Structural Mechanisms of RNA Recognition: Sequence-Specific and Non-Specific RNA-Binding Proteins and the Cas9-RNA-DNA Complex
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Side-Chain Liquid Crystal Polymers (SCLCP): Methods and Materials. an Overview
Materials 2009, 2, 95-128; doi:10.3390/ma2010095 OPEN ACCESS materials ISSN 1996-1944 www.mdpi.com/journal/materials Review Side-chain Liquid Crystal Polymers (SCLCP): Methods and Materials. An Overview Tomasz Ganicz * and Włodzimierz Stańczyk Centre of Molecular and Macromolecular Studies, Polish Academy of Science, Sienkiewicza 112, 90- 363 Łódź, Poland; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel. +48-42-684-71-13; Fax: +48-42-684-71-26 Received: 5 February 2009; in revised form: 3 March 2009 / Accepted: 9 March 2009 / Published: 11 March 2009 Abstract: This review focuses on recent developments in the chemistry of side chain liquid crystal polymers. It concentrates on current trends in synthetic methods and novel, well defined structures, supramolecular arrangements, properties, and applications. The review covers literature published in this century, apart from some areas, such as dendritic and elastomeric systems, which have been recently reviewed. Keywords: Liquid crystals, side chain polymers, polymer modification, polymer synthesis, self-assembly. 1. Introduction Over thirty years ago the work of Finkelmann and Ringsdorf [1,2] gave important momentum to synthesis of side chain liquid crystal polymers (SCLCPs), materials which combine the anisotropy of liquid crystalline mesogens with the mechanical properties of polymers. Although there were some earlier attempts [2], their approach of decoupling the motions of a polymer main chain from a mesogen, thus allowed side chain moieties to build up long range ordering (Figure 1). They were able to synthesize polymers with nematic, smectic and cholesteric phases via free radical polymerization of methacryloyl type monomers [3]. -
The Role of Side-Chain Branch Position on Thermal Property of Poly-3-Alkylthiophenes
Polymer Chemistry The Role of Side-chain Branch Position on Thermal Property of Poly-3-alkylthiophenes Journal: Polymer Chemistry Manuscript ID PY-ART-07-2019-001026.R2 Article Type: Paper Date Submitted by the 02-Oct-2019 Author: Complete List of Authors: Gu, Xiaodan; University of Southern Mississippi, School of Polymer Science and Engineering Cao, Zhiqiang; University of Southern Mississippi, School of Polymer Science and Engineering Galuska, Luke; University of Southern Mississippi, School of Polymer Science and Engineering Qian, Zhiyuan; University of Southern Mississippi, School of Polymer Science and Engineering Zhang, Song; University of Southern Mississippi, School of Polymer Science and Engineering Huang, Lifeng; University of Southern Mississippi, School of Polymers and High Performance Materials Prine, Nathaniel; University of Southern Mississippi, School of Polymer Science and Engineering Li, Tianyu; Oak Ridge National Laboratory; University of Tennessee Knoxville He, Youjun; Oak Ridge National Laboratory Hong, Kunlun; Oak Ridge National Laboratory, Center for Nanophase Materials Science; Oak Ridge National Laboratory, Center for Nanophase Materials Science Page 1 of 13 PleasePolymer do not Chemistryadjust margins ARTICLE The Role of Side-chain Branch Position on Thermal Property of Poly-3-alkylthiophenes Received 00th January 20xx, a a a a a a Accepted 00th January 20xx Zhiqiang Cao, Luke Galuska, Zhiyuan Qian, Song Zhang, Lifeng Huang, Nathaniel Prine, Tianyu Li,b, c Youjun He,b Kunlun Hong,*b, c and Xiaodan Gu*a DOI: 10.1039/x0xx00000x Thermomechanical properties of conjugated polymers (CPs) are greatly influenced by both their microstructures and backbone structures. In the present work, to investigate the effect of side-chain branch position on the backbone’s mobility and molecular packing structure, four poly (3-alkylthiophene-2, 5-diyl) derivatives (P3ATs) with different side chains, either branched and linear, were synthesized by a quasi-living Kumada catalyst transfer polymerization (KCTP) method. -
Improved Prediction of Protein Side-Chain Conformations with SCWRL4 Georgii G
proteins STRUCTURE O FUNCTION O BIOINFORMATICS Improved prediction of protein side-chain conformations with SCWRL4 Georgii G. Krivov,1,2 Maxim V. Shapovalov,1 and Roland L. Dunbrack Jr.1* 1 Institute for Cancer Research, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, Pennsylvania 19111 2 Department of Applied Mathematics, Moscow Engineering Physics Institute (MEPhI), Kashirskoe Shosse 31, Moscow 115409, Russian Federation INTRODUCTION ABSTRACT The side-chain conformation prediction problem is an integral Determination of side-chain conformations is an component of protein structure determination, protein structure important step in protein structure prediction and protein design. Many such methods have prediction, and protein design. In single-site mutants and in closely been presented, although only a small number related proteins, the backbone often changes little and structure pre- 1 are in widespread use. SCWRL is one such diction can be accomplished by accurate side-chain prediction. In method, and the SCWRL3 program (2003) has docking of ligands and other proteins, taking into account changes remained popular because of its speed, accuracy, in side-chain conformation is often critical to accurate structure pre- and ease-of-use for the purpose of homology dictions of complexes.2–4 Even in methods that take account of modeling. However, higher accuracy at compara- changes in backbone conformation, one step in the process is recal- ble speed is desirable. This has been achieved in culation of side-chain conformation or ‘‘repacking.’’5 Because many a new program SCWRL4 through: (1) a new backbone conformations may be sampled in model refinements, backbone-dependent rotamer library based on side-chain prediction must also be very fast. -
Molecular Modelling Virtual Chemistry Resource Pymol Experiment Answer Sheet Well Done for Completing Our Pymol Experiment! We Really Hope You Enjoyed It!
#Outtheboxthinking Faculty of Natural & Mathematical Sciences Department of Chemistry Molecular Modelling Virtual Chemistry Resource PyMol Experiment Answer Sheet Well done for completing our PyMol experiment! We really hope you enjoyed it! Please make sure you have completed our post experiment questionnaire. https://kings.onlinesurveys.ac.uk/post-questionnaire-for-outtheboxthinking-resources Send us photos, comments, or thoughts to either our twitter or Instagram accounts using the hashtag #outtheboxthinking. We also encourage you to make a poster of your data and email it to us. Exploring how proteins are formed Press “Amino Acid” Q. What is the R group in the side chain of this amino acid? CH3- Methyl Group Q. Which amino acid is shown here? Alanine Press the button “ALA_ASP” and an additional amino acid will appear Q. What is the chemical formula of the side chain of the new amino acid? CH2COOH Q. What is the name of the second, new amino acid? Aspartic Acid or Aspartate Press the button “Bonded_Ala_Asp” Q. What colour(s) is the amide bond connecting the two amino acids? Blue and green. It is important to highlight the bond between the nitrogen of one amino acid and the carbonyl of the second amino acid and not any other bond (Figure 1). Figure 1: Arrow points to the amide bond formed between two amino acids. Page 1 of 8 Instagram: kclchemoutreach #outtheboxthinking Q. Which elements have been lost from each amino acid following their bonding? Amino acid 1:: Alanine has lost an oxygen and a hydrogen Amino acid 2: Aspartic Acid has lost a hydrogen If you are unsure why this is correct look at figure 2 and open the PyMol document again to visualise the bonding Figure 2: Reaction scheme for amino acid bonding, resulting in the formation of an amide bond and the loss of water. -
Serine Arginine-Rich Protein-Dependent Suppression Of
Serine͞arginine-rich protein-dependent suppression of exon skipping by exonic splicing enhancers El Che´ rif Ibrahim*, Thomas D. Schaal†, Klemens J. Hertel‡, Robin Reed*, and Tom Maniatis†§ *Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, MA 02115; †Department of Molecular and Cellular Biology, Harvard University, 7 Divinity Avenue, Cambridge, MA 02138; and ‡Department of Microbiology and Molecular Genetics, University of California, Irvine, CA 92697-4025 Contributed by Tom Maniatis, January 28, 2005 The 5 and 3 splice sites within an intron can, in principle, be joined mechanisms by which exon skipping is prevented. Our data to those within any other intron during pre-mRNA splicing. How- reveal that splicing to the distal 3Ј splice site is suppressed by ever, exons are joined in a strict 5 to 3 linear order in constitu- proximal exonic sequences and that SR proteins are required for tively spliced pre-mRNAs. Thus, specific mechanisms must exist to this suppression. Thus, SR protein͞exonic enhancer complexes prevent the random joining of exons. Here we report that insertion not only function in exon and splice-site recognition but also play of exon sequences into an intron can inhibit splicing to the a role in ensuring that 5Ј and 3Ј splice sites within the same intron .downstream 3 splice site and that this inhibition is independent of are used, thus suppressing exon skipping intron size. The exon sequences required for splicing inhibition were found to be exonic enhancer elements, and their inhibitory Materials and Methods activity requires the binding of serine͞arginine-rich splicing fac- Construction of Plasmids. -
Amino Acid Recognition by Aminoacyl-Trna Synthetases
www.nature.com/scientificreports OPEN The structural basis of the genetic code: amino acid recognition by aminoacyl‑tRNA synthetases Florian Kaiser1,2,4*, Sarah Krautwurst3,4, Sebastian Salentin1, V. Joachim Haupt1,2, Christoph Leberecht3, Sebastian Bittrich3, Dirk Labudde3 & Michael Schroeder1 Storage and directed transfer of information is the key requirement for the development of life. Yet any information stored on our genes is useless without its correct interpretation. The genetic code defnes the rule set to decode this information. Aminoacyl-tRNA synthetases are at the heart of this process. We extensively characterize how these enzymes distinguish all natural amino acids based on the computational analysis of crystallographic structure data. The results of this meta-analysis show that the correct read-out of genetic information is a delicate interplay between the composition of the binding site, non-covalent interactions, error correction mechanisms, and steric efects. One of the most profound open questions in biology is how the genetic code was established. While proteins are encoded by nucleic acid blueprints, decoding this information in turn requires proteins. Te emergence of this self-referencing system poses a chicken-or-egg dilemma and its origin is still heavily debated 1,2. Aminoacyl-tRNA synthetases (aaRSs) implement the correct assignment of amino acids to their codons and are thus inherently connected to the emergence of genetic coding. Tese enzymes link tRNA molecules with their amino acid cargo and are consequently vital for protein biosynthesis. Beside the correct recognition of tRNA features3, highly specifc non-covalent interactions in the binding sites of aaRSs are required to correctly detect the designated amino acid4–7 and to prevent errors in biosynthesis5,8. -
2. Proteins Have Hierarchies of Structure
27 2. Proteins have Hierarchies of Structure Protein structure is usually described at four different levels (Fig. II.2.1). The first level, called the primary structure, describes the linear sequence of the amino acids in the chain. The different primary structures correspond to the different sequences in which the amino acids are covalently linked together. The secondary structure describes two common patterns of structural repetition in proteins: the coiling up into helices of segments of the chain, and the pairing together of strands of the chain into β-sheets. The tertiary structure is the next higher level of organization, the overall arrangement of secondary structural elements. The quaternary structure describes how different polypeptide chains are assembled into complexes. Figure II.2.1. Different levels of protein structure. A protein chain’s primary structure is its amino acid sequence. Secondary structure consists of the regular organization of helices and sheets. The example shown is a schematic representation of an α helix. Tertiary structure is a polypeptide chain’s three- dimensional native conformation, which often involves compact packing of secondary structure elements. The example given in the figure is a schematic drawing of one of the four polypeptide chains (subunits) of hemoglobin, the protein that transports oxygen in the blood. α-helices along the chain are represented as cylinders. N is the amino terminus and C is the carboxyl terminus of the polypeptide chain. Quaternary structure is the arrangement of multiple polypeptide chains (subunits) to form a functional biomolecular structure. The figure shows the quaternary arrangement of four subunits to form the functional hemoglobin molecule. -
Sorting out the Complexity of SR Protein Functions
Downloaded from rnajournal.cshlp.org on February 6, 2009 - Published by Cold Spring Harbor Laboratory Press RNA (2000), 6:1197–1211+ Cambridge University Press+ Printed in the USA+ Copyright © 2000 RNA Society+ REVIEW Sorting out the complexity of SR protein functions BRENTON R. GRAVELEY Department of Genetics and Developmental Biology, University of Connecticut Health Center, Farmington, Connecticut 06030, USA INTRODUCTION been clear whether all of these activities occur during the removal of each intron+ Recent studies now sug- Members of the serine/arginine-rich (SR) protein fam- gest that all of the proposed SR protein functions are ily have multiple functions in the pre-mRNA splicing carried out during each round of splicing, and at least reaction+ In addition to being required for the removal some of these functions are performed by independent of constitutively spliced introns, SR proteins can func- SR protein molecules+ This review discusses recent tion to regulate alternative splicing both in vitro and in advances in understanding the diverse functions of SR vivo (Ge & Manley, 1990; Krainer et al+, 1990a; Fu proteins in metazoan pre-mRNA splicing and presents et al+, 1992; Zahler et al+, 1993a; Caceres et al+, 1994; a model that takes these new findings into account+ Wang & Manley, 1995)+ In the cell, SR proteins migrate Although the reader should keep in mind that the ac- from speckles—subnuclear domains that may function tivity of SR proteins in vivo can be influenced by mod- as storage sites for certain splicing factors—to -
Functional Control of HIV-1 Post-Transcriptional Gene Expression by Host Cell Factors
Functional control of HIV-1 post-transcriptional gene expression by host cell factors DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Amit Sharma, B.Tech. Graduate Program in Molecular Genetics The Ohio State University 2012 Dissertation Committee Dr. Kathleen Boris-Lawrie, Advisor Dr. Anita Hopper Dr. Karin Musier-Forsyth Dr. Stephen Osmani Copyright by Amit Sharma 2012 Abstract Retroviruses are etiological agents of several human and animal immunosuppressive disorders. They are associated with certain types of cancer and are useful tools for gene transfer applications. All retroviruses encode a single primary transcript that encodes a complex proteome. The RNA genome is reverse transcribed into DNA, integrated into the host genome, and uses host cell factors to transcribe, process and traffic transcripts that encode viral proteins and act as virion precursor RNA, which is packaged into the progeny virions. The functionality of retroviral RNA is governed by ribonucleoprotein (RNP) complexes formed by host RNA helicases and other RNA- binding proteins. The 5’ leader of retroviral RNA undergoes alternative inter- and intra- molecular RNA-RNA and RNA-protein interactions to complete multiple steps of the viral life cycle. Retroviruses do not encode any RNA helicases and are dependent on host enzymes and RNA chaperones. Several members of the host RNA helicase superfamily are necessary for progressive steps during the retroviral replication. RNA helicase A (RHA) interacts with the redundant structural elements in the 5’ untranslated region (UTR) of retroviral and selected cellular mRNAs and this interaction is necessary to facilitate polyribosome formation and productive protein synthesis. -
Prediction of Amino Acid Side Chain Conformation Using a Deep Neural
Prediction of amino acid side chain conformation using a deep neural network Ke Liu 1, Xiangyan Sun3, Jun Ma3, Zhenyu Zhou3, Qilin Dong4, Shengwen Peng3, Junqiu Wu3, Suocheng Tan3, Günter Blobel2, and Jie Fan1, Corresponding author details: Jie Fan, Accutar Biotechnology, 760 Parkside Ave, Room 213 Brooklyn, NY 11226, USA. [email protected] 1. Accutar Biotechnology, 760 parkside Ave, Room 213, Brooklyn, NY 11226, USA. 2. Laboratory of Cell Biology, Howard Hughes Medical Institute, The Rockefeller University, New York, New York 10065, USA 3. Accutar Biotechnology (Shanghai) Room 307, No. 6 Building, 898 Halei Rd, Shanghai, China 4. Fudan University 220 Handan Rd, Shanghai, China Summary: A deep neural network based architecture was constructed to predict amino acid side chain conformation with unprecedented accuracy. Amino acid side chain conformation prediction is essential for protein homology modeling and protein design. Current widely-adopted methods use physics-based energy functions to evaluate side chain conformation. Here, using a deep neural network architecture without physics-based assumptions, we have demonstrated that side chain conformation prediction accuracy can be improved by more than 25%, especially for aromatic residues compared with current standard methods. More strikingly, the prediction method presented here is robust enough to identify individual conformational outliers from high resolution structures in a protein data bank without providing its structural factors. We envisage that our amino acid side chain predictor could be used as a quality check step for future protein structure model validation and many other potential applications such as side chain assignment in Cryo-electron microscopy, crystallography model auto-building, protein folding and small molecule ligand docking. -
6 Synthesis of N-Alkyl Amino Acids Luigi Aurelio and Andrew B
j245 6 Synthesis of N-Alkyl Amino Acids Luigi Aurelio and Andrew B. Hughes 6.1 Introduction Among the numerous reactions of nonribosomal peptide synthesis, N-methylation of amino acids is one of the common motifs. Consequently, the chemical research community interested in peptide synthesis and peptide modification has generated a sizeable body of literature focused on the synthesis of N-methyl amino acids (NMA). That literature is summarized herein. Alkyl groups substituted on to nitrogen larger than methyl are exceedingly rare among natural products. However, medicinal chemistry programs and peptide drug development projects are not limited to N-methylation. While being a much smaller body of research, there is a range of methods for the N-alkylation of amino acids and those reports are also covered in this chapter. The literature on N-alkyl, primarily N-methyl amino acids comes about due to the useful properties that the N-methyl group confers on peptides. N-Methylation increases lipophilicity, which has the effect of increasing solubility in nonaqueous solvents and improving membrane permeability. On balance this makes peptides more bioavailable and makes them better therapeutic candidates. One potential disadvantage is the methyl group removes the possibility of hydro- gen bonding and so binding events may be discouraged. It is notable though that the N-methyl group does not fundamentally alter the identity of the amino acid. Some medicinal chemists have taken advantage of this fact to deliberately discourage binding of certain peptides that can still participate in the general or partial chemistry of a peptide. A series of recent papers relating to Alzheimers disease by Doig et al. -
Srsf10 and the Minor Spliceosome Control Tissue-Specific and Dynamic
SHORT REPORT Srsf10 and the minor spliceosome control tissue-specific and dynamic SR protein expression Stefan Meinke1, Gesine Goldammer1, A Ioana Weber1,2, Victor Tarabykin2, Alexander Neumann1†, Marco Preussner1*, Florian Heyd1* 1Freie Universita¨ t Berlin, Institute of Chemistry and Biochemistry, Laboratory of RNA Biochemistry, Berlin, Germany; 2Institute of Cell Biology and Neurobiology, Charite´-Universita¨ tsmedizin Berlin, corporate member of Freie Universita¨ t Berlin, Humboldt-Universita¨ t zu Berlin, and Berlin Institute of Health, Berlin, Germany Abstract Minor and major spliceosomes control splicing of distinct intron types and are thought to act largely independent of one another. SR proteins are essential splicing regulators mostly connected to the major spliceosome. Here, we show that Srsf10 expression is controlled through an autoregulated minor intron, tightly correlating Srsf10 with minor spliceosome abundance across different tissues and differentiation stages in mammals. Surprisingly, all other SR proteins also correlate with the minor spliceosome and Srsf10, and abolishing Srsf10 autoregulation by Crispr/ Cas9-mediated deletion of the autoregulatory exon induces expression of all SR proteins in a human cell line. Our data thus reveal extensive crosstalk and a global impact of the minor spliceosome on major intron splicing. *For correspondence: [email protected] (MP); [email protected] (FH) Introduction Present address: †Omiqa Alternative splicing (AS) is a major mechanism that controls gene expression (GE) and expands the Corporation, c/o Freie proteome diversity generated from a limited number of primary transcripts (Nilsen and Graveley, Universita¨ t Berlin, Altensteinstraße, Germany 2010). Splicing is carried out by a multi-megadalton molecular machinery called the spliceosome of which two distinct complexes exist.