EUGM 2013 - Akos Papp (ChemAxon) - Compound Registration
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The Compound Registration product was released in January, and now is joining ChemAxon’s standard release cycles from version 6.0. The presentation will cover functionalities, such as the automatic registration process including the bulk loading of chemical compounds, performing corrections in the Staging Area, the amendment of exiting compounds as well as other helpful administrative tools. A dedicated section of the demonstration will focus on both the configurability of the software to handle different business logics and the seamless integration into corporate systems using the related web services. Finally, an overview of the short and long term plans will be given.
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Biomolecule structural data management
Chemaxon is a software and services provider founded in 1998 with headquarters in Budapest and around 250 employees worldwide. Their software supports drug discovery workflows from target identification through clinical trials. They provide tools for biomolecule data management to help with challenges like understanding biological context across teams and preventing data silos. Their software allows users to model, register, standardize, visualize, and design complex biomolecules like peptides, oligonucleotides, conjugates, proteins and antibodies to facilitate collaboration in biotherapeutic fields.
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EUGM 2013 - Christopher Southan (TW2Informatics): Chemicalize.org, SureChemOp...
The ChemAxon Name to Structure functionality is not only a component of the SureChem patent extraction pipeline but also powers chemicalize.org. Both operations are now submitting sources to PubChem. The former has deposited structures that bring the patent-extracted total in PubChem to 14.5 mill. CIDs. The deposition from chemicalize is ~0.3 mill., but has been actively selected by users and is 20% unique. The final conjunction is that all three sources generate the InChIKey that turns Google into a de facto merge of PubChem and ChemSpider of ~50 mill. structures. Chemicalize.org users can convert new patents, other external or internal documents and web based text. Individual results can be Googled, searched against SureChemOpen and bulk extractions triaged against PubChem. It thus becomes possible to connect chemistry between patents, papers, abstracts and database records via exact match or similarity searching. When SureChem and chemicalize.org update their submissions, relationships with the other 47 million structures from ~200 PubChem sources (including ChEMBL and vendor databases) are re-computed and new CID links made. The synergy between SureChem and chemicalize.org is powerful because matches between them (~ 0.15 mill.) via SureChemOpen, give occurrence statistics and the location of the structure within patents. The applications of chemicalize.org are extended by web tools such as Venny for determining intersects from multiple extractions and CheS-Mapper for cluster visualization. These utility expansions will be illustrated by documents specifying BACE1 inhibitors for Alzheimer’s disease.
EUGM 2013 - Björn Windshügel (European ScreeningPort): Chemoinformatic tools ...
In the drug discovery process high-throughput screening is often applied as initial procedure for the identification of hit molecules against a certain target, e.g. an enzyme or G protein-coupled receptor. In addition, virtual screening campaigns utilizing commercially available compound libraries are often performed that allow the search for potential hit molecules within a much larger chemical space as usually accessible within the in-house compound libraries. Chemoinformatic tools provide the opportunity to assist in the setup of experimental and virtual screening campaigns (e.g. assembly of compound libraries) as well as the analysis of screening results and structures of hit compounds. In this presentation the implementation of ChemAxon tools into the European ScreeningPort workflow will be presented using selected examples from previous and ongoing experimental and virtual screening campaigns.
EUGM 2013 - Gyorgy Pirok (ChemAxon) - Prediction of Xenobiotic Metabolism
Metabolizer is a software tool that can identify experimental metabolites for drug compounds. It was tested on 310 substrates with 826 known metabolites. Metabolizer enumerated over 366,000 potential metabolites in 4 generations and predicted their likelihood of formation. For the test compounds, Metabolizer correctly identified at least one major metabolite for 95% of substrates and identified most of the experimental metabolites for 56% when considering the top 10 predictions, 73% for the top 25, and 85% for the top 50. The tool has applications for desktop use by scientists, command line batch processing, and integration via an API.
EUGM 2013 - Ian Berry, Bob Marmon (Evotec): Classification and analysis of 21...
We will discuss how we classified and calculated properties for over 21 million commercially available compounds using a variety of ChemAxon and in-house tools (and aggregated properties). We will show a summary of the analysis of the data and show how we will use that to build better virtual screens.
EUGM 2013 - Bernd Rupp (FMP) Chemical Information systems: From compound coll...
The FMP has developed a database of commercially available compounds which is used to design our in-house HTS collection and is additionally applied to create focused libraries. But the dramatically increase of unique compounds of one order of magnitude from less than 10 to around 30 to 40 million compounds currently and approximately hundred million compounds in the next years requires a reorganization and redevelopment of our storage and searching strategy. To manage such a massive amount of data we developed a Registration Database for registration and normalisation of vendor catalogues. This database contains the highly redundant data of the vendor catalogues and is converted in a second step into the non-redundant Unique Structure Database which represents a data warehouse combining vendor data, structural descriptors and in-house classification tools including our earlier developed ADMET- and reactivity filters as well as our in-house fragment-based fingerprints used for library design tasks. The management of both database systems is part of a new developed Java application, which handles the user management for the data upload in the Registration Database and the conversion into the Unique Structure Database. Further a first version of a Web service is in preparation. This service allows the scientist not only to search for compounds and fragments in the Unique Structure Database but also to combine such a search with the FMP tools to classify compounds for their usability in biological assays.
EUGM 2013 - Jon Patterson (ChemAxon) ChemAxon Platform for Scientists
As scientists we need to deal with inordinate amounts of data every day: we generate, retrieve and manipulate new data as part of our job. Simple excel worksheets are not the solution in the modern era of drug discovery, development and beyond. In this session learn how you can use and integrate ChemAxon’s tools to solve your day-by-day tasks more quickly and efficiently. Whether you prefer a desktop, web-based or touch screen application, we have a solution. Learn how to manipulate your data using Instant JChem (on your desktop or via Web layer) or draw sophisticated queries using Marvin or our new addition Marvin for Java Script (Marvin JS) to reduce the search times, visualize your data in 3D using Marvin Space, export and explore chemistry with the Ubiquitous Excel using the JChem for Excel plugin and share ideas and data with you colleagues and/or collaborators using Crais Board. Integrate our tools in Pipeline Pilot and Knime protocols and generate new data to expedite your processes. Analyze your data using Spotfire through Instant JChem. Also learn how our newest addition, Plexus, will help you do you tasks on desktop using web technology.
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ChemAxon’s Reaction Library provides a full spectrum of organic chemical reactions used in synthetic routes from recent chemical literature. It incorporates both experimental and in-silico transformation rules to help chemists explore chemical space. Reactor provides a wizard-like interface to generate products without minimal manual interference. However, users are also provided with full control over the reaction rules, and they are able to implement their own reactions easily. The presentation will highlight chemical features as well as design and application of our diverse reaction collection in Reactor.
EUGM 2013 - Timea Polgar (ChemAxon) - 3D visualization for medicinal chemists
A typical medicinal chemist research scenario involves more and more 3D molecular modelling. Current components utilized in visualization and manipulation of experimetal X-ray structures and small molecules will be demonstrated in a concept that can easily be applied by not only computational chemists but medicinal chemists as well.
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EUGM 2013 - Gabor Guta (ChemAxon) - JChem Web Services
EUGM 2013 - Gabor Guta (ChemAxon) - JChem Web Services
EUGM 2013 - Anh Kiet Tran Minh (CNRS): French Academic Compound Library: the ...
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EUGM 2013 - Dragos Horváth (Labooratoire de Chemoinformatique Univ Strasbourg...
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EUGM 2013 - Steve Hajkowski (Thomson Reuters): Patent analytics - what can Ma...
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EUGM 2013 - Björn Windshügel (European ScreeningPort): Chemoinformatic tools ...
EUGM 2013 - Gyorgy Pirok (ChemAxon) - Prediction of Xenobiotic Metabolism
EUGM 2013 - Gyorgy Pirok (ChemAxon) - Prediction of Xenobiotic Metabolism
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EUGM 2013 - Ian Berry, Bob Marmon (Evotec): Classification and analysis of 21...
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EUGM 2013 - Bernd Rupp (FMP) Chemical Information systems: From compound coll...
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EUGM 2013 - Anna Tomin (ChemAxon) - Reaction Library Design
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EUGM 2013 - Timea Polgar (ChemAxon) - 3D visualization for medicinal chemists
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Akos Tarcsay (ChemAxon): How fast is Chemaxon RDBMS Search?
Ákos' study aims to provide an overview of ChemAxon's different search engines and web services. A benchmark will be presented along with statistics on the performance of the different JChem engines.
Chemaxon EU UGM 2022 | Translating data to predictive models
Biological, chemical, and physical properties of molecules are encoded in their molecular structure. The challenge lies in discovering the relationships between the structure of the molecular graphs and the measured activity. In this presentation, we introduce Chemaxon’s new product, the Trainer Engine. It is designed to streamline the workflow starting from input data containing measured activities until validated models are implemented for a wide audience.
In addition to summarizing our results obtained with various machine learning model training scenarios, our goal is to highlight the model inference aspects. Accordingly, we present an integration use case with Chemaxon’s Design Hub. Connecting these applications widens the range of information resources available for decision-making on compound series to enhance drug discovery pipelines.
Translating data to predictive models
Biological, chemical and physical properties of molecules are encoded in their molecular structure. The challenge lies in discovering the relationships between the molecular graphs and the measured activity. Where data is measured, collected and curated for a series of compounds there is an opportunity to find the hidden relationships.
Chemical structures come in various shapes and sizes, depending on the scientists or even algorithms that create them. Though variability may sometimes seem subtle to a trained chemist’s eyes, these can introduce inconsistencies that impair chemical search algorithms or model building. Structure normalization is a key component of any cheminformatics workflow with an often underestimated significance. Finding relationships between chemical structures and their measured properties primarily relies on the representation of the chemical matter. Variability of the calculated features and descriptors for these representations can influence data analysis and accuracy of the predictions. During the first part of the presentation we will present the effect of chemical normalization on investigating correlations and building predictive models.
The second part of the talk will incorporate the results of model building on 163 ChEMBL targets extracted from the bioactivity benchmark set1. Results with different descriptor generation methods including ECFP fingerprints, MACCS key, structural properties, geometry properties and phy-chem properties will be discussed in detail. This part focuses on summarizing the results of more than 3000 Random Forest models.
Finally model development for ADMET targets will be highlighted including hERG cardiotoxicity prediction, permeability and blood brain barrier penetration. We will describe how these models can be built, analyzed, optimized and deployed using our new machine learning platform.
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In this joint event our experts are coming together to elaborate on the technical and scientific opportunities coming from this partnership. If you are working on the discovery of next generation drugs and using structure-based approach in your research, join us to learn how to leverage vast biomolecular structural data with innovative technologies.
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Chemaxon is a software and services provider founded in 1998 with headquarters in Budapest and around 250 employees worldwide. Their software supports drug discovery workflows from target identification through clinical trials. They provide tools for biomolecule data management to help with challenges like understanding biological context across teams and preventing data silos. Their software allows users to model, register, standardize, visualize, and design complex biomolecules like peptides, oligonucleotides, conjugates, proteins and antibodies to facilitate collaboration in biotherapeutic fields.
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Marvin Pro is a new web-based chemical editor capable of drawing large synthesis schemes and biomolecules in publication quality. It can be extended with other modules and integrated with ChemAxon and third-party products. Some key features include impeccable visual quality matching journal styles, fast drawing using keyboard shortcuts, and chemical understanding for clean 2D structures and properties display. An alpha version is available on the Chemicalize website and the developers welcome feedback to help perfect the tool.
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This document discusses enhanced stereochemistry representation in molecular structures, including absolute, and, and or labels. It explains that absolute labels indicate known exact stereochemistry, and labels indicate mixtures. Or labels signify a pure but unknown structure, while and labels represent mixtures where both configurations are present. Examples are given to illustrate how these labels can be used to define stereochemical mixtures and unknown structures. The document also demonstrates how chromatographic separation can be used to separate stereoisomer mixtures into pure components.
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Leveraging IP intelligence through the researcher workflow requires the curation of chemistry patents including many thousands of molecules. This complex task is time-consuming and error-prone when done manually, whereas using ChemAxon’s ChemCuratora to analyze and extract chemical information in patents and other documents means the process can be done accurately in a fraction of the time.
GPS for Chemical Space - Digital Assistants to Support Molecule Design - Chem...
Boehringer Ingelheim's Nils Weskamp discusses eDesign: a computational platform for molecule design and optimization. This presentation explaing how to combine data, algorithms and user experience to impact compound design, and gives a glimpse into the agile and interdisciplinary teamwork as facilitated by Design Hub as a success factor for the development of digital tools.
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Cheminfo Stories APAC 2020 - Chemical Descriptors & Standardizers for Machine...
This document discusses chemical descriptors and standardizers that are useful for machine learning models. It introduces standardizers, which canonicalize chemical structures for comparability, and structure checkers, which detect errors. Extended connectivity fingerprints (ECFP) are described as circular fingerprints that encode molecular structure. Case studies demonstrate using ECFP descriptors and standardizers to train deep neural networks for hERG activity prediction, achieving over 80% accuracy. Combining ECFP with topological descriptors led to slightly better performance than ECFP alone in a random forest model. In summary, customizable fingerprints and standardizers allow application in different tasks, and combining fingerprints with other descriptors can increase model performance.
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The Synergy platform is ChemAxon’s approach to SaaS solutions for chemistry related R&D data management. It provides an integrated system that cleans, organizes and links together pre-clinical research data and a collaborative workspace where people from multiple sites can work with each other, as well as with CROs and partners. Besides giving a summary of the fundamental platform components, the presentation guides the audience through the process of capturing chemical data in our Compound Registration tool, uploading and standardizing assay results and visualizing, as well as analyzing combined chemical data and biological results.
Cheminfo Stories APAC 2020 - Introducing Design Hub & Compound Registration
This webinar will guide you through the Design Hub platform for scientific design and discovery project management using an antiviral compound optimization example. The workflow starts from capturing the first observation and corresponding hypothesis, showcase compound design relying on a vast amount of information sources and predictive models, including the new hERG toxicity prediction and docking using RDock. It will highlight how tracking the fate of compound ideas created as draft virtual compounds through synthesis targets and finally registered samples is fluently managed by the interaction of Design Hub and Compound Registration system.
Cheminfo Stories APAC 2020 - JChem Engines introduction
This document introduces ChemAxon's second generation JChem search engines, including the JChem PostgreSQL Cartridge and JChem Choral engine. It summarizes the key advantages like improved performance on large databases, enhanced tautomer matching, and new features. It also outlines how the different search products like cartridges and microservices are suited for different use cases and environments.
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This document provides an overview and summary of key features for JChem for Office and Instant JChem (IJC). JChem for Office allows embedding of live chemical structures in Microsoft Office files and includes features like chemical searching, properties calculations, and virtual library enumeration. IJC is a versatile data management framework that allows users to create, explore, share, and analyze chemical data through a project explorer interface, query builder, and grid/form views of data. It supports both structural and non-structural data management and analysis.
Cheminfo Stories APAC 2020 -- Markush technology
The document discusses Markush structures, which are used in patent claims to cover large numbers of similar chemical compounds using generalized structures. It presents tools for searching, visualizing, and extracting Markush structures from patents to help with tasks like idea validation, patent drafting, and understanding competitors' intellectual property. The case study demonstrates how these tools can be used to automatically validate that patent claims cover examples listed in the description.
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JChem Microservices provide microservices in small separate modules for different areas of ChemAxon functionalities like chemical dataset searching, conversion between chemical file formats.
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This document outlines the steps for migrating from the JChem Oracle Cartridge (JOC) to the JChem PostgreSQL Cartridge (JPC) or Choral. It discusses the reasons for migration, strategies for large ecosystems, non-cartridge migration steps, and cartridge-specific data and code migration steps. Key points include moving to new features, performance gains, compatibility with PostgreSQL and Amazon RDS, and references for more information.
ChemAxon's Compliance Checker - Cheminfo Stories 2020 Day 5
This document discusses Compliance Checker, a SaaS tool for compound screening and subscriptions. It offers different subscription tiers (Lite, Standard) with varying features - such as number of users, compounds screened per second, authentication method, and data storage. The Standard subscriptions include Basic, Medium, Professional and Premium options that provide different levels of support, performance, high availability, and license scope. The Lite subscription can be monthly, quarterly or annual based on the number of compounds that can be screened.
Chemicalize Pro - Cheminfo Stories 2020 Day 5
Chemicalize is an online SaaS product providing UI based chemical calculations, drawing and searching as well as API based endpoints for integrators and embeddable web components for website owners. In the presentation we introduce the service and showing the essence of the embeddable web components through a real-life use case focusing on the compliance questions.
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- 2. Outline History of the Compound Registration product A typical corporate architecture Demo Other configuration options
- 4. Registration Services Compound Registry Web based GUI Poller services Upstream Data Sources (ELN, IJC DBs) Amendment Staging Area Submission Correction Downstream services Form based registration Bulk Registration Other DBs Compound Repository Browser based GUI (IJC Web, Plexus) Search and reporting Audit Administration Search Autoregistration service A typical corporate architecture
- 5. Demo
- 7. Summary