Study of the Variability of the Native Protein Structure
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Structural Mechanisms of Oligomer and Amyloid Fibril Formation by the Prion Protein Cite This: Chem
ChemComm View Article Online FEATURE ARTICLE View Journal | View Issue Structural mechanisms of oligomer and amyloid fibril formation by the prion protein Cite this: Chem. Commun., 2018, 54,6230 Ishita Sengupta a and Jayant B. Udgaonkar *b Misfolding and aggregation of the prion protein is responsible for multiple neurodegenerative diseases. Works from several laboratories on folding of both the WT and multiple pathogenic mutant variants of the prion protein have identified several structurally dissimilar intermediates, which might be potential precursors to misfolding and aggregation. The misfolded aggregates themselves are morphologically distinct, critically dependent on the solution conditions under which they are prepared, but always b-sheet rich. Despite the lack of an atomic resolution structure of the infectious pathogenic agent in prion diseases, several low resolution models have identified the b-sheet rich core of the aggregates formed in vitro, to lie in the a2–a3 subdomain of the prion protein, albeit with local stabilities that vary Received 17th April 2018, with the type of aggregate. This feature article describes recent advances in the investigation of in vitro Accepted 14th May 2018 prion protein aggregation using multiple spectroscopic probes, with particular focus on (1) identifying DOI: 10.1039/c8cc03053g aggregation-prone conformations of the monomeric protein, (2) conditions which trigger misfolding and oligomerization, (3) the mechanism of misfolding and aggregation, and (4) the structure of the misfolded rsc.li/chemcomm intermediates and final aggregates. 1. Introduction The prion protein can exist in two distinct structural isoforms: a National Centre for Biological Sciences, Tata Institute of Fundamental Research, PrPC and PrPSc. -
Modal Analysis of the Lysozyme Protein Considering All-Atom and Coarse-Grained Finite Element Models
applied sciences Article Modal Analysis of the Lysozyme Protein Considering All-Atom and Coarse-Grained Finite Element Models Gustavo Giordani 1, Domenico Scaramozzino 2,* , Ignacio Iturrioz 1, Giuseppe Lacidogna 2 and Alberto Carpinteri 2 1 Applied Mechanical Group GMAP, Engineering School, Universidade Federal do Rio Grande do Sul, Sarmento Leite 425, 90040-001 Porto Alegre, Brazil; [email protected] (G.G.); [email protected] (I.I.) 2 Department of Structural, Geotechnical and Building Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy; [email protected] (G.L.); [email protected] (A.C.) * Correspondence: [email protected]; Tel.: +39-011-090-4854 Abstract: Proteins are the fundamental entities of several organic activities. They are essential for a broad range of tasks in a way that their shapes and folding processes are crucial to achieving proper biological functions. Low-frequency modes, generally associated with collective movements at terahertz (THz) and sub-terahertz frequencies, have been appointed as critical for the conformational processes of many proteins. Dynamic simulations, such as molecular dynamics, are vastly applied by biochemical researchers in this field. However, in the last years, proposals that define the protein as a simplified elastic macrostructure have shown appealing results when dealing with this type of problem. In this context, modal analysis based on different modelization techniques, i.e., considering both an all-atom (AA) and coarse-grained (CG) representation, is proposed to analyze the hen egg-white lysozyme. This work presents new considerations and conclusions compared to previous analyses. Experimental values for the B-factor, considering all the heavy atoms or only one representative point per amino acid, are used to evaluate the validity of the numerical solutions. -
Native-Like Mean Structure in the Unfolded Ensemble of Small Proteins
B doi:10.1016/S0022-2836(02)00888-4 available online at http://www.idealibrary.com on w J. Mol. Biol. (2002) 323, 153–164 Native-like Mean Structure in the Unfolded Ensemble of Small Proteins Bojan Zagrovic1, Christopher D. Snow1, Siraj Khaliq2 Michael R. Shirts2 and Vijay S. Pande1,2* 1Biophysics Program The nature of the unfolded state plays a great role in our understanding of Stanford University, Stanford proteins. However, accurately studying the unfolded state with computer CA 94305-5080, USA simulation is difficult, due to its complexity and the great deal of sampling required. Using a supercluster of over 10,000 processors we 2Department of Chemistry have performed close to 800 ms of molecular dynamics simulation in Stanford University, Stanford atomistic detail of the folded and unfolded states of three polypeptides CA 94305-5080, USA from a range of structural classes: the all-alpha villin headpiece molecule, the beta hairpin tryptophan zipper, and a designed alpha-beta zinc finger mimic. A comparison between the folded and the unfolded ensembles reveals that, even though virtually none of the individual members of the unfolded ensemble exhibits native-like features, the mean unfolded structure (averaged over the entire unfolded ensemble) has a native-like geometry. This suggests several novel implications for protein folding and structure prediction as well as new interpretations for experiments which find structure in ensemble-averaged measurements. q 2002 Elsevier Science Ltd. All rights reserved Keywords: mean-structure hypothesis; unfolded state of proteins; *Corresponding author distributed computing; conformational averaging Introduction under folding conditions, with some notable exceptions.14 – 16 This is understandable since under Historically, the unfolded state of proteins has such conditions the unfolded state is an unstable, received significantly less attention than the folded fleeting species making any kind of quantitative state.1 The reasons for this are primarily its struc- experimental measurement very difficult. -
DNA Energy Landscapes Via Calorimetric Detection of Microstate Ensembles of Metastable Macrostates and Triplet Repeat Diseases
DNA energy landscapes via calorimetric detection of microstate ensembles of metastable macrostates and triplet repeat diseases Jens Vo¨ lkera, Horst H. Klumpb, and Kenneth J. Breslauera,c,1 aDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Rd, Piscataway, NJ 08854; bDepartment of Molecular and Cell Biology, University of Cape Town, Private Bag, Rondebosch 7800, South Africa; and cCancer Institute of New Jersey, New Brunswick, NJ 08901 Communicated by I. M. Gelfand, Rutgers, The State University of New Jersey, Piscataway, NJ, October 15, 2008 (received for review September 8, 2008) Biopolymers exhibit rough energy landscapes, thereby allowing biological role(s), if any, of kinetically stable (metastable) mi- biological processes to access a broad range of kinetic and ther- crostates that make up the time-averaged, native state ensembles modynamic states. In contrast to proteins, the energy landscapes of macroscopic nucleic acid states remains to be determined. of nucleic acids have been the subject of relatively few experimen- As part of an effort to address this deficiency, we report here tal investigations. In this study, we use calorimetric and spectro- experimental evidence for the presence of discrete microstates scopic observables to detect, resolve, and selectively enrich ener- in metastable triplet repeat bulge looped ⍀-DNAs of potential getically discrete ensembles of microstates within metastable DNA biological significance. The specific triplet repeat bulge looped structures. Our results are consistent with metastable, ‘‘native’’ ⍀-DNA species investigated mimic slipped DNA structures DNA states being composed of an ensemble of discrete and corresponding to intermediates in the processes that lead to kinetically stable microstates of differential stabilities, rather than DNA expansion in triplet repeat diseases (36). -
Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids Yin-Chen Hsieh, Frédéric Poitevin, Marc Delarue, Patrice Koehl
Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids Yin-Chen Hsieh, Frédéric Poitevin, Marc Delarue, Patrice Koehl To cite this version: Yin-Chen Hsieh, Frédéric Poitevin, Marc Delarue, Patrice Koehl. Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids. Frontiers in Molecular Biosciences, Frontiers Media, 2016, 3, pp.85. 10.3389/fmolb.2016.00085. pasteur-02174598 HAL Id: pasteur-02174598 https://hal-pasteur.archives-ouvertes.fr/pasteur-02174598 Submitted on 5 Jul 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License ORIGINAL RESEARCH published: 27 December 2016 doi: 10.3389/fmolb.2016.00085 Comparative Normal Mode Analysis of the Dynamics of DENV and ZIKV Capsids Yin-Chen Hsieh 1, Frédéric Poitevin 2, 3, Marc Delarue 4 and Patrice Koehl 1* 1 Department of Computer Science and Genome Center, University of California, Davis, Davis, CA, USA, 2 Department of Structural Biology, Stanford University, Stanford, CA, USA, 3 SLAC National Accelerator Laboratory, Stanford PULSE Institute, Menlo Park, CA, USA, 4 Unit of Structural Dynamics of Macromolecules, UMR 3528 du Centre National de la Recherche Scientifique, Institut Pasteur, Paris, France Key steps in the life cycle of a virus, such as the fusion event as the virus infects a host cell and its maturation process, relate to an intricate interplay between the structure and the dynamics of its constituent proteins, especially those that define its capsid, much akin to an envelope that protects its genomic material. -
Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses
Chapter 7 Elastic Network Models For Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses Timothy R. Lezon, Indira H. Shrivastava, Zheng Yang and Ivet Bahar ∗ Department of Computational Biology, School of Medicine, University of Pittsburgh, Suite 3064, Biomedical Science Tower 3, 3051 Fifth Ave., Pittsburgh, PA 15213 7.1. Introduction Elastic network models (ENMs) have over the last decade enjoyed considerable success in the study of macromolecular dynamics. These models have been used to predict the global dynamics of a variety of proteins and protein complexes, ranging in size from single enzymes to macromolecular machines (Keskin et al. 2002), ribosomes (Tama et al. 2003, Wang et al. 2004) and viral capsids (Tama & Brooks, 2002, Tama & Brooks, 2005, Rader et al . 2005). They have provided insights into a wide range of protein behaviors, such as mechanisms of allosteric regulation (Ming & Wall, 2005, Bahar et al . 2007, Chennubhotla et al . 2008), protein-protein binding (Tobi and Bahar 2005), anisotropic response to uniaxial tension and unfolding (Eyal and Bahar, 2008, Sulkowska et al . 2008), co- localization of catalytic sites and key mechanical sites (e.g., hinges) (Yang & Bahar 2005), interactions at the binding sites (Ming & Wall, 2006), and energetics (Miller et al. 2008), to name a few. ENMs allow the global motions of a molecule to be quickly calculated, making them an ideal complement to conventional molecular dynamics (MD) simulations. Increasingly, variants of ENMs are being applied to non-equilibrium situations, such as the prediction of transition pathways between functional states separated by low energy barriers (Zheng et al. 2007) or driving MD simulations (Isin et al. -
Conformational Search for the Protein Native State
CHAPTER 19 CONFORMATIONAL SEARCH FOR THE PROTEIN NATIVE STATE Amarda Shehu Assistant Professor Dept. of Comp. Sci. Al. Appnt. Dept. of Comp. Biol. and Bioinf. George Mason University 4400 University Blvd. MSN 4A5 Fairfax, Virginia, 22030, USA Abstract This chapter presents a survey of computational methods that obtain a struc- tural description of the protein native state. This description is important to understand a protein's biological function. The chapter presents the problem of characterizing the native state in conformational detail in terms of the chal- lenges that it raises in computation. Computing the conformations populated by a protein under native conditions is cast as a search problem. Methods such as Molecular Dynamics and Monte Carlo are treated rst. Multiscaling, the combination of reduced and high complexity models of conformations, is briey summarized as a powerful strategy to rapidly extract important fea- tures of the energy surface associated with the protein conformational space. Other strategies that narrow the search space through information obtained in the wet lab are also presented. The chapter then focuses on enhanced sam- Protein Structure Prediction:Method and Algorithms. By H. Rangwala & G. Karypis 1 Copyright c 2013 John Wiley & Sons, Inc. 2 CONFORMATIONAL SEARCH FOR THE PROTEIN NATIVE STATE pling strategies employed to compute native-like conformations when given only amino-acid sequence. Fragment-based assembly methods are analyzed for their success and what they are revealing about the physical process of folding. The chapter concludes with a discussion of future research directions in the computational quest for the protein native state. 19.1 THE QUEST FOR THE PROTEIN NATIVE STATE From the rst formulation of the protein folding problem by Wu in 1931 to the experiments of Mirsky and Pauling in 1936, chemical and physical properties of protein molecules were attributed to the amino-acid composition and structural arrangement of the protein chain [86, 56]. -
A Comparison of the Folding Kinetics of a Small, Artificially Selected DNA Aptamer with Those of Equivalently Simple Naturally Occurring Proteins
A comparison of the folding kinetics of a small, artificially selected DNA aptamer with those of equivalently simple naturally occurring proteins Camille Lawrence,1 Alexis Vallee-B elisle, 2,3 Shawn H. Pfeil,4,5 Derek de Mornay,2 Everett A. Lipman,1,4 and Kevin W. Plaxco1,2* 1Interdepartmental Program in Biomolecular Science and Engineering, University of California, Santa Barbara, California 93106 2Department of Chemistry and Biochemistry, University of California, Santa Barbara, California 93106 3Laboratory of Biosensors and Nanomachines, Departement de Chimie, Universite de Montreal, Quebec, Canada 4Department of Physics, University of California, Santa Barbara, California 93106 5Department of Physics, West Chester University of Pennsylvania, West Chester, Pennsylvania 19383 Received 16 July 2013; Revised 17 October 2013; Accepted 23 October 2013 DOI: 10.1002/pro.2390 Published online 29 October 2013 proteinscience.org Abstract: The folding of larger proteins generally differs from the folding of similarly large nucleic acids in the number and stability of the intermediates involved. To date, however, no similar com- parison has been made between the folding of smaller proteins, which typically fold without well- populated intermediates, and the folding of small, simple nucleic acids. In response, in this study, we compare the folding of a 38-base DNA aptamer with the folding of a set of equivalently simple proteins. We find that, as is true for the large majority of simple, single domain proteins, the aptamer folds through a concerted, millisecond-scale process lacking well-populated intermedi- ates. Perhaps surprisingly, the observed folding rate falls within error of a previously described relationship between the folding kinetics of single-domain proteins and their native state topology. -
Evolution of Biomolecular Structure Class II Trna-Synthetases and Trna
University of Illinois at Urbana-Champaign Luthey-Schulten Group Theoretical and Computational Biophysics Group Evolution of Biomolecular Structure Class II tRNA-Synthetases and tRNA MultiSeq Developers: Prof. Zan Luthey-Schulten Elijah Roberts Patrick O’Donoghue John Eargle Anurag Sethi Dan Wright Brijeet Dhaliwal March 2006. A current version of this tutorial is available at http://www.ks.uiuc.edu/Training/Tutorials/ CONTENTS 2 Contents 1 Introduction 4 1.1 The MultiSeq Bioinformatic Analysis Environment . 4 1.2 Aminoacyl-tRNA Synthetases: Role in translation . 4 1.3 Getting Started . 7 1.3.1 Requirements . 7 1.3.2 Copying the tutorial files . 7 1.3.3 Configuring MultiSeq . 8 1.3.4 Configuring BLAST for MultiSeq . 10 1.4 The Aspartyl-tRNA Synthetase/tRNA Complex . 12 1.4.1 Loading the structure into MultiSeq . 12 1.4.2 Selecting and highlighting residues . 13 1.4.3 Domain organization of the synthetase . 14 1.4.4 Nearest neighbor contacts . 14 2 Evolutionary Analysis of AARS Structures 17 2.1 Loading Molecules . 17 2.2 Multiple Structure Alignments . 18 2.3 Structural Conservation Measure: Qres . 19 2.4 Structure Based Phylogenetic Analysis . 21 2.4.1 Limitations of sequence data . 21 2.4.2 Structural metrics look further back in time . 23 3 Complete Evolutionary Profile of AspRS 26 3.1 BLASTing Sequence Databases . 26 3.1.1 Importing the archaeal sequences . 26 3.1.2 Now the other domains of life . 27 3.2 Organizing Your Data . 28 3.3 Finding a Structural Domain in a Sequence . 29 3.4 Aligning to a Structural Profile using ClustalW . -
New Generation of Elastic Network Models
Available online at www.sciencedirect.com ScienceDirect New generation of elastic network models Jose´ Ramo´ n Lo´ pez-Blanco and Pablo Chaco´ n The intrinsic flexibility of proteins and nucleic acids can be the years to be an effective approach to understanding grasped from remarkably simple mechanical models of the intrinsic dynamics of biomolecules [5,6 ,7]. particles connected by springs. In recent decades, Elastic Network Models (ENMs) combined with Normal Model Analysis Although there are many variations to reduce the complex widely confirmed their ability to predict biologically relevant biomolecular structures into a network of nodes and motions of biomolecules and soon became a popular springs, the basic assumption (and limitation) of ENMs methodology to reveal large-scale dynamics in multiple is that the potential energy is described by a quadratic structural biology scenarios. The simplicity, robustness, low function around a minimum energy conformation: computational cost, and relatively high accuracy are the X 0 2 reasons behind the success of ENMs. This review focuses on V ¼ KijðrijÀrijÞ (1) recent advances in the development and application of ENMs, i < j paying particular attention to combinations with experimental where the superindex 0 indicates the initial conformation, data. Successful application scenarios include large r is the distance between atoms i and j, and K is a spring macromolecular machines, structural refinement, docking, and ij ij stiffness function. The intrinsic dynamics of an ENM is evolutionary conservation. mostly assessed by NMA. In this classical mechanics Address technique, all the complex motions around an initial Department of Biological Chemical Physics, Rocasolano Physical Chemistry Institute C.S.I.C., Serrano 119, 28006 Madrid, Spain conformation are decoupled into a linear combination of orthogonal basis vectors, the so-called normal modes. -
Protein Folding
Protein Folding I. Characteristics of proteins 1. Proteins are one of the most important molecules of life. They perform numerous functions, from storing oxygen in tissues or transporting it in a blood (proteins myoglobin and hemoglobin) to muscle contraction and relaxation (titin) or cell mobility (fibronectin) to name a few. 2. Proteins are heteropolymers and consist of 20 different monomers or amino acids (Fig. 1). When amino acids are linked in a chain, they become residues and form a polypeptide sequence. Amino acids differ with respect to their side chains. i i-1 i+1 Cα Fig. 1 Structure of a polypeptide chain. A single amino acid residue i boxed by a dashed lines contains amide group NH, carboxyl group CO and Cα-carbon. Amino acid side chain Ri along with hydrogen H are attached to Cα-carbon. Amino acids differ with respect to their side chains Ri. Protein sequences utilize twenty different residues. Roughly speaking, depending on the nature of their side chains amino acids may be divided into three classes – hydrophobic, hydrophilic (polar), and charged (i.e., carrying positive or negative net charge) amino acids. The average number of amino acids N in protein is about 450, but N may range from about 30 to 104. 3. The remarkable feature of proteins is an existence of unique native state - a single well-defined structure, in which a protein performs its biological function (Fig. 2). Native states of proteins arise due to the diversity in amino acids. (Illustration of the uniqueness of the native state using lattice model is given in the class.) Large proteins are often folded into relatively independent units called domains. -
Native-Like Secondary Structure in a Peptide From
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Research Paper 473 Native-like secondary structure in a peptide from the ␣-domain of hen lysozyme Jenny J Yang1*, Bert van den Berg*, Maureen Pitkeathly, Lorna J Smith, Kimberly A Bolin2, Timothy A Keiderling3, Christina Redfield, Christopher M Dobson and Sheena E Radford4 Background: To gain insight into the local and nonlocal interactions that Addresses: Oxford Centre for Molecular Sciences contribute to the stability of hen lysozyme, we have synthesized two peptides and New Chemistry Laboratory, University of Oxford, South Parks Road, Oxford OX1 3QT, UK. that together comprise the entire ␣-domain of the protein. One peptide (peptide Present addresses: 1Department of Molecular 1–40) corresponds to the sequence that forms two ␣-helices, a loop region, and Physics and Biochemistry, Yale University, 266 a small -sheet in the N-terminal region of the native protein. The other (peptide Whitney Avenue, PO Box 208114, New Haven, 84–129) makes up the C-terminal part of the ␣-domain and encompasses two CT 06520-8114, USA. 2Department of Chemistry ␣-helices and a 310 helix in the native protein. and Biochemistry, University of California, Santa Cruz, CA 96064, USA. 3Department of Chemistry, University of Illinois, 845 West Taylor Street, Results: As judged by CD and a range of NMR parameters, peptide 1–40 has Chicago, IL 60607-7061, USA. 4Department of little secondary structure in aqueous solution and only a small number of local Biochemistry and Molecular Biology, University of hydrophobic interactions, largely in the loop region.