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Computation and Visualization of Protein Topology Graphs Including Ligand Information
Computation and Visualization of Protein Topology Graphs Including Ligand Information Tim Schäfer1, Patrick May2, and Ina Koch1 1 Institute of Computer Science, Department of Molecular Bioinformatics, Johann Wolfgang Goethe-University Frankfurt (Main), Robert-Mayer-Straße 11–15, 60325 Frankfurt (Main), Germany, [email protected] 2 Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Campus Belval, 7 Avenue des Hauts-Fourneaux, L–4362 Esch-sur-Alzette, Luxembourg Abstract Motivation: Ligand information is of great interest to understand protein function. Protein structure topology can be modeled as a graph with secondary structure elements as vertices and spatial contacts between them as edges. Meaningful representations of such graphs in 2D are required for the visual inspection, comparison and analysis of protein folds, but their automatic visualization is still challenging. We present an approach which solves this task, supports different graph types and can optionally include ligand contacts. Results: Our method extends the field of protein structure description and visualization by including ligand information. It generates a mathematically unique representation and high- quality 2D plots of the secondary structure of a protein based on a protein-ligand graph. This graph is computed from 3D atom coordinates in PDB files and the corresponding SSE assignments of the DSSP algorithm. The related software supports different notations and allows a rapid visualization of protein structures. It can also export graphs in various standard file formats so they can be used with other software. Our approach visualizes ligands in relationship to protein structure topology and thus represents a useful tool for exploring protein structures. Availability: The software is released under an open source license and available at http://www.bioinformatik.uni-frankfurt.de/ in the Software section under Visualization of Protein Ligand Graphs. -
Predictive Energy Landscapes for Folding Α-Helical Transmembrane Proteins
Predictive energy landscapes for folding α-helical transmembrane proteins Bobby L. Kim, Nicholas P. Schafer, and Peter G. Wolynes1 Departments of Chemistry and Physics and Astronomy and the Center for Theoretical Biological Physics, Rice University, Houston, TX 77005 Contributed by Peter G. Wolynes, June 11, 2014 (sent for review May 19, 2014; reviewed by Zaida A. Luthey-Schulten, Shoji Takada, and Margaret Cheung) We explore the hypothesis that the folding landscapes of mem- folding. Starting with Khorana’swork(7),numerousα-helical brane proteins are funneled once the proteins’ topology within the transmembrane proteins have been refolded from a chemically membrane is established. We extend a protein folding model, denatured state in vitro (8). This indicates that at least some the associative memory, water-mediated, structure, and energy transmembrane domains may not require the translocon to fold model (AWSEM) by adding an implicit membrane potential and properly. In addition, recent experiments on a few α-helical reoptimizing the force field to account for the differing nature of transmembrane proteins have succeeded in characterizing the the interactions that stabilize proteins within lipid membranes, structure of transition state ensembles, in a manner like that used yielding a model that we call AWSEM-membrane. Once the pro- for globular proteins. These studies suggest that native contacts tein topology is set in the membrane, hydrophobic attractions are important in the folding nucleus but may not represent the play a lesser role in finding the native structure, whereas po- whole story (9, 10). Whether membrane proteins possess energy lar–polar attractions are more important than for globular pro- landscapes as funneled as globular proteins remains an open teins. -
This Article Appeared in a Journal Published by Elsevier. the Attached
This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright Author's personal copy Available online at www.sciencedirect.com Recent advances in genetic code engineering in Escherichia coli Michael Georg Hoesl and Nediljko Budisa The expansion of the genetic code is gradually becoming a modifications (PTMs). These reactions are selectively core discipline in Synthetic Biology. It offers the best possible and timely coordinated chemistries performed by dedi- platform for the transfer of numerous chemical reactions and cated enzymes and enzymatic complexes, usually in processes from the chemical synthetic laboratory into the specialized cell compartments. biochemistry of living cells. The incorporation of biologically occurring or chemically synthesized non-canonical amino Certainly, one of the main goals of Synthetic Biology is acids into recombinant proteins and even proteomes via to generate new and emergent biological functions in reprogrammed protein translation is in the heart of these streamlined cells which are equipped with ‘tailor-made efforts. Orthogonal pairs consisting of aminoacyl-tRNA biochemical production lines’. However, it is extremely synthetase and its cognate tRNA proved to be a general difficult to mimic nature’s complex machineries such as tool for the assignment of certain codons of the genetic code the PTM-apparatus. -
Alternative Biochemistries for Alien Life: Basic Concepts and Requirements for the Design of a Robust Biocontainment System in Genetic Isolation
G C A T T A C G G C A T genes Review Alternative Biochemistries for Alien Life: Basic Concepts and Requirements for the Design of a Robust Biocontainment System in Genetic Isolation Christian Diwo 1 and Nediljko Budisa 1,2,* 1 Institut für Chemie, Technische Universität Berlin Müller-Breslau-Straße 10, 10623 Berlin, Germany; [email protected] 2 Department of Chemistry, University of Manitoba, 144 Dysart Rd, 360 Parker Building, Winnipeg, MB R3T 2N2, Canada * Correspondence: [email protected] or [email protected]; Tel.: +49-30-314-28821 or +1-204-474-9178 Received: 27 November 2018; Accepted: 21 December 2018; Published: 28 December 2018 Abstract: The universal genetic code, which is the foundation of cellular organization for almost all organisms, has fostered the exchange of genetic information from very different paths of evolution. The result of this communication network of potentially beneficial traits can be observed as modern biodiversity. Today, the genetic modification techniques of synthetic biology allow for the design of specialized organisms and their employment as tools, creating an artificial biodiversity based on the same universal genetic code. As there is no natural barrier towards the proliferation of genetic information which confers an advantage for a certain species, the naturally evolved genetic pool could be irreversibly altered if modified genetic information is exchanged. We argue that an alien genetic code which is incompatible with nature is likely to assure the inhibition of all mechanisms of genetic information transfer in an open environment. The two conceivable routes to synthetic life are either de novo cellular design or the successive alienation of a complex biological organism through laboratory evolution. -
Orthogonal Dual-Modification of Proteins for the Engineering of Multivalent Protein Scaffolds
Orthogonal dual-modification of proteins for the engineering of multivalent protein scaffolds Michaela Mühlberg‡1,2, Michael G. Hoesl‡3, Christian Kuehne4, Jens Dernedde4, Nediljko Budisa*3 and Christian P. R. Hackenberger*1,5,§ Full Research Paper Open Access Address: Beilstein J. Org. Chem. 2015, 11, 784–791. 1Forschungsinstitut für Molekulare Pharmakologie (FMP), doi:10.3762/bjoc.11.88 Robert-Roessle-Str. 10, 13125 Berlin, Germany, 2Freie Universität Berlin, Institut für Chemie und Biochemie, Takustr. 3, 14195 Berlin, Received: 11 February 2015 Germany, 3Technische Universität Berlin, AK Biokatalyse, Institut für Accepted: 05 May 2015 Chemie, Müller-Breslau-Str. 10, 10623 Berlin, Germany, 4Charité - Published: 13 May 2015 Universitätsmedizin Berlin, Institut für Laboratoriumsmedizin, Klinische Chemie und Pathobiochemie, Augustenburger Platz 1, This article is part of the Thematic Series "Multivalency as a chemical 13353 Berlin, Germany and 5Humboldt Universität zu Berlin, Institut organization and action principle". für Organische und Bioorganische Chemie, Institut für Chemie, Brook-Taylor-Str. 2, 12489 Berlin, Germany Guest Editor: R. Haag Email: © 2015 Mühlberg et al; licensee Beilstein-Institut. Nediljko Budisa* - [email protected]; License and terms: see end of document. Christian P. R. Hackenberger* - [email protected] * Corresponding author ‡ Equal contributors § Fax: +49 (0)30 94793-188 Keywords: chemoselectivity; dual protein modification; lectin; multivalency Abstract To add new tools to the repertoire of protein-based multivalent scaffold design, we have developed a novel dual-labeling strategy for proteins that combines residue-specific incorporation of unnatural amino acids with chemical oxidative aldehyde formation at the N-terminus of a protein. Our approach relies on the selective introduction of two different functional moieties in a protein by mutually orthogonal copper-catalyzed azide–alkyne cycloaddition (CuAAC) and oxime ligation. -
Protein Folding and the Organization of the Protein Topology Universe
Opinion TRENDS in Biochemical Sciences Vol.30 No.1 January 2005 Protein folding and the organization of the protein topology universe Kresten Lindorff-Larsen1, Peter Røgen2, Emanuele Paci3, Michele Vendruscolo1 and Christopher M. Dobson1 1University of Cambridge, Department of Chemistry, Lensfield Road, Cambridge, UK, CB2 1EW 2Department of Mathematics, Technical University of Denmark, Building 303, DK-2800 Kongens Lyngby, Denmark 3University of Zu¨ rich, Department of Biochemistry, Winterthurerstrasse 190, 8057 Zu¨ rich, Switzerland The mechanism by which proteins fold to their native ensembles has shown that establishing the correct overall states has been the focus of intense research in recent topology of the polypeptide chain is a crucial aspect of years. The rate-limiting event in the folding reaction is protein folding. This observation is in accord with a series the formation of a conformation in a set known as the of studies that have shown that the folding rate of a transition-state ensemble. The structural features pre- protein, to a first approximation, can be related to the sent within such ensembles have now been analysed for entropic cost of forming the native-like topology [16–22]. a series of proteins using data from a combination of The structural changes occurring during protein fold- biochemical and biophysical experiments together with ing have also been analysed in detail for a series of computer-simulation methods. These studies show that proteins and we discuss some of these studies here. The the topology of the transition state is determined by a results enable the topological view of folding to be set of interactions involving a small number of key reconciled with the well-established concept of nucleation residues and, in addition, that the topology of the [23] by showing that – despite the many different ways in transition state is closer to that of the native state than which a given topology could, in principle, be generated – to that of any other fold in the protein universe. -
Using the Spycatcher-Spytag and Related Systems for Labeling and Localizing Bacterial Proteins
International Journal of Molecular Sciences Review Catching a SPY: Using the SpyCatcher-SpyTag and Related Systems for Labeling and Localizing Bacterial Proteins Daniel Hatlem , Thomas Trunk, Dirk Linke and Jack C. Leo * Bacterial Cell Surface Group, Section for Evolution and Genetics, Department of Biosciences, University of Oslo, 0316 Oslo, Norway; [email protected] (D.H.); [email protected] (T.T.); [email protected] (D.L.) * Correspondence: [email protected]; Tel.: +47-228-59027 Received: 2 April 2019; Accepted: 26 April 2019; Published: 30 April 2019 Abstract: The SpyCatcher-SpyTag system was developed seven years ago as a method for protein ligation. It is based on a modified domain from a Streptococcus pyogenes surface protein (SpyCatcher), which recognizes a cognate 13-amino-acid peptide (SpyTag). Upon recognition, the two form a covalent isopeptide bond between the side chains of a lysine in SpyCatcher and an aspartate in SpyTag. This technology has been used, among other applications, to create covalently stabilized multi-protein complexes, for modular vaccine production, and to label proteins (e.g., for microscopy). The SpyTag system is versatile as the tag is a short, unfolded peptide that can be genetically fused to exposed positions in target proteins; similarly, SpyCatcher can be fused to reporter proteins such as GFP, and to epitope or purification tags. Additionally, an orthogonal system called SnoopTag-SnoopCatcher has been developed from an S. pneumoniae pilin that can be combined with SpyCatcher-SpyTag to produce protein fusions with multiple components. Furthermore, tripartite applications have been produced from both systems allowing the fusion of two peptides by a separate, catalytically active protein unit, SpyLigase or SnoopLigase. -
UC San Diego UC San Diego Electronic Theses and Dissertations
UC San Diego UC San Diego Electronic Theses and Dissertations Title Structural analysis of a forkhead-associated domain from the type III secretion system protein YscD Permalink https://escholarship.org/uc/item/6410g6n9 Author Gamez, Alicia Margarita Publication Date 2011 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Structural analysis of a forkhead-associated domain from the type III secretion system protein YscD A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Chemistry by Alicia Margarita Gamez Committee in charge: Professor Partho Ghosh, Chair Professor Michael Burkart Professor Daniel Donoghue Professor Victor Nizet Professor Susan Taylor 2011 The Dissertation of Alicia Margarita Gamez is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Chair University of California, San Diego 2011 iii DEDICATION This thesis is dedicated to my family. iv TABLE OF CONTENTS Signature Page .......................................................................................................... iii Dedication ................................................................................................................. iv Table of Contents ....................................................................................................... v List of Figures .......................................................................................................... -
1 Engineering Lipases with an Expanded Genetic Code Alessandro De Simone, Michael Georg Hoesl, and Nediljko Budisa
3 1 Engineering Lipases with an Expanded Genetic Code Alessandro De Simone, Michael Georg Hoesl, and Nediljko Budisa 1.1 Introduction Lipases (EC 3.1.1.3) are a class of ubiquitous enzymes that catalyze both the hydrolysis and synthesis of acylglycerols with long acyl chains (carbon atoms >10) [1]. Currently, they constitute one of the most important groups of biocatalysts applied in many fields, including foods, detergents, flavors, fine chemicals, cosmetics, biodiesel, and pharmaceuticals owing to their high specificity, regios- electivity, and enantioselectivity [2]. Lipases can be found in a broad range of organisms, including plants and animals, however, it is chiefly the microbial lipases that find immense application. This is because of their high yields and ease of genetic manipulation, as well as wide substrate specificity [3]. Although lipases’ properties (molecular weight, pH and temperature optima, stability, substrate specificity) are source dependent, they all share a common structure consisting of a compact minimal α/β hydrolase fold. The hydrolase fold is composed of a central β-sheet consisting of up to eight different β strands connected by up to six α helices [1]. The active site of the α/β hydrolase fold enzymes contains a nucleophilic residue (serine), a catalytic acid residue (aspartate/glutamate), and a histidine residue, always in this order in the amino acid sequence. These residues act cooperatively in the catalytic mechanism of ester hydrolysis [4]. The lipolytic reaction takes place at the interface between an insoluble substrate phase and the aqueous phase in which the enzyme is dissolved. Lipases are activated by the presence of this emulsion interface, a phenomenon called interfacial activation, which differentiates them from similar esterases. -
APEX2 Proximity Proteomics Resolves Flagellum Subdomains and Identifies Flagellum Tip-Specific
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.09.984815; this version posted March 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 APEX2 proximity proteomics resolves flagellum subdomains and identifies flagellum tip-specific 2 proteins in Trypanosoma brucei 3 4 Daniel E. Vélez-Ramírez,a,b Michelle M. Shimogawa,a Sunayan Ray,a* Andrew Lopez,a Shima 5 Rayatpisheh,c* Gerasimos Langousis,a* Marcus Gallagher-Jones,d Samuel Dean,e James A. Wohlschlegel,c 6 Kent L. Hill,a,f,g# 7 8 aDepartment of Microbiology, Immunology, and Molecular Genetics, University of California Los 9 Angeles, Los Angeles, California, USA 10 bPosgrado en Ciencias Biológicas, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de 11 México, México 12 cDepartment of Biological Chemistry, University of California Los Angeles, Los Angeles, California, USA 13 dDepartment of Chemistry and Biochemistry, UCLA-DOE Institute for Genomics and Proteomics, Los 14 Angeles, California, USA 15 eWarwick Medical School, University of Warwick, Coventry, England, United Kingdom 16 fMolecular Biology Institute, University of California Los Angeles, Los Angeles, California, USA 17 gCalifornia NanoSystems Institute, University of California Los Angeles, Los Angeles, California, USA 18 19 Running title: APEX2 proteomics in Trypanosoma brucei 20 21 #Address correspondence to Kent L. Hill, [email protected]. Page 1 of 33 bioRxiv preprint doi: https://doi.org/10.1101/2020.03.09.984815; this version posted March 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
Machine Learning Methods for Protein Structure Prediction Jianlin Cheng, Allison N
IEEE REVIEWS IN BIOMEDICAL ENGINEERING, VOL. 1, 2008 41 Machine Learning Methods for Protein Structure Prediction Jianlin Cheng, Allison N. Tegge, Member, IEEE, and Pierre Baldi, Senior Member, IEEE Methodological Review Abstract—Machine learning methods are widely used in bioin- formatics and computational and systems biology. Here, we review the development of machine learning methods for protein structure prediction, one of the most fundamental problems in structural biology and bioinformatics. Protein structure predic- tion is such a complex problem that it is often decomposed and attacked at four different levels: 1-D prediction of structural features along the primary sequence of amino acids; 2-D predic- tion of spatial relationships between amino acids; 3-D prediction Fig. 1. Protein sequence-structure-function relationship. A protein is a linear of the tertiary structure of a protein; and 4-D prediction of the polypeptide chain composed of 20 different kinds of amino acids represented quaternary structure of a multiprotein complex. A diverse set of by a sequence of letters (left). It folds into a tertiary (3-D) structure (middle) both supervised and unsupervised machine learning methods has composed of three kinds of local secondary structure elements (helix – red; beta- strand – yellow; loop – green). The protein with its native 3-D structure can carry been applied over the years to tackle these problems and has sig- out several biological functions in the cell (right). nificantly contributed to advancing the state-of-the-art of protein structure prediction. In this paper, we review the development and application of hidden Markov models, neural networks, support vector machines, Bayesian methods, and clustering methods in structure elements are further packed to form a tertiary structure 1-D, 2-D, 3-D, and 4-D protein structure predictions. -
The Relationship Between APOL1 Structure and Function: Clinical Implications
Kidney360 Publish Ahead of Print, published on November 4, 2020 as doi:10.34067/KID.0002482020 The relationship between APOL1 structure and function: Clinical implications Sethu M. Madhavan1, Matthias Buck2 1Department of Medicine, The Ohio State University, Columbus, OH, 2Department of Physiology & Biophysics, Case Western Reserve University School of Medicine, Cleveland, OH Corresponding author: Sethu M. Madhavan, M.D. 495 W 12th Avenue Columbus, OH 43210 Email: [email protected] Phone: 614-293-6389 1 Copyright 2020 by American Society of Nephrology. Abstract Common variants in the APOL1 gene are associated with an increased risk of nondiabetic kidney disease in individuals of African ancestry. Mechanisms by which APOL1 variants mediate kidney disease pathogenesis are not well understood. Amino acid changes resulting from the kidney disease-associated APOL1 variants alter the three-dimensional structure and conformational dynamics of the C-terminal α- helical domain of the protein, which can rationalize the functional consequences. Understanding the three-dimensional structure of the protein with and without the risk variants can provide insights into the pathogenesis of kidney diseases mediated by APOL1 variants. Introduction Population-based studies have established a strong association of two variants in the APOL1 gene with the excess risk of nondiabetic chronic kidney disease (CKD) in individuals of African ancestry.1-5 One variant involves the substitution of two amino acids (S342G and I384M; termed G1), and the other the deletion of two consecutive amino acids (N388 and Y389; termed G2) compared to the ancestral nonrisk allele termed G0. APOL1 G1 and G2 variants are common in individuals with African ancestry, with at least 50 % of individuals carrying one copy of the risk allele and 15 % with two copies of the risk allele.1,3 Despite the strong association of APOL1 variants with kidney disease, the molecular mechanisms by which these APOL1 variants contribute to CKD pathogenesis and progression remains unclear.