Teaching with SCIGRESS
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Mercury 2.4 User Guide and Tutorials 2011 CSDS Release
Mercury 2.4 User Guide and Tutorials 2011 CSDS Release Copyright © 2010 The Cambridge Crystallographic Data Centre Registered Charity No 800579 Conditions of Use The Cambridge Structural Database System (CSD System) comprising all or some of the following: ConQuest, Quest, PreQuest, Mercury, (Mercury CSD and Materials module of Mercury), VISTA, Mogul, IsoStar, SuperStar, web accessible CSD tools and services, WebCSD, CSD Java sketcher, CSD data file, CSD-UNITY, CSD-MDL, CSD-SDfile, CSD data updates, sub files derived from the foregoing data files, documentation and command procedures (each individually a Component) is a database and copyright work belonging to the Cambridge Crystallographic Data Centre (CCDC) and its licensors and all rights are protected. Use of the CSD System is permitted solely in accordance with a valid Licence of Access Agreement and all Components included are proprietary. When a Component is supplied independently of the CSD System its use is subject to the conditions of the separate licence. All persons accessing the CSD System or its Components should make themselves aware of the conditions contained in the Licence of Access Agreement or the relevant licence. In particular: • The CSD System and its Components are licensed subject to a time limit for use by a specified organisation at a specified location. • The CSD System and its Components are to be treated as confidential and may NOT be disclosed or re- distributed in any form, in whole or in part, to any third party. • Software or data derived from or developed using the CSD System may not be distributed without prior written approval of the CCDC. -
GROMACS: Fast, Flexible, and Free
GROMACS: Fast, Flexible, and Free DAVID VAN DER SPOEL,1 ERIK LINDAHL,2 BERK HESS,3 GERRIT GROENHOF,4 ALAN E. MARK,4 HERMAN J. C. BERENDSEN4 1Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, Box 596, S-75124 Uppsala, Sweden 2Stockholm Bioinformatics Center, SCFAB, Stockholm University, SE-10691 Stockholm, Sweden 3Max-Planck Institut fu¨r Polymerforschung, Ackermannweg 10, D-55128 Mainz, Germany 4Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 4, NL-9747 AG Groningen, The Netherlands Received 12 February 2005; Accepted 18 March 2005 DOI 10.1002/jcc.20291 Published online in Wiley InterScience (www.interscience.wiley.com). Abstract: This article describes the software suite GROMACS (Groningen MAchine for Chemical Simulation) that was developed at the University of Groningen, The Netherlands, in the early 1990s. The software, written in ANSI C, originates from a parallel hardware project, and is well suited for parallelization on processor clusters. By careful optimization of neighbor searching and of inner loop performance, GROMACS is a very fast program for molecular dynamics simulation. It does not have a force field of its own, but is compatible with GROMOS, OPLS, AMBER, and ENCAD force fields. In addition, it can handle polarizable shell models and flexible constraints. The program is versatile, as force routines can be added by the user, tabulated functions can be specified, and analyses can be easily customized. Nonequilibrium dynamics and free energy determinations are incorporated. Interfaces with popular quantum-chemical packages (MOPAC, GAMES-UK, GAUSSIAN) are provided to perform mixed MM/QM simula- tions. The package includes about 100 utility and analysis programs. -
Quantitative Evaluation of Dissociation Mechanisms in Phenolphthalein and the Related Compounds
J. Comput. Chem. Jpn., Vol. 15, No. 1, pp. 13–21 (2016) ©2016 Society of Computer Chemistry, Japan Technical Paper Quantitative Evaluation of Dissociation Mechanisms in Phenolphthalein and the Related Compounds Toshihiko HANAI Health Research Foundation, Research Institute for Production Development 4F, 15 Shimogamo-morimoto-cho, Sakyo-ku, Kyoto 606-0805, Japan e-mail: [email protected] (Received: October 11, 2015; Accepted for publication: April 14, 2016; Online publication: May 6, 2016) Computational chemistry programs were evaluated as aids to teaching qualitative analytical chemistry. Compu- tational chemical calculations can predict absorption spectra, thus enabling the modeling of indicator dissociation mechanisms by different computational chemical programs using a personal computer. An updated MNDO program among 51 programs was found to be the best predictor to explain the dissociation mechanisms of isobenzofuranones and sulfonephthaleins. Unknown dissociation constants were predicted from atomic partial charges instead of Ham- mett's constants. Keywords: Quantitative analysis of dissociation mechanisms, Isobenzofuranone, Sulfonephthalein, Computational chemistry 1 Introduction the absorption wavelength and electron density changes were not well described. The dissociation mechanisms, maximum How to quantitatively teach qualitative analytical chemistry is wavelengths, and electron density maps of isobenzofuranones a very important subject for analytical chemists. Previously, a and sulfonephthaleins were, therefore, evaluated by in silico method to teach molecular interaction mechanisms in chroma- analysis despite the anticipated poor precision. The experimen- tography was quantitatively achieved using molecular mechan- tally measured dissociation of phenolphthalein is described ics and MOPAC programs [1]. Furthermore, the reaction mech- using four dissociation structures, where the ionization of two anisms of highly sensitive detections were also quantitatively phenolic hydroxyl groups converts the neutral molecular form described [2,3]. -
A Comparative Study of the Efficiency of HCV NS3/4A Protease Drugs
Life Sciences 217 (2019) 176–184 Contents lists available at ScienceDirect Life Sciences journal homepage: www.elsevier.com/locate/lifescie A comparative study of the efficiency of HCV NS3/4A protease drugs against different HCV genotypes using in silico approaches T ⁎ Ahmed A. Ezat , Wael M. Elshemey Biophysics Department, Faculty of Science, Cairo University, 12613 Giza, Egypt ARTICLE INFO ABSTRACT Keywords: Aims: To investigate the efficacy of Direct Acting Antivirals (DAAs) in the treatment of different Hepatitis C HCV Virus (HCV) genotypes. NS3/4A protease Main methods: Homology modeling is used to predict the 3D structures of different genotypes while molecular Molecular docking docking is employed to predict genotype – drug interactions (Binding Mode) and binding free energy (Docking Homology modeling Score). Key findings: Simeprevir (TMC435) and to a lesser degree MK6325 are the best drugs among the studied drugs. The predicted affinity of drugs against genotype 1a is always better than other genotypes. P2–P4 macrocyclic drugs show better performance against genotypes 2, 3 and 5. Macrocyclic drugs are better than linear drugs. Significance: HCV is one of the major health problems worldwide. Until the discovery of DAAs, HCV treatment faced many failures. DAAs target key functional machines of the virus life cycle and shut it down. NS3/4A protease is an important target and several drugs have been designed to inhibit its functions. There are several NS3/4A protease drugs approved by Food and Drug Administration (FDA). Unfortunately, the virus exhibits resistance against these drugs. This study is significant in elucidating that no one drug is able to treat different genotypes with the same efficiency. -
Introduction to Organic Chemistry 2018 More
Introduction to Organic Chemistry 25 Introduction to Organic Chemistry Handout 2 - Stereochemistry OH O O OH enantiomers Me OH HO Me A B NH2 NH2 diastereomers diastereomers diastereomers OH O O OH Me OH HO Me C D NH2 enantiomers NH2 http://burton.chem.ox.ac.uk/teaching.html ◼ Organic Chemistry J. Clayden, N. Greeves, S. Warren ◼ Stereochemistry at a Glance J. Eames & J. M. Peach ◼ The majority of organic chemistry text books have good chapters on the topics covered by these lectures ◼ Eliel Stereochemistry of Organic Compounds (advanced reference text) Introduction to Organic Chemistry 26 ◼ representations of formulae in organic chemistry ◼ skeletal representations are far less cluttered and as a result are much clearer than drawing all carbon and hydrogen atoms explicitly, they also give a much better representation of the likely bond angles and hence hybridisation states of the carbon atoms ◼ skeletal representations allow functional groups (sites of reactivity) to be clearly seen ◼ guidelines for drawing skeletal structures i) draw chains of atoms as zig-zags ii) do not draw C atoms unless there is good reason to draw them iii) do not draw C-H bonds unless there is good reason to draw then iv) do not draw Hs attached to carbon atoms unless there is good reason to draw them v) make drawings realistic Introduction to Organic Chemistry 27 ◼ representing structures in three dimensions ◼ a wedged bond indicates the bond is projecting out in front of the plane of the paper ◼ a dashed bond indicates the bond is projecting behind the plane -
Kingston University London the Antibiotic Resistance Growth Plate
Kingston University London The Antibiotic Resistance Growth Plate (ARGP) as an experimental evolution tool to explore the phenotypic and genotypic mutational pathways underlying the emergence of antimicrobial resistance in Escherichia coli. A thesis submitted in partial fulfilment for the degree of Doctor of Philosophy By Lucky Bonnie Lucia CULLEN Faculty of Science, Engineering and Computing February 2019 Declaration This thesis entitled ‘The Antibiotic Resistance Growth Plate (ARGP)’ as an experimental evolution tool to explore the phenotypic and genotypic mutational pathways underlying the emergence of antimicrobial resistance in Escherichia coli’ is based upon the work conducted in the Faculty of Science, Engineering and Computing at Kingston University London and in collaboration with Dr Philip Aldridge at Newcastle University and Katie Hopkins and Neil Woodford from Public Health England. All the work described is the candidate’s own original work unless otherwise stated. None of the work presented has been submitted for another degree internally or externally. i Acknowledgements At the start of this PhD I had a dream, a dream which could have never been accomplished without the support of many people. Firstly, I would like to express my sincere appreciation to my director of studies Professor Mark Fielder, your provision, guidance and unconditional belief in my potential has contributed significantly to the completion of this thesis. I would also like to acknowledge the overwhelming support received from, Dr Scott Lawton, Camilla Eldridge and Ben Jones, your wealth of knowledge and expertise in the field of evolutionary biology and bioinformatics has assisted greatly in concluding the work within this PhD. I would also like to praise the incredible multidisciplinary support received at Kingston University, specifically that from Dr Gary-Forster Wilkins, Dr Adam Le Gresley, Dr Brian Rooney, Dr James Denholm-Price and Richard Giddens. -
Conformational Analysis with Scigress
CONFORMATIONAL ANALYSIS WITH SCIGRESS During this laboratory period you will use two computational chemistry methods to carry out conformational analysis experiments on butane, cyclohexanol and cis-1,3-cyclohexanediol. Mechanics is a method which uses classical Newtonian mechanics to compute the energies of molecules. Bonds are treated as springs and atoms as balls attached to these springs. MOPAC is a method which uses quantum mechanics to calculate the energies of molecules and determine their optimum geometries and other properties; MOPAC is an acronym for Molecular Orbital PACkage Conformational Energy of Butane 1. Build and beautify a molecule of butane. Save your drawing with the name "butane." 2. Highlight (select) the four carbon atoms (in order). All other atoms should be grayed out. Choose Adjust→Dihedral Angle from the menu bar. Select “Define Geometry Label” and “Search”. Apply and then click OK. The workspace containing the butane molecule will reappear with the dihedral angle written in blue across it. The letter S will appear next to the value of the dihedral angle indicating that it is a search label. Re-save the drawing 3. Choose Experiment→New from the menu bar; the experiment dialog box should appear. Choose chemical sample conformations (CAChe 5.0 experiments) from the “Property of” box. Choose optimized map in the “Property” box. Click Start (if an error appears click OK and re-try). 4. Two adjacent windows should appear presenting the results of the calculation. The left window is a plot of potential energy versus dihedral angle for the butane molecule. The graph colors represent the relative energies of the butane molecule with various dihedral angles. -
Energy Functions and Their Relationship to Molecular Conformation
Molecular dynamics simulation CS/CME/BioE/Biophys/BMI 279 Oct. 5, 2021 Ron Dror 1 Outline • Molecular dynamics (MD): The basic idea • Equations of motion • Key properties of MD simulations • Sample applications • Limitations of MD simulations • Software packages and force fields • Accelerating MD simulations • Monte Carlo simulation 2 Molecular dynamics: The basic idea 3 The idea • Mimic what atoms do in real life, assuming a given potential energy function – The energy function allows us to calculate the force experienced by any atom given the positions of the other atoms – Newton’s laws tell us how those forces will affect the motions of the atoms ) U Energy( Position Position 4 Basic algorithm • Divide time into discrete time steps, no more than a few femtoseconds (10–15 s) each • At each time step: – Compute the forces acting on each atom, using a molecular mechanics force field – Move the atoms a little bit: update position and velocity of each atom using Newton’s laws of motion 5 Molecular dynamics movie Equations of motion 7 Specifying atom positions • For a system with N x1 atoms, we can specify y1 the position of all z1 atoms by a single x2 vector x of length 3N y2 x = – This vector contains z2 the x, y, and z ⋮ coordinates of every xN atom yN zN Specifying forces ∂U • A single vector F specifies F1,x ∂x1 the force acting on every F ∂U atom in the system 1,y ∂y1 • For a system with N F ∂U atoms, F is a vector of 1,z ∂z1 length 3N ∂U F2,x – This vector lists the force ∂x2 ∂U on each atom in the x-, y-, F2,y and z- directions F -
Molecular Docking : Current Advances and Challenges
ARTÍCULO DE REVISIÓN © 2018 Universidad Nacional Autónoma de México, Facultad de Estudios Superiores Zaragoza. This is an Open Access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). TIP Revista Especializada en Ciencias Químico-Biológicas, 21(Supl. 1): 65-87, 2018. DOI: 10.22201/fesz.23958723e.2018.0.143 MOLECULAR DOCKING: CURRENT ADVANCES AND CHALLENGES Fernando D. Prieto-Martínez,1a Marcelino Arciniega2 and José L. Medina-Franco1b 1Facultad de Química, Departamento de Farmacia, Universidad Nacional Autónoma de México, Avenida Universidad # 3000, Delegación Coyoacán, Ciudad de México 04510, México 2Instituto de Fisiología Celular, Departamento de Bioquímica y Biología Estructural, Universidad Nacional Autónoma de México E-mails: [email protected], [email protected],[email protected] ABSTRACT Automated molecular docking aims at predicting the possible interactions between two molecules. This method has proven useful in medicinal chemistry and drug discovery providing atomistic insights into molecular recognition. Over the last 20 years methods for molecular docking have been improved, yielding accurate results on pose prediction. Nonetheless, several aspects of molecular docking need revision due to changes in the paradigm of drug discovery. In the present article, we review the principles, techniques, and algorithms for docking with emphasis on protein-ligand docking for drug discovery. We also discuss current approaches to address major challenges of docking. Key Words: chemoinformatics, computer-aided drug design, drug discovery, structure-activity relationships. Acoplamiento Molecular: Avances Recientes y Retos RESUMEN El acoplamiento molecular automatizado tiene como objetivo proponer un modelo de unión entre dos moléculas. Este método ha sido útil en química farmacéutica y en el descubrimiento de nuevos fármacos por medio del entendimiento de las fuerzas de interacción involucradas en el reconocimiento molecular. -
Recent Advances in Molecular Docking for the Research and Discovery of Potential Marine Drugs
marine drugs Review Recent Advances in Molecular Docking for the Research and Discovery of Potential Marine Drugs Guilin Chen 1,2,3, Armel Jackson Seukep 1,2,3,4 and Mingquan Guo 1,2,3,* 1 Key Laboratory of Plant Germplasm Enhancement & Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China; [email protected] (G.C.); [email protected] (A.J.S.) 2 Sino-Africa Joint Research Center, Chinese Academy of Sciences, Wuhan 430074, China 3 Innovation Academy for Drug Discovery and Development, Chinese Academy of Sciences, Shanghai 201203, China 4 Department of Biomedical Sciences, Faculty of Health Sciences, University of Buea, P.O. Box 63 Buea, Cameroon * Correspondence: [email protected]; Tel.: +86-27-8770-0850 Received: 16 September 2020; Accepted: 28 October 2020; Published: 30 October 2020 Abstract: Marine drugs have long been used and exhibit unique advantages in clinical practices. Among the marine drugs that have been approved by the Food and Drug Administration (FDA), the protein–ligand interactions, such as cytarabine–DNA polymerase, vidarabine–adenylyl cyclase, and eribulin–tubulin complexes, are the important mechanisms of action for their efficacy. However, the complex and multi-targeted components in marine medicinal resources, their bio-active chemical basis, and mechanisms of action have posed huge challenges in the discovery and development of marine drugs so far, which need to be systematically investigated in-depth. Molecular docking could effectively predict the binding mode and binding energy of the protein–ligand complexes and has become a major method of computer-aided drug design (CADD), hence this powerful tool has been widely used in many aspects of the research on marine drugs. -
Molecular Dynamics (MD) for Cancer Control Protocol
Molecular Dynamics (MD) for Cancer control Protocol Claudio Nicolini ( [email protected] ) Claudio Ando Nicolini's Lab, NanoWorld, USA; HC Professor Nanobiotechnology, Lomonosov Moscow State University, Russia; Foreign Member Russian Academy of Sciences; President NWI Fondazione EL.B.A. Nicolini; Editor-in-Chief NWJ, Santa Clara, USA Marine Bozdaganyan Claudio Ando Nicolini's Lab, NanoWorld, USA; Lomonosov Moscow State University (MSU), Moscow, Russia; Fondazione EL.B.A. Nicolini Nicola Luigi Bragazzi Claudio Ando Nicolini's Lab, NanoWorld, USA Philippe Orekhov Claudio Ando Nicolini's Lab, NanoWorld, USA Eugenia Pechkova Claudio Ando Nicolini's Lab, NanoWorld, USA Method Article Keywords: Langmuir-Blodgett (LB)-based crystallography Posted Date: March 15th, 2016 DOI: https://doi.org/10.1038/protex.2016.016 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/13 Abstract In the present protocol, we describe how molecular dynamics \(MD) can be applied for studying Langmuir-Blodgett \(LB)-based crystal proteins. MD can therefore play a major role in nanomedicine, as well as in personalized medicine. Introduction The computer simulation of dynamics in molecular systems is widely used in molecular physics, biotechnology, medicine, chemistry and material sciences to predict physical and mechanical properties of new samples of matter. In the molecular dynamics method there is a polyatomic molecular system in which all atoms are interacting like material points, and behavior of the atoms is described by the equations of classical mechanics. This method allows doing simulations of the system of the order of 106 atoms in the time range up to 1 microsecond. -
Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens
International Journal of Molecular Sciences Review Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens Anna Helena Mazurek 1 , Łukasz Szeleszczuk 1,* , Thomas Simonson 2 and Dariusz Maciej Pisklak 1 1 Chair and Department of Physical Pharmacy and Bioanalysis, Department of Physical Chemistry, Medical Faculty of Pharmacy, University of Warsaw, Banacha 1 str., 02-093 Warsaw Poland; [email protected] (A.H.M.); [email protected] (D.M.P.) 2 Laboratoire de Biochimie (CNRS UMR7654), Ecole Polytechnique, 91-120 Palaiseau, France; [email protected] * Correspondence: [email protected]; Tel.: +48-501-255-121 Received: 21 July 2020; Accepted: 1 September 2020; Published: 3 September 2020 Abstract: In this review, applications of various molecular modelling methods in the study of estrogens and xenoestrogens are summarized. Selected biomolecules that are the most commonly chosen as molecular modelling objects in this field are presented. In most of the reviewed works, ligand docking using solely force field methods was performed, employing various molecular targets involved in metabolism and action of estrogens. Other molecular modelling methods such as molecular dynamics and combined quantum mechanics with molecular mechanics have also been successfully used to predict the properties of estrogens and xenoestrogens. Among published works, a great number also focused on the application of different types of quantitative structure–activity relationship (QSAR) analyses to examine estrogen’s structures and activities. Although the interactions between estrogens and xenoestrogens with various proteins are the most commonly studied, other aspects such as penetration of estrogens through lipid bilayers or their ability to adsorb on different materials are also explored using theoretical calculations.