DOCSLIB.ORG

Kapitel 9 Literaturverzeichnis

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Kapitel 9 Literaturverzeichnis Kapitel 9 Literaturverzeichnis [1] Fischer, E., Einfluß der Configuration auf die Wirkung der Enzyme, Ber. Dtsch. Chem. Ges., 27, 1894, 2985 - 2993. [2] Koshland, D. E. Jr., Protein Shape and Biological Control, Sci. Amer., 229(4), 1973, 52 - 64. [3] Casher, O.; Chandramohan, G. K.; Hargreaves, M. J.; Leach, C.; Murray-Rust, P.; Rzepa, H. S.; Sayle, R.; Whitaker, B. J., Hyperactive Molecules and the World-Wide- Web Information System, J. Chem. Soc. Perkin Trans. 2, 2, 1995, 7 - 11. [4] Warr, W. A., Communications and Communities of Chemists, J. Chem. Inf. Comput. Sci., 38(6), 1998, 966 - 975. [5] Rzepa, H. S., A History of Hyperactive Chemistry on the Web: From Text and Images to Objects, Models and Molecular Components, Chimia, 52, 1998, 123 - 132. [6] Rzepa, H. S.; Whitaker, B. J.; Winter, M. J., Applications of the World-Wide-Web System, J. Chem. Soc., Chem. Commun., 17, 1994, 1907 - 1910. [7] Clark, T.; Roth, H., The Journal of Molecular Modeling: Impact, Expectations and Experience, Chimia, 52(11), 1998, 664 - 667. [8] Rzepa, H. S., Internet-based Computational Chemistry Tools, In: Encyclopaedia of Computational Chemistry, von Rague-Schleyer, P.; Allinger,N. L.; Clark, T.; Gasteiger, J.; Kollman, P. A.; Schaefer, III, H. F.; Schreiner, P. R., Eds.; John Wiley & Sons, Inc.: Chichester, UK, 1998, 1426 - 1438. [9] Vollhardt, H.; Brickmann, J., 3D Molecular Graphics on the World Wide Web, Pac. Symp. Biocomput., 1996, 663 - 673. [10] Ihlenfeldt, W. D.; Gasteiger, J., Beyond the Hyperactive Molecule: Search, Salvage and Visualization of Chemical Information from the Internet, Pac. Symp. Biocomput., 1996, 384 - 395. [11] Krassavine, A., Java and JavaBeans for Cheminformatics, Chimia, 52, 1998, 668 - 672. [12] Ertl, P.; Jacob, O., WWW-based Chemical Information Systems, Theochem, 419(1-3), 1997, 113 - 130. [13] Bormann, S., Combinatorial Chemistry, Chem & Eng. News, 4/98, 1998. siehe auch http://pubs.acs.org/hotartcl/cenear/980406/comb.html 193 9 Literaturverzeichnis [14] Quelle: Kiser, P.; Ihlenfeldt, W.-D.; Eichenbaum, G.; Bienfait, B., ChemCodes Inc. 2001. [15] Houghten, R. A.; Blondelle, S. E.; Cuervo, J. H., Development of New Antimicrobial Agents using a Synthetic Peptide Combinatorial Library involving more than 34 Mil- lion Hexamers. In: Innovation and Perspectives in Solid Phase Synthesis: Peptides, Polypeptides and Oligonucleotides, Epton, R., Ed.; Intercept Ltd., Andover, UK, 1992, 237 - 239. [16] Gasteiger, J., Database Mining: From Information to Knowledge, In: Proceedings of 1997 Chem. Inf. Conf., Collier, H., Ed.; Infonortics Ltd., Calne, UK, 1997, 1 - 6. [17] Upson, C.; Faulhaber, T.; Kamins, D.; Laidlaw, D.; Schlegel, D.; Vroom, J.; Gurwitz, R.; van Dam, A., The Application Visualization System: A Computational Environment for Scientific Visualization, IEEE Computer Graphics and Applications, 1989, 32 - 40. [18] ChemSymphony: http://www.chemsymphony.com/ [19] Sayle, R., Glaxo Group Research, Greenford, UK. http://www.umass.edu/microbio/rasmol/ [20] Rezk-Salama, C.; Engel, K.; Bauer, M.; Greiner, G.; Ertl, T., Interactive Volume Rende- ring on Standard PC Graphics Hardware Using Multi-Textures and Multi-Stage Rasteri- zation, In: Proceedings of Eurographics SIGGRAPH, Workshop on Graphics Hardware, 147, 2000, 109 - 118. [21] OpenGL Architecture Review Board. OpenGL Reference Manual, Release 1, Addison- Wesley, Reading, Massachusetts, USA, 1992. [22] http://www.microsoft.com/directx/default.asp. [23] Drebin, B.; Carpenter, L.; Hanrahan, P., Volume Rendering, In: Proceedings of SIGGRAPH, Computer Graphics Conference Series, 1988, 65 - 74. [24] GAUSSIAN: http://www.gaussian.com/ [25] Lorensen, W. E.; Cline, H. E., Marching Cubes: A High Resolution 3D Surface Con- struction Algorthm. In: Proceedings of SIGGRAPH, Computer Graphics Conference Series, 1987, 163 - 169. [26] Engel, K. D., Strategien und Algorithmen zur interaktiven Volumenvisualisierung in Digitalen Dokumenten, Dissertation, Institut für Informatik der Universität Stuttgart, 2002. [27] Foley, J.; van Dam, A.; Hughes, J., Computer Graphics: Principles and Practic, 2nd edition in C, Addison-Wesley, Reading, Massachusetts, USA, 1997. [28] http://www.cave.vt.edu/ [29] http://www.pdc.kth.se/projects/vr-cube/ [30] Actuality Systems Inc., Burlington, MA, USA http://www.actuality-systems.com/ [31] Borenstein, N. S., Upper Layer Protocols, In: Architectures and Applications, Elsevier, Amsterdam, 1992, Vol. 7, Kapitel 37, 461 - 462. 194 9 Literaturverzeichnis [32] Van-Vliet, B.; Maffet, T., Recent Advances in Structure Search and Retrieval via Nets- cape Navigator and MDL CHEMSCAPE(tm), Abs. Papers Am. Chem. Soc., 212th ACS National Meeting, Orlando, FL, USA, 212, CINF-29, 1996. [33] Arnold, K.; Gosling, J., The Java Programming Language, Addison-Wesley, Reading, Massachusetts, USA, 1998. [34] ISO/IEC 14772-1:1997. The Virtual Reality Modeling Language. http://www.web3d.org/technicalinfo/specifications/vrml97/, 1997. [35] ISO/IEC 14772-2:1997. External Authoring Interface. http://www.vrml.org/WorkingGroups/vrml-eai/Specification/, 1997. [36] Sowizral, H.; Nadeau, D.; Bailey, M.; Deering, M., Introduction to Programming with Java3D. ACM SIGGRAPH 98 Course Notes, July 1998, 1998. [37] Ihlenfeldt, W. D.; Takahashi, Y.; Abe, H.; Sasaki, S. J., Computation and Management of Chemical Properties in CACTVS: An Extensible Networked Approach toward Modularity and Compatibility, J. Chem. Inf. Comput. Sci., 34, 1994, 109 - 116. [38] Ihlenfeldt, W. D.; Takahashi, Y., Abe, H.; Sasaki, S., CACTVS: A Chemistry Algorithm Development Environment, In: Proceedings of the 15th Symposium on Chemical Infor- mation and Computer Sciences/20th Symposium on Structure-Activity Relationships; Machida, K.; Nishioka, T., Eds., Kyoto University, Kyoto, Japan, 1992, 102 - 105. [39] Ousterhout, J. K., Tcl and the Tk Toolkit, Addison-Wesley, Reading, Massachusetts, USA, 1994. [40] Sadowski, J.; Gasteiger, J., From Atoms and Bonds to Three-dimensional Atomic Coor- dinates: Automatic Model Builders., Chem. Reviews, 93, 1993, 2567-2581. [41] Sadowski, J.; Gasteiger, J.; Klebe, G., Comparison of Automatic Three-dimensional Model Builders Using 639 X-Ray Structures, J. Chem. Inf. Comput. Sci., 34, 1994, 1000-1008. [42] Rauhut, G.; Alex, A.; Chandrasekhar, J.; Steinke, T.; Sauer, W.; Beck, B.; Hutter, M.; Gedeck, P.; Clark, T., VAMP 6.1, Oxford Molecular, 1996. [43] Kendrew, J. C.; Bodo, G.; Dintzis, H. M.; Parrish, R.G.; Wyckoff, H.; Phillips, D. C., A three Dimensional Model of the Myoglobin Molecule obtained by X-ray Analysis, Nature, 181, 1958, 662 - 666. [44] Rubin, B.; Richardson, J. S., The Simple Construction of Protein Alpha-Carbon Models, Biopolymers, 11(11), 1972, 2381 - 2385. [45] Richardson J. S.; Richardson, D. C.; Thomas, K. A.; Silverton, E. W. Davies, D. R., Similarity of three-dimensional Structure between the Immunoglobulin Domain and the Copper-Zinc Superoxide Dismutase Subunit, J. Mol. Biol., 102, 1976, 221 - 235. [46] Levinthal, C., In: Proceedings of the IBM Scientific Computing Symposium on Compu- ter Aided Experimentation, International Business Machines, Yorktown Heights, NY, USA, 1965, 315 - 321. [47] Levinthal, C., Molecular Model-Building by Computer, Sci. Am., 214, 1966, 42 - 52. [48] Langridge, R., Interactive Three-Dimensional Computer Graphics in Molecular Bio- logy, In: Computers in Life Science Research, Siler, W.; Lindberg, D. A. B., Eds, Ple- num Publishing Corp., New York, USA, 1975, 53 - 59. 195 9 Literaturverzeichnis [49] Lesk, A. M., Macromolecular Marionettes, Comput. Biol. Med., 7, 1977, 113 - 129. [50] Beem, K. M.; Richardson, D. C.; Rajagopalan, K. V., Metal Sites of Copper-Zinc Superoxidase Dismutase, Biochemistry, 16, 1977, 1930 - 1936. [51] Feldmann, R. J., The Design of Computing Systems for Molecular Modelling, Annu. Rev. Biophys. Bioeng., 5, 1976, 477 - 510. [52] Porter, T. K., Spherical Shading, Comput. Graphics (SIGGRAPH), 12, 1978, 282 - 285. [53] Porter, T. K., Comput. Graphics (SIGGRAPH), 13, 1979, 234 - 236. [54] Koradi, R.; Billeter, M.; Wüthrich, K., MOLMOL: A Program for Display and Analysis of Macromolecular Structures, J. Mol. Graphics, 14, 1996, 51 - 55. [55] Dreiding, A. S., Simple Molecular Models, Helv. Chim. Acta, 42, 1959, 1339 - 1344. [56] Gouraud, H., Shading of Curved Surfaces, IEEE Trans. Comput., 20(6), 1971, 623 - 628. [57] Richardson, J. S., The Anatomy and Taxonomy of Protein Structure, Adv. Protein. Chem., 34, 1981, 167 - 339. [58] Richards, F. M., Areas, Volumes, Packing, and Protein Structure, Annu. Rev. Biophys. Bioeng., 6, 1977, 151 - 176. [59] Connolly, M. L., Analytical Molecular Surface Calculation, J. Appl. Crystallogr., 16, 1983, 548 - 558. [60] Connolly, M. L., Solvent-Accessible Surfaces of Proteins and Nucleic Acids, Science, 221, 1983, 709 - 713. [61] Lee, B.; Richards, F. M., The Interpretation of Protein Structures: Estimation of Static Accessibilty, J. Mol. Biol., 55(3), 1971, 379 - 400. [62] Duncan, B. S.; Olson, A. J., Approximation and Visualization of large-scale Motion of Proteins Surfaces, J. Mol. Graphics, 13, 1995, 250 - 257. [63] Jain, A. N.; Dietterich, T. G.; Lathrop, R. H.; Chapman, D., Compass: A Shape-based Machine Learning Tool for Drug Design, J. Comput.-Aided Mol. Design, 8, 1994, 635 - 652. [64] Mezey, P. G., Molecular Surfaces, In: Reviews in Computational Chemistry, Lipkowitz, K.; Boyd, D., Ed., VCH, Weinheim, 1990, 265 - 294. [65] Kühlbrandt, W.; Williams, A., Analysis of Macromolecular Structure and Dynamics by Electron Cryo-Microscopy, Curr. Opin. in Chem. Biol., 3, 1999, 537 - 543. [66]
Load more

Recommended publications
  • Quantitative Structure–Activity Relationships (Qsar) Study on Novel 4-Amidinoquinoline and 10- Amidinobenzonaphthyridine Derivatives As Potent Antimalaria Agent
    JCECThe Journal of Engineering and Exact Sciences – JCEC, Vol. 05 N. 03 (2019) journal homepage: https://periodicos.ufv.br/ojs/jcec doi: 10.18540/jcecvl5iss3pp0271-0282 OPEN ACCESS – ISSN: 2527-1075 QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS (QSAR) STUDY ON NOVEL 4-AMIDINOQUINOLINE AND 10- AMIDINOBENZONAPHTHYRIDINE DERIVATIVES AS POTENT ANTIMALARIA AGENT A. W. MAHMUD1, G. A. SHALLANGWA1 and A. UZAIRU1 1Ahmadu Bello University, Department of Chemistry, Zaria, Kaduna, Nigeria. A R T I C L E I N F O A B S T R A C T Article history: Quantitative structure–activity relationships (QSAR) has been a reliable study in the Received 2019-02-16 development of models that predict biological activities of chemical substances based on Accepted 2019-06-27 Available online 2019-06-30 their structures for the development of novel chemical entities. This study was carried out on 44 compounds of 4-amidinoquinoline and 10-amidinobenzonaphthyridine derivatives to p a l a v r a s - c h a v e develop a model that relates their structures to their activities against Plasmodium QSAR falciparum. Density Functional Theory (DFT) with basis set B3LYP/6-31G was used to ∗ Antimalaria optimize the compounds. Genetic Function Algorithm (GFA) was employed in selecting Plasmodium falciparum descriptors and building the model. Four models were generated and the model with best 4-Amidinoquinolina internal and external validation has internal squared correlation coefficient ( 2) of 0.9288, k e y w o r d s adjusted squared correlation coefficient ( adj) of 0.9103, leave-one-out (LOO) cross- 2 2 QSAR validation coefficient ( cv) value of 0.8924 and external squared correlation coefficient ( ) Antimalaria value of 0.8188.
    [Show full text]
  • Reversal of Multidrug Resistance in Mouse Lymphoma Cells by Extracts and Flavonoids from Pistacia Integerrima
    DOI:http://dx.doi.org/10.7314/APJCP.2016.17.1.51 Reversal of Multidrug Resistance in Mouse Lymphoma Cells by Extract and Flavonoids from Pistacia integerrima RESEARCH ARTICLE Reversal of Multidrug Resistance in Mouse Lymphoma Cells by Extracts and Flavonoids from Pistacia integerrima Abdur Rauf1*, Ghias Uddin2, Muslim Raza3, Bashir Ahmad4, Noor Jehan1, Bina S Siddiqui5, Joseph Molnar6, Akos Csonka6, Diana Szabo6 Abstract Phytochemical investigation of Pistacia integerrima has highlighted isolation of two known compounds naringenin (1) and dihydrokaempferol (2). A crude extract and these isolated compounds were here evaluated for their effects on reversion of multidrug resistance (MDR) mediated by P-glycoprotein (P-gp). The multidrug resistance P-glycoprotein is a target for chemotherapeutic drugs from cancer cells. In the present study rhodamine- 123 exclusion screening test on human mdr1 gene transfected mouse gene transfected L5178 and L5178Y mouse T-cell lymphoma cells showed excellent MDR reversing effects in a dose dependent manner. In-silico molecular docking investigations demonstrated a common binding site for Rhodamine123, and compounds naringenin and dihydrokaempferol. Our results showed that the relative docking energies estimated by docking softwares were in satisfactory correlation with the experimental activities. Preliminary interaction profile of P-gp docked complexes were also analysed in order to understand the nature of binding modes of these compounds. Our computational investigation suggested that the compounds interactions with the hydrophobic pocket of P-gp are mainly related to the inhibitory activity. Moreover this study s a platform for the discovery of novel natural compounds from herbal origin, as inhibitor molecules against the P-glycoprotein for the treatment of cancer.
    [Show full text]
  • Organi &C Biomolecular Chemistry
    Organic Biomolecular& Chemistry INDEXED IN MEDLINE Incorporating Acta Chemica Scandinavica Instructions for Authors (2004) Also see www.rsc.org/illustrations and www.rsc.org/electronicfiles CONTENTS 1.0 General Policy 1.0 General Policy Organic & Biomolecular Chemistry is a bimonthly journal 1.1 Articles for the publication of original research papers (articles), 1.2 Communications communications, Emerging Areas and Perspectives focusing on 1.3 Emerging Areas all aspects of synthetic, physical and biomolecular organic 1.4 Perspective Articles chemistry. 1.5 Submission of Articles Authors should note that papers that mainly emphasise the novel properties, applications or potential applications of 2.0 Administration materials may be more suited for submission to Journal of Materials Chemistry. (http://www.rsc.org/materials). 3.0 Notes on the Preparation of Papers There is no page charge for papers published in Organic & 3.1 Organisation of Material Biomolecular Chemistry. 3.2 Artwork Guidelines 3.3 Nomenclature Scope of the Journal 3.4 Deposition of Supplementary Data Organic & Biomolecular Chemistry brings together molecular 3.5 Guidelines on submitting files for proof preparation design, synthesis, structure, function and reactivity in one journal. It publishes fundamental work on synthetic, physical 4.0 Experimental and Characterisation Requirements and biomolecular organic chemistry as well as all organic 4.1 Physical Characteristics of Compounds aspects of: chemical biology, medicinal chemistry, natural 4.2 Characterisation of New Compounds
    [Show full text]
  • Molecular Dynamics Simulations of Tight Junction Proteins
    Molecular Dynamics Simulations of Tight Junction Proteins Eleni Fitsiou This dissertation is submitted for the degree of Doctor of Philosophy August 2020 Department of Chemistry I would like to dedicate this dissertation to my husband Antonios and sons Dimitrios and Ioannis. ii “Wisdom begins in wonder” Socrates iii Declaration I, Eleni Fitsiou, declare that this thesis titled ‘Molecular Dynamics Simulations of Tight Junction Proteins’ has not been submitted in support of an application for another degree at this or any other university. It is the result of my own work and includes nothing that is the outcome of work done in collaboration except where specifically indicated. Where I have quoted from the work of others, the source is always given. Lancaster University, UK iv Abstract Tight junctions (TJs) are specialised cell-cell structures that serve primarily as a barrier to molecular transport through the intercellular space between the cells. The claudin family of proteins are the main structural and functional components of the TJ strands that circumscribe the cells. The detailed molecular organisation at the TJs is not entirely resolved, being relatively inaccessible by current experimental methods. Here, we have employed molecular dynamics simulations using both atomistic and coarse-grained models to investigate the TJ structure formed by claudin-1 using self-assembly coupled with free energy calculations and enhanced sampling techniques. A feature of the studies is that the self-assembly simulations have been carried out using atomistic detail (a first) by simulating only the extracellular domains of claudin-1 in an implied membrane. The results show that the cis-interaction can occur in the absence of trans-interacting partners and that a claudin dimer is the smallest stable unit.
    [Show full text]
  • Interpretation of Molecule Conformations from Drawn Diagrams” by Dana Tenneson, Ph.D., Brown University, May 2008
    Abstract of \Interpretation of Molecule Conformations from Drawn Diagrams" by Dana Tenneson, Ph.D., Brown University, May 2008. In chemistry, molecules are drawn on paper and chalkboards as diagrams consisting of lines, letters, and symbols which represent not only the atoms and bonds in the molecules but concisely encode cues to the 3D geometry of the molecules. Recent efforts into pen-based input methods for chemistry software have made progress at allowing chemists to input 2D diagrams of molecules into a computer simply by drawing them on a digitizer tablet. However, the task of interpreting these parsed sketches into proper 3D models has been largely unsolved due to the difficulty in making the models satisfy both the natural properties of molecule structure and the geometric cues made explicit in the drawing. This dissertation presents a set of techniques developed to solve this model construction problem within the context of an educational application for chemistry students. Our primary contribution is a framework for combining molecular structure knowledge and molecule diagram understanding via augmenting molecular mechanics equations to include drawing-based penalty terms. Additionally, we present an algorithm for generating molecule models from drawn diagrams which leverages domain- specific and diagram-driven heuristics. These heuristics make our process fast and accurate enough for molecule diagram drawing to be used as an interactive technique for model construction on modern Tablet PC computers. Interpretation of Molecule Conformations
    [Show full text]
  • Introduction to Bioinformatics (Elective) – SBB1609
    SCHOOL OF BIO AND CHEMICAL ENGINEERING DEPARTMENT OF BIOTECHNOLOGY Unit 1 – Introduction to Bioinformatics (Elective) – SBB1609 1 I HISTORY OF BIOINFORMATICS Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biologicaldata. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to analyze and interpret biological data. Bioinformatics has been used for in silico analyses of biological queries using mathematical and statistical techniques. Bioinformatics derives knowledge from computer analysis of biological data. These can consist of the information stored in the genetic code, but also experimental results from various sources, patient statistics, and scientific literature. Research in bioinformatics includes method development for storage, retrieval, and analysis of the data. Bioinformatics is a rapidly developing branch of biology and is highly interdisciplinary, using techniques and concepts from informatics, statistics, mathematics, chemistry, biochemistry, physics, and linguistics. It has many practical applications in different areas of biology and medicine. Bioinformatics: Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. Computational Biology: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. "Classical" bioinformatics: "The mathematical, statistical and computing methods that aim to solve biological problems using DNA and amino acid sequences and related information.” The National Center for Biotechnology Information (NCBI 2001) defines bioinformatics as: "Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline.
    [Show full text]
  • Titelei 1..30
    Johann Gasteiger, Thomas Engel (Eds.) Chemoinformatics Chemoinformatics: A Textbook. Edited by Johann Gasteiger and Thomas Engel Copyright 2003 Wiley-VCH Verlag GmbH & Co. KGaA. ISBN: 3-527-30681-1 Related Titles from WILEY-VCH Hans-Dieter HoÈltje, Wolfgang Sippl, Didier Rognan, Gerd Folkers Molecular Modeling 2003 ISBN 3-527-30589-0 Helmut GuÈnzler, Hans-Ulrich Gremlich IR Spectroscopy An Introduction 2002 ISBN 3-527-28896-1 Jure Zupan, Johann Gasteiger Neural Networks in Chemistry and Drug Design An Introduction 1999 ISBN 3-527-29778-2 (HC) ISBN 3-527-29779-0 (SC) Siegmar Braun, Hans-Otto Kalinowski, Stefan Berger 150 and More Basic NMR Experiments A Practical Course 1998 ISBN 3-527-29512-7 Johann Gasteiger, Thomas Engel (Eds.) Chemoinformatics A Textbook Editors: This book was carefully produced. Never- theless, editors, authors and publisher do Prof. Dr. Johann Gasteiger not warrant the information contained Computer-Chemie-Centrum and Institute therein to be free of errors. Readers are ofOrganic Chemistry advised to keep in mind that statements, University ofErlangen-NuÈrnberg data, illustrations, procedural details or NaÈgelsbachstraûe 25 other items may inadvertently be inaccurate. 91052 Erlangen Germany Library of Congress Card No.: applied for A catalogue record for this book is available from the British Library. Dr. Thomas Engel Computer-Chemie-Centrum and Institute Bibliographic information published by ofOrganic Chemistry Die Deutsche Bibliothek University ofErlangen-NuÈrnberg Die Deutsche Bibliothek lists this publica- NaÈgelsbachstraûe 25 tion in the Deutsche Nationalbibliografie; 91052 Erlangen detailed bibliographic data is available in the Germany Internet at http://dnb.ddb.de ISBN 3-527-30681-1 c 2003 WILEY-VCH Verlag GmbH & Co.
    [Show full text]
  • ED359038.Pdf
    DOCUMENT RESUME ED 359 038 SE 053 379 AUTHOR Russell, Arlene A., Ed. TITLE Changing the Image of Chemistry. Biennial Conference on Chemical Education, Abstracts (12th, Davis, California, August 2-6, 1992). INSTITUTION American Chemical Society, Washington, DC. Div. of Chemical Education. SPONS AGENCY American Chemical Society, Washington, DC. Div. of Chemical Education.; California Univ., Davis. PUB DATE Aug 92 NOTE 151p.; For abstracts from the previous conference, see ED 324 245. PUB TYPE Collected Works Conference Proceedings (021) EDRS PRICE MF01/PC07 Plus Postage. DESCRIPTORS Chemical Equilibrium; Chemical Reactions; *Chemistry; Classroom Research; College Science; *Computer Assisted Instruction; Computer Uses in Education; Concept Formation; Demonstrations (Educational); Educational Research; Elementary School Science; Elementary Secondary Education; Higher. Education; High Schools; Hypothesis Testing: Physical Sciences: Problem Solving; *Science Education; *Science Laboratories; Science Materials; Science Teachers; Scientific Literacy; Secondary School Science; Teacher Education IDENTIFIERS Hands On Science; Science Process Skills ABSTRACT This document contains 395 abstracts of presentations on the theme of changing the image of chemistry, made ata conference on chemical education. Included with the abstractsare the presenters' names and addresses. The conferenceincluded the following sessions: Lecture and Learning:Are They Compatible?; ChemSource; Relevant Chemistry for the Non-Science Major; Industry-Education Initiatives; Innovative
    [Show full text]
  • Application of Hartree-Fock Method for Modeling of Bioactive Molecules Using SAR and QSPR
    Computational Molecular Bioscience, 2014, 4, 1-24 Published Online March 2014 in SciRes. http://www.scirp.org/journal/cmb http://dx.doi.org/10.4236/cmb.2014.41001 Application of Hartree-Fock Method for Modeling of Bioactive Molecules Using SAR and QSPR Cleydson B. R. Santos1,2,3*, Cleison C. Lobato1, Francinaldo S. Braga1, Sílvia S. S. Morais4, Cesar F. Santos1, Caio P. Fernandes1,3, Davi S. B. Brasil1,5, Lorane I. S. Hage-Melim1, Williams J. C. Macêdo1,2, José C. T. Carvalho1,2,3 1Laboratory of Modeling and Computational Chemistry, Federal University of Amapá, Macapá, Brazil 2Postgraduate Program in Biotechnology and Biodiversity-Network BIONORTE, Campus Universitário Marco Zero, Macapá, Brazil 3Laboratory of Drug Research, School of Pharmaceutical Sciences, Federal University of Amapá, Macapá, Brazil 4Laboratory of Statistical and Computational Modeling, University of the State of Amapá, Macapá, Brazil 5Institute of Technology, Federal University of Pará, Belém, Brazil Email: *[email protected] Received 12 January 2014; revised 12 February 2014; accepted 20 February 2014 Copyright © 2014 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract The central importance of quantum chemistry is to obtain solutions of the Schrödinger equation for the accurate determination of the properties of atomic and molecular systems that occurred from the calculation of wave functions accurate for many diatomic and polyatomic molecules, us- ing Self Consistent Field method (SCF). The application of quantum chemical methods in the study and planning of bioactive compounds has become a common practice nowadays.
    [Show full text]
  • Plasmodium Falciparum
    Mahmud et al. Beni-Suef University Journal of Basic and Applied Sciences Beni-Suef University Journal of (2020) 9:19 https://doi.org/10.1186/s43088-020-00044-0 Basic and Applied Sciences RESEARCH Open Access In silico modeling of tetraoxane-8- aminoquinoline hybrids active against Plasmodium falciparum Aliyu Wappah Mahmud1*, Gideon Adamu Shallangwa2 and Adamu Uzairu2 Abstract Background: Quantitative structure-activity relationships (QSAR) is a technique that is used to produce a model that connects biological activities of compounds to their chemical structures, and molecular docking is a technique that reveals the binding mode and interactions between a drug and its target enzyme. These techniques have been successfully applied in the design and development of many drug candidates and herein were employed to build a model that could help in the development of more potent antimalaria drugs. Results: Descriptors of the compounds were calculated using the PaDEL-Descriptor software, and Genetic Function Algorithm (GFA) was used to select descriptors and build the model. A robust and reliable model was generated and validated to have internal and external squared correlation coefficient (R2) of 0.9622 and 0.8191, respectively, 2 adjusted squared correlation coefficient (Radj) of 0.9471, and leave-one-out (LOO) cross-validation coefficient (Q cv) of 0.9223. The model revealed that the antiplasmodial activities of 1,2,4,5-tetraoxane-8-aminoquinoline hybrids depend on MATS3m, GATS8p, GATS8i, and RDF50s descriptors. MATS3m, GATS8i, and RDF50s influenced the antiplasmodial activities of the compounds positively while GATS8p negatively with the greatest influence. The docking result shows strong interactions between 1,2,4,5-tetraoxane-8-aminoquinoline hybrids and Plasmodium falciparum lactate dehydrogenase (pfLDH) with binding affinities ranging from − 6.3 to − 10.9 kcal/mol which were better than that of chloroquine (− 6.1 kcal/mol), suggesting that these compounds could be better inhibitors of pfLDH than chloroquine.
    [Show full text]
  • Titelei 1..30
    Johann Gasteiger, Thomas Engel (Eds.) Chemoinformatics Chemoinformatics: A Textbook. Edited by Johann Gasteiger and Thomas Engel Copyright 2003 Wiley-VCH Verlag GmbH & Co. KGaA. ISBN: 3-527-30681-1 Related Titles from WILEY-VCH Hans-Dieter HoÈltje, Wolfgang Sippl, Didier Rognan, Gerd Folkers Molecular Modeling 2003 ISBN 3-527-30589-0 Helmut GuÈnzler, Hans-Ulrich Gremlich IR Spectroscopy An Introduction 2002 ISBN 3-527-28896-1 Jure Zupan, Johann Gasteiger Neural Networks in Chemistry and Drug Design An Introduction 1999 ISBN 3-527-29778-2 (HC) ISBN 3-527-29779-0 (SC) Siegmar Braun, Hans-Otto Kalinowski, Stefan Berger 150 and More Basic NMR Experiments A Practical Course 1998 ISBN 3-527-29512-7 Johann Gasteiger, Thomas Engel (Eds.) Chemoinformatics A Textbook Editors: This book was carefully produced. Never- theless, editors, authors and publisher do Prof. Dr. Johann Gasteiger not warrant the information contained Computer-Chemie-Centrum and Institute therein to be free of errors. Readers are ofOrganic Chemistry advised to keep in mind that statements, University ofErlangen-NuÈrnberg data, illustrations, procedural details or NaÈgelsbachstraûe 25 other items may inadvertently be inaccurate. 91052 Erlangen Germany Library of Congress Card No.: applied for A catalogue record for this book is available from the British Library. Dr. Thomas Engel Computer-Chemie-Centrum and Institute Bibliographic information published by ofOrganic Chemistry Die Deutsche Bibliothek University ofErlangen-NuÈrnberg Die Deutsche Bibliothek lists this publica- NaÈgelsbachstraûe 25 tion in the Deutsche Nationalbibliografie; 91052 Erlangen detailed bibliographic data is available in the Germany Internet at http://dnb.ddb.de ISBN 3-527-30681-1 c 2003 WILEY-VCH Verlag GmbH & Co.
    [Show full text]
  • Computer-Aided Information Retrieval and Management System from Scientific Documents
    Computergestützte Informationsbeschaffung und -verwaltung aus wissenschaftlichen Dokumenten Computer-aided information retrieval and management system from scientific documents Zur Erlangung des akademischen Grades eines DOKTORS DER NATURWISSENSCHAFTEN (Dr. rer. nat.) von der KIT-Fakultät für Chemie und Biowissenschaften des Karlsruher Instituts für Technologie (KIT) genehmigte DISSERTATION von M.Sc. Thanh Cam An Nguyen aus Hue, Vietnam Dekan: Prof. Dr. Manfred Wilhelm Referent: Prof. Dr. Stefan Bräse Koreferent: Prof. Dr. Ralf H. Reussner Tag der mündlichen Prüfung: 12.12.2019 Für meine Familie, meine Freunde und mich. Probleme kann man niemals mit derselben Denkweise lösen, durch die sie entstanden sind. - Albert Einstein Die vorliegende Arbeit wurde in der Zeit vom 15.06.2016 bis 06.11.2019 am Institut für Organische Chemie der Fakultät für Chemie und Biowissenschaften am Karlsruher Institut für Technologie (KIT) Campus Nord unter der Leitung von Prof. Dr. Stefan Bräse angefertigt. Hiermit versichere ich, die vorliegende Dissertation selbstständig verfasst und ohne unerlaubte Hilfsmittel angefertigt zu haben. Es wurden keine anderen als die angegebenen Quellen und Hilfsmittel benutzt. Die aus Quellen – wörtlich oder inhaltlich – entnommenen Stellen wurden als solche kenntlich gemacht. Die Arbeit wurde bisher weder in gleicher, noch in ähnlicher Form einer anderen Prüfungsbehörde vorgelegt oder veröffentlicht. Ich habe die Regeln zur Sicherung guter wissenschaftlicher Praxis im Karlsruher Institut für Technologie (KIT) beachtet. Table
    [Show full text]