Prediction of Amino Acid Side Chain Conformation Using a Deep Neural
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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]. -
Biomolecules
CHAPTER 3 Biomolecules 3.1 Carbohydrates In the previous chapter you have learnt about the cell and 3.2 Fatty Acids and its organelles. Each organelle has distinct structure and Lipids therefore performs different function. For example, cell membrane is made up of lipids and proteins. Cell wall is 3.3 Amino Acids made up of carbohydrates. Chromosomes are made up of 3.4 Protein Structure protein and nucleic acid, i.e., DNA and ribosomes are made 3.5 Nucleic Acids up of protein and nucleic acids, i.e., RNA. These ingredients of cellular organelles are also called macromolecules or biomolecules. There are four major types of biomolecules— carbohydrates, proteins, lipids and nucleic acids. Apart from being structural entities of the cell, these biomolecules play important functions in cellular processes. In this chapter you will study the structure and functions of these biomolecules. 3.1 CARBOHYDRATES Carbohydrates are one of the most abundant classes of biomolecules in nature and found widely distributed in all life forms. Chemically, they are aldehyde and ketone derivatives of the polyhydric alcohols. Major role of carbohydrates in living organisms is to function as a primary source of energy. These molecules also serve as energy stores, 2021-22 Chapter 3 Carbohydrade Final 30.018.2018.indd 50 11/14/2019 10:11:16 AM 51 BIOMOLECULES metabolic intermediates, and one of the major components of bacterial and plant cell wall. Also, these are part of DNA and RNA, which you will study later in this chapter. The cell walls of bacteria and plants are made up of polymers of carbohydrates. -
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. -
Density Estimation for Protein Conformation Angles Using a Bivariate Von Mises Distribution and Bayesian Nonparametrics
Density Estimation for Protein Conformation Angles Using a Bivariate von Mises Distribution and Bayesian Nonparametrics Kristin P. LENNOX, David B. DAHL, Marina VANNUCCI, and Jerry W. TSAI Interest in predicting protein backbone conformational angles has prompted the development of modeling and inference procedures for bivariate angular distributions. We present a Bayesian approach to density estimation for bivariate angular data that uses a Dirichlet process mixture model and a bivariate von Mises distribution. We derive the necessary full conditional distributions to fit the model, as well as the details for sampling from the posterior predictive distribution. We show how our density estimation method makes it possible to improve current approaches for protein structure prediction by comparing the performance of the so-called ‘‘whole’’ and ‘‘half’’ position dis- tributions. Current methods in the field are based on whole position distributions, as density estimation for the half positions requires techniques, such as ours, that can provide good estimates for small datasets. With our method we are able to demonstrate that half position data provides a better approximation for the distribution of conformational angles at a given sequence position, therefore providing increased efficiency and accuracy in structure prediction. KEY WORDS: Angular data; Density estimation; Dirichlet process mixture model; Torsion angles; von Mises distribution. 1. INTRODUCTION and Ohlson 2002; Lovell et al. 2003; Rother, Sapiro, and Pande 2008), but they behave poorly for these subdivided datasets. Computational structural genomics has emerged as a pow- This is unfortunate, because these subsets provide structure erful tool for better understanding protein structure and func- prediction that is more accurate, as it utilizes more specific tion using the wealth of data from ongoing genome projects. -
Structure Validation Article
14 STRUCTURAL QUALITY ASSURANCE Roman A. Laskowski The experimentally determined three-dimensional (3D) structures of proteins and nucleic acids represent the knowledge base from which so much understanding of biological processes has been derived over the last three decades of the twentieth cen- tury. Individual structures have provided explanations of specific biochemical functions and mechanisms, while comparisons of structures have given insights into general principles governing these complex molecules, the interactions they make, and their biological roles. The 3D structures form the foundation of structural bioinformatics; all structural analyses depend on them and would be impossible without them. Therefore, it is crucial to bear in mind two important truths about these structures, both of which result from the fact that they have been determined experimentally. The first is that the result of any experiment is merely a model that aims to give as good an explanation for the experimental data as possible. The term structure is commonly used, but you should realize that this should be correctly read as model. As such the model may be an accurate and meaningful representation of the molecule, or it may be a poor one. The quality of the data and the care with which the experiment has been performed will determine which it is. Independently performed experiments can arrive at very similar models of the same molecule; this suggests that both are accurate representations, that they are good models. The second important truth is that any experiment, however carefully performed, will have errors associated with it. These errors come in two distinct varieties: sys- tematic and random. -
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. -
Chapter 13 Protein Structure Learning Objectives
Chapter 13 Protein structure Learning objectives Upon completing this material you should be able to: ■ understand the principles of protein primary, secondary, tertiary, and quaternary structure; ■use the NCBI tool CN3D to view a protein structure; ■use the NCBI tool VAST to align two structures; ■explain the role of PDB including its purpose, contents, and tools; ■explain the role of structure annotation databases such as SCOP and CATH; and ■describe approaches to modeling the three-dimensional structure of proteins. Outline Overview of protein structure Principles of protein structure Protein Data Bank Protein structure prediction Intrinsically disordered proteins Protein structure and disease Overview: protein structure The three-dimensional structure of a protein determines its capacity to function. Christian Anfinsen and others denatured ribonuclease, observed rapid refolding, and demonstrated that the primary amino acid sequence determines its three-dimensional structure. We can study protein structure to understand problems such as the consequence of disease-causing mutations; the properties of ligand-binding sites; and the functions of homologs. Outline Overview of protein structure Principles of protein structure Protein Data Bank Protein structure prediction Intrinsically disordered proteins Protein structure and disease Protein primary and secondary structure Results from three secondary structure programs are shown, with their consensus. h: alpha helix; c: random coil; e: extended strand Protein tertiary and quaternary structure Quarternary structure: the four subunits of hemoglobin are shown (with an α 2β2 composition and one beta globin chain high- lighted) as well as four noncovalently attached heme groups. The peptide bond; phi and psi angles The peptide bond; phi and psi angles in DeepView Protein secondary structure Protein secondary structure is determined by the amino acid side chains. -
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. -
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.