Principles of Protein Folding - a Perspective from Simple Exact Models
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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. -
Algorithms & Experiments for the Protein
ALGORITHMS & EXPERIMENTS FOR THE PROTEIN CHAIN LATTICE FITTING PROBLEM DALLAS THOMAS Bachelor of Science, University of Lethbridge, 2004 Bachelor of Science, Kings University College, 2002 A Thesis Submitted to the School of Graduate Studies of the University of Lethbridge in Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE Department of Mathematics and Computer Science University of Lethbridge LETHBRIDGE, ALBERTA, CANADA c Dallas Thomas, 2006 Abstract This study seeks to design algorithms that may be used to determine if a given lattice is a good approximation to a given rigid protein structure. Ideal lattice models discovered using our techniques may then be used in algorithms for protein folding and inverse protein folding. In this study we develop methods based on dynamic programming and branch and bound in an effort to identify “ideal” lattice models. To further our understanding of the concepts behind the methods we have utilized a simple cubic lattice for our analysis. The algorithms may be adapted to work on any lattice. We describe two algorithms. One for aligning the protein backbone to the lattice as a walk. This algorithm runs in polynomial time. The sec- ond algorithm for aligning a protein backbone as a path to the lattice. Both the algorithms seek to minimize the CRMS deviation of the alignment. The second problem was recently shown to be NP-Complete, hence it is highly unlikely that an efficient algorithm exists. The first algorithm gives a lower bound on the optimal solution to the second problem, and can be used in a branch and bound procedure. -
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. -
Resource-Efficient Quantum Algorithm for Protein Folding
www.nature.com/npjqi ARTICLE OPEN Resource-efficient quantum algorithm for protein folding ✉ Anton Robert1,2, Panagiotis Kl. Barkoutsos 1, Stefan Woerner 1 and Ivano Tavernelli 1 Predicting the three-dimensional structure of a protein from its primary sequence of amino acids is known as the protein folding problem. Due to the central role of proteins’ structures in chemistry, biology and medicine applications, this subject has been intensively studied for over half a century. Although classical algorithms provide practical solutions for the sampling of the conformation space of small proteins, they cannot tackle the intrinsic NP-hard complexity of the problem, even when reduced to the simplest Hydrophobic-Polar model. On the other hand, while fault-tolerant quantum computers are beyond reach for state-of- the-art quantum technologies, there is evidence that quantum algorithms can be successfully used in noisy state-of-the-art quantum computers to accelerate energy optimization in frustrated systems. In this work, we present a model Hamiltonian with OðN4Þ scaling and a corresponding quantum variational algorithm for the folding of a polymer chain with N monomers on a lattice. The model reflects many physico-chemical properties of the protein, reducing the gap between coarse-grained representations and mere lattice models. In addition, we use a robust and versatile optimization scheme, bringing together variational quantum algorithms specifically adapted to classical cost functions and evolutionary strategies to simulate the folding of the 10 amino acid Angiotensin on 22 qubits. The same method is also successfully applied to the study of the folding of a 7 amino acid neuropeptide using 9 qubits on an IBM 20-qubit quantum computer. -
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). -
How Fast Is Protein Hydrophobic Collapse?
How fast is protein hydrophobic collapse? Mourad Sadqi*, Lisa J. Lapidus†‡, and Victor Mun˜ oz*§ *Department of Chemistry and Biochemistry and Center for Biomolecular Structure and Organization, University of Maryland, College Park, MD 20742; and †Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892 Edited by Michael Levitt, Stanford University School of Medicine, Stanford, CA, and approved August 18, 2003 (received for review June 21, 2003) One of the most recurring questions in protein folding refers to the Equilibrium FRET Experiments. Equilibrium FRET experiments interplay between formation of secondary structure and hydro- were performed at 25 M concentration in citrate buffer at pH phobic collapse. In contrast with secondary structure, it is hard to 3.0 in an Applied Photophysics (Surrey, U.K.) PiStar instrument. isolate hydrophobic collapse from other folding events. We have Efficiency of energy transfer between naphtyl-alanine (donor) directly measured the dynamics of protein hydrophobic collapse in and dansyl-lysine (acceptor) was determined from the fluores- the absence of competing processes. Collapse was triggered with cence quantum yield of the donor by using the equation: laser-induced temperature jumps in the acid-denatured form of a Qda simple protein and monitored by fluorescence resonance energy E ϭ 1 Ϫ . [1] transfer between probes placed at the protein ends. The relaxation Qd time for hydrophobic collapse is only Ϸ60 ns at 305 K, even faster than secondary structure formation. At higher temperatures, as the The intrinsic quantum yield of the donor (Qd) was measured by protein becomes increasingly compact by a stronger hydrophobic exciting at 288 nm in the protein labeled at the N terminus with naphtyl-alanine and nonlabeled at the C terminus and using force, we observe a slowdown of the dynamics of collapse. -
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]. -
Translation and Folding of Single Proteins in Real Time PNAS PLUS
Translation and folding of single proteins in real time PNAS PLUS Florian Wrucka,1, Alexandros Katranidisb,2, Knud H. Nierhausc,3, Georg Büldtb,d, and Martin Hegnera,2 aCentre for Research on Adaptive Nanostructures and Nanodevices, School of Physics, Trinity College Dublin, Dublin 2, Ireland; bInstitute of Complex Systems ICS-5, Forschungszentrum Jülich, 52425 Jülich, Germany; cInstitute for Medical Physics and Biophysics, Charité–Universitätsmedizin Berlin, 10117 Berlin, Germany; and dLaboratory for Advanced Studies of Membrane Proteins, Moscow Institute of Physics and Technology, 141700 Dolgoprudny, Russia Edited by George H. Lorimer, University of Maryland, College Park, MD, and approved April 21, 2017 (received for review October 27, 2016) Protein biosynthesis is inherently coupled to cotranslational pro- ensemble methods. Optical tweezers have been used to observe tein folding. Folding of the nascent chain already occurs during stepping of motor proteins (19–23), DNA–protein complexes (24), synthesis and is mediated by spatial constraints imposed by the as well as unfolding and refolding of RNA molecules and proteins ribosomal exit tunnel as well as self-interactions. The polypeptide’s (25, 26). This powerful single-molecule method has provided in- vectorial emergence from the ribosomal tunnel establishes the possi- formation on (i) the translation machinery by reporting on the ble folding pathways leading to its native tertiary structure. How strength of interactions between the ribosome and mRNA (27), cotranslational protein folding and the rate of synthesis are linked (ii) its translocation along a short hairpin-forming mRNA mole- to a protein’s amino acid sequence is still not well defined. Here, we cule (28), as well as (iii) the release of an arrested nascent chain follow synthesis by individual ribosomes using dual-trap optical twee- (7). -
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. -
Doctor of Philosophy
Protein structure recognition: From eigenvector analysis to structural threading method by Haibo Cao A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Major: Condensed Matter Physics Program of Study Committee: Kai-Ming Bo, Major Professor Drena Dobbs Amy Andreotti Alan Goldman Bruce Harmon Joerg Schmalian Iowa State University Ames, Iowa 2003 .. 11 Graduate College Iowa State University This is to certify that the doctoral dissertation of Haibo Cao has met the dissertation requirements of Iowa State University Major Professor For the Major Program ... 111 TABLE OF CONTENTS ... Acknowledgments ................................... vm Abstract and Organization of Dissertation ..................... X CHAPTER 1. Protein Structure And Building Blocks ............. 1 Proteins. .......................................... 1 AminoAcids ........................................ 3 Secondary Structure ................................... 4 aHelix ...................................... 4 psheet ......................................... 5 Bibliography ........................................ 11 CHAPTER 2 . Protein Folding Problem ...................... 13 Levinthal’s Paradox .................................... 13 Interactions ......................................... 15 MJmatrix ....................................... 16 LTW parameterization ................................ 19 Bibliography ........................................ 25 CHAPTER 3 . Simple Exact Model ....................... -
Cell-Penetrating Peptides: Design Strategies Beyond Primary Structure and Amphipathicity
molecules Review Cell-Penetrating Peptides: Design Strategies beyond Primary Structure and Amphipathicity Daniela Kalafatovic 1 and Ernest Giralt 1,2,* 1 Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology (BIST), Baldiri Reixac, 10, 08028 Barcelona, Spain; [email protected] 2 Department of Inorganic and Organic Chemistry, University of Barcelona, Marti i Franques, 1-5, 08028 Barcelona, Spain * Correspondence: [email protected]; Tel.: +34-93-40-37125 Received: 26 September 2017; Accepted: 4 November 2017; Published: 8 November 2017 Abstract: Efficient intracellular drug delivery and target specificity are often hampered by the presence of biological barriers. Thus, compounds that efficiently cross cell membranes are the key to improving the therapeutic value and on-target specificity of non-permeable drugs. The discovery of cell-penetrating peptides (CPPs) and the early design approaches through mimicking the natural penetration domains used by viruses have led to greater efficiency of intracellular delivery. Following these nature-inspired examples, a number of rationally designed CPPs has been developed. In this review, a variety of CPP designs will be described, including linear and flexible, positively charged and often amphipathic CPPs, and more rigid versions comprising cyclic, stapled, or dimeric and/or multivalent, self-assembled peptides or peptido-mimetics. The application of distinct design strategies to known physico-chemical properties of CPPs offers the opportunity to improve their penetration efficiency and/or internalization kinetics. This led to increased design complexity of new CPPs that does not always result in greater CPP activity. Therefore, the transition of CPPs to a clinical setting remains a challenge also due to the concomitant involvement of various internalization routes and heterogeneity of cells used in the in vitro studies. -
Combinatorial Algorithms for Protein Folding in Lattice Models: a Survey of Mathematical Results
Combinatorial Algorithms for Protein Folding in Lattice Models: A Survey of Mathematical Results Sorin Istrail∗ Center for Computational Molecular Biology Department of Computer Science Brown University Providence, RI 02912 Fumei Lam† Center for Computational Molecular Biology Department of Computer Science Brown University Providence, RI 02912 Dedicated to Michael Waterman’s 67th Birthday June 17, 2009 “ ... a very nice step forward in the computerology of proteins.” Ken Dill 1995[1] Abstract We present a comprehensive survey of combinatorial algorithms and theorems about lattice protein folding models obtained in the almost 15 years since the publication in 1995 of the first protein folding approximation algorithm with mathematically guar- anteed error bounds [60]. The results presented here are mainly about the HP-protein folding model introduced by Ken Dill in 1985 [37]. The main topics of this survey include: approximation algorithms for linear-chain and side-chain lattice models, as well as off-lattice models, NP-completeness theorems about a variety of protein folding models, contact map structure of self-avoiding walks and HP-folds, combinatorics and algorithmics of side-chain models, bi-sphere packing and the Kepler conjecture, and the protein side-chain self-assembly conjecture. As an appealing bridge between the hybrid of continuous mathematics and discrete mathematics, a cornerstone of the mathemat- ical difficulty of the protein folding problem, we show how work on 2D self-avoiding walks contact-map decomposition [56] can build upon the exact RNA contacts counting formula by Mike Waterman and collaborators [96] which lead to renewed hope for ana- lytical closed-form approximations for statistical mechanics of protein folding in lattice models.