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Density Functional Theory
Density Functional Approach Francesco Sottile Ecole Polytechnique, Palaiseau - France European Theoretical Spectroscopy Facility (ETSF) 22 October 2010 Density Functional Theory 1. Any observable of a quantum system can be obtained from the density of the system alone. < O >= O[n] Hohenberg, P. and W. Kohn, 1964, Phys. Rev. 136, B864 Density Functional Theory 1. Any observable of a quantum system can be obtained from the density of the system alone. < O >= O[n] 2. The density of an interacting-particles system can be calculated as the density of an auxiliary system of non-interacting particles. Hohenberg, P. and W. Kohn, 1964, Phys. Rev. 136, B864 Kohn, W. and L. Sham, 1965, Phys. Rev. 140, A1133 Density Functional ... Why ? Basic ideas of DFT Importance of the density Example: atom of Nitrogen (7 electron) 1. Any observable of a quantum Ψ(r1; ::; r7) 21 coordinates system can be obtained from 10 entries/coordinate ) 1021 entries the density of the system alone. 8 bytes/entry ) 8 · 1021 bytes 4:7 × 109 bytes/DVD ) 2 × 1012 DVDs 2. The density of an interacting-particles system can be calculated as the density of an auxiliary system of non-interacting particles. Density Functional ... Why ? Density Functional ... Why ? Density Functional ... Why ? Basic ideas of DFT Importance of the density Example: atom of Oxygen (8 electron) 1. Any (ground-state) observable Ψ(r1; ::; r8) 24 coordinates of a quantum system can be 24 obtained from the density of the 10 entries/coordinate ) 10 entries 8 bytes/entry ) 8 · 1024 bytes system alone. 5 · 109 bytes/DVD ) 1015 DVDs 2. -
Istls Information Services to Life Science Internet Bioinformatics Resources Josef Maier [E-Mail: [email protected]] Last Checked August, 17Th, 2011
IStLS Information Services to Life Science Internet Bioinformatics Resources Josef Maier [e-mail: [email protected]] Last checked August, 17th, 2011 IStLS Bioinformatics Resources http://www.istls.de/bioinfolinks.php Courses and lectures Bioinformatics - Online Courses and Tutorials http://www.bioinformatik.de/cgi-bin/browse/Catalog/Research_and_Education/Online_Courses_and_Tutorials/ EMBRACE Network of Excellence http://www.embracegrid.info/page.php EMBNet Quick Guides http://www.embnet.org/node/64 EMBNet Courses http://www.embnet.org/ Sequence Analysis with distributed Resources http://bibiserv.techfak.uni-bielefeld.de/sadr/ Tutorial Protein Structures (EXPASY) SwissModel http://swissmodel.expasy.org/course/course-index.htm CMBI Courses for protein structure http://swift.cmbi.ru.nl/teach/courses/index.html 2Can Support Portal - Bioinformatics educational resource http://www.ebi.ac.uk/2can Bioconductor Workshops http://www.bioconductor.org/workshops/ CBS Bioinformatics Courses http://www.cbs.dtu.dk/courses.php The European School In Bioinformatics (Biosapiens) http://www.biosapiens.info/page.php?page=esb Institutes Centers Networks Bioinformatics Institutes Germany WSI Wilhelm-Schickard-Institut für Informatik - Universitaet Tuebingen http://www.uni-tuebingen.de/en/faculties/faculty-of-science/departments/computer-science/department.html WSI Huson - Algorithms in Bioinformatics http://www-ab.informatik.uni-tuebingen.de/welcome.html WSI Prof. Zell - Computer Architecture http://www.ra.cs.uni-tuebingen.de/ WSI Kohlbacher - Div. for Simulation -
Robust Determination of the Chemical Potential in the Pole
Robust determination of the chemical potential in the pole expansion and selected inversion method for solving Kohn-Sham density functional theory Weile Jia, and Lin Lin Citation: The Journal of Chemical Physics 147, 144107 (2017); doi: 10.1063/1.5000255 View online: http://dx.doi.org/10.1063/1.5000255 View Table of Contents: http://aip.scitation.org/toc/jcp/147/14 Published by the American Institute of Physics THE JOURNAL OF CHEMICAL PHYSICS 147, 144107 (2017) Robust determination of the chemical potential in the pole expansion and selected inversion method for solving Kohn-Sham density functional theory Weile Jia1,a) and Lin Lin1,2,b) 1Department of Mathematics, University of California, Berkeley, California 94720, USA 2Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA (Received 14 August 2017; accepted 24 September 2017; published online 11 October 2017) Fermi operator expansion (FOE) methods are powerful alternatives to diagonalization type methods for solving Kohn-Sham density functional theory (KSDFT). One example is the pole expansion and selected inversion (PEXSI) method, which approximates the Fermi operator by rational matrix functions and reduces the computational complexity to at most quadratic scaling for solving KSDFT. Unlike diagonalization type methods, the chemical potential often cannot be directly read off from the result of a single step of evaluation of the Fermi operator. Hence multiple evaluations are needed to be sequentially performed to compute the chemical potential to ensure the correct number of electrons within a given tolerance. This hinders the performance of FOE methods in practice. In this paper, we develop an efficient and robust strategy to determine the chemical potential in the context of the PEXSI method. -
Multiscale Simulation of Laser Ablation and Processing of Semiconductor Materials
University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2012 Multiscale Simulation Of Laser Ablation And Processing Of Semiconductor Materials Lalit Shokeen University of Central Florida Part of the Materials Science and Engineering Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Doctoral Dissertation (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Shokeen, Lalit, "Multiscale Simulation Of Laser Ablation And Processing Of Semiconductor Materials" (2012). Electronic Theses and Dissertations, 2004-2019. 2420. https://stars.library.ucf.edu/etd/2420 MULTISCALE SIMULATION OF LASER PROCESSING AND ABLATION OF SEMICONDUCTOR MATERIALS by LALIT SHOKEEN Bachelor of Science (B.Sc. Physics), University of Delhi, India, 2006 Masters of Science (M.Sc. Physics), University of Delhi, India, 2008 Master of Science (M.S. Materials Engg.), University of Central Florida, USA, 2009 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Mechanical, Materials and Aerospace Engineering in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida, USA Fall Term 2012 Major Professor: Patrick Schelling © 2012 Lalit Shokeen ii ABSTRACT We present a model of laser-solid interactions in silicon based on an empirical potential developed under conditions of strong electronic excitations. The parameters of the interatomic potential depends on the temperature of the electronic subsystem Te, which is directly related to the density of the electron-hole pairs and hence the number of broken bonds. -
Open Babel Documentation Release 2.3.1
Open Babel Documentation Release 2.3.1 Geoffrey R Hutchison Chris Morley Craig James Chris Swain Hans De Winter Tim Vandermeersch Noel M O’Boyle (Ed.) December 05, 2011 Contents 1 Introduction 3 1.1 Goals of the Open Babel project ..................................... 3 1.2 Frequently Asked Questions ....................................... 4 1.3 Thanks .................................................. 7 2 Install Open Babel 9 2.1 Install a binary package ......................................... 9 2.2 Compiling Open Babel .......................................... 9 3 obabel and babel - Convert, Filter and Manipulate Chemical Data 17 3.1 Synopsis ................................................. 17 3.2 Options .................................................. 17 3.3 Examples ................................................. 19 3.4 Differences between babel and obabel .................................. 21 3.5 Format Options .............................................. 22 3.6 Append property values to the title .................................... 22 3.7 Filtering molecules from a multimolecule file .............................. 22 3.8 Substructure and similarity searching .................................. 25 3.9 Sorting molecules ............................................ 25 3.10 Remove duplicate molecules ....................................... 25 3.11 Aliases for chemical groups ....................................... 26 4 The Open Babel GUI 29 4.1 Basic operation .............................................. 29 4.2 Options ................................................. -
Open Data, Open Source, and Open Standards in Chemistry: the Blue Obelisk Five Years On" Journal of Cheminformatics Vol
Oral Roberts University Digital Showcase College of Science and Engineering Faculty College of Science and Engineering Research and Scholarship 10-14-2011 Open Data, Open Source, and Open Standards in Chemistry: The lueB Obelisk five years on Andrew Lang Noel M. O'Boyle Rajarshi Guha National Institutes of Health Egon Willighagen Maastricht University Samuel Adams See next page for additional authors Follow this and additional works at: http://digitalshowcase.oru.edu/cose_pub Part of the Chemistry Commons Recommended Citation Andrew Lang, Noel M O'Boyle, Rajarshi Guha, Egon Willighagen, et al.. "Open Data, Open Source, and Open Standards in Chemistry: The Blue Obelisk five years on" Journal of Cheminformatics Vol. 3 Iss. 37 (2011) Available at: http://works.bepress.com/andrew-sid-lang/ 19/ This Article is brought to you for free and open access by the College of Science and Engineering at Digital Showcase. It has been accepted for inclusion in College of Science and Engineering Faculty Research and Scholarship by an authorized administrator of Digital Showcase. For more information, please contact [email protected]. Authors Andrew Lang, Noel M. O'Boyle, Rajarshi Guha, Egon Willighagen, Samuel Adams, Jonathan Alvarsson, Jean- Claude Bradley, Igor Filippov, Robert M. Hanson, Marcus D. Hanwell, Geoffrey R. Hutchison, Craig A. James, Nina Jeliazkova, Karol M. Langner, David C. Lonie, Daniel M. Lowe, Jerome Pansanel, Dmitry Pavlov, Ola Spjuth, Christoph Steinbeck, Adam L. Tenderholt, Kevin J. Theisen, and Peter Murray-Rust This article is available at Digital Showcase: http://digitalshowcase.oru.edu/cose_pub/34 Oral Roberts University From the SelectedWorks of Andrew Lang October 14, 2011 Open Data, Open Source, and Open Standards in Chemistry: The Blue Obelisk five years on Andrew Lang Noel M O'Boyle Rajarshi Guha, National Institutes of Health Egon Willighagen, Maastricht University Samuel Adams, et al. -
Aqueous Pka Prediction for Tautomerizable Compounds Using Equilibrium Bond Lengths
ARTICLE https://doi.org/10.1038/s42004-020-0264-7 OPEN Aqueous pKa prediction for tautomerizable compounds using equilibrium bond lengths Beth A. Caine1,2, Maddalena Bronzato3, Torquil Fraser3, Nathan Kidley3, Christophe Dardonville 4 & ✉ Paul L.A. Popelier 1,2 1234567890():,; The accurate prediction of aqueous pKa values for tautomerizable compounds is a formidable task, even for the most established in silico tools. Empirical approaches often fall short due to a lack of pre-existing knowledge of dominant tautomeric forms. In a rigorous first-principles approach, calculations for low-energy tautomers must be performed in protonated and deprotonated forms, often both in gas and solvent phases, thus representing a significant computational task. Here we report an alternative approach, predicting pKa values for her- bicide/therapeutic derivatives of 1,3-cyclohexanedione and 1,3-cyclopentanedione to within just 0.24 units. A model, using a single ab initio bond length from one protonation state, is as accurate as other more complex regression approaches using more input features, and outperforms the program Marvin. Our approach can be used for other tautomerizable spe- cies, to predict trends across congeneric series and to correct experimental pKa values. 1 Department of Chemistry, University of Manchester, Manchester, UK. 2 Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester, UK. 3 Syngenta AG, Jealott’s Hill, Warfield, Bracknell RG42 6E7, UK. 4 Instituto de Química Médica, IQM–CSIC, C/Juan de la Cierva 3, Madrid 28006, Spain. ✉ email: [email protected] COMMUNICATIONS CHEMISTRY | (2020) 3:21 | https://doi.org/10.1038/s42004-020-0264-7 | www.nature.com/commschem 1 ARTICLE COMMUNICATIONS CHEMISTRY | https://doi.org/10.1038/s42004-020-0264-7 pproximately 21% of the compounds that make up (http://vcclab.org), Marvin (http://www.chemaxon.com) and pharmaceutical databases are said to exist in two or more Pallas (www.compudrug.com)) on 248 compounds of the Gold A 1 12 tautomeric forms . -
A Java-Based Platform for Evolutionary De Novo Molecular Design
Article MoleGear: A Java-Based Platform for Evolutionary De Novo Molecular Design Yunhan Chu and Xuezhong He * Department of Chemical Engineering, Norwegian University of Science and Technology, N-7491 Trondheim, Norway; [email protected] * Correspondence: [email protected]; Tel.: +47-73593942 Received: 25 March 2019; Accepted: 10 April 2019; Published: 11 April 2019 Abstract: A Java-based platform, MoleGear, is developed for de novo molecular design based on the chemistry development kit (CDK) and other Java packages. MoleGear uses evolutionary algorithm (EA) to explore chemical space, and a suite of fragment-based operators of growing, crossover, and mutation for assembling novel molecules that can be scored by prediction of binding free energy or a weighted-sum multi-objective fitness function. The EA can be conducted in parallel over multiple nodes to support large-scale molecular optimizations. Some complementary utilities such as fragment library design, chemical space analysis, and graphical user interface are also integrated into MoleGear. The candidate molecules as inhibitors for the human immunodeficiency virus 1 (HIV-1) protease were designed by MoleGear, which validates the potential capability for de novo molecular design. Keywords: de novo design; evolutionary algorithm; drug molecules; fitness; multi-objective function 1. Introduction Computational chemistry plays an important role in the design of new drug-like molecules [1– 5], catalysts [6–8], and novel solvents of ionic liquids [9–11]. De novo molecular design has been an active research area of drug design/discovery over the last decades, and many approaches such as LUDI [12], LEA3D [13], Flux [14,15], and pharmacophore-linked fragment virtual screening (PFVS) [16] have been developed by using protein and ligand structures. -
Structural Insight Into Pichia Pastoris Fatty Acid Synthase Joseph S
www.nature.com/scientificreports OPEN Structural insight into Pichia pastoris fatty acid synthase Joseph S. Snowden, Jehad Alzahrani, Lee Sherry, Martin Stacey, David J. Rowlands, Neil A. Ranson* & Nicola J. Stonehouse* Type I fatty acid synthases (FASs) are critical metabolic enzymes which are common targets for bioengineering in the production of biofuels and other products. Serendipitously, we identifed FAS as a contaminant in a cryoEM dataset of virus-like particles (VLPs) purifed from P. pastoris, an important model organism and common expression system used in protein production. From these data, we determined the structure of P. pastoris FAS to 3.1 Å resolution. While the overall organisation of the complex was typical of type I FASs, we identifed several diferences in both structural and enzymatic domains through comparison with the prototypical yeast FAS from S. cerevisiae. Using focussed classifcation, we were also able to resolve and model the mobile acyl-carrier protein (ACP) domain, which is key for function. Ultimately, the structure reported here will be a useful resource for further eforts to engineer yeast FAS for synthesis of alternate products. Fatty acid synthases (FASs) are critical metabolic enzymes for the endogenous biosynthesis of fatty acids in a diverse range of organisms. Trough iterative cycles of chain elongation, FASs catalyse the synthesis of long-chain fatty acids that can produce raw materials for membrane bilayer synthesis, lipid anchors of peripheral membrane proteins, metabolic energy stores, or precursors for various fatty acid-derived signalling compounds1. In addition to their key physiological importance, microbial FAS systems are also a common target of metabolic engineering approaches, usually with the aim of generating short chain fatty acids for an expanded repertoire of fatty acid- derived chemicals, including chemicals with key industrial signifcance such as α-olefns2–6. -
ORGANIZATION of BIOMOLECULES in a 3-DIMENSIONAL SPACE by Sameer Sajja a Thesis Submitted to the Faculty of the University Of
ORGANIZATION OF BIOMOLECULES IN A 3-DIMENSIONAL SPACE by Sameer Sajja A thesis submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Master of Science in Chemistry Charlotte 2019 Approved by: ________________________________ Dr. Kirill Afonin ________________________________ Dr. Caryn Striplin ________________________________ Dr. Joanna Krueger ________________________________ Dr. Yuri Nesmelov ii ©2019 Sameer Sajja ALL RIGHTS RESERVED iii ABSTRACT SAMEER SAJJA. Organization of Biomolecules in a 3-Dimensional Space (Under the direction of DR. KIRILL A. AFONIN) The human body operates using various stimuli-responsive mechanisms, dictating biological activity via reaction to external cues. Hydrogels are networked hydrophilic polymeric materials that offer the potential to recreate aqueous environments with controlled organization of biomolecules for research purposes and potential therapeutic use. The unique, programmable structure of hydrogels exhibit similar physicochemical properties to those of living tissues while also introducing component-mediated biocompatibility. The design of stimuli-responsive biocompatible hydrogels would further allow for controllable mechanical and functional properties tuned by changes in environmental factors. This study investigates individual biomolecular components needed to potentially engineer biocompatible and stimuli-responsive hydrogels. By utilizing programmable biomolecules such as nucleic acids (DNA and RNA) and proteins -
Delphi: a Comprehensive Suite for Delphi Software and Associated Resources Lin Li Clemson University
Clemson University TigerPrints Publications Physics and Astronomy 5-2012 DelPhi: A Comprehensive Suite for DelPhi Software and Associated Resources Lin Li Clemson University Chuan Li Clemson University Subhra Sarkar Clemson University Jie Zhang Clemson University Shawn Witham Clemson University See next page for additional authors Follow this and additional works at: https://tigerprints.clemson.edu/physastro_pubs Part of the Biological and Chemical Physics Commons Recommended Citation Please use publisher's recommended citation. This Article is brought to you for free and open access by the Physics and Astronomy at TigerPrints. It has been accepted for inclusion in Publications by an authorized administrator of TigerPrints. For more information, please contact [email protected]. Authors Lin Li, Chuan Li, Subhra Sarkar, Jie Zhang, Shawn Witham, Zhe Zhang, Lin Wang, Nicholas Smith, Marharyta Petukh, and Emil Alexov This article is available at TigerPrints: https://tigerprints.clemson.edu/physastro_pubs/421 Li et al. BMC Biophysics 2012, 5:9 http://www.biomedcentral.com/2046-1682/5/9 SOFTWARE Open Access DelPhi: a comprehensive suite for DelPhi software and associated resources Lin Li1, Chuan Li1, Subhra Sarkar1,2, Jie Zhang1,2, Shawn Witham1, Zhe Zhang1, Lin Wang1, Nicholas Smith1, Marharyta Petukh1 and Emil Alexov1* Abstract Background: Accurate modeling of electrostatic potential and corresponding energies becomes increasingly important for understanding properties of biological macromolecules and their complexes. However, this is not an easy task due to the irregular shape of biological entities and the presence of water and mobile ions. Results: Here we report a comprehensive suite for the well-known Poisson-Boltzmann solver, DelPhi, enriched with additional features to facilitate DelPhi usage. -
Implementation of Methods to Accurately Predict Transition Pathways and the Underlying Potential Energy Surface of Biomolecular Systems
IMPLEMENTATION OF METHODS TO ACCURATELY PREDICT TRANSITION PATHWAYS AND THE UNDERLYING POTENTIAL ENERGY SURFACE OF BIOMOLECULAR SYSTEMS By DELARAM GHOREISHI A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2019 c 2019 Delaram Ghoreishi I dedicate this dissertation to my mother, my brother, and my partner. For their endless love, support, and encouragement. ACKNOWLEDGMENTS I am thankful to my advisor, Adrian Roitberg, for his guidance during my graduate studies. I am grateful for the opportunities he provided me and for allowing me to work independently. I also thank my committee members, Rodney Bartlett, Xiaoguang Zhang, and Alberto Perez, for their valuable inputs. I am grateful to the University of Florida Informatics Institue for providing financial support in 2016, allowing me to take a break from teaching and focus more on research. I like to acknowledge my group members and friends for their moral support and technical assistance. Natali di Russo helped me become familiar with Amber. I thank Pilar Buteler, Sunidhi Lenka, and Vinicius Cruzeiro for daily conversations regarding science and life. Pancham Lal Gupta was my cpptraj encyclopedia. I thank my physicist colleagues, Ankita Sarkar and Dustin Tracy, who went through the intense physics coursework with me during the first year. I thank Farhad Ramezanghorbani, Justin Smith, Kavindri Ranasinghe, and Xiang Gao for helpful discussions regarding ANI and active learning. I also thank David Cerutti from Rutgers University for his help with NEB implementation. I thank Pilar Buteler and Alvaro Gonzalez for the good times we had camping and climbing.