PubChem data extraction and integration using Instant JChem. Oleg Ursu Cristian Bologa Tudor I. Oprea Division of Biocomputing

Size: px
Start display at page:

Download "PubChem data extraction and integration using Instant JChem. Oleg Ursu Cristian Bologa Tudor I. Oprea Division of Biocomputing"

Transcription

1 PubChem data extraction and integration using Instant JChem Oleg Ursu Cristian Bologa Tudor I. Oprea Division of Biocomputing

2 PubChem - why not? Custom SQL queries Pipelining with custom in house or commercial tools Structure search not complete Integration with in house databases Speed of access/queries

3 PubChem structure search July 24, 2008 (and earlier)

4 DrugBank structure search tool July 24, 2008 (and earlier)

5 Integration with other databases Quickly identify HTS hits activity on other target(s)/assays Is there any relationship between my target and other targets in a cell based assay? Profile compounds activity on other than PubChem assay data WOMBAT records overlap with MLSMR ~9000 WOMBAT unique compounds overlap with MLSMR ~ 1700

6 Small Molecules Repository Large subset of PubChem libraries tested in multiple assays The same supplier, multiple centers including NMMLSC Need to pipeline/automate post HTS analysis for multiple targets Integration with WOMBAT in house database

7 Building IJC database Download the MLSMR library from PubChem Download assays data and description from PubChem FTP Extract and prepare data from assays files Design and create database tables, relationships and forms

8 Structures import PubChem limit for download 250,000 structures 2 download batches Clean up using ChemAxon Standardizer with the following configuration

9 Database creation Import WOMBAT RDF file Assign PUBCHEM_SUBSTANCE_ID to structures in WOMBAT present MLSMR library Import MLSMR library checking for duplicate structures already present in SUBSTANCES table Import PubChem assay data Import PubChem assay description data

10 PubChem structures import

11 Assays import CSV file assay test data XML file assay description data Shell script to process and extract assays data XMLStarlet Command Line XML Toolkit to query and extract assays description data ( Examples: $ xml sel -t -m //PC-AssayDescription -v PC-AssayDescription_name 761.descr.xml > HTS to identify specific small molecule inhibitors of Ras and Ras-related GTPases specifically Cdc42 wildtype $ xml sel -t -m //PC-AssayTargetInfo -v PC-AssayTargetInfo_name -n 761.descr.xml > cell division cycle 42 (GTP binding protein, 25kDa) [Homo sapiens]

12 Entity relationships Link ACTIVITY table Data with SUBSTANCES table on PUBCHEM_SUBSTANCE_ID Link WOMBAT.ACT.LIST/WOMBAT.MO L.KW with WOMBAT SUBSTANCES table on SMDL.ID

13 PubChem (MLSMR) view

14 Wombat view

15 Analyzing HTS hits Cluster HTS hits, SAR relationships Profile HTS hits on PubChem assays and WOMBAT targets Virtual screening of commercial libraries using ROCS, FP, and docking

16 Integration with other tools GUI is nice, doesn t play well with other tools jcsearch, jcman ChemAxon command line tools, doesn t allow for join select SQL statements Designed custom search application based on JChemSearch object and JChem API

17 Using JChemSearch object

18 Pipelining db search with other tools Select active compounds in GTPases screening assays SQL filter: select distinct cd_id from substances,activity where activity.pubchem_substance_id=substances.pubchem_substance_i d and activity.aid in (757,758,759,760,761,764) and activity.activity_outcome=2 Pipelining search results to MCES based clustering tool $ db_search s get_actives.sql t substances pubchem_substance_id pubchem_ext_datasource_regid mcs -i - -mt 0.4 -o gtp.actives.meas -- out-type m -s 0.3 Apply MESA Analytics grouping module to the result measures matrix $ Clustering gtp.actives.meas -T > cluster.28.out $ ClusterOutput cluster.28.out gtp.actives.smiles 2 T N > cluster.28.out.smiles Generate Omega conformations needed for ROCS screening $ db_search s get_actives.sql t substances pubchem_substance_id omega2 in - -out gtp.actives.confs.oeb.gz maxconfs 100

19 Selected Cluster

20 Similar compounds in MLSMR - Active in other assays

21

22 WOMBAT compounds

23 BIRT reporting framework Use the list of SIDs to create a report on PubChem assays profiling

24 Cluster compounds profile in PubChem and WOMBAT Active in GTPases assays Active in other PubChem assays # of compounds Tested Active Target(s) name Rac1 protein GTP-binding protein (rab7) ras protein Ras-related protein Rab-2A. cell division cycle 42 (GTP binding protein, 25kDa) Rac1 protein qhts Assay for Disrupters of an Hsp90 Co-Chaperone Interaction Catalytic epsilon subunit of the translation initiation factor eif2b, the guaninenucleotide exchange factor for eif2; activity& cytochrome P450, family 2, subfamily C, polypeptide 9 cytochrome P450, family 2, subfamily C, polypeptide 19 thyroid stimulating hormone receptor WOMBAT DP; prostaglandin D2 receptor EP1; prostaglandin E2 receptor, EP1 subtype EP2; prostaglandin E2 receptor, EP2 subtype EP3; prostaglandin E2 receptor, EP3 subtype EP4; prostaglandin E2 receptor, EP4 subtype cpla2; cytosolic phospholipase A2; phospholipase A2 group IVA Total

25 ROCS screening Plate1A02_000A-0214 Rac_act RawMCF Log Compound Conc [M] BOTTOM TOP LOGEC50 HILLSLOPE EC50 Rac_act e-007 ROCS hit from ChemDiv library, dose response EC 50 =0.102 μm

26 Future plans Automatic synchronization with PubChem Integration with other databases: DrugBank, Protein Ligand Databases, EMBL-EBI, in house assay data, etc.

27 Acknowledgments ChemAxon OpenEye Eclipse project Division of Biocomputing at UNM

28 Division of Biocomputing at UNM Tudor Oprea Cristian Bologa Steve Mathias Jerome Abear Andrei Leitao Ramona Curpan Liliana Halip Jeremy Yang Niranjan Kumar Oleg Ursu

RoadRunner A publicly available bioactivity database

RoadRunner A publicly available bioactivity database RoadRunner A publicly available bioactivity database Steve Mathias, Jeremy Yang, Cristian Bologa, Tudor Oprea UNM Biocomputing Cheminformatics: From Teaching to Research (A. Varnek, A. Tropsha), CINF 27

More information

Integrated Cheminformatics to Guide Drug Discovery

Integrated Cheminformatics to Guide Drug Discovery Integrated Cheminformatics to Guide Drug Discovery Matthew Segall, Ed Champness, Peter Hunt, Tamsin Mansley CINF Drug Discovery Cheminformatics Approaches August 23 rd 2017 Optibrium, StarDrop, Auto-Modeller,

More information

Cross Discipline Analysis made possible with Data Pipelining. J.R. Tozer SciTegic

Cross Discipline Analysis made possible with Data Pipelining. J.R. Tozer SciTegic Cross Discipline Analysis made possible with Data Pipelining J.R. Tozer SciTegic System Genesis Pipelining tool created to automate data processing in cheminformatics Modular system built with generic

More information

Ákos Tarcsay CHEMAXON SOLUTIONS

Ákos Tarcsay CHEMAXON SOLUTIONS Ákos Tarcsay CHEMAXON SOLUTIONS FINDING NOVEL COMPOUNDS WITH IMPROVED OVERALL PROPERTY PROFILES Two faces of one world Structure Footprint Linked Data Reactions Analytical Batch Phys-Chem Assay Project

More information

Pipeline Pilot Integration

Pipeline Pilot Integration Pipeline Pilot Integration Szilard Dorant Solutions for Cheminformatics The Component Collection: Quick facts Provides access to ChemAxon tools from Pipeline Pilot Developed and Supported by ChemAxon Free

More information

Pipeline Pilot Integration

Pipeline Pilot Integration Scientific & technical Presentation Pipeline Pilot Integration Szilárd Dóránt July 2009 The Component Collection: Quick facts Provides access to ChemAxon tools from Pipeline Pilot Free of charge Open source

More information

The PhilOEsophy. There are only two fundamental molecular descriptors

The PhilOEsophy. There are only two fundamental molecular descriptors The PhilOEsophy There are only two fundamental molecular descriptors Where can we use shape? Virtual screening More effective than 2D Lead-hopping Shape analogues are not graph analogues Molecular alignment

More information

Using AutoDock for Virtual Screening

Using AutoDock for Virtual Screening Using AutoDock for Virtual Screening CUHK Croucher ASI Workshop 2011 Stefano Forli, PhD Prof. Arthur J. Olson, Ph.D Molecular Graphics Lab Screening and Virtual Screening The ultimate tool for identifying

More information

DRUG DISCOVERY TODAY ELN ELN. Chemistry. Biology. Known ligands. DBs. Generate chemistry ideas. Check chemical feasibility In-house.

DRUG DISCOVERY TODAY ELN ELN. Chemistry. Biology. Known ligands. DBs. Generate chemistry ideas. Check chemical feasibility In-house. DRUG DISCOVERY TODAY Known ligands Chemistry ELN DBs Knowledge survey Therapeutic target Generate chemistry ideas Check chemical feasibility In-house Analyze SAR Synthesize or buy Report Test Journals

More information

Computational chemical biology to address non-traditional drug targets. John Karanicolas

Computational chemical biology to address non-traditional drug targets. John Karanicolas Computational chemical biology to address non-traditional drug targets John Karanicolas Our computational toolbox Structure-based approaches Ligand-based approaches Detailed MD simulations 2D fingerprints

More information

Expanding the scope of literature data with document to structure tools PatentInformatics applications at Aptuit

Expanding the scope of literature data with document to structure tools PatentInformatics applications at Aptuit Expanding the scope of literature data with document to structure tools PatentInformatics applications at Aptuit Alfonso Pozzan Computational and Analytical Chemistry Drug Design and Discovery Department

More information

Virtual Libraries and Virtual Screening in Drug Discovery Processes using KNIME

Virtual Libraries and Virtual Screening in Drug Discovery Processes using KNIME Virtual Libraries and Virtual Screening in Drug Discovery Processes using KNIME Iván Solt Solutions for Cheminformatics Drug Discovery Strategies for known targets High-Throughput Screening (HTS) Cells

More information

Farewell, PipelinePilot Migrating the Exquiron cheminformatics platform to KNIME and the ChemAxon technology

Farewell, PipelinePilot Migrating the Exquiron cheminformatics platform to KNIME and the ChemAxon technology Farewell, PipelinePilot Migrating the Exquiron cheminformatics platform to KNIME and the ChemAxon technology Serge P. Parel, PhD ChemAxon User Group Meeting, Budapest 21 st May, 2014 Outline Exquiron Who

More information

Ligand Scout Tutorials

Ligand Scout Tutorials Ligand Scout Tutorials Step : Creating a pharmacophore from a protein-ligand complex. Type ke6 in the upper right area of the screen and press the button Download *+. The protein will be downloaded and

More information

The Schrödinger KNIME extensions

The Schrödinger KNIME extensions The Schrödinger KNIME extensions Computational Chemistry and Cheminformatics in a workflow environment Jean-Christophe Mozziconacci Volker Eyrich KNIME UGM, Zurich, February 2014 The Schrödinger extensions

More information

Reaxys Medicinal Chemistry Fact Sheet

Reaxys Medicinal Chemistry Fact Sheet R&D SOLUTIONS FOR PHARMA & LIFE SCIENCES Reaxys Medicinal Chemistry Fact Sheet Essential data for lead identification and optimization Reaxys Medicinal Chemistry empowers early discovery in drug development

More information

Contents 1 Open-Source Tools, Techniques, and Data in Chemoinformatics

Contents 1 Open-Source Tools, Techniques, and Data in Chemoinformatics Contents 1 Open-Source Tools, Techniques, and Data in Chemoinformatics... 1 1.1 Chemoinformatics... 2 1.1.1 Open-Source Tools... 2 1.1.2 Introduction to Programming Languages... 3 1.2 Chemical Structure

More information

Early Stages of Drug Discovery in the Pharmaceutical Industry

Early Stages of Drug Discovery in the Pharmaceutical Industry Early Stages of Drug Discovery in the Pharmaceutical Industry Daniel Seeliger / Jan Kriegl, Discovery Research, Boehringer Ingelheim September 29, 2016 Historical Drug Discovery From Accidential Discovery

More information

The Schrödinger KNIME extensions

The Schrödinger KNIME extensions The Schrödinger KNIME extensions Computational Chemistry and Cheminformatics in a workflow environment Jean-Christophe Mozziconacci Volker Eyrich Topics What are the Schrödinger extensions? Workflow application

More information

Practical QSAR and Library Design: Advanced tools for research teams

Practical QSAR and Library Design: Advanced tools for research teams DS QSAR and Library Design Webinar Practical QSAR and Library Design: Advanced tools for research teams Reservationless-Plus Dial-In Number (US): (866) 519-8942 Reservationless-Plus International Dial-In

More information

Command-line tools of ChemAxon: tips and tricks

Command-line tools of ChemAxon: tips and tricks Command-line tools of ChemAxon: tips and tricks György Pirok Solutions for Cheminformatics Command-line interface A command-line interface (CLI) is a mechanism for interacting with a computer operating

More information

est Drive K20 GPUs! Experience The Acceleration Run Computational Chemistry Codes on Tesla K20 GPU today

est Drive K20 GPUs! Experience The Acceleration Run Computational Chemistry Codes on Tesla K20 GPU today est Drive K20 GPUs! Experience The Acceleration Run Computational Chemistry Codes on Tesla K20 GPU today Sign up for FREE GPU Test Drive on remotely hosted clusters www.nvidia.com/gputestd rive Shape Searching

More information

TRAINING REAXYS MEDICINAL CHEMISTRY

TRAINING REAXYS MEDICINAL CHEMISTRY TRAINING REAXYS MEDICINAL CHEMISTRY 1 SITUATION: DRUG DISCOVERY Knowledge survey Therapeutic target Known ligands Generate chemistry ideas Chemistry Check chemical feasibility ELN DBs In-house Analyze

More information

The Schrödinger KNIME extensions

The Schrödinger KNIME extensions The Schrödinger KNIME extensions Computational Chemistry and Cheminformatics in a workflow environment Jean-Christophe Mozziconacci Volker Eyrich KNIME UGM, Berlin, February 2015 The Schrödinger Extensions

More information

Receptor Based Drug Design (1)

Receptor Based Drug Design (1) Induced Fit Model For more than 100 years, the behaviour of enzymes had been explained by the "lock-and-key" mechanism developed by pioneering German chemist Emil Fischer. Fischer thought that the chemicals

More information

FROM MOLECULAR FORMULAS TO MARKUSH STRUCTURES

FROM MOLECULAR FORMULAS TO MARKUSH STRUCTURES FROM MOLECULAR FORMULAS TO MARKUSH STRUCTURES DIFFERENT LEVELS OF KNOWLEDGE REPRESENTATION IN CHEMISTRY Michael Braden, PhD ACS / San Diego/ 2016 Overview ChemAxon Who are we? Examples/use cases: Create

More information

LIBRARY DESIGN FOR COLLABORATIVE DRUG DISCOVERY: EXPANDING DRUGGABLE CHEMOGENOMIC SPACE

LIBRARY DESIGN FOR COLLABORATIVE DRUG DISCOVERY: EXPANDING DRUGGABLE CHEMOGENOMIC SPACE 5 th /June/2018@British Embassy in Tokyo LIBRARY DESIGN FOR COLLABORATIVE DRUG DISCOVERY: EXPANDING DRUGGABLE CHEMOGENOMIC SPACE Kazuyoshi Ikeda, Ph.D. Keio University SELF-INTRODUCTION Keio University,

More information

Biologically Relevant Molecular Comparisons. Mark Mackey

Biologically Relevant Molecular Comparisons. Mark Mackey Biologically Relevant Molecular Comparisons Mark Mackey Agenda > Cresset Technology > Cresset Products > FieldStere > FieldScreen > FieldAlign > FieldTemplater > Cresset and Knime About Cresset > Specialist

More information

Chemical Data Retrieval and Management

Chemical Data Retrieval and Management Chemical Data Retrieval and Management ChEMBL, ChEBI, and the Chemistry Development Kit Stephan A. Beisken What is EMBL-EBI? Part of the European Molecular Biology Laboratory International, non-profit

More information

Introduction. OntoChem

Introduction. OntoChem Introduction ntochem Providing drug discovery knowledge & small molecules... Supporting the task of medicinal chemistry Allows selecting best possible small molecule starting point From target to leads

More information

In Silico Investigation of Off-Target Effects

In Silico Investigation of Off-Target Effects PHARMA & LIFE SCIENCES WHITEPAPER In Silico Investigation of Off-Target Effects STREAMLINING IN SILICO PROFILING In silico techniques require exhaustive data and sophisticated, well-structured informatics

More information

Improving structural similarity based virtual screening using background knowledge

Improving structural similarity based virtual screening using background knowledge Girschick et al. Journal of Cheminformatics 2013, 5:50 RESEARCH ARTICLE Open Access Improving structural similarity based virtual screening using background knowledge Tobias Girschick 1, Lucia Puchbauer

More information

Marvin. Sketching, viewing and predicting properties with Marvin - features, tips and tricks. Gyorgy Pirok. Solutions for Cheminformatics

Marvin. Sketching, viewing and predicting properties with Marvin - features, tips and tricks. Gyorgy Pirok. Solutions for Cheminformatics Marvin Sketching, viewing and predicting properties with Marvin - features, tips and tricks Gyorgy Pirok Solutions for Cheminformatics The Marvin family The Marvin toolkit provides web-enabled components

More information

Drug Informatics for Chemical Genomics...

Drug Informatics for Chemical Genomics... Drug Informatics for Chemical Genomics... An Overview First Annual ChemGen IGERT Retreat Sept 2005 Drug Informatics for Chemical Genomics... p. Topics ChemGen Informatics The ChemMine Project Library Comparison

More information

CSD. CSD-Enterprise. Access the CSD and ALL CCDC application software

CSD. CSD-Enterprise. Access the CSD and ALL CCDC application software CSD CSD-Enterprise Access the CSD and ALL CCDC application software CSD-Enterprise brings it all: access to the Cambridge Structural Database (CSD), the world s comprehensive and up-to-date database of

More information

How IJC is Adding Value to a Molecular Design Business

How IJC is Adding Value to a Molecular Design Business How IJC is Adding Value to a Molecular Design Business James Mills Sexis LLP ChemAxon TechTalk Stevenage, ov 2012 james.mills@sexis.co.uk Overview Introduction to Sexis Sexis IJC use cases Data visualisation

More information

The Conformation Search Problem

The Conformation Search Problem Jon Sutter Senior Manager Life Sciences R&D jms@accelrys.com Jiabo Li Senior Scientist Life Sciences R&D jli@accelrys.com CAESAR: Conformer Algorithm based on Energy Screening and Recursive Buildup The

More information

Hit Finding and Optimization Using BLAZE & FORGE

Hit Finding and Optimization Using BLAZE & FORGE Hit Finding and Optimization Using BLAZE & FORGE Kevin Cusack,* Maria Argiriadi, Eric Breinlinger, Jeremy Edmunds, Michael Hoemann, Michael Friedman, Sami Osman, Raymond Huntley, Thomas Vargo AbbVie, Immunology

More information

Merck Virtual Library (MVL): Deployment, Application, and Future Enhancement

Merck Virtual Library (MVL): Deployment, Application, and Future Enhancement Merck Virtual Library (MVL): Deployment, Application, and Future Enhancement Zhengwei Peng Informatics, Discovery Chemistry, Merck & Co., Inc., Kenilworth, NJ, USA, and ChemAxon UGM, Boston, MA, USA Contents

More information

Introducing a Bioinformatics Similarity Search Solution

Introducing a Bioinformatics Similarity Search Solution Introducing a Bioinformatics Similarity Search Solution 1 Page About the APU 3 The APU as a Driver of Similarity Search 3 Similarity Search in Bioinformatics 3 POC: GSI Joins Forces with the Weizmann Institute

More information

GCC E x h i b i t i o n N e w s l e t t e r. 8 th GERMAN CONFERENCE ON CHEMOINFORMATICS TOPICS

GCC E x h i b i t i o n N e w s l e t t e r. 8 th GERMAN CONFERENCE ON CHEMOINFORMATICS TOPICS TOPICS GCC 2012 8 th GERMAN CONFERENCE ON CHEMOINFORMATICS E x h i b i t i o n N e w s l e t t e r List of Exhibitors Pre-Conference Workshops Free Software Session Room Plans Exhibitor One-Pagers www.gdch.de/gcc2012

More information

Dr. Sander B. Nabuurs. Computational Drug Discovery group Center for Molecular and Biomolecular Informatics Radboud University Medical Centre

Dr. Sander B. Nabuurs. Computational Drug Discovery group Center for Molecular and Biomolecular Informatics Radboud University Medical Centre Dr. Sander B. Nabuurs Computational Drug Discovery group Center for Molecular and Biomolecular Informatics Radboud University Medical Centre The road to new drugs. How to find new hits? High Throughput

More information

Implementation of novel tools to facilitate fragment-based drug discovery by NMR:

Implementation of novel tools to facilitate fragment-based drug discovery by NMR: Implementation of novel tools to facilitate fragment-based drug discovery by NMR: Automated analysis of large sets of ligand-observed NMR binding data and 19 F methods Andreas Lingel Global Discovery Chemistry

More information

COMPARISON OF SIMILARITY METHOD TO IMPROVE RETRIEVAL PERFORMANCE FOR CHEMICAL DATA

COMPARISON OF SIMILARITY METHOD TO IMPROVE RETRIEVAL PERFORMANCE FOR CHEMICAL DATA http://www.ftsm.ukm.my/apjitm Asia-Pacific Journal of Information Technology and Multimedia Jurnal Teknologi Maklumat dan Multimedia Asia-Pasifik Vol. 7 No. 1, June 2018: 91-98 e-issn: 2289-2192 COMPARISON

More information

FRAGMENT SCREENING IN LEAD DISCOVERY BY WEAK AFFINITY CHROMATOGRAPHY (WAC )

FRAGMENT SCREENING IN LEAD DISCOVERY BY WEAK AFFINITY CHROMATOGRAPHY (WAC ) FRAGMENT SCREENING IN LEAD DISCOVERY BY WEAK AFFINITY CHROMATOGRAPHY (WAC ) SARomics Biostructures AB & Red Glead Discovery AB Medicon Village, Lund, Sweden Fragment-based lead discovery The basic idea:

More information

How Diverse Are Diversity Assessment Methods? A Comparative Analysis and Benchmarking of Molecular Descriptor Space

How Diverse Are Diversity Assessment Methods? A Comparative Analysis and Benchmarking of Molecular Descriptor Space pubs.acs.org/jcim How Diverse Are Diversity Assessment Methods? A Comparative Analysis and Benchmarking of Molecular Descriptor Space Alexios Koutsoukas,, Shardul Paricharak,,, Warren R. J. D. Galloway,

More information

Different conformations of the drugs within the virtual library of FDA approved drugs will be generated.

Different conformations of the drugs within the virtual library of FDA approved drugs will be generated. Chapter 3 Molecular Modeling 3.1. Introduction In this study pharmacophore models will be created to screen a virtual library of FDA approved drugs for compounds that may inhibit MA-A and MA-B. The virtual

More information

BLAST Database Searching. BME 110: CompBio Tools Todd Lowe April 8, 2010

BLAST Database Searching. BME 110: CompBio Tools Todd Lowe April 8, 2010 BLAST Database Searching BME 110: CompBio Tools Todd Lowe April 8, 2010 Admin Reading: Read chapter 7, and the NCBI Blast Guide and tutorial http://www.ncbi.nlm.nih.gov/blast/why.shtml Read Chapter 8 for

More information

Using the File Geodatabase API. Lance Shipman David Sousa

Using the File Geodatabase API. Lance Shipman David Sousa Using the File Geodatabase API Lance Shipman David Sousa Overview File Geodatabase API - Introduction - Supported Tasks - API Overview - What s not supported - Updates - Demo File Geodatabase API Provide

More information

bcl::cheminfo Suite Enables Machine Learning-Based Drug Discovery Using GPUs Edward W. Lowe, Jr. Nils Woetzel May 17, 2012

bcl::cheminfo Suite Enables Machine Learning-Based Drug Discovery Using GPUs Edward W. Lowe, Jr. Nils Woetzel May 17, 2012 bcl::cheminfo Suite Enables Machine Learning-Based Drug Discovery Using GPUs Edward W. Lowe, Jr. Nils Woetzel May 17, 2012 Outline Machine Learning Cheminformatics Framework QSPR logp QSAR mglur 5 CYP

More information

Docking. GBCB 5874: Problem Solving in GBCB

Docking. GBCB 5874: Problem Solving in GBCB Docking Benzamidine Docking to Trypsin Relationship to Drug Design Ligand-based design QSAR Pharmacophore modeling Can be done without 3-D structure of protein Receptor/Structure-based design Molecular

More information

Next Generation Computational Chemistry Tools to Predict Toxicity of CWAs

Next Generation Computational Chemistry Tools to Predict Toxicity of CWAs Next Generation Computational Chemistry Tools to Predict Toxicity of CWAs William (Bill) Welsh welshwj@umdnj.edu Prospective Funding by DTRA/JSTO-CBD CBIS Conference 1 A State-wide, Regional and National

More information

Virtual Screening: How Are We Doing?

Virtual Screening: How Are We Doing? Virtual Screening: How Are We Doing? Mark E. Snow, James Dunbar, Lakshmi Narasimhan, Jack A. Bikker, Dan Ortwine, Christopher Whitehead, Yiannis Kaznessis, Dave Moreland, Christine Humblet Pfizer Global

More information

Patent Searching using Bayesian Statistics

Patent Searching using Bayesian Statistics Patent Searching using Bayesian Statistics Willem van Hoorn, Exscientia Ltd Biovia European Forum, London, June 2017 Contents Who are we? Searching molecules in patents What can Pipeline Pilot do for you?

More information

BLAST. Varieties of BLAST

BLAST. Varieties of BLAST BLAST Basic Local Alignment Search Tool (1990) Altschul, Gish, Miller, Myers, & Lipman Uses short-cuts or heuristics to improve search speed Like speed-reading, does not examine every nucleotide of database

More information

Searching Substances in Reaxys

Searching Substances in Reaxys Searching Substances in Reaxys Learning Objectives Understand that substances in Reaxys have different sources (e.g., Reaxys, PubChem) and can be found in Document, Reaction and Substance Records Recognize

More information

Introduction to Chemoinformatics and Drug Discovery

Introduction to Chemoinformatics and Drug Discovery Introduction to Chemoinformatics and Drug Discovery Irene Kouskoumvekaki Associate Professor February 15 th, 2013 The Chemical Space There are atoms and space. Everything else is opinion. Democritus (ca.

More information

Differential Scanning Fluorimetry: Detection of ligands and conditions that promote protein stability and crystallization

Differential Scanning Fluorimetry: Detection of ligands and conditions that promote protein stability and crystallization Differential Scanning Fluorimetry: Detection of ligands and conditions that promote protein stability and crystallization Frank Niesen PX school 2008, Como, Italy Method introduction Topics Applications

More information

Retrieving hits through in silico screening and expert assessment M. N. Drwal a,b and R. Griffith a

Retrieving hits through in silico screening and expert assessment M. N. Drwal a,b and R. Griffith a Retrieving hits through in silico screening and expert assessment M.. Drwal a,b and R. Griffith a a: School of Medical Sciences/Pharmacology, USW, Sydney, Australia b: Charité Berlin, Germany Abstract:

More information

has its own advantages and drawbacks, depending on the questions facing the drug discovery.

has its own advantages and drawbacks, depending on the questions facing the drug discovery. 2013 First International Conference on Artificial Intelligence, Modelling & Simulation Comparison of Similarity Coefficients for Chemical Database Retrieval Mukhsin Syuib School of Information Technology

More information

MM-PBSA Validation Study. Trent E. Balius Department of Applied Mathematics and Statistics AMS

MM-PBSA Validation Study. Trent E. Balius Department of Applied Mathematics and Statistics AMS MM-PBSA Validation Study Trent. Balius Department of Applied Mathematics and Statistics AMS 535 11-26-2008 Overview MM-PBSA Introduction MD ensembles one snap-shots relaxed structures nrichment Computational

More information

Medicinal Chemistry/ CHEM 458/658 Chapter 8- Receptors and Messengers

Medicinal Chemistry/ CHEM 458/658 Chapter 8- Receptors and Messengers Medicinal Chemistry/ CHEM 458/658 Chapter 8- Receptors and Messengers Bela Torok Department of Chemistry University of Massachusetts Boston Boston, MA 1 Introduction Receptor specific areas of proteins

More information

Building innovative drug discovery alliances. Just in KNIME: Successful Process Driven Drug Discovery

Building innovative drug discovery alliances. Just in KNIME: Successful Process Driven Drug Discovery Building innovative drug discovery alliances Just in KIME: Successful Process Driven Drug Discovery Berlin KIME Spring Summit, Feb 2016 Research Informatics @ Evotec Evotec s worldwide operations 2 Pharmaceuticals

More information

Structure-Based Drug Discovery An Overview

Structure-Based Drug Discovery An Overview Structure-Based Drug Discovery An Overview Edited by Roderick E. Hubbard University of York, Heslington, York, UK and Vernalis (R&D) Ltd, Abington, Cambridge, UK RSC Publishing Contents Chapter 1 3D Structure

More information

Scale in the biological world

Scale in the biological world Scale in the biological world 2 A cell seen by TEM 3 4 From living cells to atoms 5 Compartmentalisation in the cell: internal membranes and the cytosol 6 The Origin of mitochondria: The endosymbion hypothesis

More information

Regulation and signaling. Overview. Control of gene expression. Cells need to regulate the amounts of different proteins they express, depending on

Regulation and signaling. Overview. Control of gene expression. Cells need to regulate the amounts of different proteins they express, depending on Regulation and signaling Overview Cells need to regulate the amounts of different proteins they express, depending on cell development (skin vs liver cell) cell stage environmental conditions (food, temperature,

More information

Fast similarity searching making the virtual real. Stephen Pickett, GSK

Fast similarity searching making the virtual real. Stephen Pickett, GSK Fast similarity searching making the virtual real Stephen Pickett, GSK Introduction Introduction to similarity searching Use cases Why is speed so crucial? Why MadFast? Some performance stats Implementation

More information

The Rockefeller University Compound Library

The Rockefeller University Compound Library The Rockefeller University Compound Library J. Fraser Glickman Rockefeller University High Throughput and Spectroscopy Resource Center April 4 th, 2014 Technologies Resources Available Microplate assay

More information

Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining

Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining Samer Haidar 1, Zouhair Bouaziz 2, Christelle Marminon 2, Tiomo Laitinen 3, Anti Poso

More information

Using Self-Organizing maps to accelerate similarity search

Using Self-Organizing maps to accelerate similarity search YOU LOGO Using Self-Organizing maps to accelerate similarity search Fanny Bonachera, Gilles Marcou, Natalia Kireeva, Alexandre Varnek, Dragos Horvath Laboratoire d Infochimie, UM 7177. 1, rue Blaise Pascal,

More information

Richik N. Ghosh, Linnette Grove, and Oleg Lapets ASSAY and Drug Development Technologies 2004, 2:

Richik N. Ghosh, Linnette Grove, and Oleg Lapets ASSAY and Drug Development Technologies 2004, 2: 1 3/1/2005 A Quantitative Cell-Based High-Content Screening Assay for the Epidermal Growth Factor Receptor-Specific Activation of Mitogen-Activated Protein Kinase Richik N. Ghosh, Linnette Grove, and Oleg

More information

13-3. Synthesis-Secretory pathway: Sort lumenal proteins, Secrete proteins, Sort membrane proteins

13-3. Synthesis-Secretory pathway: Sort lumenal proteins, Secrete proteins, Sort membrane proteins 13-3. Synthesis-Secretory pathway: Sort lumenal proteins, Secrete proteins, Sort membrane proteins Molecular sorting: specific budding, vesicular transport, fusion 1. Why is this important? A. Form and

More information

Large Scale Evaluation of Chemical Structure Recognition 4 th Text Mining Symposium in Life Sciences October 10, Dr.

Large Scale Evaluation of Chemical Structure Recognition 4 th Text Mining Symposium in Life Sciences October 10, Dr. Large Scale Evaluation of Chemical Structure Recognition 4 th Text Mining Symposium in Life Sciences October 10, 2006 Dr. Overview Brief introduction Chemical Structure Recognition (chemocr) Manual conversion

More information

SABIO-RK Integration and Curation of Reaction Kinetics Data Ulrike Wittig

SABIO-RK Integration and Curation of Reaction Kinetics Data  Ulrike Wittig SABIO-RK Integration and Curation of Reaction Kinetics Data http://sabio.villa-bosch.de/sabiork Ulrike Wittig Overview Introduction /Motivation Database content /User interface Data integration Curation

More information

Aalto University 2) University of Oxford

Aalto University 2) University of Oxford RFID-Based Logistics Monitoring with Semantics-Driven Event Processing Mikko Rinne 1), Monika Solanki 2) and Esko Nuutila 1) 23rd of June 2016 DEBS 2016 1) Aalto University 2) University of Oxford Scenario:

More information

Chemogenomic: Approaches to Rational Drug Design. Jonas Skjødt Møller

Chemogenomic: Approaches to Rational Drug Design. Jonas Skjødt Møller Chemogenomic: Approaches to Rational Drug Design Jonas Skjødt Møller Chemogenomic Chemistry Biology Chemical biology Medical chemistry Chemical genetics Chemoinformatics Bioinformatics Chemoproteomics

More information

Karsten Vennemann, Seattle. QGIS Workshop CUGOS Spring Fling 2015

Karsten Vennemann, Seattle. QGIS Workshop CUGOS Spring Fling 2015 Karsten Vennemann, Seattle 2015 a very capable and flexible Desktop GIS QGIS QGIS Karsten Workshop Vennemann, Seattle slide 2 of 13 QGIS - Desktop GIS originally a GIS viewing environment QGIS for the

More information

Part 6. 3D Pharmacophore Modeling

Part 6. 3D Pharmacophore Modeling 279 Part 6 3D Pharmacophore Modeling 281 20 3D Pharmacophore Modeling Techniques in Computer Aided Molecular Design Using LigandScout Thomas Seidel, Sharon D. Bryant, Gökhan Ibis, Giulio Poli, and Thierry

More information

Supplementary Material

Supplementary Material upplementary Material Molecular docking and ligand specificity in fragmentbased inhibitor discovery Chen & hoichet 26 27 (a) 2 1 2 3 4 5 6 7 8 9 10 11 12 15 16 13 14 17 18 19 (b) (c) igure 1 Inhibitors

More information

Roadblocks in HTS Assay Development

Roadblocks in HTS Assay Development Roadblocks in HTS Assay Development Average HTS biochemical assay development time = 4.1 months One off assay development is typically required for each enzyme class Novel or complex targets can be difficult

More information

QSAR Modeling of ErbB1 Inhibitors Using Genetic Algorithm-Based Regression

QSAR Modeling of ErbB1 Inhibitors Using Genetic Algorithm-Based Regression APPLICATION NOTE QSAR Modeling of ErbB1 Inhibitors Using Genetic Algorithm-Based Regression GAINING EFFICIENCY IN QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS ErbB1 kinase is the cell-surface receptor

More information

Interrogation of small GTPase Activity. Screening GAPs and GEFs with the PHERAstar FSX from BMG LABTECH and Transcreener Assays from BellBrook Labs

Interrogation of small GTPase Activity. Screening GAPs and GEFs with the PHERAstar FSX from BMG LABTECH and Transcreener Assays from BellBrook Labs Interrogation of small GTPase Activity Screening GAPs and GEFs with the PHERAstar FSX from BMG LABTECH and Transcreener Assays from BellBrook Labs Introducing the New PHERAstar FSX Most sensitive reader

More information

Structure based drug design and LIE models for GPCRs

Structure based drug design and LIE models for GPCRs Structure based drug design and LIE models for GPCRs Peter Kolb kolb@docking.org Shoichet Lab ACS 237 th National Meeting, March 24, 2009 p.1/26 [Acknowledgements] Brian Shoichet John Irwin Mike Keiser

More information

Portal. User Guide Version 1.0. Contributors

Portal.   User Guide Version 1.0. Contributors Portal www.dockthor.lncc.br User Guide Version 1.0 Contributors Diogo A. Marinho, Isabella A. Guedes, Eduardo Krempser, Camila S. de Magalhães, Hélio J. C. Barbosa and Laurent E. Dardenne www.gmmsb.lncc.br

More information

Mnova Software Tools for Fragment-Based Drug Discovery

Mnova Software Tools for Fragment-Based Drug Discovery Mnova Software Tools for Fragment-Based Drug Discovery Chen Peng, PhD, VP of Business Development, US & China Mestrelab Research SL San Diego, CA chen.peng@mestrelab.com 858.736.4563 Agenda Brief intro

More information

User Guide for LeDock

User Guide for LeDock User Guide for LeDock Hongtao Zhao, PhD Email: htzhao@lephar.com Website: www.lephar.com Copyright 2017 Hongtao Zhao. All rights reserved. Introduction LeDock is flexible small-molecule docking software,

More information

Progress of Compound Library Design Using In-silico Approach for Collaborative Drug Discovery

Progress of Compound Library Design Using In-silico Approach for Collaborative Drug Discovery 21 th /June/2018@CUGM Progress of Compound Library Design Using In-silico Approach for Collaborative Drug Discovery Kaz Ikeda, Ph.D. Keio University Self Introduction Keio University, Tokyo, Japan (Established

More information

In silico pharmacology for drug discovery

In silico pharmacology for drug discovery In silico pharmacology for drug discovery In silico drug design In silico methods can contribute to drug targets identification through application of bionformatics tools. Currently, the application of

More information

Tautomerism in chemical information management systems

Tautomerism in chemical information management systems Tautomerism in chemical information management systems Dr. Wendy A. Warr http://www.warr.com Tautomerism in chemical information management systems Author: Wendy A. Warr DOI: 10.1007/s10822-010-9338-4

More information

An Integrated Approach to in-silico

An Integrated Approach to in-silico An Integrated Approach to in-silico Screening Joseph L. Durant Jr., Douglas. R. Henry, Maurizio Bronzetti, and David. A. Evans MDL Information Systems, Inc. 14600 Catalina St., San Leandro, CA 94577 Goals

More information

EMPIRICAL VS. RATIONAL METHODS OF DISCOVERING NEW DRUGS

EMPIRICAL VS. RATIONAL METHODS OF DISCOVERING NEW DRUGS EMPIRICAL VS. RATIONAL METHODS OF DISCOVERING NEW DRUGS PETER GUND Pharmacopeia Inc., CN 5350 Princeton, NJ 08543, USA pgund@pharmacop.com Empirical and theoretical approaches to drug discovery have often

More information

Ranking of HIV-protease inhibitors using AutoDock

Ranking of HIV-protease inhibitors using AutoDock Ranking of HIV-protease inhibitors using AutoDock 1. Task Calculate possible binding modes and estimate the binding free energies for 1 3 inhibitors of HIV-protease. You will learn: Some of the theory

More information

OntoChem Software. Chemoinformatic Solutions for Life Sciences Problems

OntoChem Software. Chemoinformatic Solutions for Life Sciences Problems ntochem Software. Chemoinformatic Solutions for Life Sciences Problems ntochem GmbH H.-Damerow-Str. 4 Halle 612 Short Company verview Founded in 25 Dr. Lutz Weber (Roche, Morphochem) Prof. Ludger Wessjohann

More information

CSD. Unlock value from crystal structure information in the CSD

CSD. Unlock value from crystal structure information in the CSD CSD CSD-System Unlock value from crystal structure information in the CSD The Cambridge Structural Database (CSD) is the world s most comprehensive and up-todate knowledge base of crystal structure data,

More information

On InChI and evaluating the quality of cross-reference links

On InChI and evaluating the quality of cross-reference links Galgonek and Vondrášek Journal of Cheminformatics 2014, 6:15 RESEARCH ARTICLE Open Access On InChI and evaluating the quality of cross-reference links Jakub Galgonek * and Jiří Vondrášek * Abstract Background:

More information

Molecular Dynamics Graphical Visualization 3-D QSAR Pharmacophore QSAR, COMBINE, Scoring Functions, Homology Modeling,..

Molecular Dynamics Graphical Visualization 3-D QSAR Pharmacophore QSAR, COMBINE, Scoring Functions, Homology Modeling,.. 3 Conformational Search Molecular Docking Simulate Annealing Ab Initio QM Molecular Dynamics Graphical Visualization 3-D QSAR Pharmacophore QSAR, COMBINE, Scoring Functions, Homology Modeling,.. Rino Ragno:

More information

Using Phase for Pharmacophore Modelling. 5th European Life Science Bootcamp March, 2017

Using Phase for Pharmacophore Modelling. 5th European Life Science Bootcamp March, 2017 Using Phase for Pharmacophore Modelling 5th European Life Science Bootcamp March, 2017 Phase: Our Pharmacohore generation tool Significant improvements to Phase methods in 2016 New highly interactive interface

More information

Transcriptome analysis of a wild bird reveals physiological responses to the urban environment

Transcriptome analysis of a wild bird reveals physiological responses to the urban environment Supplementary Information ppendix S1 Transcriptome analysis of a wild bird reveals physiological responses to the urban environment Hannah Watson 1*, Elin Videvall 1, Martin N. ndersson 1 and Caroline

More information

Capturing Chemistry. What you see is what you get In the world of mechanism and chemical transformations

Capturing Chemistry. What you see is what you get In the world of mechanism and chemical transformations Capturing Chemistry What you see is what you get In the world of mechanism and chemical transformations Dr. Stephan Schürer ead of Intl. Sci. Content Libraria, Inc. sschurer@libraria.com Distribution of

More information

A Tiered Screen Protocol for the Discovery of Structurally Diverse HIV Integrase Inhibitors

A Tiered Screen Protocol for the Discovery of Structurally Diverse HIV Integrase Inhibitors A Tiered Screen Protocol for the Discovery of Structurally Diverse HIV Integrase Inhibitors Rajarshi Guha, Debojyoti Dutta, Ting Chen and David J. Wild School of Informatics Indiana University and Dept.

More information