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Rdock Reference Guide Rdock Development Team August 27, 2015 Contents
rDock Reference Guide rDock Development Team August 27, 2015 Contents 1 Preface 4 2 Acknowledgements 4 3 Introduction 4 4 Configuration 4 5 Cavity mapping 6 5.1 Two sphere method . 6 5.2 Reference ligand method . 8 6 Scoring function reference 11 6.1 Component Scoring Functions . 11 6.1.1 van der Waals potential . 11 6.1.2 Empirical attractive and repulsive polar potentials . 11 6.1.3 Solvation potential . 12 6.1.4 Dihedral potential . 13 6.2 Intermolecular scoring functions under evaluation . 13 6.2.1 Training sets . 13 6.2.2 Scoring Functions Design . 13 6.2.3 Scoring Functions Validation . 14 6.3 Code Implementation . 15 7 Docking protocol 17 7.1 Protocol Summary . 17 7.1.1 Pose Generation . 17 7.1.2 Genetic Algorithm . 17 7.1.3 Monte Carlo . 17 7.1.4 Simplex . 18 7.2 Code Implementation . 18 7.3 Standard rDock docking protocol (dock.prm) . 18 8 System definition file reference 22 8.1 Receptor definition . 22 8.2 Ligand definition . 23 8.3 Solvent definition . 24 8.4 Cavity mapping . 25 8.5 Cavity restraint . 27 8.6 Pharmacophore restraints . 27 8.7 NMR restraints . 28 8.8 Example system definition files . 28 9 Molecular files and atoms typing 30 9.1 Atomic properties. 30 9.2 Difference between formal charge and distributed formal charge . 30 9.3 Parsing a MOL2 file . 31 9.4 Parsing an SD file . 31 9.5 Assigning distributed formal charges to the receptor . 31 10 rDock file formats 32 10.1 .prm file format . -
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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 -
Pyplif HIPPOS-Assisted Prediction of Molecular Determinants of Ligand Binding to Receptors
molecules Article PyPLIF HIPPOS-Assisted Prediction of Molecular Determinants of Ligand Binding to Receptors Enade P. Istyastono 1,* , Nunung Yuniarti 2, Vivitri D. Prasasty 3 and Sudi Mungkasi 4 1 Faculty of Pharmacy, Sanata Dharma University, Yogyakarta 55282, Indonesia 2 Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia; [email protected] 3 Faculty of Biotechnology, Atma Jaya Catholic University of Indonesia, Jakarta 12930, Indonesia; [email protected] 4 Department of Mathematics, Faculty of Science and Technology, Sanata Dharma University, Yogyakarta 55282, Indonesia; [email protected] * Correspondence: [email protected]; Tel.: +62-274883037 Abstract: Identification of molecular determinants of receptor-ligand binding could significantly increase the quality of structure-based virtual screening protocols. In turn, drug design process, especially the fragment-based approaches, could benefit from the knowledge. Retrospective virtual screening campaigns by employing AutoDock Vina followed by protein-ligand interaction finger- printing (PLIF) identification by using recently published PyPLIF HIPPOS were the main techniques used here. The ligands and decoys datasets from the enhanced version of the database of useful de- coys (DUDE) targeting human G protein-coupled receptors (GPCRs) were employed in this research since the mutation data are available and could be used to retrospectively verify the prediction. The results show that the method presented in this article could pinpoint some retrospectively verified molecular determinants. The method is therefore suggested to be employed as a routine in drug Citation: Istyastono, E.P.; Yuniarti, design and discovery. N.; Prasasty, V.D.; Mungkasi, S. PyPLIF HIPPOS-Assisted Prediction Keywords: PyPLIF HIPPOS; AutoDock Vina; drug discovery; fragment-based; molecular determi- of Molecular Determinants of Ligand Binding to Receptors. -
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. -
A Study on Cheminformatics and Its Applications on Modern Drug Discovery
Available online at www.sciencedirect.com Procedia Engineering 38 ( 2012 ) 1264 – 1275 Internatio na l Conference on Modeling Optimisatio n and Computing (ICMOC 2012) A Study on Cheminformatics and its Applications on Modern Drug Discovery B.Firdaus Begama and Dr. J.Satheesh Kumarb aResearch Scholar, Bharathiar University, Coimbatore, India, [email protected] bAssistant Professor, Bharathiar University, Coimbatore, India, [email protected] Abstract Discovering drugs to a disease is still a challenging task for medical researchers due to the complex structures of biomolecules which are responsible for disease such as AIDS, Cancer, Autism, Alzimear etc. Design and development of new efficient anti-drugs for the disease without any side effects are becoming mandatory in the recent history of human life cycle due to changes in various factors which includes food habit, environmental and migration in human life style. Cheminformaticds deals with discovering drugs based in modern drug discovery techniques which in turn rectifies complex issues in traditional drug discovery system. Cheminformatics tools, helps medical chemist for better understanding of complex structures of chemical compounds. Cheminformatics is a new emerging interdisciplinary field which primarily aims to discover Novel Chemical Entities [NCE] which ultimately results in design of new molecule [chemical data]. It also plays an important role for collecting, storing and analysing the chemical data. This paper focuses on cheminformatics and its applications on drug discovery and modern drug discovery techniques which helps chemist and medical researchers for finding solution to the complex disease. © 2012 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Noorul Islam Centre for Higher Education. -
Molecular Structure Input on the Web Peter Ertl
Ertl Journal of Cheminformatics 2010, 2:1 http://www.jcheminf.com/content/2/1/1 REVIEW Open Access Molecular structure input on the web Peter Ertl Abstract A molecule editor, that is program for input and editing of molecules, is an indispensable part of every cheminfor- matics or molecular processing system. This review focuses on a special type of molecule editors, namely those that are used for molecule structure input on the web. Scientific computing is now moving more and more in the direction of web services and cloud computing, with servers scattered all around the Internet. Thus a web browser has become the universal scientific user interface, and a tool to edit molecules directly within the web browser is essential. The review covers a history of web-based structure input, starting with simple text entry boxes and early molecule editors based on clickable maps, before moving to the current situation dominated by Java applets. One typical example - the popular JME Molecule Editor - will be described in more detail. Modern Ajax server-side molecule editors are also presented. And finally, the possible future direction of web-based molecule editing, based on tech- nologies like JavaScript and Flash, is discussed. Introduction this trend and input of molecular structures directly A program for the input and editing of molecules is an within a web browser is therefore of utmost importance. indispensable part of every cheminformatics or molecu- In this overview a history of entering molecules into lar processing system. Such a program is known as a web applications will be covered, starting from simple molecule editor, molecular editor or structure sketcher. -
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. -
JRC QSAR Model Database
JRC QSAR Model Database EURL ECVAM DataBase service on ALternative Methods to animal experimentation To promote the development and uptake of alternative and advanced methods in toxicology and biomedical sciences SDF - STRUCTURE DATA FORMAT: How to create from SMILES The European Commission’s science and knowledge service Joint Research Centre Directorate F Health, Consumers & Reference Materials Chemicals Safety & Alternative Methods Unit The European Commission’s science and knowledge service Joint Research Centre EUR 28708 EN This publication is a Tutorial by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It aims to provide user support. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication. Contact information Email: [email protected] JRC Science Hub https://ec.europa.eu/jrc JRC107492 EUR 28708 EN PDF ISBN 978-92-79-71294-4 ISSN 1831-9424 doi:10.2760/952280 Print ISBN 978-92-79-71295-1 ISSN 1018-5593 doi:10.2760/668595 Luxembourg: Publications Office of the European Union, 2017 Ispra: European Commission, 2017 © European Union, 2017 The reuse of the document is authorised, provided the source is acknowledged and the original meaning or message of the texts are not distorted. The European Commission shall not be held liable for any consequences stemming from the reuse. How to cite this document: Triebe -
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. -
Evaluation of Protein-Ligand Docking Methods on Peptide-Ligand
bioRxiv preprint doi: https://doi.org/10.1101/212514; this version posted November 1, 2017. 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. Evaluation of protein-ligand docking methods on peptide-ligand complexes for docking small ligands to peptides Sandeep Singh1#, Hemant Kumar Srivastava1#, Gaurav Kishor1#, Harinder Singh1, Piyush Agrawal1 and G.P.S. Raghava1,2* 1CSIR-Institute of Microbial Technology, Sector 39A, Chandigarh, India. 2Indraprastha Institute of Information Technology, Okhla Phase III, Delhi India #Authors Contributed Equally Emails of Authors: SS: [email protected] HKS: [email protected] GK: [email protected] HS: [email protected] PA: [email protected] * Corresponding author Professor of Center for Computation Biology, Indraprastha Institute of Information Technology (IIIT Delhi), Okhla Phase III, New Delhi-110020, India Phone: +91-172-26907444 Fax: +91-172-26907410 E-mail: [email protected] Running Title: Benchmarking of docking methods 1 bioRxiv preprint doi: https://doi.org/10.1101/212514; this version posted November 1, 2017. 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 In the past, many benchmarking studies have been performed on protein-protein and protein-ligand docking however there is no study on peptide-ligand docking. -
The Norbornene Mystery Revealed
Supplementary Material (ESI) for Chemical Communications This journal is (c) The Royal Society of Chemistry 2010 Electronic Supporting Information The Norbornene Mystery Revealed Stephan N. Steinmann, Pierre Vogel, Yirong Mo, and Clémence Corminboeuf* To be published in Chemical Communication. The supplementary Data were prepared on June 22, 2010 and contains 14 pages. Contents: Method Section Figure S1: Molecules used for the comparisons between known experimental 1 Jcc-coupling constants (in Hertz) and the computed values. 1 Table S1 JCC-coupling comparison between experiment and computation. 1 Table S2: JCC-coupling constants for all compounds considered. Cartesian coordinates: B3LYP/6-311+G(d,p) (BLW and canonical) optimized structures for all compounds considered in the article. Contents: Computational Details 1 Table S1: JCC-coupling constants for all compounds considered. 1 Figure S1: Molecules for JCC-coupling comparison between experiment and computation. 1 Table S2: JCC-coupling comparison between experiment and computation. B3LYP/6-311+G(d,p) (BLW and canonical) optimized structures for all compounds considered in the article. Computational Details Standard geometries were optimized at the B3LYP1, 2/6-311+G** level using Gaussian 09.3 The BLW- constrained B3LYP/6-311+G** geometries (‘loc’) were optimized using a modified version of GAMESS-US (release 2008)4interfaced with the BLW-module.5, 6 Both the density and the J-coupling constants have been computed at the PBE7/IGLO-III level in Dalton 2.0.8 The BLW-eigenvalues and eigenvectors were optimized at the given DFT level with the SCF module of Dalton, SIRIUS, that has been interfaced with the BLW- module.