SAR_EMBL_EBI_EC_BLAST_NOV_2013_Industry_workshop
•Download as PPTX, PDF•
0 likes•8,115 views
This document describes EC-BLAST, a novel tool for finding chemically similar enzyme reactions. EC-BLAST allows users to classify and compare enzymes based on their ability to perform similar reactions. It uses an ontology-based system to classify enzymes into hierarchical categories. The tool works by analyzing and comparing the bond changes and reaction centers of enzyme-catalyzed reactions to determine their similarity on a quantitative scale. This helps with tasks like predicting enzyme function, designing new enzymes, and analyzing metabolic pathways. The document provides examples of using EC-BLAST to analyze similar reactions and link chemical features to protein domains and sequences.
Report
Share
Report
Share
Recommended
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. In order to examine its performance for structure identification, especially in terms of rank-ordering database hits, we have compared it with the ChemSpider database, a well-regarded public database that has become one of the community standards for structure identification. The study has shown that the CompTox Dashboard outperforms ChemSpider in terms of structure identification and ranking providing improved outcomes for mass spectrometry analysis of “known unknowns”. Metabolite Set Enrichment Analysis (ChemRICH)
Metabolomics answers a fundamental question in biology: How does metabolism respond to genetic, environmental or phenotypic perturbations? Combining several metabolomics assays can yield datasets for more than 800 structurally identified metabolites. However, biological interpretations of metabolic regulation in these datasets are hindered by inherent limits of pathway enrichment statistics. We have developed ChemRICH, a statistical enrichment approach that is based on chemical similarity rather than sparse biochemical knowledge annotations. ChemRICH utilizes structure similarity and chemical ontologies to map all known metabolites and name metabolic modules. Unlike pathway mapping, this strategy yields study-specific, non-overlapping sets of all identified metabolites. Subsequent enrichment statistics is superior to pathway enrichments because ChemRICH sets have a self-contained size where p-values do not rely on the size of a background database. We demonstrate ChemRICH’s efficiency on a public metabolomics data set discerning the development of type 1 diabetes in a non-obese diabetic mouse model. ChemRICH is available at www.chemrich.fiehnlab.ucdavis.edu
Metabolic network mapping for metabolomics
We present a novel approach to integrate biochemical pathway and chemical relationships to map all detected metabolites in network graphs (MetaMapp) using KEGG reactant pair database, Tanimoto chemical and NIST mass spectral similarity scores. In fetal and maternal lungs, and in maternal blood plasma from pregnant rats exposed to environmental tobacco smoke (ETS), 459 unique metabolites comprising 179 structurally identified compounds were detected by gas chromatography time of flight mass spectrometry (GC-TOF MS) and BinBase data processing. MetaMapp graphs in Cytoscape showed much clearer metabolic modularity and complete content visualization compared to conventional biochemical mapping approaches. Cytoscape visualization of differential statistics results using these graphs showed that overall, fetal lung metabolism was more impaired than lungs and blood metabolism in dams. Fetuses from ETS-exposed dams expressed lower lipid and nucleotide levels and higher amounts of energy metabolism intermediates than control animals, indicating lower biosynthetic rates of metabolites for cell division, structural proteins and lipids that are critical for in lung development.
MetaMapp graphs efficiently visualizes mass spectrometry based metabolomics datasets as network graphs in Cytoscape, and highlights metabolic alterations that can be associated with higher rate of pulmonary diseases and infections in children prenatally exposed to ETS. The MetaMapp scripts can be accessed at http://metamapp.fiehnlab.ucdavis.edu.
Intro reaxys
Learn Reaxys search methods and best practices around database search querying. With access to over 500 million published experimental facts, chemists can efficiently support their early drug discovery research, material selection and synthesis planning.
- How to use the main features in Reaxys
- The ways in which search results focus on relevance versus comprehensiveness
- How information is indexed and organized according to the principles of chemistry taxonomy
More about Reaxys.
Reaxys is a unique web-based chemistry workflow solution. It supports research and fuels discovery by integrating searches for reaction and substance data with synthesis planning and chemical sourcing. Check out www.reaxys.com/info for more information.
Metabolic Set Enrichment Analysis - chemrich - 2019
Fundamentals of metabolite set enrichment analysis
Environmental Chemistry Compound Identification Using High Resolution Mass Sp...
Environmental Chemistry Compound Identification Using High Resolution Mass Sp...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
There is a growing need for rapid chemical screening and prioritization to inform regulatory decision-making on thousands of chemicals in the environment. We have previously used high-resolution mass spectrometry to examine household vacuum dust samples using liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS). Using a combination of exact mass, isotope distribution, and isotope spacing, molecular features were matched with a list of chemical formulas from the EPA’s Distributed Structure-Searchable Toxicity (DSSTox) database. This has further developed our understanding of how openly available chemical databases, together with the appropriate searches, could be used for the purpose of compound identification. We report here on the utility of the EPA’s iCSS Chemistry Dashboard for the purpose of compound identification using searches against a database of over 720,000 chemicals. We also examine the benefits of QSAR prediction for the purpose of retention time prediction to allow for alignment of both chromatographic and mass spectral properties. This abstract does not reflect U.S. EPA policy.Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new publicly-accessible CompTox Dashboard as the first application built on our newly developed architecture. This abstract does not reflect U.S. EPA policy. Mapping metabolites against pathway databases
Mapping of metabolites onto pathway databases. I covered KEGG, Reactome, HMDB and ConsensusPathDB in this lecture.
Recommended
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. In order to examine its performance for structure identification, especially in terms of rank-ordering database hits, we have compared it with the ChemSpider database, a well-regarded public database that has become one of the community standards for structure identification. The study has shown that the CompTox Dashboard outperforms ChemSpider in terms of structure identification and ranking providing improved outcomes for mass spectrometry analysis of “known unknowns”. Metabolite Set Enrichment Analysis (ChemRICH)
Metabolomics answers a fundamental question in biology: How does metabolism respond to genetic, environmental or phenotypic perturbations? Combining several metabolomics assays can yield datasets for more than 800 structurally identified metabolites. However, biological interpretations of metabolic regulation in these datasets are hindered by inherent limits of pathway enrichment statistics. We have developed ChemRICH, a statistical enrichment approach that is based on chemical similarity rather than sparse biochemical knowledge annotations. ChemRICH utilizes structure similarity and chemical ontologies to map all known metabolites and name metabolic modules. Unlike pathway mapping, this strategy yields study-specific, non-overlapping sets of all identified metabolites. Subsequent enrichment statistics is superior to pathway enrichments because ChemRICH sets have a self-contained size where p-values do not rely on the size of a background database. We demonstrate ChemRICH’s efficiency on a public metabolomics data set discerning the development of type 1 diabetes in a non-obese diabetic mouse model. ChemRICH is available at www.chemrich.fiehnlab.ucdavis.edu
Metabolic network mapping for metabolomics
We present a novel approach to integrate biochemical pathway and chemical relationships to map all detected metabolites in network graphs (MetaMapp) using KEGG reactant pair database, Tanimoto chemical and NIST mass spectral similarity scores. In fetal and maternal lungs, and in maternal blood plasma from pregnant rats exposed to environmental tobacco smoke (ETS), 459 unique metabolites comprising 179 structurally identified compounds were detected by gas chromatography time of flight mass spectrometry (GC-TOF MS) and BinBase data processing. MetaMapp graphs in Cytoscape showed much clearer metabolic modularity and complete content visualization compared to conventional biochemical mapping approaches. Cytoscape visualization of differential statistics results using these graphs showed that overall, fetal lung metabolism was more impaired than lungs and blood metabolism in dams. Fetuses from ETS-exposed dams expressed lower lipid and nucleotide levels and higher amounts of energy metabolism intermediates than control animals, indicating lower biosynthetic rates of metabolites for cell division, structural proteins and lipids that are critical for in lung development.
MetaMapp graphs efficiently visualizes mass spectrometry based metabolomics datasets as network graphs in Cytoscape, and highlights metabolic alterations that can be associated with higher rate of pulmonary diseases and infections in children prenatally exposed to ETS. The MetaMapp scripts can be accessed at http://metamapp.fiehnlab.ucdavis.edu.
Intro reaxys
Learn Reaxys search methods and best practices around database search querying. With access to over 500 million published experimental facts, chemists can efficiently support their early drug discovery research, material selection and synthesis planning.
- How to use the main features in Reaxys
- The ways in which search results focus on relevance versus comprehensiveness
- How information is indexed and organized according to the principles of chemistry taxonomy
More about Reaxys.
Reaxys is a unique web-based chemistry workflow solution. It supports research and fuels discovery by integrating searches for reaction and substance data with synthesis planning and chemical sourcing. Check out www.reaxys.com/info for more information.
Metabolic Set Enrichment Analysis - chemrich - 2019
Fundamentals of metabolite set enrichment analysis
Environmental Chemistry Compound Identification Using High Resolution Mass Sp...
Environmental Chemistry Compound Identification Using High Resolution Mass Sp...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
There is a growing need for rapid chemical screening and prioritization to inform regulatory decision-making on thousands of chemicals in the environment. We have previously used high-resolution mass spectrometry to examine household vacuum dust samples using liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS). Using a combination of exact mass, isotope distribution, and isotope spacing, molecular features were matched with a list of chemical formulas from the EPA’s Distributed Structure-Searchable Toxicity (DSSTox) database. This has further developed our understanding of how openly available chemical databases, together with the appropriate searches, could be used for the purpose of compound identification. We report here on the utility of the EPA’s iCSS Chemistry Dashboard for the purpose of compound identification using searches against a database of over 720,000 chemicals. We also examine the benefits of QSAR prediction for the purpose of retention time prediction to allow for alignment of both chromatographic and mass spectral properties. This abstract does not reflect U.S. EPA policy.Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new publicly-accessible CompTox Dashboard as the first application built on our newly developed architecture. This abstract does not reflect U.S. EPA policy. Mapping metabolites against pathway databases
Mapping of metabolites onto pathway databases. I covered KEGG, Reactome, HMDB and ConsensusPathDB in this lecture.
Data drivenapproach to medicinalchemistry
Learn how large-scale normalized data empowers the critical early phases of drug discovery.
To address the core concerns about data quality, comprehensiveness and comparability, the Reaxys product team has developed a completely new repository for bioactivity information. Reaxys Medicinal Chemistry stands as a unique source for normalized data in vitro efficacy, in vivo animal models, compound metabolism, pharmacokinetics and toxicity. This presentation takes a look at how this approach to data supports critical early discovery methods such as in silico screening and target profiling.
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. This poster reviews the benefits of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. Standard approaches for both mass and formula lookup are available but the dashboard delivers a novel approach for hit ranking based on functional use of the chemicals. The focus on high-quality data, novel ranking approaches and integration to other resources of value to mass spectrometrists makes the CompTox Dashboard a valuable resource for the identification of environmental chemicals. This abstract does not reflect U.S. EPA policy. The influence of data curation on QSAR Modeling – examining issues of qualit...
The influence of data curation on QSAR Modeling – examining issues of qualit...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The construction of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to develop and validate QSAR models. We have focused our efforts on the widely used EPISuite software that was initially developed over two decades ago. Specific examples of quality issues for the EPISuite data include multiple records for the same chemical structure with different measured property values, inconsistency between the structure, chemical name and CAS registry number for single records, the inability to convert the SMILES strings into chemical structures, hypervalency in the chemical structures and the absence of stereochemistry for thousands of data records. Relative to the era of EPISuite development, modern cheminformatics tools allow for more advanced capabilities in terms of chemical structure representation and storage, as well as enabling automated data validation and standardization approaches to examine data quality. This presentation will review both our manual and automated approaches to examining key datasets related to the EPISuite training and test data. This includes approaches to validate between chemical structure representations (e.g. molfile and SMILES) and identifiers (chemical names and registry numbers), as well as approaches to standardize the data into QSAR-consumable formats for modeling. We have quantified and segregated the data into various quality categories to allow us to thoroughly investigate the resulting models that can be developed from these data slices and to examine to what extent efforts into the development of large high-quality datasets have the expected pay-off in terms of prediction performance. This abstract does not reflect U.S. EPA policy.Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much reduced cost relative to historical approaches. This work involves computational and data driven approaches including high-throughput screening, modeling, text-mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy.VLife SCOPE for Lead Optimization
VLifeSCOPE is Structure Based Compound Optimization, Prioritization & Evolution. It brings together two powerful approaches namely - comparative binding energy analysis based method for lead optimization and score based approach for activity prediction.
Validation of homology modeling
Validation is the process of checking that your model is consistent with stereochemical standards i.e., validation is the process of evaluating reliability
In this presentation various aspects of validation are discussed
Molecular modelling for in silico drug discovery
A slide set based on the small molecule section of "Introduction to in silico drug discovery" with more detail on molecular modelling and simulation aspects. Including a bit more on protein structure prediction
The royal society of chemistry and its adoption of semantic web technologies ...
Semantic web technologies have quickly penetrated all areas of traditional and new database systems and have become the de facto standard in information exchange and communication. The Royal Society of Chemistry has built a new chemistry data repository with the semantic web at the core of the system. Every module of the data repository contains a semantic web layer and is able to interact internally and externally using standard approaches and formats including RDF, appropriate ontologies, SPARQL querying and so on. In this presentation we will review the challenges associated with developing this new system based on semantic web technologies and how the approach that we have taken offers distinct advantages over the original data model designed to produce the ChemSpider database. Its advantages include extensibility, an ontological underpinning, federated integration and the adoption of modern standards rather than the constraints of a standard SQL model.
Reaxys Medicinal Chemistry 2014
Introduction to the Reaxys Medicinal Chemistry Database. These slides were used for a webinar presented on July 22, 2014.
Serving the medicinal chemistry community with Royal Society of Chemistry che...
Serving the medicinal chemistry community with Royal Society of Chemistry che...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The Royal Society of Chemistry (RSC) is a major participant in providing access to chemistry related data via the web. As an internationally renowned society for the chemical sciences, a scientific publisher and the host of the ChemSpider database for the community, RSC continues to make dramatic strides in providing online access to data. ChemSpider provides access to over 30 million chemicals sourced from over 500 data suppliers and linked out to related information on the web. The platform is a crowdsourcing environment whereby members of the community can participate in validating and expanding the content of the database. With a set of application programming interfaces ChemSpider is used by various organizations and projects to serve up data for various purposes. These include structure identification for mass spectrometry instrument vendors, RSC databases such as the Marinlit natural products database and a European grant-based project from the Innovative Medicines Initiative fund. This presentation will provide an overview of various cheminformatics activities and projects that RSC is involved with to serve the medicinal chemistry community. This will include the Open PHACTS semantic web project, the PharmaSea project to identify new pharmaceutical leads from the ocean and the UK National Compound Collection to identify new lead compounds contained within PhD theses.Drug design
THE DRUG DESIGN AND DEVELOPMENT BASED ON DRUG DISCOVERY ,HERE ITS NEED RATIONALE ARE EXPLAINED ALSO QSAR, MOLECULAR DOCKING ITS HISTORY NEED, STRUCTURE BASED DRUG DESIGN IN EASY WAY WE HAVE MENTIONED. THIS WILL MAKE READERS EASY TO COLLECT DATA AT A PLACE ALL OVER THIS IS FOR PHARMA STUDENTS, ACADEMICS, PROFESSIONL AND OST USEFUL FOR RESEARCHERS.
THANK YOU
HOPE YOU WILL LIKE AND SHARE
The application of cloud computing to royal society of chemistry data platforms
Cloud computing offers significant advantages for the hosting of RSC chemistry databases in terms of reliability, performance and access to large scale computational power. The ChemSpider database contains almost 30 million unique chemical compounds and access to compute power to regenerate properties and add new properties is essential for efficient delivery on a manageable timescale. The use of cloud-based facilities reduces the needs for internal infrastructure and enhances performance generally at the cost of significant recoding of the platforms. This presentation will review our move of our ChemSpider related projects to the cloud, the associated challenges and both the obvious and unforeseen benefits. We will also discuss our use of parallelization technologies for mass calculation using Hadoop.
How an Online Resource for Chemistry Can Change Our World
How an Online Resource for Chemistry Can Change Our WorldUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
This is a presentation given at the Triangle Chromatography Discussion Group with a focus on Mass Spectrometry and associated web services and what is possible for chromatographersStructure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. We will also discuss progress towards a high-throughput non-targeted analysis platform for use by the mass spectrometry community. This abstract does not reflect U.S. EPA policy.OPERA, AN OPEN SOURCE AND OPEN DATA SUITE OF QSAR MODELS
OPERA is a free and open source/open data suite of QSAR models
providing predictions for toxicity endpoints and physicochemical,
environmental fate, and ADME properties.
•
In addition to predictions, OPERA provides accuracy estimates, applicability
domain assessment and experimental data when available.
•
Recent additions to OPERA include models for estrogenic activity,
androgenic activity, and acute oral systemic toxicity developed through
international collaborative modeling projects, and updates to models
predicting plasma protein binding and intrinsic hepatic clearance.
New developments in delivering public access to data from the National Center...
New developments in delivering public access to data from the National Center...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new CompTox Chemistry Dashboard and the developing architecture to support real-time property and toxicity endpoint prediction. This abstract does not reflect U.S. EPA policy.Recent improvements in marvin v6 reaction atom mapping and its application to...
Automatic atom mapping attempts to determine the correspondence between the atoms of the reactants and products of a chemical reaction. Such mappings are useful for allowing greater specificity in queries of reaction databases. Recently there has been increased interest in their use to assist in the validation and standardisation of reactions in pharmaceutical ELNs (electronic lab notebooks). Atom mappings can, for example, detect if a reactant is missing or if a reactant does not contribute atoms to the product and hence may be better stored as an agent.
We have evaluated the performance of the new atom mapping algorithm introduced with Marvin v6 compared to the prior version on a publically available dataset extracted from the patent literature and on reactions from multiple pharmaceutical ELNs. Dramatic improvements are observed in all cases both in the percentage of reactions that can be successfully atom-mapped and the quality of mappings produced.
Finally we examine the difficulties that remain in validating reactions for which a complete atom mapping is not possible, such as for “routine” reactions where the reactant that was added is missing.
More Related Content
What's hot
Data drivenapproach to medicinalchemistry
Learn how large-scale normalized data empowers the critical early phases of drug discovery.
To address the core concerns about data quality, comprehensiveness and comparability, the Reaxys product team has developed a completely new repository for bioactivity information. Reaxys Medicinal Chemistry stands as a unique source for normalized data in vitro efficacy, in vivo animal models, compound metabolism, pharmacokinetics and toxicity. This presentation takes a look at how this approach to data supports critical early discovery methods such as in silico screening and target profiling.
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. This poster reviews the benefits of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. Standard approaches for both mass and formula lookup are available but the dashboard delivers a novel approach for hit ranking based on functional use of the chemicals. The focus on high-quality data, novel ranking approaches and integration to other resources of value to mass spectrometrists makes the CompTox Dashboard a valuable resource for the identification of environmental chemicals. This abstract does not reflect U.S. EPA policy. The influence of data curation on QSAR Modeling – examining issues of qualit...
The influence of data curation on QSAR Modeling – examining issues of qualit...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The construction of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to develop and validate QSAR models. We have focused our efforts on the widely used EPISuite software that was initially developed over two decades ago. Specific examples of quality issues for the EPISuite data include multiple records for the same chemical structure with different measured property values, inconsistency between the structure, chemical name and CAS registry number for single records, the inability to convert the SMILES strings into chemical structures, hypervalency in the chemical structures and the absence of stereochemistry for thousands of data records. Relative to the era of EPISuite development, modern cheminformatics tools allow for more advanced capabilities in terms of chemical structure representation and storage, as well as enabling automated data validation and standardization approaches to examine data quality. This presentation will review both our manual and automated approaches to examining key datasets related to the EPISuite training and test data. This includes approaches to validate between chemical structure representations (e.g. molfile and SMILES) and identifiers (chemical names and registry numbers), as well as approaches to standardize the data into QSAR-consumable formats for modeling. We have quantified and segregated the data into various quality categories to allow us to thoroughly investigate the resulting models that can be developed from these data slices and to examine to what extent efforts into the development of large high-quality datasets have the expected pay-off in terms of prediction performance. This abstract does not reflect U.S. EPA policy.Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much reduced cost relative to historical approaches. This work involves computational and data driven approaches including high-throughput screening, modeling, text-mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy.VLife SCOPE for Lead Optimization
VLifeSCOPE is Structure Based Compound Optimization, Prioritization & Evolution. It brings together two powerful approaches namely - comparative binding energy analysis based method for lead optimization and score based approach for activity prediction.
Validation of homology modeling
Validation is the process of checking that your model is consistent with stereochemical standards i.e., validation is the process of evaluating reliability
In this presentation various aspects of validation are discussed
Molecular modelling for in silico drug discovery
A slide set based on the small molecule section of "Introduction to in silico drug discovery" with more detail on molecular modelling and simulation aspects. Including a bit more on protein structure prediction
The royal society of chemistry and its adoption of semantic web technologies ...
Semantic web technologies have quickly penetrated all areas of traditional and new database systems and have become the de facto standard in information exchange and communication. The Royal Society of Chemistry has built a new chemistry data repository with the semantic web at the core of the system. Every module of the data repository contains a semantic web layer and is able to interact internally and externally using standard approaches and formats including RDF, appropriate ontologies, SPARQL querying and so on. In this presentation we will review the challenges associated with developing this new system based on semantic web technologies and how the approach that we have taken offers distinct advantages over the original data model designed to produce the ChemSpider database. Its advantages include extensibility, an ontological underpinning, federated integration and the adoption of modern standards rather than the constraints of a standard SQL model.
Reaxys Medicinal Chemistry 2014
Introduction to the Reaxys Medicinal Chemistry Database. These slides were used for a webinar presented on July 22, 2014.
Serving the medicinal chemistry community with Royal Society of Chemistry che...
Serving the medicinal chemistry community with Royal Society of Chemistry che...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The Royal Society of Chemistry (RSC) is a major participant in providing access to chemistry related data via the web. As an internationally renowned society for the chemical sciences, a scientific publisher and the host of the ChemSpider database for the community, RSC continues to make dramatic strides in providing online access to data. ChemSpider provides access to over 30 million chemicals sourced from over 500 data suppliers and linked out to related information on the web. The platform is a crowdsourcing environment whereby members of the community can participate in validating and expanding the content of the database. With a set of application programming interfaces ChemSpider is used by various organizations and projects to serve up data for various purposes. These include structure identification for mass spectrometry instrument vendors, RSC databases such as the Marinlit natural products database and a European grant-based project from the Innovative Medicines Initiative fund. This presentation will provide an overview of various cheminformatics activities and projects that RSC is involved with to serve the medicinal chemistry community. This will include the Open PHACTS semantic web project, the PharmaSea project to identify new pharmaceutical leads from the ocean and the UK National Compound Collection to identify new lead compounds contained within PhD theses.Drug design
THE DRUG DESIGN AND DEVELOPMENT BASED ON DRUG DISCOVERY ,HERE ITS NEED RATIONALE ARE EXPLAINED ALSO QSAR, MOLECULAR DOCKING ITS HISTORY NEED, STRUCTURE BASED DRUG DESIGN IN EASY WAY WE HAVE MENTIONED. THIS WILL MAKE READERS EASY TO COLLECT DATA AT A PLACE ALL OVER THIS IS FOR PHARMA STUDENTS, ACADEMICS, PROFESSIONL AND OST USEFUL FOR RESEARCHERS.
THANK YOU
HOPE YOU WILL LIKE AND SHARE
The application of cloud computing to royal society of chemistry data platforms
Cloud computing offers significant advantages for the hosting of RSC chemistry databases in terms of reliability, performance and access to large scale computational power. The ChemSpider database contains almost 30 million unique chemical compounds and access to compute power to regenerate properties and add new properties is essential for efficient delivery on a manageable timescale. The use of cloud-based facilities reduces the needs for internal infrastructure and enhances performance generally at the cost of significant recoding of the platforms. This presentation will review our move of our ChemSpider related projects to the cloud, the associated challenges and both the obvious and unforeseen benefits. We will also discuss our use of parallelization technologies for mass calculation using Hadoop.
How an Online Resource for Chemistry Can Change Our World
How an Online Resource for Chemistry Can Change Our WorldUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
This is a presentation given at the Triangle Chromatography Discussion Group with a focus on Mass Spectrometry and associated web services and what is possible for chromatographersStructure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. We will also discuss progress towards a high-throughput non-targeted analysis platform for use by the mass spectrometry community. This abstract does not reflect U.S. EPA policy.OPERA, AN OPEN SOURCE AND OPEN DATA SUITE OF QSAR MODELS
OPERA is a free and open source/open data suite of QSAR models
providing predictions for toxicity endpoints and physicochemical,
environmental fate, and ADME properties.
•
In addition to predictions, OPERA provides accuracy estimates, applicability
domain assessment and experimental data when available.
•
Recent additions to OPERA include models for estrogenic activity,
androgenic activity, and acute oral systemic toxicity developed through
international collaborative modeling projects, and updates to models
predicting plasma protein binding and intrinsic hepatic clearance.
New developments in delivering public access to data from the National Center...
New developments in delivering public access to data from the National Center...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new CompTox Chemistry Dashboard and the developing architecture to support real-time property and toxicity endpoint prediction. This abstract does not reflect U.S. EPA policy.What's hot (20)
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
The influence of data curation on QSAR Modeling – examining issues of qualit...
The influence of data curation on QSAR Modeling – examining issues of qualit...
Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...
The royal society of chemistry and its adoption of semantic web technologies ...
The royal society of chemistry and its adoption of semantic web technologies ...
Serving the medicinal chemistry community with Royal Society of Chemistry che...
Serving the medicinal chemistry community with Royal Society of Chemistry che...
The application of cloud computing to royal society of chemistry data platforms
The application of cloud computing to royal society of chemistry data platforms
How an Online Resource for Chemistry Can Change Our World
How an Online Resource for Chemistry Can Change Our World
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
OPERA, AN OPEN SOURCE AND OPEN DATA SUITE OF QSAR MODELS
OPERA, AN OPEN SOURCE AND OPEN DATA SUITE OF QSAR MODELS
New developments in delivering public access to data from the National Center...
New developments in delivering public access to data from the National Center...
Viewers also liked
Recent improvements in marvin v6 reaction atom mapping and its application to...
Automatic atom mapping attempts to determine the correspondence between the atoms of the reactants and products of a chemical reaction. Such mappings are useful for allowing greater specificity in queries of reaction databases. Recently there has been increased interest in their use to assist in the validation and standardisation of reactions in pharmaceutical ELNs (electronic lab notebooks). Atom mappings can, for example, detect if a reactant is missing or if a reactant does not contribute atoms to the product and hence may be better stored as an agent.
We have evaluated the performance of the new atom mapping algorithm introduced with Marvin v6 compared to the prior version on a publically available dataset extracted from the patent literature and on reactions from multiple pharmaceutical ELNs. Dramatic improvements are observed in all cases both in the percentage of reactions that can be successfully atom-mapped and the quality of mappings produced.
Finally we examine the difficulties that remain in validating reactions for which a complete atom mapping is not possible, such as for “routine” reactions where the reactant that was added is missing.
BioJS Human Genetic Variant Viewer
BioJavascript Human Genetic Variation Viewer
presented at the USC/UCLA Joint Bioinformatics Meeting held at University Of Southern California.
Developed as part of Google Summer of Code 2014
Building an Online Profile Using Social Networking and Amplification Tools fo...
Building an Online Profile Using Social Networking and Amplification Tools fo...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Many of us nowadays invest significant amounts of time in sharing our activities and opinions with friends and family via social networking tools such as Facebook, Twitter or other related websites. However, despite the availability of many platforms for scientists to connect and share with their peers in the scientific community the majority do not make use of these tools, despite their promise and potential impact and influence on our careers. We are already being indexed and exposed on the internet via our publications, presentations and data and new “AltMetric scores” are being assigned to scientific publications as measures of popularity and, supposedly, of impact. We now have even more ways to contribute to science, to annotate and curate data, to “publish” in new ways, and many of these activities are as part of a growing crowdsourcing network. This presentation provides an overview of the various types of networking and collaborative sites available to scientists and ways to expose your scientific activities online. It will discuss the new world of AltMetrics that is in an explosive growth curve and will help you understand how to influence and leverage some of these new measures. Participating online, whether it be simply for career advancement or for wider exposure of your research, there are now a series of web applications that can provide a great opportunity to develop a scientific profile within the community.A really really fast introduction to PySpark - lightning fast cluster computi...
Apache Spark is a fast and general engine for distributed computing & big data processing with APIs in Scala, Java, Python, and R. This tutorial will briefly introduce PySpark (the Python API for Spark) with some hands-on-exercises combined with a quick introduction to Spark's core concepts. We will cover the obligatory wordcount example which comes in with every big-data tutorial, as well as discuss Spark's unique methods for handling node failure and other relevant internals. Then we will briefly look at how to access some of Spark's libraries (like Spark SQL & Spark ML) from Python. While Spark is available in a variety of languages this workshop will be focused on using Spark and Python together.
Viewers also liked (6)
Recent improvements in marvin v6 reaction atom mapping and its application to...
Recent improvements in marvin v6 reaction atom mapping and its application to...
Building an Online Profile Using Social Networking and Amplification Tools fo...
Building an Online Profile Using Social Networking and Amplification Tools fo...
A really really fast introduction to PySpark - lightning fast cluster computi...
A really really fast introduction to PySpark - lightning fast cluster computi...
Similar to SAR_EMBL_EBI_EC_BLAST_NOV_2013_Industry_workshop
CERAPP - Collaborative Estrogen Receptor Activity Prediction Project. Computa...
•U.S. Congress mandated that the EPA screen chemicals for their potential to be endocrine disruptors
•Led to development of the Endocrine Disruptor Screening Program (EDSP)
•Initial focus was on environmental estrogens, but program expanded to include androgens and thyroid pathway disruptors
EUGM15 - George Papadatos, Mark Davies, Nathan Dedman (EMBL-EBI): SureChEMBL:...
SureChEMBL is a new resource provided by the European Bioinformatics Institute (EMBL-EBI) that annotates, extracts and indexes chemistry from full text patent documents by means of continuous, automated text and image mining. SureChEMBL is perhaps the only open, freely available, live patent chemistry resource available, in a field that has been traditionally commercial.
Since its launch last September, the SureChEMBL interface provides sophisticated keyword and chemistry-based querying and exporting functionality against a corpus of more than 16 million compounds extracted from 13 million patent documents. Both the interface and the underlying data pipeline leverage extensively ChemAxon technologies for name to structure conversion, as well as compound standardisation, registration and searching.
In addition to providing an overview of the system, recent developments and improvements will be described. These include the introduction of various data interexchange and exporting options, such as flat files and a data feed client. Furthermore, our future plans for the SureChEMBL system will be outlined. To date, such plans include complementing the chemical annotations with biological ones, covering genes, proteins, diseases and indications. Furthermore, we are planning to further enrich the chemical annotations with a relevance score, indicating their importance in the patent document.
The US-EPA CompTox Chemicals Dashboard – a key player in the domain of Open S...
The US-EPA CompTox Chemicals Dashboard – a key player in the domain of Open S...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are advancing the identification of emerging contaminants in environmental matrices, improving the means by which exposure analyses can be conducted. However, confidence in structure identification of unknowns in NTA presents challenges to analytical chemists. Structure identification requires integration of complementary data types such as reference databases (either commercial or open databases), fragmentation prediction tools, and retention time prediction models. One goal of our research is to optimize and implement structure identification functionality within the US EPA’s CompTox Chemicals Dashboard, an open chemistry resource and web application containing data for ~900,000 substances. Database searching using mass or formula-based inputs has been optimized for structure identification using “MS-Ready Structures”: de-salted, stripped of stereochemistry, and mixture separated to replicate the form of a chemical observed via HRMS. Functionality to conduct batch searching of molecular formulae and monoisotopic masses has also been implemented. While the increasing number of free online databases are of value to support chemical structure verification and elucidation there are known issues regarding data quality and careful data curation is a very necessary part of the development of these resources. This presentation will provide an overview of our latest enhancements to the dashboard to support mass spectrometry, incorporation of specific datasets (i.e. to support breath research and household dust analysis) and the value of metadata and predicted fragmentation spectral matching to support structure identification. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Protein Structural predection
Protein Structural Prediction
1. Molecular Structure prediction
2. Sequence
3. Protein Folding
4. The Leventhal Paradox
5. Energy (Minimization )
6. The Hydrophobic Effect
7. Protein Structure Determination ( X-ray,NMR)
8. Ab initio Prediction
9. Lattice String Folding
10. Rosetta (Monte Carlo based method)
11. Homology-based Prediction
Computational Drug Discovery: Machine Learning for Making Sense of Big Data i...
In this lecture, I provide an overview on how computers can be instrumental in drug discovery efforts. Topics covered includes: big data as a result of omics effort; bioinformatics; cheminformatics; biological space; chemical space; how computers particularly machine learning (and data science) can be applied in the context of drug discovery.
A video of this lecture is also provided on the "Data Professor" YouTube channel available at http://bit.ly/dataprofessor
If you are fascinated about data science, it would mean the world to me if you would consider subscribing to this channel (by clicking the link below):
http://bit.ly/dataprofessor
Ontology work at the Royal Society of Chemistry
Ontology work at the Royal Society of ChemistryUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
We provide an overview of the use we make of ontologies at the Royal Society of Chemistry. Our engagement with the ontology community began in 2006 with preparations for Project Prospect, which used ChEBI and other Open Biomedical Ontologies to mark up journal articles. Subsequently Project Prospect has evolved into DERA (Digitally Enhancing the RSC Archive) and we have developed further ontologies for text markup, covering analytical methods and name reactions. Most recently we have been contributing to CHEMINF, an open-source cheminformatics ontology, as part of our work on disseminating calculated physicochemical properties of molecules via the Open PHACTS. We show how we represent these properties and how it can serve as a template for disseminating different sorts of chemical information.MetSim: Integrated Programmatic Access and Pathway Management for Xenobiotic ...
MetSim: Integrated Programmatic Access and Pathway Management for Xenobiotic ...Louis C. Groff II, PhD
Metabolic similarity is a key consideration in read-across but approaches to characterise and quantify the contribution metabolism plays are still evolving. A major challenge lies in the lack of a standardized database of human xenobiotic metabolism pathways for environmental chemicals. To address this issue, we developed a metabolic simulation framework called MetSim, comprised of three main components. First, we propose a harmonised graph-based representation for managing xenobiotic metabolism pathway information between different in silico tools and empirical evidence from the literature. This schema is implemented in a Mongo database to store, retrieve and analyze large-scale metabolic graphs. Second, MetSim includes a standardised application programming interface (API) for available metabolic simulators, including BioTransformer, the OECD Toolbox, and Tissue Metabolism Simulator (TIMES). Third, MetSim includes functions to systematically evaluate the performance of metabolism simulators using recall, precision and overall accuracy on benchmark data sets. Here we report on the overall architecture of MetSim, and performance results for two data sets: (a) 59 drugs (mostly NSAIDs) and their 179 published metabolites, and (b) 718 diverse substances in the EPA Distributed Structure-Searchable Toxicity (DSSTox) database and their 1632 metabolites. The 59 drugs were processed with MetSim using BioTransformer (CypReact model with 3 cycles of human Phase I metabolism), TIMES (in vivo rat simulator model) and OECD Toolbox (in vitro rat Liver S9), producing 11202, 590, and 539 metabolites, respectively. The recall for Biotransformer, TIMES and OECD Toolbox was 0.62, 0.41 and 0.52, respectively. For the larger DSSTox dataset, two cycles of human phase I (CypReact) and one cycle of phase II metabolism were modeled using BioTransformer, and both TIMES and OECD Toolbox using the same two rat liver models, producing 60097, 6654, and 5204 metabolites, respectively. The recall for Biotransformer, TIMES and OECD Toolbox was 0.16, 0.41 and 0.38, respectively. We summarized the performance of these tools by data set, chemical class (using ClassyFire) and metabolic simulator. All tools performed well for phenanthrenes, piperadines, lactams, and azoles but poorly for pyrrolines, organonitrogen compounds, and nucleotide analogues. BioTransformer performed well for benzoxazines, benzothaizepines, and quinolines, but poorly for steroids, benzothiazines, and diazines. Conversely, TIMES and the OECD Toolbox performed well for steroids, benzothiazines, and diazines, but poorly for benzoxazines, diazinines and organooxygen compounds. MetSim provides useful data and insights on the performance and limitations of in silico metabolism tools, which will inform our subsequent efforts in characterising metabolic similarity. This abstract does not reflect EPA policy.Structure identification approaches using the EPA CompTox Chemicals Dashboard...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are utilized to identify emerging contaminants and chemical signatures of interest detected in various media. At the US Environmental Protection Agency the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) is an open chemistry resource and web-based application containing data for ~900,000 substances and supports non-targeted and suspect screening analyses. Searching functionality includes identifier searches (e.g. systematic names, trade names and CAS Registry Numbers), mass and formula-based searches and prototype developments include combined substructure-mass/formula searches and searching experimental mass spectral data against predicted fragmentation spectra. A specific type of data mapping in the database uses “MS-Ready” structures, a way to process all registered substances to separate multi-component chemicals into their individual components, removal of stereochemical bonds and desalting and neutralization. This MS-Ready processing supports batch-searching using either mass or formulae to identify candidate chemicals and their mapped substances. A number of chemical lists (https://comptox.epa.gov/dashboard/chemical_lists) have also been developed to support the identification of chemicals related to agrochemistry, specifically pesticides (both active and inert constituents), insecticides and their metabolites and environmental breakdown products). This presentation will provide an overview of how the CompTox Chemicals Dashboard supports mass spectrometry based structure identification and non-targeted analysis of chemicals in agrochemistry. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.EDSP Prioritization: Collaborative Estrogen Receptor Activity Prediction Proj...
Humans are potentially exposed to tens of thousands of man-made chemicals in the environment. It is well known that some environmental chemicals mimic natural hormones and thus have the potential to be endocrine disruptors. Most of these environmental chemicals have never been tested for their ability to disrupt the endocrine system, in particular, their ability to interact with the estrogen receptor. EPA needs tools to prioritize thousands of chemicals, for instance in the Endocrine Disruptor Screening Program (EDSP). This project was intended to be a demonstration of the use of predictive computational models on HTS data including ToxCast and Tox21 assays to prioritize a large chemical universe of 32464 unique structures for one specific molecular target – the estrogen receptor. CERAPP combined multiple computational models for prediction of estrogen receptor activity, and used the predicted results to build a unique consensus model. Models were developed in collaboration between 17 groups in the U.S. and Europe and applied to predict the common set of chemicals. Structure-based techniques such as docking and several QSAR modeling approaches were employed, mostly using a common training set of 1677 compounds provided by U.S. EPA, to build a total of 42 classification models and 8 regression models for binding, agonist and antagonist activity. All predictions were evaluated on ToxCast data and on an external validation set collected from the literature. In order to overcome the limitations of single models, a consensus was built weighting models based on their prediction accuracy scores (including sensitivity and specificity against training and external sets). Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. The final consensus predicted 4001 chemicals as actives to be considered as high priority for further testing and 6742 as suspicious chemicals. This abstract does not necessarily reflect U.S. EPA policy
Metabolic engineering approaches in medicinal plants
A general review on metabolic engineering of valuable plants as good sources of bioactive compounds.
Expanding Surface Plasmon Resonance Capabilities with Reichert
Surface Plasmon Resonance (SPR) is a widely-used label-free technique to characterize a variety of molecular interactions. SPR is an optical phenomenon that is sensitive to changes in the dielectric properties of the medium close to a metal surface. Specifically, the resonance condition is affected by changes in refractive index occurring up to 300 nm above the metal surface (Au) and thus by the material absorbed onto the metal film. Therefore, the SPR signal is a measure of the total mass concentration at the gold sensor chip surface.
Typically, a mobile molecule (analyte) is injected across an immobilized binding partner (ligand) and as the analyte binds, this mass accumulation on the sensor surface leads to an increase in refractive index, and the result is plotted as response versus time. SPR is commonly utilized by researchers to determine association/dissociation rates, affinities and thermodynamics of biomolecular interactions.
Traditionally, the interactions under study with SPR include those occurring with and between the major classes of biological macromolecules along with those involving small molecules and drugs. These classic experiments have been primarily carried with just purified samples. Reichert’s SPR systems implement a very robust fluidics arrangement that can accommodate a wide variety of sample compositions including crude samples such as lysates, whole cells and serum. In addition, Reichert’s systems are housed in an open architecture that easily allows coupling to other analytical techniques and instruments. Along with excelling at traditional biomolecular interactions, Reichert’s systems pave the way for new avenues of investigation involving crude samples and whole cells along with the ability to couple SPR to other techniques. This presentation will focus on the SPR technique and provide examples of unique applications with cells along with the possibility of interfacing SPR with other analytical methods.
http://www.reichertspr.com/webinars/general/expanding-surface-plasmon-resonance-capabilities-with-reichert/
Chapter 2 enzymology.ppt
Incidence and predictors of poor treatment outcomes among Multi-drug-resistant Tuberculosis
New Approach Methods - What is That?
New Approach Methods - What is That?US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Presentation for Texas A&M Superfund Research Center virtual learning series, Big Data in Environmental Science and Toxicology. More details at https://superfund.tamu.edu/big-data-session-2-aug-18-2021/Similar to SAR_EMBL_EBI_EC_BLAST_NOV_2013_Industry_workshop (20)
CERAPP - Collaborative Estrogen Receptor Activity Prediction Project. Computa...
CERAPP - Collaborative Estrogen Receptor Activity Prediction Project. Computa...
EUGM15 - George Papadatos, Mark Davies, Nathan Dedman (EMBL-EBI): SureChEMBL:...
EUGM15 - George Papadatos, Mark Davies, Nathan Dedman (EMBL-EBI): SureChEMBL:...
The US-EPA CompTox Chemicals Dashboard – a key player in the domain of Open S...
The US-EPA CompTox Chemicals Dashboard – a key player in the domain of Open S...
Computational Drug Discovery: Machine Learning for Making Sense of Big Data i...
Computational Drug Discovery: Machine Learning for Making Sense of Big Data i...
MetSim: Integrated Programmatic Access and Pathway Management for Xenobiotic ...
MetSim: Integrated Programmatic Access and Pathway Management for Xenobiotic ...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...
EDSP Prioritization: Collaborative Estrogen Receptor Activity Prediction Proj...
EDSP Prioritization: Collaborative Estrogen Receptor Activity Prediction Proj...
Metabolic engineering approaches in medicinal plants
Metabolic engineering approaches in medicinal plants
Expanding Surface Plasmon Resonance Capabilities with Reichert
Expanding Surface Plasmon Resonance Capabilities with Reichert
Recently uploaded
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
The French Revolution Class 9 Study Material pdf free download
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH ANSWERS.
Chapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptxMohd Adib Abd Muin, Senior Lecturer at Universiti Utara Malaysia
This slide is prepared for master's students (MIFB & MIBS) UUM. May it be useful to all.1.4 modern child centered education - mahatma gandhi-2.pptx
Child centred education is an educational approach that priorities the interest, needs and abilities of the child in the learning process.
Acetabularia Information For Class 9 .docx
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
How to Make a Field invisible in Odoo 17
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Operation Blue Star - Saka Neela Tara
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Event Link:-
https://meetups.mulesoft.com/events/details/mulesoft-mysore-presents-exploring-gemini-ai-and-integration-with-mulesoft/
Agenda
● Java 17 Upgrade Overview
● Why and by when do customers need to upgrade to Java 17?
● Is there any immediate impact to upgrading to Mule Runtime 4.6 and beyond?
● Which MuleSoft products are in scope?
For Upcoming Meetups Join Mysore Meetup Group - https://meetups.mulesoft.com/mysore/
YouTube:- youtube.com/@mulesoftmysore
Mysore WhatsApp group:- https://chat.whatsapp.com/EhqtHtCC75vCAX7gaO842N
Speaker:-
Shubham Chaurasia - https://www.linkedin.com/in/shubhamchaurasia1/
Priya Shaw - https://www.linkedin.com/in/priya-shaw
Organizers:-
Shubham Chaurasia - https://www.linkedin.com/in/shubhamchaurasia1/
Giridhar Meka - https://www.linkedin.com/in/giridharmeka
Priya Shaw - https://www.linkedin.com/in/priya-shaw
Shyam Raj Prasad-
https://www.linkedin.com/in/shyam-raj-prasad/
Model Attribute Check Company Auto Property
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
678020731-Sumas-y-Restas-Para-Colorear.pdf
KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK
Honest Reviews of Tim Han LMA Course Program.pptx
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Unit 8 - Information and Communication Technology (Paper I).pdf
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Digital Tools and AI for Teaching Learning and Research
This Presentation in details discusses on Digital Tools and AI for Teaching Learning and Research
The approach at University of Liverpool.pptx
How libraries can support authors with open access requirements for UKRI funded books
Wednesday 22 May 2024, 14:00-15:00.
special B.ed 2nd year old paper_20240531.pdf
Instagram:-
https://instagram.com/special_education_needs_01?igshid=YmMyMTA2M2Y=
WhatsApp:-
https://chat.whatsapp.com/JVakNIYlSV94x7bwunO3Dc
YouTube:-
https://youtube.com/@special_education_needs
Teligram :- https://t.me/special_education_needs
Slide Shere :-
https://www.slideshare.net/shabnambano20?utm_campaign=profiletracking&utm_medium=sssite&utm_source=ssslideview
Biological Screening of Herbal Drugs in detailed.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Supporting (UKRI) OA monographs at Salford.pptx
How libraries can support authors with open access requirements for UKRI funded books
Wednesday 22 May 2024, 14:00-15:00.
Recently uploaded (20)
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
The French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free download
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
Chapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Unit 8 - Information and Communication Technology (Paper I).pdf
Unit 8 - Information and Communication Technology (Paper I).pdf
Digital Tools and AI for Teaching Learning and Research
Digital Tools and AI for Teaching Learning and Research
SAR_EMBL_EBI_EC_BLAST_NOV_2013_Industry_workshop
- 1. EC-BLAST: A Novel Tool for Finding Chemically Similar Reactions Dr. Syed Asad Rahman asad@ebi.ac.uk Thornton Group Computational Tools for Chemical Biology Nov-2013
- 3. How to classify and compare enzymes? • Find similar enzymes which can perform similar task (Superfamily) • Design de-novo enzymes and small molecule pathway analysis • Optimise enzymes of commercial importance • Drug and mode of action/ cross reactivity • Assignment/Clustering of EC numbers based on the quantitative measure
- 4. Ontology based Classification Method • IUBMB Enzyme Commission • 6 Primary classes with 4 levels of sub-classification • EC 1(Oxidoreductases), EC 2 (Transferases), EC 3 (Hydrolases), EC 4 (Lyases), EC 5 (Isomerases), EC 6 (Ligases) • 6.1.1.1 (ligase) • EC 6.1 Forming Carbon-Oxygen Bonds • EC 6.1.1 Ligases Forming Aminoacyl-tRNA and Related Compounds • EC 6.1.1.1 tyrosine—tRNA ligase
- 5. ECBLAST S. A. Rahman et. al., EC-BLAST: A Tool to Automatically Search and Compare Enzyme Reactions, Nature Methods (accepted) http://www.ebi.ac.uk/thornton-srv/software/rbl/
- 6. Algorithm
- 7. EC Clusters: Bond and Reaction Centre Similarity
- 8. Enzyme Similarity in the Metabolic • Teichmann SA et. al. Pathways (2001, PubMed ID: 11518524), • Rison RC et. al. (2002, PubMed ID: 12054833). Comparison of Reaction Centre (RC) similarity in the E-coli core metabolic pathway 1.00 Tanimoto Scores 0.75 0.50 0.25 0.00 EC-BLAST top score Pathway Neighbours Random Reactions Reaction Centre Similarity
- 10. Linking Sequence Domains and Chemical Attributes • Find all the sequence domains using Pfam/CATH • Find all the chemical attributes interacting with those domains from EC-BLAST DB • Report the chemical features and common substructure Chemical Domains Sequence EC: 6.2.1.* Pfam: PF00501-AMP-binding UniProt: Q6FLU2 Core Fragment
- 11. Future • • • • • • Integrated database with Rhea and BRENDA reactions ~ 15,000 Reactions linked to UniProt, Pfam etc Link Chemistry to Sequence Toxicity Web service Collaborations
- 12. Acknowledgements • • • • • • Gemma L. Holliday Gilleain Torrence Franz Fenninger Lorenzo Baldacci Dame Prof. Janet M. Thornton Nicholas Furnham Sergio Martinez Cuesta • Nimish Gopal, Sophie Williams and Saket Choudhary • Funded by
- 13. http://www.ebi.ac.uk/thornton-srv/software/rbl Dr. Syed Asad Rahman asad@ebi.ac.uk Computational Tools for Chemical Biology Workshop
- 14. Warm up exercise • Reaction similarity search using EC 6.1.1.1 • Look at the similarity scores and the top 10 hits. • EC number and linked information (Pfam, PDB etc) by clicking on them
- 15. Exercise 1 • Search for “penicillin G” using molecule search option in the EC-BLAST
- 16. Exercise 1- Step 1 • Find Reactions with “penicillin G”
- 17. Exercise 2 in 3 Steps 1. Select the top hit and return to the main screen 2. Then perform EC-BLAST using one of the reaction similarity measures.
- 18. Step 1- Select the top hit
- 19. Step 2- Perform EC-BLAST
- 20. Step 3- Top 10 Hits
- 21. Exercise 3: Top 3 hits using Reaction Structure Similarity (KEGG ID R04868)