology Information, 245 Daehak-ro, Daejeon 34141, Republic of Korea
| | - Mayank Dixit
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Russell DeVane
- Modeling & Simulation, Corporate Research & Development, The Procter and Gamble Company, West Chester, Ohio 45069, United States
| | - Christopher MacDermaid
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Giacomo Fiorin
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Michael L Klein
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Wataru Shinoda
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan.,Department of Chemistry, Faculty of Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan
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19
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Blanco MA. Computational models for studying physical instabilities in high concentration biotherapeutic formulations. MAbs 2022; 14:2044744. [PMID: 35282775 PMCID: PMC8928847 DOI: 10.1080/19420862.2022.2044744] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.
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Affiliation(s)
- Marco A. Blanco
- Materials and Biophysical Characterization, Analytical R & D, Merck & Co., Inc, Kenilworth, NJ USA
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20
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Wong KM, Robang AS, Lint AH, Wang Y, Dong X, Xiao X, Seroski DT, Liu R, Shao Q, Hudalla GA, Hall CK, Paravastu AK. Engineering β-Sheet Peptide Coassemblies for Biomaterial Applications. J Phys Chem B 2021; 125:13599-13609. [PMID: 34905370 DOI: 10.1021/acs.jpcb.1c04873] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Peptide coassembly, wherein at least two different peptides interact to form multicomponent nanostructures, is an attractive approach for generating functional biomaterials. Current efforts seek to design pairs of peptides, A and B, that form nanostructures (e.g., β-sheets with ABABA-type β-strand patterning) while resisting self-assembly (e.g., AAAAA-type or BBBBB-type β-sheets). To confer coassembly behavior, most existing designs have been based on highly charged variants of known self-assembling peptides; like-charge repulsion limits self-assembly while opposite-charge attraction promotes coassembly. Recent analyses using solid-state NMR and coarse-grained simulations reveal that preconceived notions of structure and molecular organization are not always correct. This perspective highlights recent advances and key challenges to understanding and controlling peptide coassembly.
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Affiliation(s)
- Kong M Wong
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Alicia S Robang
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Annabelle H Lint
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yiming Wang
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Xin Dong
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Xingqing Xiao
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Dillon T Seroski
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Drive, Biomedical Sciences J293, P.O. BOX 116131, Gainesville, Florida 32611, United States
| | - Renjie Liu
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Drive, Biomedical Sciences J293, P.O. BOX 116131, Gainesville, Florida 32611, United States
| | - Qing Shao
- Department of Chemical and Materials Engineering, University of Kentucky, Lexington, Kentucky 40506, United States
| | - Gregory A Hudalla
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, 1275 Center Drive, Biomedical Sciences J293, P.O. BOX 116131, Gainesville, Florida 32611, United States
| | - Carol K Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Anant K Paravastu
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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21
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Ng YK, Tajoddin NN, Scrosati PM, Konermann L. Mechanism of Thermal Protein Aggregation: Experiments and Molecular Dynamics Simulations on the High-Temperature Behavior of Myoglobin. J Phys Chem B 2021; 125:13099-13110. [PMID: 34808050 DOI: 10.1021/acs.jpcb.1c07210] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Proteins that encounter unfavorable solvent conditions are prone to aggregation, a phenomenon that remains poorly understood. This work focuses on myoglobin (Mb) as a model protein. Upon heating, Mb produces amorphous aggregates. Thermal unfolding experiments at low concentration (where aggregation is negligible), along with centrifugation assays, imply that Mb aggregation proceeds via globally unfolded conformers. This contrasts studies on other proteins that emphasized the role of partially folded structures as aggregate precursors. Molecular dynamics (MD) simulations were performed to gain insights into the mechanism by which heat-unfolded Mb molecules associate with one another. A prerequisite for these simulations was the development of a method for generating monomeric starting structures. Periodic boundary condition artifacts necessitated the implementation of a partially immobilized water layer lining the walls of the simulation box. Aggregation simulations were performed at 370 K to track the assembly of monomeric Mb into pentameric species. Binding events were preceded by multiple unsuccessful encounters. Even after association, protein-protein contacts remained in flux. Binding was mediated by hydrophobic contacts, along with salt bridges that involved hydrophobically embedded Lys residues. Overall, this work illustrates that atomistic MD simulations are well suited for garnering insights into protein aggregation mechanisms.
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Affiliation(s)
- Yuen Ki Ng
- Department of Chemistry, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Nastaran N Tajoddin
- Department of Chemistry, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Pablo M Scrosati
- Department of Chemistry, The University of Western Ontario, London, Ontario N6A 5B7, Canada
| | - Lars Konermann
- Department of Chemistry, The University of Western Ontario, London, Ontario N6A 5B7, Canada
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22
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Hall CK. Autobiography of Carol K. Hall. J Phys Chem B 2021. [DOI: 10.1021/acs.jpcb.1c07825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
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23
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Sahoo A, Matysiak S. Effects of applied surface-tension on membrane-assisted Aβ aggregation. Phys Chem Chem Phys 2021; 23:20627-20633. [PMID: 34514475 DOI: 10.1039/d1cp02642a] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Accumulation of protein-based (Aβ) aggregates on cellular membranes with varying structural properties is commonly recognized as the key step in Alzheimer's pathogenesis. But experimental and computational challenges have made this biophysical characterization difficult. In particular, studies connecting biological membrane organization and Aβ aggregation are limited. While experiments have suggested that an increased membrane curvature results in faster Aβ peptide aggregation in the context of Alzheimer's disease, a mechanistic explanation for this relation is missing. In this work, we are leveraging molecular simulations with a physics-based coarse grained model to address and understand the relationships between curved cellular membranes and aggregation of a model template peptide Aβ 16-22. In agreement with experimental results, our simulations also suggest a positive correlation between increased peptide aggregation and membrane curvature. More curved membranes have higher lipid packing defects that engage peptide hydrophobic groups and promote faster diffusion leading to peptide fibrillar structures. In addition, we curated the effects of peptide aggregation on the membrane's structure and organization. Interfacial peptide aggregation results in heterogeneous headgroup-peptide interactions and an induced crowding effect at the lipid headgroup region, leading to a more ordered headgroup region and disordered lipid-tails at the membrane core. This work presents a mechanistic and morphological overview of the relationships between the biomembrane local structure and organization, and Aβ peptide aggregation.
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Affiliation(s)
- Abhilash Sahoo
- Biophysics Program, Institute of Physical Science and Technology, University of Maryland, College Park, MD, USA
| | - Silvina Matysiak
- Biophysics Program, Institute of Physical Science and Technology, University of Maryland, College Park, MD, USA.,Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA.
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24
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Liwo A, Czaplewski C, Sieradzan AK, Lipska AG, Samsonov SA, Murarka RK. Theory and Practice of Coarse-Grained Molecular Dynamics of Biologically Important Systems. Biomolecules 2021; 11:1347. [PMID: 34572559 PMCID: PMC8465211 DOI: 10.3390/biom11091347] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 09/03/2021] [Accepted: 09/09/2021] [Indexed: 12/16/2022] Open
Abstract
Molecular dynamics with coarse-grained models is nowadays extensively used to simulate biomolecular systems at large time and size scales, compared to those accessible to all-atom molecular dynamics. In this review article, we describe the physical basis of coarse-grained molecular dynamics, the coarse-grained force fields, the equations of motion and the respective numerical integration algorithms, and selected practical applications of coarse-grained molecular dynamics. We demonstrate that the motion of coarse-grained sites is governed by the potential of mean force and the friction and stochastic forces, resulting from integrating out the secondary degrees of freedom. Consequently, Langevin dynamics is a natural means of describing the motion of a system at the coarse-grained level and the potential of mean force is the physical basis of the coarse-grained force fields. Moreover, the choice of coarse-grained variables and the fact that coarse-grained sites often do not have spherical symmetry implies a non-diagonal inertia tensor. We describe selected coarse-grained models used in molecular dynamics simulations, including the most popular MARTINI model developed by Marrink's group and the UNICORN model of biological macromolecules developed in our laboratory. We conclude by discussing examples of the application of coarse-grained molecular dynamics to study biologically important processes.
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Affiliation(s)
- Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Adam K. Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Agnieszka G. Lipska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Sergey A. Samsonov
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Rajesh K. Murarka
- Department of Chemistry, Indian Institute of Science Education and Research Bhopal, Bhopal Bypass Road, Bhopal 462066, MP, India;
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25
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Xiao X, Wang Y, Seroski DT, Wong KM, Liu R, Paravastu AK, Hudalla GA, Hall CK. De novo design of peptides that coassemble into β sheet-based nanofibrils. SCIENCE ADVANCES 2021; 7:eabf7668. [PMID: 34516924 PMCID: PMC8442925 DOI: 10.1126/sciadv.abf7668] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Peptides’ hierarchical coassembly into nanostructures enables controllable fabrication of multicomponent biomaterials. In this work, we describe a computational and experimental approach to design pairs of charge-complementary peptides that selectively coassemble into β-sheet nanofibers when mixed together but remain unassembled when isolated separately. The key advance is a peptide coassembly design (PepCAD) algorithm that searches for pairs of coassembling peptides. Six peptide pairs are identified from a pool of ~106 candidates via the PepCAD algorithm and then subjected to DMD/PRIME20 simulations to examine their co-/self-association kinetics. The five pairs that spontaneously aggregate in kinetic simulations selectively coassemble in biophysical experiments, with four forming β-sheet nanofibers and one forming a stable nonfibrillar aggregate. Solid-state NMR, which is applied to characterize the coassembling pairs, suggests that the in silico peptides exhibit a higher degree of structural order than the previously reported CATCH(+/−) peptides.
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Affiliation(s)
- Xingqing Xiao
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA
| | - Yiming Wang
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA
| | - Dillon T. Seroski
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Kong M. Wong
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Renjie Liu
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Anant K. Paravastu
- Department of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Gregory A. Hudalla
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA
- Corresponding author.
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26
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Giulini M, Rigoli M, Mattiotti G, Menichetti R, Tarenzi T, Fiorentini R, Potestio R. From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules. Front Mol Biosci 2021; 8:676976. [PMID: 34164432 PMCID: PMC8215203 DOI: 10.3389/fmolb.2021.676976] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 05/06/2021] [Indexed: 12/18/2022] Open
Abstract
The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.
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Affiliation(s)
- Marco Giulini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Marta Rigoli
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Giovanni Mattiotti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Roberto Menichetti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Thomas Tarenzi
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaele Fiorentini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaello Potestio
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
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27
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Trist BG, Hilton JB, Hare DJ, Crouch PJ, Double KL. Superoxide Dismutase 1 in Health and Disease: How a Frontline Antioxidant Becomes Neurotoxic. Angew Chem Int Ed Engl 2021; 60:9215-9246. [PMID: 32144830 PMCID: PMC8247289 DOI: 10.1002/anie.202000451] [Citation(s) in RCA: 98] [Impact Index Per Article: 32.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Indexed: 12/11/2022]
Abstract
Cu/Zn superoxide dismutase (SOD1) is a frontline antioxidant enzyme catalysing superoxide breakdown and is important for most forms of eukaryotic life. The evolution of aerobic respiration by mitochondria increased cellular production of superoxide, resulting in an increased reliance upon SOD1. Consistent with the importance of SOD1 for cellular health, many human diseases of the central nervous system involve perturbations in SOD1 biology. But far from providing a simple demonstration of how disease arises from SOD1 loss-of-function, attempts to elucidate pathways by which atypical SOD1 biology leads to neurodegeneration have revealed unexpectedly complex molecular characteristics delineating healthy, functional SOD1 protein from that which likely contributes to central nervous system disease. This review summarises current understanding of SOD1 biology from SOD1 genetics through to protein function and stability.
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Affiliation(s)
- Benjamin G. Trist
- Brain and Mind Centre and Discipline of PharmacologyThe University of Sydney, CamperdownSydneyNew South Wales2050Australia
| | - James B. Hilton
- Department of Pharmacology and TherapeuticsThe University of MelbourneParkvilleVictoria3052Australia
| | - Dominic J. Hare
- Brain and Mind Centre and Discipline of PharmacologyThe University of Sydney, CamperdownSydneyNew South Wales2050Australia
- School of BioSciencesThe University of MelbourneParkvilleVictoria3052Australia
- Atomic Medicine InitiativeThe University of Technology SydneyBroadwayNew South Wales2007Australia
| | - Peter J. Crouch
- Department of Pharmacology and TherapeuticsThe University of MelbourneParkvilleVictoria3052Australia
| | - Kay L. Double
- Brain and Mind Centre and Discipline of PharmacologyThe University of Sydney, CamperdownSydneyNew South Wales2050Australia
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28
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Gao Y, Saccuzzo EG, Hill SE, Huard DJE, Robang AS, Lieberman RL, Paravastu AK. Structural Arrangement within a Peptide Fibril Derived from the Glaucoma-Associated Myocilin Olfactomedin Domain. J Phys Chem B 2021; 125:2886-2897. [PMID: 33683890 DOI: 10.1021/acs.jpcb.0c11460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Myocilin-associated glaucoma is a new addition to the list of diseases linked to protein misfolding and amyloid formation. Single point variants of the ∼257-residue myocilin olfactomedin domain (mOLF) lead to mutant myocilin aggregation. Here, we analyze the 12-residue peptide P1 (GAVVYSGSLYFQ), corresponding to residues 326-337 of mOLF, previously shown to form amyloid fibrils in vitro and in silico. We applied solid-state NMR structural measurements to test the hypothesis that P1 fibrils adopt one of three predicted structures. Our data are consistent with a U-shaped fibril arrangement for P1, one that is related to the U-shape predicted previously in silico. Our data are also consistent with an antiparallel fibril arrangement, likely driven by terminal electrostatics. Our proposed structural model is reminiscent of fibrils formed by the Aβ(1-40) Iowa mutant peptide, but with a different arrangement of molecular turn regions. Taken together, our results strengthen the connection between mOLF fibrils and the broader amylome and contribute to our understanding of the fundamental molecular interactions governing fibril architecture and stability.
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29
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Bunce SJ, Wang Y, Radford SE, Wilson AJ, Hall CK. Structural insights into peptide self-assembly using photo-induced crosslinking experiments and discontinuous molecular dynamics. AIChE J 2021; 67:e17101. [PMID: 33776061 PMCID: PMC7988534 DOI: 10.1002/aic.17101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 10/07/2020] [Indexed: 11/09/2022]
Abstract
Determining the structure of the (oligomeric) intermediates that form during the self-assembly of amyloidogenic peptides is challenging because of their heterogeneous and dynamic nature. Thus, there is need for methodology to analyze the underlying molecular structure of these transient species. In this work, a combination of fluorescence quenching, photo-induced crosslinking (PIC) and molecular dynamics simulation was used to study the assembly of a synthetic amyloid-forming peptide, Aβ16-22. A PIC amino acid containing a trifluormethyldiazirine (TFMD) group-Fmoc(TFMD)Phe-was incorporated into the sequence (Aβ*16-22). Electrospray ionization ion-mobility spectrometry mass-spectrometry (ESI-IMS-MS) analysis of the PIC products confirmed that Aβ*16-22 forms assemblies with the monomers arranged as anti-parallel, in-register β-strands at all time points during the aggregation assay. The assembly process was also monitored separately using fluorescence quenching to profile the fibril assembly reaction. The molecular picture resulting from discontinuous molecule dynamics simulations showed that Aβ16-22 assembles through a single-step nucleation into a β-sheet fibril in agreement with these experimental observations. This study provides detailed structural insights into the Aβ16-22 self-assembly processes, paving the way to explore the self-assembly mechanism of larger, more complex peptides, including those whose aggregation is responsible for human disease.
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Affiliation(s)
- Samuel J. Bunce
- School of ChemistryUniversity of LeedsLeedsUK
- Astbury Centre for Structural Molecular BiologyUniversity of LeedsLeedsUK
| | - Yiming Wang
- Department of Chemical and Biomolecular EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
- Department of Chemical and Biological EngineeringPrinceton UniversityPrincetonNew JerseyUSA
| | - Sheena E. Radford
- Astbury Centre for Structural Molecular BiologyUniversity of LeedsLeedsUK
- School of Molecular and Cellular BiologyUniversity of LeedsLeedsUK
| | - Andrew J. Wilson
- School of ChemistryUniversity of LeedsLeedsUK
- Astbury Centre for Structural Molecular BiologyUniversity of LeedsLeedsUK
| | - Carol K. Hall
- Department of Chemical and Biomolecular EngineeringNorth Carolina State UniversityRaleighNorth CarolinaUSA
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30
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Nguyen PH, Ramamoorthy A, Sahoo BR, Zheng J, Faller P, Straub JE, Dominguez L, Shea JE, Dokholyan NV, De Simone A, Ma B, Nussinov R, Najafi S, Ngo ST, Loquet A, Chiricotto M, Ganguly P, McCarty J, Li MS, Hall C, Wang Y, Miller Y, Melchionna S, Habenstein B, Timr S, Chen J, Hnath B, Strodel B, Kayed R, Lesné S, Wei G, Sterpone F, Doig AJ, Derreumaux P. Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis. Chem Rev 2021; 121:2545-2647. [PMID: 33543942 PMCID: PMC8836097 DOI: 10.1021/acs.chemrev.0c01122] [Citation(s) in RCA: 412] [Impact Index Per Article: 137.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.
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Affiliation(s)
- Phuong H Nguyen
- CNRS, UPR9080, Université de Paris, Laboratory of Theoretical Biochemistry, IBPC, Fondation Edmond de Rothschild, PSL Research University, Paris 75005, France
| | - Ayyalusamy Ramamoorthy
- Biophysics and Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Bikash R Sahoo
- Biophysics and Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Jie Zheng
- Department of Chemical & Biomolecular Engineering, The University of Akron, Akron, Ohio 44325, United States
| | - Peter Faller
- Institut de Chimie, UMR 7177, CNRS-Université de Strasbourg, 4 rue Blaise Pascal, 67000 Strasbourg, France
| | - John E Straub
- Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, United States
| | - Laura Dominguez
- Facultad de Química, Departamento de Fisicoquímica, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico
| | - Joan-Emma Shea
- Department of Chemistry and Biochemistry, and Department of Physics, University of California, Santa Barbara, California 93106, United States
| | - Nikolay V Dokholyan
- Department of Pharmacology and Biochemistry & Molecular Biology, Penn State University College of Medicine, Hershey, Pennsylvania 17033, United States
- Department of Chemistry, and Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Alfonso De Simone
- Department of Life Sciences, Imperial College London, London SW7 2AZ, U.K
- Molecular Biology, University of Naples Federico II, Naples 80138, Italy
| | - Buyong Ma
- Basic Science Program, Leidos Biomedical Research, Inc., Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland 21702, United States
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, China
| | - Ruth Nussinov
- Basic Science Program, Leidos Biomedical Research, Inc., Cancer and Inflammation Program, National Cancer Institute, Frederick, Maryland 21702, United States
- Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Saeed Najafi
- Department of Chemistry and Biochemistry, and Department of Physics, University of California, Santa Barbara, California 93106, United States
| | - Son Tung Ngo
- Laboratory of Theoretical and Computational Biophysics & Faculty of Applied Sciences, Ton Duc Thang University, 33000 Ho Chi Minh City, Vietnam
| | - Antoine Loquet
- Institute of Chemistry & Biology of Membranes & Nanoobjects, (UMR5248 CBMN), CNRS, Université Bordeaux, Institut Européen de Chimie et Biologie, 33600 Pessac, France
| | - Mara Chiricotto
- Department of Chemical Engineering and Analytical Science, University of Manchester, Manchester M13 9PL, U.K
| | - Pritam Ganguly
- Department of Chemistry and Biochemistry, and Department of Physics, University of California, Santa Barbara, California 93106, United States
| | - James McCarty
- Chemistry Department, Western Washington University, Bellingham, Washington 98225, United States
| | - Mai Suan Li
- Institute for Computational Science and Technology, SBI Building, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City 700000, Vietnam
- Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw, Poland
| | - Carol Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Yiming Wang
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695-7905, United States
| | - Yifat Miller
- Department of Chemistry and The Ilse Katz Institute for Nanoscale Science & Technology, Ben-Gurion University of the Negev, Be'er Sheva 84105, Israel
| | | | - Birgit Habenstein
- Institute of Chemistry & Biology of Membranes & Nanoobjects, (UMR5248 CBMN), CNRS, Université Bordeaux, Institut Européen de Chimie et Biologie, 33600 Pessac, France
| | - Stepan Timr
- CNRS, UPR9080, Université de Paris, Laboratory of Theoretical Biochemistry, IBPC, Fondation Edmond de Rothschild, PSL Research University, Paris 75005, France
| | - Jiaxing Chen
- Department of Pharmacology and Biochemistry & Molecular Biology, Penn State University College of Medicine, Hershey, Pennsylvania 17033, United States
| | - Brianna Hnath
- Department of Pharmacology and Biochemistry & Molecular Biology, Penn State University College of Medicine, Hershey, Pennsylvania 17033, United States
| | - Birgit Strodel
- Institute of Complex Systems: Structural Biochemistry (ICS-6), Forschungszentrum Jülich, 52425 Jülich, Germany
| | - Rakez Kayed
- Mitchell Center for Neurodegenerative Diseases, and Departments of Neurology, Neuroscience and Cell Biology, University of Texas Medical Branch, Galveston, Texas 77555, United States
| | - Sylvain Lesné
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota 55455, United States
| | - Guanghong Wei
- Department of Physics, State Key Laboratory of Surface Physics, and Key Laboratory for Computational Physical Science, Multiscale Research Institute of Complex Systems, Fudan University, Shanghai 200438, China
| | - Fabio Sterpone
- CNRS, UPR9080, Université de Paris, Laboratory of Theoretical Biochemistry, IBPC, Fondation Edmond de Rothschild, PSL Research University, Paris 75005, France
| | - Andrew J Doig
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, U.K
| | - Philippe Derreumaux
- CNRS, UPR9080, Université de Paris, Laboratory of Theoretical Biochemistry, IBPC, Fondation Edmond de Rothschild, PSL Research University, Paris 75005, France
- Laboratory of Theoretical Chemistry, Ton Duc Thang University, 33000 Ho Chi Minh City, Vietnam
- Faculty of Pharmacy, Ton Duc Thang University, 33000 Ho Chi Minh City, Vietnam
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31
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Abstract
Self-assembly of proteins and peptides into the amyloid fold is a widespread phenomenon in the natural world. The structural hallmark of self-assembly into amyloid fibrillar assemblies is the cross-beta motif, which conveys distinct morphological and mechanical properties. The amyloid fibril formation has contrasting results depending on the organism, in the sense that it can bestow an organism with the advantages of mechanical strength and improved functionality or, on the contrary, could give rise to pathological states. In this chapter we review the existing information on amyloid-like peptide aggregates, which could either be derived from protein sequences, but also could be rationally or de novo designed in order to self-assemble into amyloid fibrils under physiological conditions. Moreover, the development of self-assembled fibrillar biomaterials that are tailored for the desired properties towards applications in biomedical or environmental areas is extensively analyzed. We also review computational studies predicting the amyloid propensity of the natural amino acid sequences and the structure of amyloids, as well as designing novel functional amyloid materials.
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Affiliation(s)
- C. Kokotidou
- University of Crete, Department of Materials Science and Technology Voutes Campus GR-70013 Heraklion Crete Greece
- FORTH, Institute for Electronic Structure and Laser N. Plastira 100 GR 70013 Heraklion Greece
| | - P. Tamamis
- Texas A&M University, Artie McFerrin Department of Chemical Engineering College Station Texas 77843-3122 USA
| | - A. Mitraki
- University of Crete, Department of Materials Science and Technology Voutes Campus GR-70013 Heraklion Crete Greece
- FORTH, Institute for Electronic Structure and Laser N. Plastira 100 GR 70013 Heraklion Greece
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32
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Trist BG, Hilton JB, Hare DJ, Crouch PJ, Double KL. Superoxide Dismutase 1 in Health and Disease: How a Frontline Antioxidant Becomes Neurotoxic. Angew Chem Int Ed Engl 2020. [DOI: 10.1002/ange.202000451] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Benjamin G. Trist
- Brain and Mind Centre and Discipline of Pharmacology The University of Sydney, Camperdown Sydney New South Wales 2050 Australia
| | - James B. Hilton
- Department of Pharmacology and Therapeutics The University of Melbourne Parkville Victoria 3052 Australia
| | - Dominic J. Hare
- Brain and Mind Centre and Discipline of Pharmacology The University of Sydney, Camperdown Sydney New South Wales 2050 Australia
- School of BioSciences The University of Melbourne Parkville Victoria 3052 Australia
- Atomic Medicine Initiative The University of Technology Sydney Broadway New South Wales 2007 Australia
| | - Peter J. Crouch
- Department of Pharmacology and Therapeutics The University of Melbourne Parkville Victoria 3052 Australia
| | - Kay L. Double
- Brain and Mind Centre and Discipline of Pharmacology The University of Sydney, Camperdown Sydney New South Wales 2050 Australia
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33
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Wang KW, Wang Y, Hall CK. Development of a coarse-grained lipid model, LIME 2.0, for DSPE using multistate iterative Boltzmann inversion and discontinuous molecular dynamics simulations. FLUID PHASE EQUILIBRIA 2020; 521:112704. [PMID: 37982069 PMCID: PMC10655612 DOI: 10.1016/j.fluid.2020.112704] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
We suggest an improved version of the intermediate resolution implicit solvent model for lipids, LIME, that was previously developed for use with discontinuous molecular dynamics (DMD) simulations. LIME gets its geometrical and the energy parameters between bonded and nonbonded pairs of coarse-grained (CG) sites from atomistic simulations. The improved model, LIME 2.0, uses multiple square wells rather than the single square well used in original LIME to obtain intermolecular interactions that more faithfully mimic those from atomistic simulations. The multi-state iterative Boltzmann inversion (MS-IBI) scheme is used to determine the interaction parameters. This means that a single set of interaction parameters between coarse-grained sites can be used to represent the lipid bilayers at different temperatures. The physical properties of CG DSPE lipid bilayer are calculated using CG simulations and compared to atomistic simulations results to verify the improved model. The phase transition temperature of the lipid bilayer is measured accurately and the lipid translocation phenomenon, " flip-flop" is observed through CG simulation. These results suggest that CG parameterization using multiple square-well and the MS-IBI scheme is well suited to the study of lipid bilayers cross a range of temperatures with DMD simulations.
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Affiliation(s)
- Kye Won Wang
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, 27695
| | - Yiming Wang
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, 27695
| | - Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, 27695
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34
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Ozgur B, Sayar M. Representation of the conformational ensemble of peptides in coarse grained simulations. J Chem Phys 2020; 153:054108. [DOI: 10.1063/5.0012391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
| | - Mehmet Sayar
- Chemical and Biological Engineering and Mechanical Engineering Departments, College of Engineering, Koç University, 34450 Istanbul, Turkey
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35
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Hall CK. A ChemE Grows in Brooklyn. Annu Rev Chem Biomol Eng 2020; 11:1-22. [PMID: 32151158 DOI: 10.1146/annurev-chembioeng-101519-120354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
I profile my personal and professional journey from being a girl of the 1950s, with expectations typical for the times, to a chemical engineering professor and still-enthusiastic researcher. I describe my family, my early education, my college and graduate school training in physics, my postdoc years in chemistry, and my subsequent transformation into a chemical engineering faculty member-one of the first women to be appointed to a chemical engineering faculty in the United States. I focus on the events that shaped me, the people who noticed and supported me, and the environment for women scientists and engineers in what some would call the "early days." My initial research activities centered on applications of statistical mechanics to predict phase equilibria in simple systems. Over time, my interests evolved to focus on applying molecule-level computer simulations to systems of interest to chemical engineers, e.g., hydrocarbons and polymers. Eventually, spurred on by my personal interest in amyloid diseases and my wish to make a contribution to human health, I turned to more biologically oriented problems having to do with protein aggregation and protein design. I give a candid assessment of my strengths and weaknesses, successes and failures. Finally, I share the most valuable lessons that I have learned over a lifetime of professional and personal experience.
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Affiliation(s)
- Carol K Hall
- Chemical and Biomolecular Engineering Department, North Carolina State University, Raleigh, North Carolina 27695, USA;
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36
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Amyloid assembly is dominated by misregistered kinetic traps on an unbiased energy landscape. Proc Natl Acad Sci U S A 2020; 117:10322-10328. [PMID: 32345723 DOI: 10.1073/pnas.1911153117] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Atomistic description of protein fibril formation has been elusive due to the complexity and long time scales of the conformational search. Here, we develop a multiscale approach combining numerous atomistic simulations in explicit solvent to construct Markov State Models (MSMs) of fibril growth. The search for the in-register fully bound fibril state is modeled as a random walk on a rugged two-dimensional energy landscape defined by β-sheet alignment and hydrogen-bonding states, whereas transitions involving states without hydrogen bonds are derived from kinetic clustering. The reversible association/dissociation of an incoming peptide and overall growth kinetics are then computed from MSM simulations. This approach is applied to derive a parameter-free, comprehensive description of fibril elongation of Aβ16-22 and how it is modulated by phenylalanine-to-cyclohexylalanine (CHA) mutations. The trajectories show an aggregation mechanism in which the peptide spends most of its time trapped in misregistered β-sheet states connected by weakly bound states twith short lifetimes. Our results recapitulate the experimental observation that mutants CHA19 and CHA1920 accelerate fibril elongation but have a relatively minor effect on the critical concentration for fibril growth. Importantly, the kinetic consequences of mutations arise from cumulative effects of perturbing the network of productive and nonproductive pathways of fibril growth. This is consistent with the expectation that nonfunctional states will not have evolved efficient folding pathways and, therefore, will require a random search of configuration space. This study highlights the importance of describing the complete energy landscape when studying the elongation mechanism and kinetics of protein fibrils.
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37
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Wong KM, Wang Y, Seroski DT, Larkin GE, Mehta AK, Hudalla GA, Hall CK, Paravastu AK. Molecular complementarity and structural heterogeneity within co-assembled peptide β-sheet nanofibers. NANOSCALE 2020; 12:4506-4518. [PMID: 32039428 DOI: 10.1039/c9nr08725g] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Self-assembling peptides have garnered an increasing amount of interest as a functional biomaterial for medical and biotechnological applications. Recently, β-sheet peptide designs utilizing complementary pairs of peptides composed of charged amino acids positioned to impart co-assembly behavior have expanded the portfolio of peptide aggregate structures. Structural characterization of these charge-complementary peptide co-assemblies has been limited. Thus, it is not known how the complementary peptides organize on the molecular level. Through a combination of solid-state NMR measurements and discontinuous molecular dynamics simulations, we investigate the molecular organization of King-Webb peptide nanofibers. KW+ and KW- peptides co-assemble into near stoichiometric two-component β-sheet structures as observed by computational simulations and 13C-13C dipolar couplings. A majority of β-strands are aligned with antiparallel nearest neighbors within the β-sheet as previously suggested by Fourier transform infrared spectroscopy measurements. Surprisingly, however, a significant proportion of β-strand neighbors are parallel. While charge-complementary peptides were previously assumed to organize in an ideal (AB)n pattern, dipolar recoupling measurements on isotopically diluted nanofiber samples reveal a non-negligible amount of self-associated (AA and BB) pairs. Furthermore, computational simulations predict these different structures can coexist within the same nanofiber. Our results highlight structural disorder at the molecular level in a charge-complementary peptide system with implications on co-assembling peptide designs.
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Affiliation(s)
- Kong M Wong
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
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38
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Abstract
Peptide self-assembly, wherein molecule A associates with other A molecules to form fibrillar β-sheet structures, is common in nature and widely used to fabricate synthetic biomaterials. Selective coassembly of peptide pairs A and B with complementary partial charges is gaining interest due to its potential for expanding the form and function of biomaterials that can be realized. It has been hypothesized that charge-complementary peptides organize into alternating ABAB-type arrangements within assembled β-sheets, but no direct molecular-level evidence exists to support this interpretation. We report a computational and experimental approach to characterize molecular-level organization of the established peptide pair, CATCH. Discontinuous molecular dynamics simulations predict that CATCH(+) and CATCH(-) peptides coassemble but do not self-assemble. Two-layer β-sheet amyloid structures predominate, but off-pathway β-barrel oligomers are also predicted. At low concentration, transmission electron microscopy and dynamic light scattering identified nonfibrillar ∼20-nm oligomers, while at high concentrations elongated fibers predominated. Thioflavin T fluorimetry estimates rapid and near-stoichiometric coassembly of CATCH(+) and CATCH(-) at concentrations ≥100 μM. Natural abundance 13C NMR and isotope-edited Fourier transform infrared spectroscopy indicate that CATCH(+) and CATCH(-) coassemble into two-component nanofibers instead of self-sorting. However, 13C-13C dipolar recoupling solid-state NMR measurements also identify nonnegligible AA and BB interactions among a majority of AB pairs. Collectively, these results demonstrate that strictly alternating arrangements of β-strands predominate in coassembled CATCH structures, but deviations from perfect alternation occur. Off-pathway β-barrel oligomers are also suggested to occur in coassembled β-strand peptide systems.
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39
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Theoretical and computational advances in protein misfolding. ADVANCES IN PROTEIN CHEMISTRY AND STRUCTURAL BIOLOGY 2020; 118:1-31. [PMID: 31928722 DOI: 10.1016/bs.apcsb.2019.08.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
Misfolded proteins escape the cellular quality control mechanism and fail to fold properly or remain correctly folded leading to a loss in their functional specificity. Thus misfolding of proteins cause a large number of very different diseases ranging from errors in metabolism to various types of complex neurodegenerative diseases. A theoretical and computational perspective of protein misfolding is presented with a special emphasis on its salient features, mechanism and consequences. These insights quantitatively analyze different determinants of misfolding, that may be applied to design disease specific molecular targets.
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40
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Rajagopal N, Irudayanathan FJ, Nangia S. Computational Nanoscopy of Tight Junctions at the Blood-Brain Barrier Interface. Int J Mol Sci 2019; 20:E5583. [PMID: 31717316 PMCID: PMC6888702 DOI: 10.3390/ijms20225583] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 11/05/2019] [Accepted: 11/06/2019] [Indexed: 12/16/2022] Open
Abstract
The selectivity of the blood-brain barrier (BBB) is primarily maintained by tight junctions (TJs), which act as gatekeepers of the paracellular space by blocking blood-borne toxins, drugs, and pathogens from entering the brain. The BBB presents a significant challenge in designing neurotherapeutics, so a comprehensive understanding of the TJ architecture can aid in the design of novel therapeutics. Unraveling the intricacies of TJs with conventional experimental techniques alone is challenging, but recently developed computational tools can provide a valuable molecular-level understanding of TJ architecture. We employed the computational methods toolkit to investigate claudin-5, a highly expressed TJ protein at the BBB interface. Our approach started with the prediction of claudin-5 structure, evaluation of stable dimer conformations and nanoscale assemblies, followed by the impact of lipid environments, and posttranslational modifications on these claudin-5 assemblies. These led to the study of TJ pores and barriers and finally understanding of ion and small molecule transport through the TJs. Some of these in silico, molecular-level findings, will need to be corroborated by future experiments. The resulting understanding can be advantageous towards the eventual goal of drug delivery across the BBB. This review provides key insights gleaned from a series of state-of-the-art nanoscale simulations (or computational nanoscopy studies) performed on the TJ architecture.
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Affiliation(s)
| | | | - Shikha Nangia
- Department of Biomedical and Chemical Engineering, Syracuse University, Syracuse, NY 13244, USA
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41
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Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications. Int J Mol Sci 2019; 20:ijms20153774. [PMID: 31375023 PMCID: PMC6696403 DOI: 10.3390/ijms20153774] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 07/28/2019] [Accepted: 07/30/2019] [Indexed: 12/23/2022] Open
Abstract
Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.
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42
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Szała B, Molski A. Aggregation kinetics of short peptides: All-atom and coarse-grained molecular dynamics study. Biophys Chem 2019; 253:106219. [PMID: 31301554 DOI: 10.1016/j.bpc.2019.106219] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Revised: 06/14/2019] [Accepted: 07/03/2019] [Indexed: 11/30/2022]
Abstract
Peptides can aggregate into ordered structures with different morphologies. The aggregation mechanism and evolving structures are the subject of intense research. In this paper we have used molecular dynamics to examine the sequence-dependence of aggregation kinetics for three short peptides: octaalanine (Ala8), octaasparagine (Asn8), and the heptapeptide GNNQQNY (abbreviated as GNN). First, we compared the aggregation of 20 randomly distributed peptides using the coarse-grained MARTINI force field and the atomistic OPLS-AA force field. We found that the MARTINI and OPLS-AA aggregation kinetics are similar for Ala8, Asn8, and GNN. Second, we used the MARTINI force field to study the early stages of aggregation kinetics for a larger system with 72 peptides. In the initial stage of aggregation small clusters grow by monomer addition. In the second stage, when the free monomers are depleted, the dominant cluster growth path is cluster-cluster coalescence. We quantified the aggregation kinetics in terms of rate equations. Our study shows that the initial aggregation kinetics are similar for Ala8, Asn8, and GNN but the molecular details can be different, especially for MARTINI Ala8. We hypothesize that peptide aggregation proceed in two steps. In the first step amorphous aggregates are formed, and then, in the second step, they reorganize into ordered structures. We conclude that sequence-specific differences show up in the second step of aggregation.
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Affiliation(s)
- Beata Szała
- Adam Mickiewicz University in Poznań, Faculty of Chemistry, Umultowska 89b, 61-614 Poznań, Poland.
| | - Andrzej Molski
- Adam Mickiewicz University in Poznań, Faculty of Chemistry, Umultowska 89b, 61-614 Poznań, Poland.
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43
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Bunce SJ, Wang Y, Stewart KL, Ashcroft AE, Radford SE, Hall CK, Wilson AJ. Molecular insights into the surface-catalyzed secondary nucleation of amyloid-β 40 (Aβ 40) by the peptide fragment Aβ 16-22. SCIENCE ADVANCES 2019; 5:eaav8216. [PMID: 31245536 PMCID: PMC6588359 DOI: 10.1126/sciadv.aav8216] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 05/15/2019] [Indexed: 05/15/2023]
Abstract
Understanding the structural mechanism by which proteins and peptides aggregate is crucial, given the role of fibrillar aggregates in debilitating amyloid diseases and bioinspired materials. Yet, this is a major challenge as the assembly involves multiple heterogeneous and transient intermediates. Here, we analyze the co-aggregation of Aβ40 and Aβ16-22, two widely studied peptide fragments of Aβ42 implicated in Alzheimer's disease. We demonstrate that Aβ16-22 increases the aggregation rate of Aβ40 through a surface-catalyzed secondary nucleation mechanism. Discontinuous molecular dynamics simulations allowed aggregation to be tracked from the initial random coil monomer to the catalysis of nucleation on the fibril surface. Together, the results provide insight into how dynamic interactions between Aβ40 monomers/oligomers on the surface of preformed Aβ16-22 fibrils nucleate Aβ40 amyloid assembly. This new understanding may facilitate development of surfaces designed to enhance or suppress secondary nucleation and hence to control the rates and products of fibril assembly.
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Affiliation(s)
- Samuel J. Bunce
- School of Chemistry, University of Leeds, Leeds LS2 9JT, UK
- Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK
| | - Yiming Wang
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA
| | - Katie L. Stewart
- Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK
| | - Alison E. Ashcroft
- Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK
| | - Sheena E. Radford
- Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK
- School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK
- Corresponding author. (S.E.R.); (C.K.H.); (A.J.W.)
| | - Carol K. Hall
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA
- Corresponding author. (S.E.R.); (C.K.H.); (A.J.W.)
| | - Andrew J. Wilson
- School of Chemistry, University of Leeds, Leeds LS2 9JT, UK
- Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, UK
- Corresponding author. (S.E.R.); (C.K.H.); (A.J.W.)
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44
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Patterson-Orazem AC, Hill SE, Wang Y, Dominic IM, Hall CK, Lieberman RL. Differential Misfolding Properties of Glaucoma-Associated Olfactomedin Domains from Humans and Mice. Biochemistry 2019; 58:1718-1727. [PMID: 30802039 DOI: 10.1021/acs.biochem.8b01309] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Mutations in myocilin, predominantly within its olfactomedin (OLF) domain, are causative for the heritable form of open angle glaucoma in humans. Surprisingly, mice expressing Tyr423His mutant myocilin, corresponding to a severe glaucoma-causing mutation (Tyr437His) in human subjects, exhibit a weak, if any, glaucoma phenotype. To address possible protein-level discrepancies between mouse and human OLFs, which might lead to this outcome, biophysical properties of mouse OLF were characterized for comparison with those of human OLF. The 1.55 Å resolution crystal structure of mouse OLF reveals an asymmetric 5-bladed β-propeller that is nearly indistinguishable from previous structures of human OLF. Wild-type and selected mutant mouse OLFs mirror thermal stabilities of their human OLF counterparts, including characteristic stabilization in the presence of calcium. Mouse OLF forms thioflavin T-positive aggregates with a similar end-point morphology as human OLF, but amyloid aggregation kinetic rates of mouse OLF are faster than human OLF. Simulations and experiments support the interpretation that kinetics of mouse OLF are faster because of a decreased charge repulsion arising from more neutral surface electrostatics. Taken together, phenotypic differences observed in mouse and human studies of mutant myocilin could be a function of aggregation kinetics rates, which would alter the lifetime of putatively toxic protofibrillar intermediates.
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Affiliation(s)
- Athéna C Patterson-Orazem
- School of Chemistry & Biochemistry , Georgia Institute of Technology , Atlanta , Georgia 30332-0400 , United States
| | - Shannon E Hill
- School of Chemistry & Biochemistry , Georgia Institute of Technology , Atlanta , Georgia 30332-0400 , United States
| | - Yiming Wang
- Department of Chemical & Biomolecular Engineering , North Carolina State University , Raleigh , North Carolina 27695-7905 , United States
| | - Iramofu M Dominic
- School of Chemistry & Biochemistry , Georgia Institute of Technology , Atlanta , Georgia 30332-0400 , United States
| | - Carol K Hall
- Department of Chemical & Biomolecular Engineering , North Carolina State University , Raleigh , North Carolina 27695-7905 , United States
| | - Raquel L Lieberman
- School of Chemistry & Biochemistry , Georgia Institute of Technology , Atlanta , Georgia 30332-0400 , United States
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45
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Abstract
The aggregation of monomeric amyloid β protein (Aβ) peptide into oligomers and amyloid fibrils in the mammalian brain is associated with Alzheimer's disease. Insight into the thermodynamic stability of the Aβ peptide in different polymeric states is fundamental to defining and predicting the aggregation process. Experimental determination of Aβ thermodynamic behavior is challenging due to the transient nature of Aβ oligomers and the low peptide solubility. Furthermore, quantitative calculation of a thermodynamic phase diagram for a specific peptide requires extremely long computational times. Here, using a coarse-grained protein model, molecular dynamics (MD) simulations are performed to determine an equilibrium concentration and temperature phase diagram for the amyloidogenic peptide fragment Aβ16-22 Our results reveal that the only thermodynamically stable phases are the solution phase and the macroscopic fibrillar phase, and that there also exists a hierarchy of metastable phases. The boundary line between the solution phase and fibril phase is found by calculating the temperature-dependent solubility of a macroscopic Aβ16-22 fibril consisting of an infinite number of β-sheet layers. This in silico determination of an equilibrium (solubility) phase diagram for a real amyloid-forming peptide, Aβ16-22, over the temperature range of 277-330 K agrees well with fibrillation experiments and transmission electron microscopy (TEM) measurements of the fibril morphologies formed. This in silico approach of predicting peptide solubility is also potentially useful for optimizing biopharmaceutical production and manufacturing nanofiber scaffolds for tissue engineering.
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46
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Sahoo A, Matysiak S. Computational insights into lipid assisted peptide misfolding and aggregation in neurodegeneration. Phys Chem Chem Phys 2019; 21:22679-22694. [DOI: 10.1039/c9cp02765c] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
An overview of recent advances in computational investigation of peptide–lipid interactions in neurodegeneration – Alzheimer's, Parkinson's and Huntington's disease.
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Affiliation(s)
- Abhilash Sahoo
- Biophysics Program
- Institute of Physical Science and Technology
- University of Maryland
- College Park
- USA
| | - Silvina Matysiak
- Biophysics Program
- Institute of Physical Science and Technology
- University of Maryland
- College Park
- USA
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47
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Sahoo A, Xu H, Matysiak S. Pathways of amyloid-beta absorption and aggregation in a membranous environment. Phys Chem Chem Phys 2019; 21:8559-8568. [PMID: 30964132 DOI: 10.1039/c9cp00040b] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Aggregation of misfolded oligomeric amyloid-beta (Aβ) peptides on lipid membranes has been identified as a primary event in Alzheimer's pathogenesis. However, the structural and dynamical features of this membrane assisted Aβ aggregation have not been well characterized. The microscopic characterization of dynamic molecular-level interactions in peptide aggregation pathways has been challenging both computationally and experimentally. In this work, we explore differential patterns of membrane-induced Aβ 16-22 (K-L-V-F-F-A-E) aggregation from the microscopic perspective of molecular interactions. Physics-based coarse-grained molecular dynamics (CG-MD) simulations were employed to investigate the effect of lipid headgroup charge - zwitterionic (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine: POPC) and anionic (1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-l-serine: POPS) - on Aβ 16-22 peptide aggregation. Our analyses present an extensive overview of multiple pathways for peptide absorption and biomechanical forces governing peptide folding and aggregation. In agreement with experimental observations, anionic POPS molecules promote extended configurations in Aβ peptides that contribute towards faster emergence of ordered β-sheet-rich peptide assemblies compared to POPC, suggesting faster fibrillation. In addition, lower cumulative rates of peptide aggregation in POPS due to higher peptide-lipid interactions and slower lipid diffusion result in multiple distinct ordered peptide aggregates that can serve as nucleation seeds for subsequent Aβ aggregation. This study provides an in-silico assessment of experimentally observed aggregation patterns, presents new morphological insights and highlights the importance of lipid headgroup chemistry in modulating the peptide absorption and aggregation process.
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Affiliation(s)
- Abhilash Sahoo
- Biophysics Program, Institute of Physical Science and Technology, University of Maryland, College Park, MD, USA.
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48
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Conformational preferences and phase behavior of intrinsically disordered low complexity sequences: insights from multiscale simulations. Curr Opin Struct Biol 2018; 56:1-10. [PMID: 30439585 DOI: 10.1016/j.sbi.2018.10.003] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 10/17/2018] [Accepted: 10/19/2018] [Indexed: 11/22/2022]
Abstract
While many proteins and protein regions utilize a complex repertoire of amino acids to achieve their biological function, a subset of protein sequences are enriched in a reduced set of amino acids. These so-called low complexity (LC) sequences, specifically intrinsically disordered variants of LC sequences, have been the focus of recent investigations owing to their roles in a range of biological functions, specifically phase separation. Computational studies of LC sequences have provided rich insights into their behavior both as individual proteins in dilute solutions and as the drivers and modulators of higher-order assemblies. Here, we review how simulations performed across distinct resolutions have provided different types of insights into the biological role of LC sequences.
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49
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Pylaeva S, Böker A, Elgabarty H, Paul W, Sebastiani D. The Conformational Ensemble of Polyglutamine-14 Chains: Specific Influences of Solubility Tail and Chromophores. Chemphyschem 2018; 19:2931-2937. [PMID: 30106503 DOI: 10.1002/cphc.201800551] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Indexed: 11/11/2022]
Abstract
We address polyglutamine-14 in aqueous solution with specific chromophores and a solubility chain by means of a multiscale simulation approach, combining atomistic molecular dynamics simulations and coarse-grained Monte-Carlo conformational sampling. Despite the intrinsically disordered nature of the amyloidogenic polyglutamine, we observe transient characteristic structural motifs which exhibit a specific hydrogen bonding pattern. We illustrate the relationship between structure pattern and the distance distribution of a pair of chromophores attached to the peptide termini, in light of specific influence of a short solubility tail and the chromophores themselves on the conformational ensemble.
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Affiliation(s)
- Svetlana Pylaeva
- Chemistry Department, MLU Halle-Wittenberg, 06120, Halle (Saale), Germany
| | - Arne Böker
- Physics Department, MLU Halle-Wittenberg, 06120, Halle (Saale), Germany
| | - Hossam Elgabarty
- Chemistry Department, MLU Halle-Wittenberg, 06120, Halle (Saale), Germany
| | - Wolfgang Paul
- Physics Department, MLU Halle-Wittenberg, 06120, Halle (Saale), Germany
| | - Daniel Sebastiani
- Chemistry Department, MLU Halle-Wittenberg, 06120, Halle (Saale), Germany
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50
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Mioduszewski Ł, Cieplak M. Disordered peptide chains in an α-C-based coarse-grained model. Phys Chem Chem Phys 2018; 20:19057-19070. [PMID: 29972174 DOI: 10.1039/c8cp03309a] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
We construct a one-bead-per-residue coarse-grained dynamical model to describe intrinsically disordered proteins at significantly longer timescales than in the all-atom models. In this model, inter-residue contacts form and disappear during the course of the time evolution. The contacts may arise between the sidechains, the backbones or the sidechains and backbones of the interacting residues. The model yields results that are consistent with many all-atom and experimental data on these systems. We demonstrate that the geometrical properties of various homopeptides differ substantially in this model. In particular, the average radius of gyration scales with the sequence length in a residue-dependent manner.
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Affiliation(s)
- Łukasz Mioduszewski
- Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland.
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