Peptide-Based Fibrous Biomaterials: Some Things Old, New and Borrowed Woolfson and Ryadnov 561
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Structural Insights Into Membrane Fusion Mediated by Convergent Small Fusogens
cells Review Structural Insights into Membrane Fusion Mediated by Convergent Small Fusogens Yiming Yang * and Nandini Nagarajan Margam Department of Microbiology and Immunology, Dalhousie University, Halifax, NS B3H 4R2, Canada; [email protected] * Correspondence: [email protected] Abstract: From lifeless viral particles to complex multicellular organisms, membrane fusion is inarguably the important fundamental biological phenomena. Sitting at the heart of membrane fusion are protein mediators known as fusogens. Despite the extensive functional and structural characterization of these proteins in recent years, scientists are still grappling with the fundamental mechanisms underlying membrane fusion. From an evolutionary perspective, fusogens follow divergent evolutionary principles in that they are functionally independent and do not share any sequence identity; however, they possess structural similarity, raising the possibility that membrane fusion is mediated by essential motifs ubiquitous to all. In this review, we particularly emphasize structural characteristics of small-molecular-weight fusogens in the hope of uncovering the most fundamental aspects mediating membrane–membrane interactions. By identifying and elucidating fusion-dependent functional domains, this review paves the way for future research exploring novel fusogens in health and disease. Keywords: fusogen; SNARE; FAST; atlastin; spanin; myomaker; myomerger; membrane fusion 1. Introduction Citation: Yang, Y.; Margam, N.N. Structural Insights into Membrane Membrane fusion -
Peptoid Residues Make Diverse, Hyperstable Collagen Triple Helices
Peptoid Residues Make Diverse, Hyperstable Collagen Triple Helices Julian L. Kessler1, Grace Kang1, Zhao Qin2, Helen Kang1, Frank G. Whitby3, Thomas E. Cheatham III4, Christopher P. Hill3, Yang Li1,*, and S. Michael Yu1,5 1Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah 84112, USA 2Department of Civil & Environmental Engineering, Collagen of Engineering & Computer Science, Syracuse University, Syracuse, New York 13244, USA 3Department of Biochemistry, University of Utah School of Medicine, Salt Lake City, UT 84112, USA 4Department of Medicinal Chemistry, College of Pharmacy, L. S. Skaggs Pharmacy Research Institute, University of Utah, Salt Lake City, Utah 84112, USA 5Department of Pharmaceutics and Pharmaceutical Chemistry, University of Utah, Salt Lake City, Utah 84112, USA *Corresponding Author: Yang Li ([email protected]) Abstract The triple-helical structure of collagen, responsible for collagen’s remarkable biological and mechanical properties, has inspired both basic and applied research in synthetic peptide mimetics for decades. Since non-proline amino acids weaken the triple helix, the cyclic structure of proline has been considered necessary, and functional collagen mimetic peptides (CMPs) with diverse sidechains have been difficult to produce. Here we show that N-substituted glycines (N-glys), also known as peptoid residues, exhibit a general triple-helical propensity similar to or greater than proline, allowing synthesis of thermally stable triple-helical CMPs with unprecedented sidechain diversity. We found that the N-glys stabilize the triple helix by sterically promoting the preorganization of individual CMP chains into the polyproline-II helix conformation. Our findings were supported by the crystal structures of two atomic-resolution N-gly-containing CMPs, as well as experimental and computational studies spanning more than 30 N-gly-containing peptides. -
Eukaryotic Genome Annotation
Comparative Features of Multicellular Eukaryotic Genomes (2017) (First three statistics from www.ensembl.org; other from original papers) C. elegans A. thaliana D. melanogaster M. musculus H. sapiens Species name Nematode Thale Cress Fruit Fly Mouse Human Size (Mb) 103 136 143 3,482 3,555 # Protein-coding genes 20,362 27,655 13,918 22,598 20,338 (25,498 (13,601 original (30,000 (30,000 original est.) original est.) original est.) est.) Transcripts 58,941 55,157 34,749 131,195 200,310 Gene density (#/kb) 1/5 1/4.5 1/8.8 1/83 1/97 LINE/SINE (%) 0.4 0.5 0.7 27.4 33.6 LTR (%) 0.0 4.8 1.5 9.9 8.6 DNA Elements 5.3 5.1 0.7 0.9 3.1 Total repeats 6.5 10.5 3.1 38.6 46.4 Exons % genome size 27 28.8 24.0 per gene 4.0 5.4 4.1 8.4 8.7 average size (bp) 250 506 Introns % genome size 15.6 average size (bp) 168 Arabidopsis Chromosome Structures Sorghum Whole Genome Details Characterizing the Proteome The Protein World • Sequencing has defined o Many, many proteins • How can we use this data to: o Define genes in new genomes o Look for evolutionarily related genes o Follow evolution of genes ▪ Mixing of domains to create new proteins o Uncover important subsets of genes that ▪ That deep phylogenies • Plants vs. animals • Placental vs. non-placental animals • Monocots vs. dicots plants • Common nomenclature needed o Ensure consistency of interpretations InterPro (http://www.ebi.ac.uk/interpro/) Classification of Protein Families • Intergrated documentation resource for protein super families, families, domains and functional sites o Mitchell AL, Attwood TK, Babbitt PC, et al. -
STACK: a Toolkit for Analysing Β-Helix Proteins
STACK: a toolkit for analysing ¯-helix proteins Master of Science Thesis (20 points) Salvatore Cappadona, Lars Diestelhorst Abstract ¯-helix proteins contain a solenoid fold consisting of repeated coils forming parallel ¯-sheets. Our goal is to formalise the intuitive notion of a ¯-helix in an objective algorithm. Our approach is based on first identifying residues stacks — linear spatial arrangements of residues with similar conformations — and then combining these elementary patterns to form ¯-coils and ¯-helices. Our algorithm has been implemented within STACK, a toolkit for analyzing ¯-helix proteins. STACK distinguishes aromatic, aliphatic and amidic stacks such as the asparagine ladder. Geometrical features are computed and stored in a relational database. These features include the axis of the ¯-helix, the stacks, the cross-sectional shape, the area of the coils and related packing information. An interface between STACK and a molecular visualisation program enables structural features to be highlighted automatically. i Contents 1 Introduction 1 2 Biological Background 2 2.1 Basic Concepts of Protein Structure ....................... 2 2.2 Secondary Structure ................................ 2 2.3 The ¯-Helix Fold .................................. 3 3 Parallel ¯-Helices 6 3.1 Introduction ..................................... 6 3.2 Nomenclature .................................... 6 3.2.1 Parallel ¯-Helix and its ¯-Sheets ..................... 6 3.2.2 Stacks ................................... 8 3.2.3 Coils ..................................... 8 3.2.4 The Core Region .............................. 8 3.3 Description of Known Structures ......................... 8 3.3.1 Helix Handedness .............................. 8 3.3.2 Right-Handed Parallel ¯-Helices ..................... 13 3.3.3 Left-Handed Parallel ¯-Helices ...................... 19 3.4 Amyloidosis .................................... 20 4 The STACK Toolkit 24 4.1 Identification of Structural Elements ....................... 24 4.1.1 Stacks ................................... -
Calculating the Structure-Based Phylogenetic Relationship
CALCULATING THE STRUCTURE-BASED PHYLOGENETIC RELATIONSHIP OF DISTANTLY RELATED HOMOLOGOUS PROTEINS UTILIZING MAXIMUM LIKELIHOOD STRUCTURAL ALIGNMENT COMBINATORICS AND A NOVEL STRUCTURAL MOLECULAR CLOCK HYPOTHESIS A DISSERTATION IN Molecular Biology and Biochemistry and Cell Biology and Biophysics Presented to the Faculty of the University of Missouri-Kansas City in partial fulfillment of the requirements for the degree Doctor of Philosophy by SCOTT GARRETT FOY B.S., Southwest Baptist University, 2005 B.A., Truman State University, 2007 M.S., University of Missouri-Kansas City, 2009 Kansas City, Missouri 2013 © 2013 SCOTT GARRETT FOY ALL RIGHTS RESERVED CALCULATING THE STRUCTURE-BASED PHYLOGENETIC RELATIONSHIP OF DISTANTLY RELATED HOMOLOGOUS PROTEINS UTILIZING MAXIMUM LIKELIHOOD STRUCTURAL ALIGNMENT COMBINATORICS AND A NOVEL STRUCTURAL MOLECULAR CLOCK HYPOTHESIS Scott Garrett Foy, Candidate for the Doctor of Philosophy Degree University of Missouri-Kansas City, 2013 ABSTRACT Dendrograms establish the evolutionary relationships and homology of species, proteins, or genes. Homology modeling, ligand binding, and pharmaceutical testing all depend upon the homology ascertained by dendrograms. Regardless of the specific algorithm, all dendrograms that ascertain protein evolutionary homology are generated utilizing polypeptide sequences. However, because protein structures superiorly conserve homology and contain more biochemical information than their associated protein sequences, I hypothesize that utilizing the structure of a protein instead -
And Beta-Helical Protein Motifs
Soft Matter Mechanical Unfolding of Alpha- and Beta-helical Protein Motifs Journal: Soft Matter Manuscript ID SM-ART-10-2018-002046.R1 Article Type: Paper Date Submitted by the 28-Nov-2018 Author: Complete List of Authors: DeBenedictis, Elizabeth; Northwestern University Keten, Sinan; Northwestern University, Mechanical Engineering Page 1 of 10 Please doSoft not Matter adjust margins Soft Matter ARTICLE Mechanical Unfolding of Alpha- and Beta-helical Protein Motifs E. P. DeBenedictis and S. Keten* Received 24th September 2018, Alpha helices and beta sheets are the two most common secondary structure motifs in proteins. Beta-helical structures Accepted 00th January 20xx merge features of the two motifs, containing two or three beta-sheet faces connected by loops or turns in a single protein. Beta-helical structures form the basis of proteins with diverse mechanical functions such as bacterial adhesins, phage cell- DOI: 10.1039/x0xx00000x puncture devices, antifreeze proteins, and extracellular matrices. Alpha helices are commonly found in cellular and extracellular matrix components, whereas beta-helices such as curli fibrils are more common as bacterial and biofilm matrix www.rsc.org/ components. It is currently not known whether it may be advantageous to use one helical motif over the other for different structural and mechanical functions. To better understand the mechanical implications of using different helix motifs in networks, here we use Steered Molecular Dynamics (SMD) simulations to mechanically unfold multiple alpha- and beta- helical proteins at constant velocity at the single molecule scale. We focus on the energy dissipated during unfolding as a means of comparison between proteins and work normalized by protein characteristics (initial and final length, # H-bonds, # residues, etc.). -
Introduction to the Local Theory of Curves and Surfaces
Introduction to the Local Theory of Curves and Surfaces Notes of a course for the ICTP-CUI Master of Science in Mathematics Marco Abate, Fabrizio Bianchi (with thanks to Francesca Tovena) (Much more on this subject can be found in [1]) CHAPTER 1 Local theory of curves Elementary geometry gives a fairly accurate and well-established notion of what is a straight line, whereas is somewhat vague about curves in general. Intuitively, the difference between a straight line and a curve is that the former is, well, straight while the latter is curved. But is it possible to measure how curved a curve is, that is, how far it is from being straight? And what, exactly, is a curve? The main goal of this chapter is to answer these questions. After comparing in the first two sections advantages and disadvantages of several ways of giving a formal definition of a curve, in the third section we shall show how Differential Calculus enables us to accurately measure the curvature of a curve. For curves in space, we shall also measure the torsion of a curve, that is, how far a curve is from being contained in a plane, and we shall show how curvature and torsion completely describe a curve in space. 1.1. How to define a curve n What is a curve (in a plane, in space, in R )? Since we are in a mathematical course, rather than in a course about military history of Prussian light cavalry, the only acceptable answer to such a question is a precise definition, identifying exactly the objects that deserve being called curves and those that do not. -
Chern-Simons-Higgs Model As a Theory of Protein Molecules
ITEP-TH-12/19 Chern-Simons-Higgs Model as a Theory of Protein Molecules Dmitry Melnikov and Alyson B. F. Neves November 13, 2019 Abstract In this paper we discuss a one-dimensional Abelian Higgs model with Chern-Simons interaction as an effective theory of one-dimensional curves embedded in three-dimensional space. We demonstrate how this effective model is compatible with the geometry of protein molecules. Using standard field theory techniques we analyze phenomenologically interesting static configurations of the model and discuss their stability. This simple model predicts some characteristic relations for the geometry of secondary structure motifs of proteins, and we show how this is consistent with the experimental data. After using the data to universally fix basic local geometric parameters, such as the curvature and torsion of the helical motifs, we are left with a single free parameter. We explain how this parameter controls the abundance and shape of the principal motifs (alpha helices, beta strands and loops connecting them). 1 Introduction Proteins are very complex objects, but in the meantime there is an impressive underlying regularity beyond their structure. This regularity is captured in part by the famous Ramachandran plots that map the correlation of the dihedral (torsion) angles of consecutive bonds in the protein backbone (see for example [1, 2, 3]). The example on figure 1 shows an analogous data of about hundred of proteins, illustrating the localization of the pairs of angles around two regions.1 These two most densely populated regions, labeled α and β, correspond to the most common secondary structure elements in proteins: (right) alpha helices and beta strands. -
Computational Genomics
COMPUTATIONAL GENOMICS: GROUP MEMBERS: Anshul Kundaje (EE) [email protected] Daita Domnica Nicolae (Bio) [email protected] Deniz Sarioz (CS) [email protected] Joseph Gagliano (CS) [email protected] Predicting the Beta-helix fold from Protein sequence data Abstract: This project involves the study and implementation of Betawrap, an algorithm used to predict Beta-helix supersecondary structural motifs using protein sequence data. We begin with a biochemical view of proteins and their structural features. This is followed by a general discussion of the various methods of protein structural prediction. A structural viewpoint of the Beta-Helix is highlighted followed by a detailed discussion of Betawrap. We include the design and implementation details alongside. PERL was the programming language used for the implementation. The alpha helical filter was implemented with the help of pre-existing software known as Pred2ary. The implementation was run on a positive and negative test set, a total of 59 proteins. These tests sets were generated from the SCOP database by checking predictions made by the original Betawrap software and by directly looking at the structures in the PDB. Our program can be downloaded from betawrap.tar.gz. The archive contains a readme with necessary instructions. The program has been commented extensively. Some debugging statements have also be left as comments. The predictions made by our program are very accurate and we had a only 2 misclassifications in a set of 59 proteins. Basic Biochemistry of Protein Structure: Proteins are polymers of 20 different amino acids joined by peptide bonds. At physiological temperatures in aqueous solution, the polypeptide chains of proteins fold into a structure that in most cases is globular. -
Prediction of Certain Well-Characterized Domains of Known Functions Within the PE and PPE Proteins of Mycobacteria
RESEARCH ARTICLE Prediction of Certain Well-Characterized Domains of Known Functions within the PE and PPE Proteins of Mycobacteria Rafiya Sultana, Karunakar Tanneeru, Ashwin B. R. Kumar, Lalitha Guruprasad* School of Chemistry, University of Hyderabad, Hyderabad, 500046, India * [email protected] Abstract The PE and PPE protein family are unique to mycobacteria. Though the complete genome sequences for over 500 M. tuberculosis strains and mycobacterial species are available, few PE and PPE proteins have been structurally and functionally characterized. We have therefore used bioinformatics tools to characterize the structure and function of these pro- OPEN ACCESS teins. We selected representative members of the PE and PPE protein family by phylogeny Citation: Sultana R, Tanneeru K, Kumar ABR, analysis and using structure-based sequence annotation identified ten well-characterized Guruprasad L (2016) Prediction of Certain Well- protein domains of known function. Some of these domains were observed to be common Characterized Domains of Known Functions within the PE and PPE Proteins of Mycobacteria. PLoS to all mycobacterial species and some were species specific. ONE 11(2): e0146786. doi:10.1371/journal. pone.0146786 Editor: Bostjan Kobe, University of Queensland, AUSTRALIA Received: September 22, 2015 Introduction Accepted: December 22, 2015 Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb), remains a major global health Published: February 18, 2016 problem and one of the main causes of death around the world [1]. About one third of the world’s population has latent TB infection. TB kills about two million people annually and is Copyright: © 2016 Sultana et al. This is an open the second leading cause of death from an infectious disease worldwide, after the human access article distributed under the terms of the Creative Commons Attribution License, which permits immunodeficiency virus (HIV) [2,3]. -
Chiral Dualism As an Instrument of Hierarchical Structure Formation in Molecular Biology
S S symmetry Article Chiral Dualism as an Instrument of Hierarchical Structure Formation in Molecular Biology Vsevolod A. Tverdislov * and Ekaterina V. Malyshko * Faculty of Physics, Lomonosov Moscow State University, Leninskie gory 1-2, 119234 Moscow, Russia * Correspondence: [email protected] (V.A.T.); [email protected] (E.V.M.) Received: 6 March 2020; Accepted: 2 April 2020; Published: 8 April 2020 Abstract: The origin of chiral asymmetry in biology has attracted the attention of the research community throughout the years. In this paper we discuss the role of chirality and chirality sign alternation (L–D–L–D in proteins and D–L–D–L in DNA) in promoting self-organization in biology, starting at the level of single molecules and continuing to the level of supramolecular assemblies. In addition, we also discuss chiral assemblies in solutions of homochiral organic molecules. Sign-alternating chiral hierarchies created by proteins and nucleic acids are suggested to create the structural basis for the existence of selected mechanical degrees of freedom required for conformational dynamics in enzymes and macromolecular machines. Keywords: chirality; proteins; nucleic acids; hierarchy of structures; folding; molecular machines 1. Introduction The origin and potential role of chiral asymmetry in biology have attracted the attention of the research community throughout the years [1–18]. Although, at the macroscopic level, nonbiological structures with a homochiral molecular basis are not known, living organisms have been engaged -
Cyclic GMP–AMP Signalling Protects Bacteria Against Viral Infection
Article Cyclic GMP–AMP signalling protects bacteria against viral infection https://doi.org/10.1038/s41586-019-1605-5 Daniel Cohen1,3, Sarah Melamed1,3, Adi Millman1, Gabriela Shulman1, Yaara Oppenheimer-Shaanan1, Assaf Kacen2, Shany Doron1, Gil Amitai1* & Rotem Sorek1* Received: 25 June 2019 Accepted: 11 September 2019 The cyclic GMP–AMP synthase (cGAS)–STING pathway is a central component of the Published online: xx xx xxxx cell-autonomous innate immune system in animals1,2. The cGAS protein is a sensor of cytosolic viral DNA and, upon sensing DNA, it produces a cyclic GMP–AMP (cGAMP) signalling molecule that binds to the STING protein and activates the immune response3–5. The production of cGAMP has also been detected in bacteria6, and has been shown, in Vibrio cholerae, to activate a phospholipase that degrades the inner bacterial membrane7. However, the biological role of cGAMP signalling in bacteria remains unknown. Here we show that cGAMP signalling is part of an antiphage defence system that is common in bacteria. This system is composed of a four-gene operon that encodes the bacterial cGAS and the associated phospholipase, as well as two enzymes with the eukaryotic-like domains E1, E2 and JAB. We show that this operon confers resistance against a wide variety of phages. Phage infection triggers the production of cGAMP, which—in turn—activates the phospholipase, leading to a loss of membrane integrity and to cell death before completion of phage reproduction. Diverged versions of this system appear in more than 10% of prokaryotic genomes, and we show that variants with efectors other than phospholipase also protect against phage infection.