1
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Tolstova AP, Makarov AA, Adzhubei AA. Structure Comparison of Beta Amyloid Peptide Aβ 1-42 Isoforms. Molecular Dynamics Modeling. J Chem Inf Model 2024; 64:918-932. [PMID: 38241093 DOI: 10.1021/acs.jcim.3c01624] [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: 01/21/2024]
Abstract
Beta amyloid peptide Aβ 1-42 (Aβ42) has a unique dual role in the human organism, as both the peptide with an important physiological function and one of the most toxic biological compounds provoking Alzheimer's disease (AD). There are several known Aβ42 isoforms that we discuss here that are highly neurotoxic and lead to the early onset of AD. Aβ42 is an intrinsically disordered protein with no experimentally solved structure under physiological conditions. The objective of this research was to establish the appropriate molecular dynamics (MD) methodology and model a uniform set of structures for the Aβ42 isoforms that form the core of this study. For that purpose, force field selection and verification including convergence testing for MD simulations was made. Replica exchange MD and conventional MD modeling of several Aβ42 and Aβ16 isoforms that have neurotoxic and amyloidogenic effects impacting the severity of Alzheimer's disease were carried out with the optimal force field and solvent parameters. A standardized ensemble of structures for the Aβ42 and Aβ16 isoforms covering 30-50% of the conformational ensembles extracted from the free energy minima was calculated from MD trajectories. The resulting data set of modeled structures includes Aβ42 wild type, isoD7, pS8, D7H, and H6R-Aβ42 and Aβ16 wild type, isoD7, pS8, D7H, and H6R-Aβ16. The representative structures are given in the Supporting Information; they are open for public access. In the study, we also evaluated the differences between the structures of Aβ42 isoforms and speculate on their possible relevance to the known functions. Utilizing several representative structures for a single disordered protein for docking, with their subsequent averaging by conformations, would markedly increase the reliability of docking results.
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Affiliation(s)
- Anna P Tolstova
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia
| | - Alexander A Makarov
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia
| | - Alexei A Adzhubei
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia
- Washington University School of Medicine and Health Sciences, Washington 20052, D.C., United States
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2
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Coppa C, Bazzoli A, Barkhordari M, Contini A. Accelerated Molecular Dynamics for Peptide Folding: Benchmarking Different Combinations of Force Fields and Explicit Solvent Models. J Chem Inf Model 2023; 63:3030-3042. [PMID: 37163419 DOI: 10.1021/acs.jcim.3c00138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Accelerated molecular dynamics (aMD) protocols were assessed on predicting the secondary structure of eight peptides, of which two are helical, three are β-hairpins, and three are disordered. Protocols consisted of combinations of three force fields (ff99SB, ff14SB, ff19SB) and two explicit solvation models (TIP3P and OPC), and were evaluated in two independent aMD simulations, one starting from an extended conformation, the other starting from a misfolded conformation. The results of these analyses indicate that all three combinations performed well on helical peptides. As for β-hairpins, ff19SB performed well with both solvation methods, with a slight preference for the TIP3P solvation model, even though performance was dependent on both peptide sequence and initial conformation. The ff19SB/OPC combination had the best performance on intrinsically disordered peptides. In general, ff14SB/TIP3P suffered the strongest helical bias.
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Affiliation(s)
- Crescenzo Coppa
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Andrea Bazzoli
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Maral Barkhordari
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Alessandro Contini
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
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3
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Kragelj J, Dumarieh R, Xiao Y, Frederick KK. Conformational ensembles explain NMR spectra of frozen intrinsically disordered proteins. Protein Sci 2023; 32:e4628. [PMID: 36930141 PMCID: PMC10108432 DOI: 10.1002/pro.4628] [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: 11/15/2022] [Revised: 03/12/2023] [Accepted: 03/14/2023] [Indexed: 03/18/2023]
Abstract
Protein regions which are intrinsically disordered, exist as an ensemble of rapidly interconverting structures. Cooling proteins to cryogenic temperatures for dynamic nuclear polarization (DNP) magic angle spinning (MAS) NMR studies suspends most of the motions, resulting in peaks that are broad but not featureless. To demonstrate that detailed conformational restraints can be retrieved from the peak shapes of frozen proteins alone, we developed and used a simulation framework to assign peak features to conformers in the ensemble. We validated our simulations by comparing them to spectra of α-synuclein acquired under different experimental conditions. Our assignments of peaks to discrete dihedral angle populations suggest that structural constraints are attainable under cryogenic conditions. The ability to infer ensemble populations from peak shapes has important implications for DNP MAS NMR studies of proteins with regions of disorder in living cells because chemical shifts are the most accessible measured parameter.
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Affiliation(s)
- Jaka Kragelj
- Department of BiophysicsUT Southwestern Medical CenterDallasTexas75390‐8816USA
- Present address:
National Institute of ChemistryHajdrihova 191001LjubljanaSlovenia
| | - Rania Dumarieh
- Department of BiophysicsUT Southwestern Medical CenterDallasTexas75390‐8816USA
| | - Yiling Xiao
- Department of BiophysicsUT Southwestern Medical CenterDallasTexas75390‐8816USA
| | - Kendra K. Frederick
- Department of BiophysicsUT Southwestern Medical CenterDallasTexas75390‐8816USA
- Center for Alzheimer's and Neurodegenerative DiseaseUT Southwestern Medical CenterDallasTexas75390USA
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4
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Wu J, Gao T, Guo H, Zhao L, Lv S, Lv J, Yao R, Yu Y, Ma F. Application of molecular dynamics simulation for exploring the roles of plant biomolecules in promoting environmental health. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161871. [PMID: 36708839 DOI: 10.1016/j.scitotenv.2023.161871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 06/18/2023]
Abstract
Understanding the dynamic changes of plant biomolecules is vital for exploring their mechanisms in the environment. Molecular dynamics (MD) simulation has been widely used to study structural evolution and corresponding properties of plant biomolecules at the microscopic scale. Here, this review (i) outlines structural properties of plant biomolecules, and the crucial role of MD simulation in advancing studies of the biomolecules; (ii) describes the development of MD simulation in plant biomolecules, determinants of simulation, and analysis parameters; (iii) introduces the applications of MD simulation in plant biomolecules, including the response of the biomolecules to multiple stresses, their roles in corrosive environments, and their contributions in improving environmental health; (iv) reviews techniques integrated with MD simulation, such as molecular biology, quantum mechanics, molecular docking, and machine learning modeling, which bridge gaps in MD simulation. Finally, we make suggestions on determination of force field types, investigation of plant biomolecule mechanisms, and use of MD simulation in combination with other techniques. This review provides comprehensive summaries of the mechanisms of plant biomolecules in the environment revealed by MD simulation and validates it as an applicable tool for bridging gaps between macroscopic and microscopic behavior, providing insights into the wide application of MD simulation in plant biomolecules.
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Affiliation(s)
- Jieting Wu
- School of Environmental Science, Liaoning University, Shenyang 110036, People's Republic of China.
| | - Tian Gao
- School of Environmental Science, Liaoning University, Shenyang 110036, People's Republic of China
| | - Haijuan Guo
- School of Environmental Science, Liaoning University, Shenyang 110036, People's Republic of China
| | - Lei Zhao
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, People's Republic of China
| | - Sidi Lv
- School of Environmental Science, Liaoning University, Shenyang 110036, People's Republic of China
| | - Jin Lv
- School of Environmental Science, Liaoning University, Shenyang 110036, People's Republic of China
| | - Ruyi Yao
- School of Environmental Science, Liaoning University, Shenyang 110036, People's Republic of China
| | - Yanyi Yu
- School of Environmental Science, Liaoning University, Shenyang 110036, People's Republic of China
| | - Fang Ma
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, People's Republic of China
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5
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Amundarain MJ, Vietri A, Dodero VI, Costabel MD. IDP Force Fields Applied to Model PPII-Rich 33-mer Gliadin Peptides. J Phys Chem B 2023; 127:2407-2417. [PMID: 36884001 DOI: 10.1021/acs.jpcb.3c00200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
The 33-mer gliadin peptide and its deamidated metabolite, 33-mer DGP, are the immunodominant peptides responsible for the adaptive immune response in celiac disease (CD). CD is a complex autoimmune chronic disorder triggered by gluten ingestion that affects the small intestine and affects ∼1% of the global population. The 33-mers are polyproline II-rich (PPII) and intrinsically disordered peptides (IDPs), whose structures remain elusive. We sampled the conformational ensembles of both 33-mer peptides via molecular dynamics simulations employing two force fields (FFs) (Amber ff03ws and Amber ff99SB-disp) specifically validated for other IDPs. Our results show that both FFs allow the extensive exploration of the conformational landscape, which was not possible with the standard FF GROMOS53A6 reported before. Clustering analysis of the trajectories showed that the five largest clusters (78-88% of the total structures) present elongated, semielongated, and curved conformations in both FFs. Large average radius of gyration and solvent-exposed surfaces characterized these structures. While the structures sampled are similar, the Amber ff99SB-disp trajectories explored folded conformations with a higher probability. In addition, PPII secondary structure was preserved throughout the trajectories (58-73%) together with a non-negligible content of β structures (11-23%), in agreement with previous experimental results. This work represents the initial step in studying further the interaction of these peptides with other biologically relevant molecules, which could lead to finally disclose the molecular events that lead to CD.
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Affiliation(s)
- María J Amundarain
- Departamento de Física, Instituto de Física del Sur (IFISUR), Universidad Nacional del Sur (UNS), CONICET, Avenida Leandro N. Alem 1253, B8000CPB Bahía Blanca, Argentina
- Department of Chemistry, Organic Chemistry III, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany
| | - Agustín Vietri
- Departamento de Física, Instituto de Física del Sur (IFISUR), Universidad Nacional del Sur (UNS), CONICET, Avenida Leandro N. Alem 1253, B8000CPB Bahía Blanca, Argentina
| | - Verónica I Dodero
- Department of Chemistry, Organic Chemistry III, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany
| | - Marcelo D Costabel
- Departamento de Física, Instituto de Física del Sur (IFISUR), Universidad Nacional del Sur (UNS), CONICET, Avenida Leandro N. Alem 1253, B8000CPB Bahía Blanca, Argentina
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6
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Moore SJ, Deplazes E, Mancera RL. Influence of force field choice on the conformational landscape of rat and human islet amyloid polypeptide. Proteins 2023; 91:338-353. [PMID: 36163697 PMCID: PMC10092333 DOI: 10.1002/prot.26432] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 02/04/2023]
Abstract
Human islet amyloid polypeptide (hIAPP) is a naturally occurring, intrinsically disordered protein (IDP) whose abnormal aggregation into toxic soluble oligomers and insoluble amyloid fibrils is a pathological feature in type-2 diabetes. Rat IAPP (rIAPP) differs from hIAPP by only six amino acids yet has a reduced tendency to aggregate or form fibrils. The structures of the monomeric forms of IAPP are difficult to characterize due to their intrinsically disordered nature. Molecular dynamics simulations can provide a detailed characterization of the monomeric forms of rIAPP and hIAPP in near-physiological conditions. In this work, the conformational landscapes of rIAPP and hIAPP as a function of secondary structure content were predicted using well-tempered bias exchange metadynamics simulations. Several combinations of commonly used biomolecular force fields and water models were tested. The predicted conformational preferences of both rIAPP and hIAPP are typical of IDPs, exhibiting dominant random coil structures but showing a low propensity for transient α-helical conformations. Predicted nuclear magnetic resonance Cα chemical shifts reveal different preferences with each force field towards certain conformations, with AMBERff99SBnmr2/TIP4Pd showing the best agreement with the experiment. Comparisons of secondary structure content demonstrate residue-specific differences between hIAPP and rIAPP that may reflect their different aggregation propensities.
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Affiliation(s)
- Sandra J Moore
- Curtin Medical School, Curtin Health Innovation Research Institute, Curtin Institute for Computation, Curtin University, Perth, Western Australia, Australia
| | - Evelyne Deplazes
- Curtin Medical School, Curtin Health Innovation Research Institute, Curtin Institute for Computation, Curtin University, Perth, Western Australia, Australia.,School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, Australia
| | - Ricardo L Mancera
- Curtin Medical School, Curtin Health Innovation Research Institute, Curtin Institute for Computation, Curtin University, Perth, Western Australia, Australia
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7
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Khaled M, Strodel B, Sayyed-Ahmad A. Comparative molecular dynamics simulations of pathogenic and non-pathogenic huntingtin protein monomers and dimers. Front Mol Biosci 2023; 10:1143353. [PMID: 37101557 PMCID: PMC10123271 DOI: 10.3389/fmolb.2023.1143353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 03/29/2023] [Indexed: 04/28/2023] Open
Abstract
Polyglutamine expansion at the N-terminus of the huntingtin protein exon 1 (Htt-ex1) is closely associated with a number of neurodegenerative diseases, which result from the aggregation of the increased polyQ repeat. However, the underlying structures and aggregation mechanism are still poorly understood. We performed microsecond-long all-atom molecular dynamics simulations to study the folding and dimerization of Htt-ex1 (about 100 residues) with non-pathogenic and pathogenic polyQ lengths, and uncovered substantial differences. The non-pathogenic monomer adopts a long α-helix that includes most of the polyQ residues, which forms the interaction interface for dimerization, and a PPII-turn-PPII motif in the proline-rich region. In the pathogenic monomer, the polyQ region is disordered, leading to compact structures with many intra-protein interactions and the formation of short β-sheets. Dimerization can proceed via different modes, where those involving the N-terminal headpiece bury more hydrophobic residues and are thus more stable. Moreover, in the pathogenic Htt-ex1 dimers the proline-rich region interacts with the polyQ region, which slows the formation of β-sheets.
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Affiliation(s)
- Mohammed Khaled
- Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Forschungszentrum Jülich, Jülich, Germany
| | - Birgit Strodel
- Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Forschungszentrum Jülich, Jülich, Germany
- Institute of Theoretical and Computational Chemistry, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- *Correspondence: Birgit Strodel, ; Abdallah Sayyed-Ahmad,
| | - Abdallah Sayyed-Ahmad
- Department of Physics, Birzeit University, Birzeit, Palestine
- *Correspondence: Birgit Strodel, ; Abdallah Sayyed-Ahmad,
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8
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Roy R, Paul S. Disparate Effect of Hybrid Peptidomimetics Containing Isomers of Aminobenzoic Acid on hIAPP Aggregation. J Phys Chem B 2022; 126:10427-10444. [PMID: 36459988 DOI: 10.1021/acs.jpcb.2c05970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
The abnormal misfolding of human islet amyloid polypeptide (hIAPP) in pancreatic β-cells is implicated in the progression of type II diabetes (T2D). With the prevalence of T2D increasing worldwide, preventing the aggregation of hIAPP has been recognized as a promising therapeutic strategy to control this disease. Recently, a class of novel conformationally restricted β-sheet breaker hybrid peptidomimetics (BSBHps) was found to demonstrate efficient inhibitory ability toward amyloid formation of hIAPP. One (Ile26) or more (Gly24 and Ile26) residues in these six-membered peptide sequences, which have been extracted from the amyloidogenic core of hIAPP, N22FGAIL27, are substituted by three different isomers of the conformationally restricted aromatic amino acid, i.e., aminobenzoic acid (β, γ, and δ), to generate these BSBHps. The presence of the nonproteinogenic aminobenzoic acid moiety renders the BSBHps to be more stable toward proteolytic degradation. The different isomeric BSBHps exhibit contrasting influence on the self-assembly of hIAPP. The BSBHps containing β- and γ-aminobenzoic acid can sufficiently prevent hIAPP aggregation, but those with the δ-aminobenzoic group stabilize the β-sheet-rich aggregate of hIAPP. The difference in the angle between the amino and carboxyl groups in the isomers of the aminobenzoic moiety causes the BSBHps to attain discrete conformation and hence leads to variation in their binding preference with hIAPP and ultimately their inhibitory potency. This guides the pathway for the dissimilar effect of BSBHps on peptide aggregation and, therefore, provides insights into the design considerations for novel drugs against T2D.
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Affiliation(s)
- Rituparna Roy
- Department of Chemistry, Indian Institute of Technology, Guwahati781039, Assam, India
| | - Sandip Paul
- Department of Chemistry, Indian Institute of Technology, Guwahati781039, Assam, India
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9
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McIvor JAP, Larsen DS, Mercadante D. Simulating Polyproline II-Helix-Rich Peptides with the Latest Kirkwood-Buff Force Field: A Direct Comparison with AMBER and CHARMM. J Phys Chem B 2022; 126:7833-7846. [PMID: 36125334 DOI: 10.1021/acs.jpcb.2c03837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We simulated the dynamics of a set of peptides characterized by ensembles rich in PPII-helical content, to assess the ability of the most recent Kirkwood-Buff force field (KBFF20) to sample this conformational peculiarity. KBFF has been previously shown to capably reproduce experimental dimensions of disordered proteins, while being limited in confidently sampling structured proteins. Further development of the force field bridged this gap. It is however still unknown what are the main differences between KBFF and AMBER/CHARMM force fields. A direct comparison is now possible as both AMBER/CHARMM force fields have been used to sample peptides rich in PPII-helical content. We found that KBFF20 samples' PPII-helical content qualitatively matches both AMBER and CHARMM force fields, with the main difference being the KBFF ability to populate the αR region of the Ramachandran plot in the set of simulated peptides. Overall, KBFF20 is a well-balanced force field, able to sample the dynamics of both structured and unstructured proteins.
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Affiliation(s)
- Jordan A P McIvor
- School of Chemical Sciences, The University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand
| | - Danaé S Larsen
- School of Chemical Sciences, The University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand
| | - Davide Mercadante
- School of Chemical Sciences, The University of Auckland, 23 Symonds Street, Auckland 1010, New Zealand
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10
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Yu L, Brüschweiler R. Quantitative prediction of ensemble dynamics, shapes and contact propensities of intrinsically disordered proteins. PLoS Comput Biol 2022; 18:e1010036. [PMID: 36084124 PMCID: PMC9491582 DOI: 10.1371/journal.pcbi.1010036] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 09/21/2022] [Accepted: 08/03/2022] [Indexed: 12/29/2022] Open
Abstract
Intrinsically disordered proteins (IDPs) are highly dynamic systems that play an important role in cell signaling processes and their misfunction often causes human disease. Proper understanding of IDP function not only requires the realistic characterization of their three-dimensional conformational ensembles at atomic-level resolution but also of the time scales of interconversion between their conformational substates. Large sets of experimental data are often used in combination with molecular modeling to restrain or bias models to improve agreement with experiment. It is shown here for the N-terminal transactivation domain of p53 (p53TAD) and Pup, which are two IDPs that fold upon binding to their targets, how the latest advancements in molecular dynamics (MD) simulations methodology produces native conformational ensembles by combining replica exchange with series of microsecond MD simulations. They closely reproduce experimental data at the global conformational ensemble level, in terms of the distribution properties of the radius of gyration tensor, and at the local level, in terms of NMR properties including 15N spin relaxation, without the need for reweighting. Further inspection revealed that 10-20% of the individual MD trajectories display the formation of secondary structures not observed in the experimental NMR data. The IDP ensembles were analyzed by graph theory to identify dominant inter-residue contact clusters and characteristic amino-acid contact propensities. These findings indicate that modern MD force fields with residue-specific backbone potentials can produce highly realistic IDP ensembles sampling a hierarchy of nano- and picosecond time scales providing new insights into their biological function.
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Affiliation(s)
- Lei Yu
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio, United States of America
| | - Rafael Brüschweiler
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio, United States of America
- Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, Ohio, United States of America
- * E-mail:
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11
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Arora L, Mukhopadhyay S. Conformational Characteristics and Phase Behavior of Intrinsically Disordered Proteins─Where Physical Chemistry Meets Biology. J Phys Chem B 2022; 126:5137-5139. [PMID: 35860904 DOI: 10.1021/acs.jpcb.2c04017] [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)
- Lisha Arora
- Centre for Protein Science, Design and Engineering, Indian Institute of Science Education and Research (IISER) Mohali, Sector 81, Mohali, SAS Nagar, Knowledge City, Punjab 140306, India.,Department of Chemical Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Sector 81, Mohali, SAS Nagar, Knowledge City, Punjab 140306, India
| | - Samrat Mukhopadhyay
- Centre for Protein Science, Design and Engineering, Indian Institute of Science Education and Research (IISER) Mohali, Sector 81, Mohali, SAS Nagar, Knowledge City, Punjab 140306, India.,Department of Chemical Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Sector 81, Mohali, SAS Nagar, Knowledge City, Punjab 140306, India.,Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Mohali, Sector 81, Mohali, SAS Nagar, Knowledge City, Punjab 140306, India
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12
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Polêto MD, Lemkul JA. Integration of Experimental Data and Use of Automated Fitting Methods in Developing Protein Force Fields. Commun Chem 2022; 5:10.1038/s42004-022-00653-z. [PMID: 35382231 PMCID: PMC8979544 DOI: 10.1038/s42004-022-00653-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 02/21/2022] [Indexed: 01/27/2023] Open
Abstract
The development of accurate protein force fields has been the cornerstone of molecular simulations for the past 50 years. During this period, many lessons have been learned regarding the use of experimental target data and parameter fitting procedures. Here, we review recent advances in protein force field development. We discuss the recent emergence of polarizable force fields and the role of electronic polarization and areas in which additive force fields fall short. The use of automated fitting methods and the inclusion of additional experimental solution data during parametrization is discussed as a means to highlight possible routes to improve the accuracy of force fields even further.
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Affiliation(s)
- Marcelo D. Polêto
- Department of Biochemistry, Virginia Tech, Blacksburg, VA 24061 United States
| | - Justin A. Lemkul
- Department of Biochemistry, Virginia Tech, Blacksburg, VA 24061 United States
- Center for Drug Discovery, Virginia Tech, Blacksburg, VA 24061 United States
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13
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Li L, Casalini T, Arosio P, Salvalaglio M. Modeling the Structure and Interactions of Intrinsically Disordered Peptides with Multiple Replica, Metadynamics-Based Sampling Methods and Force-Field Combinations. J Chem Theory Comput 2022; 18:1915-1928. [PMID: 35174713 PMCID: PMC9097291 DOI: 10.1021/acs.jctc.1c00889] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Indexed: 01/08/2023]
Abstract
Intrinsically disordered proteins play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure-function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and force fields. Nevertheless, differences in fine details emerge from varying combinations of force-fields and sampling methods. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which are common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field and sampling method combinations for accurate structural and thermodynamic information in the study of disordered proteins.
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Affiliation(s)
- Lunna Li
- Thomas
Young Centre and Department of Chemical Engineering, University College London, London WC1E 7JE, U.K.
| | - Tommaso Casalini
- Department
of Chemistry and Applied Biosciences, ETH
Zurich, Zurich 8093, Switzerland
| | - Paolo Arosio
- Department
of Chemistry and Applied Biosciences, ETH
Zurich, Zurich 8093, Switzerland
| | - Matteo Salvalaglio
- Thomas
Young Centre and Department of Chemical Engineering, University College London, London WC1E 7JE, U.K.
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14
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Jephthah S, Pesce F, Lindorff-Larsen K, Skepö M. Force Field Effects in Simulations of Flexible Peptides with Varying Polyproline II Propensity. J Chem Theory Comput 2021; 17:6634-6646. [PMID: 34524800 PMCID: PMC8515809 DOI: 10.1021/acs.jctc.1c00408] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Five peptides previously suggested to possess polyproline II (PPII) structure have here been investigated by using atomistic molecular dynamics simulations to compare how well four different force fields known for simulating intrinsically disordered proteins relatively well (Amber ff99SB-disp, Amber ff99SB-ILDN, CHARM36IDPSFF, and CHARMM36m) can capture this secondary structure element. The results revealed that all force fields sample PPII structures but to different extents and with different propensities toward other secondary structure elements, in particular, the β-sheet and "random coils". A cluster analysis of the simulations of histatin 5 also revealed that the conformational ensembles of the force fields are quite different. We compared the simulations to circular dichroism and nuclear magnetic resonance spectroscopy experiments and conclude that further experiments and methods for interpreting them are needed to assess the accuracy of force fields in determining PPII structure.
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Affiliation(s)
- Stéphanie Jephthah
- Division of Theoretical Chemistry, Lund University, SE-221 00 Lund, Sweden
| | - Francesco Pesce
- Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Kresten Lindorff-Larsen
- Structural Biology and NMR Laboratory & the Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, DK-2200 Copenhagen, Denmark
| | - Marie Skepö
- Division of Theoretical Chemistry, Lund University, SE-221 00 Lund, Sweden
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Pourjafar-Dehkordi D, Zacharias M. Influence of a Ser111-phosphorylation on Rab1b GTPase conformational dynamics studied by advanced sampling simulations. Proteins 2021; 89:1324-1332. [PMID: 34056776 DOI: 10.1002/prot.26153] [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: 12/29/2020] [Revised: 02/18/2021] [Accepted: 03/10/2021] [Indexed: 11/06/2022]
Abstract
Rab GTPases constitute the largest branch of the Ras protein superfamily that regulate intra-cellular membrane trafficking. Their signaling activity is mediated by the transition between an active GTP-bound state and an inactive GDP-bound state. In the inactive state the switch I and II segments adopt largely disordered flexible conformations, whereas in the active state these regions are in well-defined conformations. The switch I and II states are central for recognition of Rab GTPases by interacting partners. Phosphorylation of the Rab1b-GTPase at residue Ser111 (pS111) results in modulation of the signaling activity due to alterations of the protein interaction interface and also due to modulation of the conformational flexibility. We have studied the flexibility of native and pS111-Rab1b in complex with GTP or GDP using extensive Molecular Dynamics (MD) simulations and an advanced sampling method called DIhedral Angle-biasing potential Replica-Exchange Molecular dynamics (DIA-REMD). The DIA-REMD method promotes backbone and side chain dihedral transitions along a series of replica simulations in selected protein segments and through exchanges also improves sampling in an unbiased reference simulation. Application to the Rab1b system results in significantly enhanced sampling of different switch I/II conformational states in the GDP-bound Rab1b state. The pS111 modification is found to reduce the conformational flexibility even in the presence of GDP, which may influence signaling activities. The stabilizing effect can be attributed to the formation of additional surface salt bridges between Arg-residues and pS111 not present in the native structure. The DIA-REMD method could be a valuable approach for studying also other signaling proteins that contain flexible segments.
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Affiliation(s)
| | - Martin Zacharias
- Center for Functional Protein Assemblies, Technical University of Munich, Garching, Germany
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