Effect of Molecular Structure of Side Chain Polymers on "Click" Synthesis of Thermosensitive Molecular Brushes
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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. -
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. -
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. -
Amino Acids, Peptides, Proteins: Introduction
Chem 109 C Bioorganic Compounds Fall 2019 HFH1104 Armen Zakarian Office: Chemistry Bldn 2217 http://labs.chem.ucsb.edu/~zakariangroup/courses.html CLAS Instructor: Dhillon Bhavan [email protected] Amino acids, Peptides, Proteins: Introduction Chapter 21 O R OH NH2 α-amino acid O O + H N R R R OH 2 R N - H2O H peptide bond = amide bond Proteins: Function 21.1 3 Proteins: Structural Histone Protein Structure: DNA packaging 4 Proteins: Protective botulinum toxin (botox) structure most toxic substance known LD50 = 10 ng/kg Amino acids, Peptides, Proteins: Introduction O O R O R O H R R OH R N OH N N OH H NH2 H NH2 O NH2 O R α-amino acid dipeptide tripeptide ! oligopeptide: 3 - 10 amino acids ! polypeptide, or protein: many amino acids Proteins: Amino Acids, Configuration NH2 HO O phenylalanine O + - NH3 natural amino acids C O +H N H same as - have the L configuration (S) 3 O2C R R Amino acids: Classification • Hydrophobic: “water-fearing”, nonpolar side chains – Alkyl side chain • Hydrophilic: “water-loving” side chains – Polar, neutral side chains – Anionic – Cationic - Table 21.1 lists 20 most common natural occurring amino acids - The structures of amino acids will be provided on the tests nonpolar side chains polar neutral (uncharged) side chains Amino acids: Classification polar acidic (anionic) side chains Amino acids: Classification polar basic (cationic) side chains Amino acids: Classification PROBLEM 1 Explain why when the imidazole ring of histidine is protonated, the double-bonded nitrogen is the nitrogen atom that accepts the proton. same for guanidine group in arginine. -
Conformational Transition of H-Shaped Branched Polymers
1 Conformational Transition of H-shaped Branched Polymers Ashok Kumar Dasmahapatra* and Venkata Mahanth Sanka Department of Chemical Engineering, Indian Institute of Technology Guwahati, Guwahati – 781039, Assam, India PACS number(s): 83.80.Rs, 87.10.Rt, 82.20.Wt, 61.25.he * Corresponding author: Phone: +91-361-258-2273; Fax: +91-361-258-2291; Email address: [email protected] 2 ABSTRACT We report dynamic Monte Carlo simulation on conformational transition of H-shaped branched polymers by varying main chain (backbone) and side chain (branch) length. H- shaped polymers in comparison with equivalent linear polymers exhibit a depression of theta temperature accompanying with smaller chain dimensions. We observed that the effect of branches on backbone dimension is more pronounced than the reverse, and is attributed to the conformational heterogeneity prevails within the molecule. With increase in branch length, backbone is slightly stretched out in coil and globule state. However, in the pre-collapsed (cf. crumpled globule) state, backbone size decreases with the increase of branch length. We attribute this non-monotonic behavior as the interplay between excluded volume interaction and intra-chain bead-bead attractive interaction during collapse transition. Structural analysis reveals that the inherent conformational heterogeneity promotes the formation of a collapsed structure with segregated backbone and branch units (resembles to “sandwich” or “Janus” morphology) rather an evenly distributed structure comprising of all the units. The shape of the collapsed globule becomes more spherical with increasing either backbone or branch length. 3 I. INTRODUCTION Branched polymers are commodious in preparing tailor-made materials for various applications such as in the area of catalysis1, nanomaterials2, and biomedicines3. -
Electrically Sensing Hachimoji DNA Nucleotides Through a Hybrid Graphene/H-BN Nanopore Cite This: Nanoscale, 2020, 12, 18289 Fábio A
Nanoscale View Article Online PAPER View Journal | View Issue Electrically sensing Hachimoji DNA nucleotides through a hybrid graphene/h-BN nanopore Cite this: Nanoscale, 2020, 12, 18289 Fábio A. L. de Souza, †a Ganesh Sivaraman, †b,g Maria Fyta, †c Ralph H. Scheicher, *†d Wanderlã L. Scopel †e and Rodrigo G. Amorim *†f The feasibility of synthesizing unnatural DNA/RNA has recently been demonstrated, giving rise to new perspectives and challenges in the emerging field of synthetic biology, DNA data storage, and even the search for extraterrestrial life in the universe. In line with this outstanding potential, solid-state nanopores have been extensively explored as promising candidates to pave the way for the next generation of label- free, fast, and low-cost DNA sequencing. In this work, we explore the sensitivity and selectivity of a gra- phene/h-BN based nanopore architecture towards detection and distinction of synthetic Hachimoji nucleobases. The study is based on a combination of density functional theory and the non-equilibrium Green’s function formalism. Our findings show that the artificial nucleobases are weakly binding to the Creative Commons Attribution 3.0 Unported Licence. device, indicating a short residence time in the nanopore during translocation. Significant changes in the Received 9th June 2020, electron transmission properties of the device are noted depending on which artificial nucleobase resides Accepted 7th August 2020 in the nanopore, leading to a sensitivity in distinction of up to 80%. Our results thus indicate that the pro- DOI: 10.1039/d0nr04363j posed nanopore device setup can qualitatively discriminate synthetic nucleobases, thereby opening up rsc.li/nanoscale the feasibility of sequencing even unnatural DNA/RNA. -
The New Architectonics: an Invitation to Structural Biology
THE ANATOMICAL RECORD (NEW ANAT.) 261:198–216, 2000 FEATURE ARTICLE The New Architectonics: An Invitation To Structural Biology CLARENCE E. SCHUTT* AND UNO LINDBERG The philosophy of art might offer an epistemological basis for talking about the complexity of biological molecules in a meaningful way. The analysis of artistic compositions requires the resolution of intrinsic tensions between disparate sensory categories—color, line and form—not unlike those encountered in looking at the surfaces of protein molecules, where charge, polarity, hydrophobicity, and shape compete for our attentions. Complex living systems exhibit behaviors such as contraction waves moving along muscle fibers, or shivers passing through the growth cones of migrating neurons, that are easy to describe with common words, but difficult to explain in terms of the language of chemistry. The problem follows from a lack of everyday experience with processes that move towards equilibrium by switching between crystalline order and chain-like disorder, a commonplace occurrence in the submicroscopic world of proteins. Since most of what is understood about protein function comes from studies of isolated macromolecules in solution, a serious gap exists between what we know and what we would like to know about organized biological systems. Closing this gap can be achieved by recognizing that protein molecules reside in gradients of Gibbs free energy, where local forces and movements can be large compared with Brownian motion. Architectonics, a term borrowed from the philosophical literature, symbolizes the eventual union of the structure of theories—how our minds construct the world—with the theory of structures—or how stability is maintained in the chaotic world of microsystems.