myChEMBL: a virtual machine implementation of open data and cheminformatics tools

Ochoa, Rodrigo; Davies, Mark; Papadatos, George; Atkinson, Francis; Overington, John P.

doi:10.1093/bioinformatics/btt666

Cited by 18 publications

(17 citation statements)

References 5 publications

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“…The myChEMBL software container is also available (47,48). It is distributed as a virtual machine disk image in many formats such as VMDK, QCOW2 and IMG that can be downloaded using FTP or Vagrant.…”

Section: Data Accessmentioning

confidence: 99%

The ChEMBL database in 2017

et al. 2016

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ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 and 2014 Nucleic Acids Research Database Issues. Since then, alongside the continued extraction of data from the medicinal chemistry literature, new sources of bioactivity data have also been added to the database. These include: deposited data sets from neglected disease screening; crop protection data; drug metabolism and disposition data and bioactivity data from patents. A number of improvements and new features have also been incorporated. These include the annotation of assays and targets using ontologies, the inclusion of targets and indications for clinical candidates, addition of metabolic pathways for drugs and calculation of structural alerts. The ChEMBL data can be accessed via a web-interface, RDF distribution, data downloads and RESTful web-services.

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Section: Data Accessmentioning

confidence: 99%

The ChEMBL database in 2017

et al. 2016

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“…Lilly has developed their Open Innovation Drug Discovery platform [229] where participating investigators get access to tools and predictions by Lilly software and data via a virtual machine where they can, for example, submit compounds for in silico evaluation. The widely used ChEMBL database makes the data and tools available as a virtual machine via the myChEMBL package [230]. Virtual machines are also a necessity for Big Data frameworks in drug discovery, for example, implementing docking on Hadoop [231] and Apache Spark [232].…”

Section: Virtual Machinesmentioning

confidence: 99%

“…combinatorial library generation, substructure search as well as ligand and protein-ligand structure visualization). Furthermore, myChEMBL [230] is an open source virtual machine that Aside from the research aspect, educational codebased tutorials on computational drug discovery has been initiated using the Java-based Chemistry Development Kit (CDK) [204,205,271] as implemented by the Teach-Discover-Treat (TDT) initiative [272]. This resulted in the development of Python-based tutorials pertaining to the virtual screening workflow to identify malarial drugs [273,274].…”

Section: Workflows For Computational Drug Discoverymentioning

confidence: 99%

Towards reproducible computational drug discovery

et al. 2020

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The reproducibility of experiments has been a long standing impediment for further scientific progress. Computational methods have been instrumental in drug discovery efforts owing to its multifaceted utilization for data collection, pre-processing, analysis and inference. This article provides an in-depth coverage on the reproducibility of computational drug discovery. This review explores the following topics: (1) the current state-of-the-art on reproducible research, (2) research documentation (e.g. electronic laboratory notebook, Jupyter notebook, etc.), (3) science of reproducible research (i.e. comparison and contrast with related concepts as replicability, reusability and reliability), (4) model development in computational drug discovery, (5) computational issues on model development and deployment, (6) use case scenarios for streamlining the computational drug discovery protocol. In computational disciplines, it has become common practice to share data and programming codes used for numerical calculations as to not only facilitate reproducibility, but also to foster collaborations (i.e. to drive the project further by introducing new ideas, growing the data, augmenting the code, etc.). It is therefore inevitable that the field of computational drug design would adopt an open approach towards the collection, curation and sharing of data/code.

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“…This system has been augmented by new tools to use structural protein–ligand interaction data from KRIPO, 30 GPCRdb, 27 and KLIFS 28,29 databases and has been made publically available on GitHub (). The previously reported myChEMBL VM 33 provided a useful template to design the 3D-e-Chem-VM and a local copy of the ChEMBL database 19 can optionally be incorporated into the VM (). The 3D-e-Chem-VM is available in the Vagrant 34 box catalog of HashiCorp called Atlas.…”

Section: Introductionmentioning

confidence: 99%

3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine

McGuire

Verhoeven

Vass

et al. 2017

J. Chem. Inf. Model.

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3D-e-Chem-VM is an open source, freely available Virtual Machine () that integrates cheminformatics and bioinformatics tools for the analysis of protein–ligand interaction data. 3D-e-Chem-VM consists of software libraries, and database and workflow tools that can analyze and combine small molecule and protein structural information in a graphical programming environment. New chemical and biological data analytics tools and workflows have been developed for the efficient exploitation of structural and pharmacological protein–ligand interaction data from proteomewide databases (e.g., ChEMBLdb and PDB), as well as customized information systems focused on, e.g., G protein-coupled receptors (GPCRdb) and protein kinases (KLIFS). The integrated structural cheminformatics research infrastructure compiled in the 3D-e-Chem-VM enables the design of new approaches in virtual ligand screening (Chemdb4VS), ligand-based metabolism prediction (SyGMa), and structure-based protein binding site comparison and bioisosteric replacement for ligand design (KRIPOdb).

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myChEMBL: a virtual machine implementation of open data and cheminformatics tools

Cited by 18 publications

References 5 publications

The ChEMBL database in 2017

The ChEMBL database in 2017

Towards reproducible computational drug discovery

3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine

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