Physical Models Enhance Molecular Three‐Dimensional Literacy in An
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A Web-Based 3D Molecular Structure Editor and Visualizer Platform
Mohebifar and Sajadi J Cheminform (2015) 7:56 DOI 10.1186/s13321-015-0101-7 SOFTWARE Open Access Chemozart: a web‑based 3D molecular structure editor and visualizer platform Mohamad Mohebifar* and Fatemehsadat Sajadi Abstract Background: Chemozart is a 3D Molecule editor and visualizer built on top of native web components. It offers an easy to access service, user-friendly graphical interface and modular design. It is a client centric web application which communicates with the server via a representational state transfer style web service. Both client-side and server-side application are written in JavaScript. A combination of JavaScript and HTML is used to draw three-dimen- sional structures of molecules. Results: With the help of WebGL, three-dimensional visualization tool is provided. Using CSS3 and HTML5, a user- friendly interface is composed. More than 30 packages are used to compose this application which adds enough flex- ibility to it to be extended. Molecule structures can be drawn on all types of platforms and is compatible with mobile devices. No installation is required in order to use this application and it can be accessed through the internet. This application can be extended on both server-side and client-side by implementing modules in JavaScript. Molecular compounds are drawn on the HTML5 Canvas element using WebGL context. Conclusions: Chemozart is a chemical platform which is powerful, flexible, and easy to access. It provides an online web-based tool used for chemical visualization along with result oriented optimization for cloud based API (applica- tion programming interface). JavaScript libraries which allow creation of web pages containing interactive three- dimensional molecular structures has also been made available. -
Integrated Multi-Selection Schemes for Complex Molecular Structures
Workshop on Molecular Graphics and Visual Analysis of Molecular Data (MolVA) (2019) J. Byška, M. Krone, and B. Sommer (Editors) MolFind – Integrated Multi-Selection Schemes for Complex Molecular Structures Robin Skånberg1;2, Mathieu Linares1;2, Martin Falk1;2, Ingrid Hotz1;2, and Anders Ynnerman1;2 1Scientific Visualization Group, Linköpings University, Sweden 2Swedish e-Science Research Centre (SeRC) Figure 1: Growing an initial selection of two residues along covalent bonds in a protein fibril. Abstract Selecting components and observing changes of properties and configurations over time is an important step in the analysis of molecular dynamics (MD) data. In this paper, we present a selection tool combining text-based queries with spatial selection and filtering. Morphological operations facilitate refinement of the selection by growth operators, e.g. across covalent bonds. The combination of different selection paradigms enables flexible and intuitive analysis on different levels of detail and visual depiction of molecular events. Immediate visual feedback during interactions ensures a smooth exploration of the data. We demonstrate the utility of our selection framework by analyzing temporal changes in the secondary structure of poly-alanine and the binding of aspirin to phospholipase A2. 1 Introduction In this paper, we present a selection framework for molecu- lar substructures embedded in the visual analytics tool VIA-MD “It is through the interactive manipulation of a visual in- [SLK∗18, KSH∗18]. The work is mostly targeted toward expert terface – the analytic discourse – that knowledge is con- users from the molecular simulation domain. The user-driven de- structed, tested, refined and shared.”[PSCO09] sign of the framework combines a large set of selection paradigms This is also true for the analysis of molecular dynamics (MD) in a flexible way while maintaining a simple and intuitive interface data and the generation of expressive visualization. -
Interdomain Zinc Site on Human Albumin SPECIAL FEATURE
Interdomain zinc site on human albumin SPECIAL FEATURE Alan J. Stewart*, Claudia A. Blindauer*, Stephen Berezenko†, Darrell Sleep†, and Peter J. Sadler*‡ *School of Chemistry, University of Edinburgh, West Mains Road, Edinburgh EH9 3JJ, United Kingdom; and †Delta Biotechnology Ltd., Castle Court, Castle Boulevard, Nottingham NG7 1FD, United Kingdom Edited by Jack Halpern, University of Chicago, Chicago, IL, and approved December 20, 2002 (received for review October 30, 2002) Albumin is the major transport protein in blood for Zn2؉, a metal binds to the thiolate sulfur at Cys-34 (23). CD studies suggest ion required for physiological processes and recruited by various that the major Zn2ϩ site is also a secondary (weaker) binding drugs and toxins. However, the Zn2؉-binding site(s) on albumin is site for Cu2ϩ and Ni2ϩ (17). Early 113Cd NMR experiments ϩ ill-defined. We have analyzed the 18 x-ray crystal structures of hu- on BSA demonstrated the existence of two Cd2 -binding sites man albumin in the PDB and identified a potential five-coordinate (18), A and B. Competition experiments on bovine and HSAs ϩ Zn site at the interface of domains I and II consisting of N ligands (18, 19, 24) have shown that site A binds Zn2 more strongly ϩ from His-67 and His-247 and O ligands from Asn-99, Asp-249, and than Cd2 . NMR peaks A (130 ppm in phosphate buffer) and 113 H2O, which are the same amino acid ligands as those in the zinc B (24 ppm) were also observed when Cd was added to in- enzymes calcineurin, endonucleotidase, and purple acid phospha- tact human blood serum, although peak A was shifted down- tase. -
Python Module Index 79
mendeleev Documentation Release 0.9.0 Lukasz Mentel Sep 04, 2021 CONTENTS 1 Getting started 3 1.1 Overview.................................................3 1.2 Contributing...............................................3 1.3 Citing...................................................3 1.4 Related projects.............................................4 1.5 Funding..................................................4 2 Installation 5 3 Tutorials 7 3.1 Quick start................................................7 3.2 Bulk data access............................................. 14 3.3 Electronic configuration......................................... 21 3.4 Ions.................................................... 23 3.5 Visualizing custom periodic tables.................................... 25 3.6 Advanced visulization tutorial...................................... 27 3.7 Jupyter notebooks............................................ 30 4 Data 31 4.1 Elements................................................. 31 4.2 Isotopes.................................................. 35 5 Electronegativities 37 5.1 Allen................................................... 37 5.2 Allred and Rochow............................................ 38 5.3 Cottrell and Sutton............................................ 38 5.4 Ghosh................................................... 38 5.5 Gordy................................................... 39 5.6 Li and Xue................................................ 39 5.7 Martynov and Batsanov........................................ -
ADP-Ribosyl)Hydrolases: Structure, Function, and Biology
Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press SPECIAL SECTION: REVIEW (ADP-ribosyl)hydrolases: structure, function, and biology Johannes Gregor Matthias Rack,1,3 Luca Palazzo,2,3 and Ivan Ahel1 1Sir William Dunn School of Pathology, University of Oxford, Oxford OX1 3RE, United Kingdom; 2Institute for the Experimental Endocrinology and Oncology, National Research Council of Italy, 80145 Naples, Italy ADP-ribosylation is an intricate and versatile posttransla- Diversification of NAD+ signaling is particularly apparent tional modification involved in the regulation of a vast in vertebrata, being linked to evolutionary optimization of variety of cellular processes in all kingdoms of life. Its NAD+ biosynthesis and increased (ADP-ribosyl) signaling complexity derives from the varied range of different (Bockwoldt et al. 2019). ADP-ribosylation is used by or- chemical linkages, including to several amino acid side ganisms from all kingdoms of life and some viruses chains as well as nucleic acids termini and bases, it can (Perina et al. 2014; Aravind et al. 2015) and controls a adopt. In this review, we provide an overview of the differ- wide range of cellular processes such as DNA repair, tran- ent families of (ADP-ribosyl)hydrolases. We discuss their scription, cell division, protein degradation, and stress re- molecular functions, physiological roles, and influence sponse to name a few (Bock and Chang 2016; Gupte et al. on human health and disease. Together, the accumulated 2017; Palazzo et al. 2017; Rechkunova et al. 2019). In ad- data support the increasingly compelling view that (ADP- dition to proteins, several in vitro observations strongly ribosyl)hydrolases are a vital element within ADP-ribosyl suggest that nucleic acids, both DNA and RNA, can be signaling pathways and they hold the potential for novel targets of ADP-ribosylation (Nakano et al. -
A Script to Highlight Hydrophobicity and Charge on Protein Surfaces
METHODS published: 13 October 2015 doi: 10.3389/fmolb.2015.00056 A script to highlight hydrophobicity and charge on protein surfaces Dominique Hagemans, Ianthe A. E. M. van Belzen, Tania Morán Luengo and Stefan G. D. Rüdiger * Cellular Protein Chemistry, Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, Netherlands The composition of protein surfaces determines both affinity and specificity of protein-protein interactions. Matching of hydrophobic contacts and charged groups on both sites of the interface are crucial to ensure specificity. Here, we propose a highlighting scheme, YRB, which highlights both hydrophobicity and charge in protein structures. YRB highlighting visualizes hydrophobicity by highlighting all carbon atoms that are not bound to nitrogen and oxygen atoms. The charged oxygens of glutamate and aspartate are highlighted red and the charged nitrogens of arginine and lysine are highlighted blue. For a set of representative examples, we demonstrate that YRB highlighting intuitively Edited by: Ophry Pines, visualizes segments on protein surfaces that contribute to specificity in protein-protein Hebrew University of Jerusalem, Israel interfaces, including Hsp90/co-chaperone complexes, the SNARE complex and a Reviewed by: transmembrane domain. We provide YRB highlighting in form of a script that runs using Paolo De Los Rios, the software PyMOL. Ecole Polytechnique Fédérale de Lausanne, Switzerland Keywords: protein-protein interaction, surface hydrophobicity, charge pairs, PyMOL, amino acid properties Eilika Weber-Ban, ETH Zurich, Switzerland *Correspondence: Introduction Stefan G. D. Rüdiger, Cellular Protein Chemistry, Bijvoet Protein-protein interactions underlie all processes in the cell. Specificity of protein-protein Center for Biomolecular Research, interactions is determined by matching of complementary functional groups with those of Utrecht University, Padualaan 8, 3584 CH Utrecht, Netherlands the opposite surface (Chothia and Janin, 1975; Eaton et al., 1995). -
Growth and Nitrogen Fixation Dynamics of Azotobacter Chroococcum in Nitrogen-Free and Omw Containing Medium
GROWTH AND NITROGEN FIXATION DYNAMICS OF AZOTOBACTER CHROOCOCCUM IN NITROGEN-FREE AND OMW CONTAINING MEDIUM A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF THE MIDDLE EAST TECHNICAL UNIVERSITY BY GÜL )ø'AN SARIBAY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN THE DEPARTMENT OF FOOD ENGINEERING DECEMBER 2003 Approval of the Graduate School of Natural and Applied Sciences. Prof. Dr. Canan Özgen Director I certify that this thesis satisfies all the requirements as a thesis for the degree of Master of Science. ¢¡¤£¦¥¨§ © ¡ § !¡¤"# Head of Department We certify that we have read this thesis and in our opinion it is fully adequate, in scope and quality, as a thesis for the degree of Master of Science in Food Engineering. 3 ABSTRACT GROWTH AND NITROGEN FIXATION DYNAMICS OF AZOTOBACTER CHROOCOCCUM IN NITROGEN-FREE AND OMW CONTAINING MEDIUM $%&¤'()%+*,¦-/.0¦13254¦%+6 M.Sc., Department of Food Engineering 789):;=<)>#?A@B;DCFEG;¤@H¨IJK; ILNM OP8QNLNMRSM+RST U December 2003, 68 Pages Olive Mill Wastewater (OMW), by-product of oil industry, is a dark liquid with a characteristic fetid smell, bitter taste and bright appearance; having a high pollution potential, creating serious problems in countries producing olive oil. Azotobacter chroococcum as a Nitrogen-fixing bacteria can bioremediate OMW, by degrading its toxic constituents. With the help of this detoxification process OMW can be used as biofertilizer. In this study, the dynamics of growth and nitrogen fixation at different physiological conditions and nutrient requirements of A. chroococcum in chemically defined N-free medium was determined. -
1 Functional Asymmetry and Chemical Reactivity of Csor Family Persulfide
bioRxiv preprint doi: https://doi.org/10.1101/2021.07.25.453692; this version posted July 25, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Functional asymmetry and chemical reactivity of CsoR family persulfide sensors Joseph N. Fakhoury1, Yifan Zhang1,2, Katherine A. Edmonds1, Mauro Bringas4, Justin L. Luebke1, Giovanni Gonzalez-Gutierrez2, Daiana A. Capdevila1,4,5 and David P. Giedroc1,2,5 †Department of Chemistry, Indiana University, 800 E. Kirkwood Ave, Bloomington, IN 47405- 7102, United States 2Department of Molecular and Cellular Biochemistry, Indiana University, 212 S. Hawthorne Drive, Bloomington, IN 47405 United States 3Graduate Program in Biochemistry, Indiana University, 212 S. Hawthorne Drive, Bloomington, IN 47405, United States 4Fundación Instituto Leloir, Av. Patricias Argentinas 435, Buenos Aires C1405BWE, Argentina 5Correspondence to David P. Giedroc: [email protected] or Daiana A. Capdevila: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.25.453692; this version posted July 25, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract CstR is a persulfide-sensing member of the functionally diverse copper-sensitive operon repressor (CsoR) superfamily that regulates the bacterial response to hydrogen sulfide (H2S) and more oxidized reactive sulfur species (RSS) in Gram-positive pathogens. -
The Anticancer Drug Cisplatin Can Cross-Link the Interdomain Zinc Site on Human Albumin
Electronic Supplementary Material (ESI) for Chemical Communications This journal is © The Royal Society of Chemistry 2011 For submission to Chem. Commun. The Anticancer Drug Cisplatin Can Cross-link the Interdomain Zinc Site on Human Albumin Wenbing Hu, Qun Luo, Kui Wu, Xianchan Li, Fuyi Wang,* Yi Chen, Xiaoyan Ma, Jianping Wang, Jianan Liu, Shaoxiang Xiong, and Peter J. Sadler* Supporting Information 1. Experimental Section 2. Table S1 3. Figure S1-S7 Electronic Supplementary Material (ESI) for Chemical Communications This journal is © The Royal Society of Chemistry 2011 Experimental Section Materials. Recombinant human albumin (rHA) was kindly provided by Delta Biotechnology Ltd (Nottingham, UK) and extensively dialyzed against NH4HCO3 buffer (100 mM) and lyophilized before use. Trypsin (sequence grade) was purchased from Promega, guanidine hydrochloride from Amresco, selenocystamine dihydrochloride from Sigma, dithiothreitol (DTT) from Pierce, iodoacetamide and acetonitrile (HPLC grade) from Merck, trifluoroacetic acid (TFA) from Acros, and triethylammonium acetate buffer (TEAA) from Transgenomic. Microcon centrifugal filtration units with a 10 kDa molecular weight cut-off were purchased from Millipore. Aqueous solutions were prepared using MilliQ water (MilliQ Reagent Water System). HPLC-ESI-MS(/MS). Positive-ion electrospray ionization mass spectra were obtained on a Micromass Q-TOF mass spectrometer (Waters) coupled to a Waters CapLC HPLC system. The tryptic digests of rHA or platinated rHA were separated on a Symmetry-C18 column (10×5mm, 100Å, 3.5 μm, waters). Mobile phases were A: 95% H2O containing 4.9% acetonitrile and 0.1% formic acid, and B: 95% acetonitrile containing 4.9% H2O and 0.1% formic acid. The peptides were eluted with a 50 min linear gradient from 1% to 45 % of B at a rate of 30 μL min-1. -
Amino Acids - Building Blocks of Proteins
Amino Acids - Building Blocks of Proteins Introduction Proteins are more than an important part of your diet. Proteins are complex molecular machines that are involved in nearly all of your cellular functions. Each protein has a specific shape (structure) that enables it to carry out its specific job (function). A core idea in the life sciences is that there is a fundamental relationship between a biological structure and the function it must perform. At the macro level, Darwin recognized that the structure of a finch’s beak was related to the food it ate. This fundamental structure-function relationship is also true at all levels below the Potassium macro level, including proteins and other structures at the molecular Ion level. For two examples of proteins and their functions, see the photos and cutlines at the right. In this activity, you will explore the structure of proteins and the chemical interactions that drive each protein to fold into its specific structure, as noted below. • Each protein is made of a specific sequence of amino acids. The potassium channel (above) spans There are 20 amino acids found in proteins. cell membranes and regulates the passage of potassium ions in and out • Each amino acid consists of two parts — a backbone and a side of cells. It folds into a “pore” for the potassium ion to pass through. chain. The backbone is the same in all 20 amino acids and The β-globin protein (below) transports the side chain is different in each one. oxygen in blood. It accomplishes this with the heme group (yellow structure in • Each side chain consists of a unique combination of atoms which photo) in which an iron atom binds to O2. -
Exercise 1: Essentials
Workshop in Computational Structural Biology (81813), Spring 2019 Exercise 1: Essentials In the field of computational structural biology, we constantly inspect and manipulate molecular structures. This exercise will introduce you to the environment and basic tools we will use to do so. Contents The Linux environment 1 PDB 1 PyMOL tutorial 2 Structural Analysis 3 Comparing Molecules 4 Scripting and High-Quality Visualization 2 5 Protein classification systems 6 SCOP 6 CATH 6 ECOD 7 The Linux environment Linux 1 is a free, open-source operating system. It is based on Unix and so is stable, powerful and flexible. Linux comes in handy when we work in the command line, which we will extensively. If you are not familiar with the Linux terminal environment – go through this tutorial. At the very minimum, you should be able to easily do the following using command lines: move around the directory tree, create/copy/move/delete files, view and edit text files. PDB The Protein Data Bank is the worldwide repository of information about the 3D structures of macromolecules, including proteins and nucleic acids. Structures are usually determined by X-ray crystallography or NMR experiments and deposited in the PDB by the scientists involved. Each such structure is assigned a unique 4-character code called a PDB ID. A structure can be described by a PDB file, which is essentially a tabulated text file (for more see its Wikipedia page) that describes all the available details about the structure, most importantly every atom's coordinates. Software tools can read, manipulate and write structures in PDB format. -
CPK Coloring Wikipedia CPK Coloring from Wikipedia, the Free Encyclopedia
10/24/2016 CPK coloring Wikipedia CPK coloring From Wikipedia, the free encyclopedia In chemistry, the CPK coloring is a popular color convention for distinguishing atoms of different chemical elements in molecular models. The scheme is named after the CPK molecular models designed by chemists Robert Corey and Linus Pauling, and improved by Walter Koltun. Contents 1 History A plastic ballandstick model of 2 Typical assignments proline. These models usually comply 3 Modern variants 4 See also with CPK coloring. 5 References 6 External links History In 1952, Corey and Pauling published a description of spacefilling models of proteins and other biomolecules that they had been building at Caltech.[1] Their models represented atoms by faceted hardwood balls, painted in different bright colors to indicate the respective chemical elements. Their color schema included White for hydrogen Black for carbon Sky blue for nitrogen Red for oxygen They also built smaller models using plastic balls with the same color schema. In 1965 Koltun patented an improved version of the Corey and Pauling modeling technique.[2] In his patent he mentions the following colors: White for hydrogen Black for carbon Blue for nitrogen Red for oxygen Deep yellow for sulfur Purple for phosphorus Light, medium, medium dark, and dark green for the halogens (F, Cl, Br, I) Silver for metals (Co, Fe, Ni, Cu) Typical assignments Typical CPK color assignments include: https://en.wikipedia.org/wiki/CPK_coloring 1/6 10/24/2016 CPK coloring Wikipedia hydrogen (H) white carbon (C) black nitrogen (N) dark blue oxygen (O) red fluorine (F), chlorine (Cl) green bromine (Br) dark red iodine (I) dark violet noble gases (He, Ne, Ar, Xe, Kr) cyan A box of ballandstick model pieces phosphorus (P) orange colored to represent several of the common elements.