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Machine-readable assay protocols
Alex M. Clark
http://collaborativedrug.com
The 21st century (supposedly)
2
504854 449764A Cell Based Secondary Assay To Explore Vero Cell Cytotoxicity of Purified and Synthesized Compounds that Inhibit Mycobacterium Tuberculosis (4)
This functional assay was developed for detection of compounds inhibiting Vero E6 cells viability as a secondary screen to the beta-lactam sensitizing M. tuberculosis bacteriocidal assay.
In this assay, we treated Vero E6 cells with compounds selected as hits in the M. tuberculosis assay for 72 hours over a 10 point 2-fold dilution series, ranging from 0.195 uM to 100 uM. Following 72 hours of treatment, relative viable cell number was determined using Cell Titer Glo from Promega. Each plate contained 64 replicates of vehicle treated cells which served as negative controls.
Outcome: Compounds that showed <70% cell viability for at least one concentration were defined as "Active". If the % viability at all doses was >70%, the compound was defined as "Inactive".
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A High Throughput Confirmatory Assay used to Identify Novel Compounds that Inhibit Mycobacterium Tuberculosis in the absence of Glycerol
Outcome: Compounds that showed >30% inhibition for at least one concentration in the Mtb dose response were defined as "Active". If the inhibition at all doses was <30% in the Mtb assay, the compound was defined as "Inactive". In the primary screen a compound was deemed "Inactive" if it had a Percent Inhibition <70.31%. Compounds with a Percent Inhibition >70.31% but were not selected for follow up dose response were labeled "Inconclusive."
The following tiered system has been implemented at Southern Research Institute for use with the PubChem Score. Compounds in the primary screen are scored on a scale of 0-40 based on inhibitory activity where a score of 40 corresponds to 100% inhibition. In the confirmatory dose response screen, active compounds were scored on a scale of 41-80 based on the IC50 result in the Mtb assay while compounds that did not confirm as actives were given the score 0.
...
69% similar (?)
Common Assay Template
• Built from semantic web ontologies:
BioAssay Ontology (BAO) Drug Target Ontology (DTO) Cell Line Ontology (CLO) Gene Ontology (GO) ... and others
• Each annotated term is a URI: compatible with the universe of linked data
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New Templates
• Editor and schema are open source:
http://github.com/cdd/bioassay-template
• The Common Assay Template (CAT) designed mainly for assays from NIH Molecular Libraries Program: to capture high level characteristics
• Personalised templates can be created
• Other general templates are planned: Toxicity ?
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Content Creation• Refining the template & user interface, and generating
training data, using text from PubChem assays:
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Machine Learning• Existing data used for learning: proposed annotations
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natural language
processing
Bayesian models
Ontology Branches
• Each annotation is part of a tree structure
• Inheritance provides extra layers of meaning
• From common assay template + ontologies
• Updated as ontologies are extended or modified
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Interoperability• Service auto-downloads assays from PubChem:
whitelisted sources (mainly MLPCN)
• Curated assays can be downloaded via API
using semantic web formats (Turtle/RDF/JSON-LD)
• Adding finalised content currently by manual upload
• Discussions with PubChem regarding two way communication, e.g. sending annotations back to the original assay record
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Deployment• www.bioassayexpress.com is public
currently used as a read-only service evolving rapidly with new experimental features free as in beer, not speech
• Private installations and derived products are planned
• Key features will be integrated into CDD Vault & ELN
• Core components & data model open source (GitHub): community adoption is welcomed
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Probes Report• Possible use case
(work in progress)
• Rows: NIH probe compounds
• Columns: Curated assay targets
• Retroactive look at the data: more of it, better quality
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Future Features• Semantic annotation of assays: make it really easy
ELNs are immediate benefactors tag, organise, search for assay protocols
• Model building: thousands of datasets - which of them are measuring the same property in the same way?
• Deep machine learning analysis (open ended!)
• Advanced schema: encode the entire protocol
• An alternative to text: annotate first, automatic report
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Toxicity Data
• One approach might be to design a new schema (e.g. the Toxicity Assay Template)
• Submission of data such as ToxCast into PubChem, divided into assays and compounds...
• ... trigger automatic downloading into BioAssay Express, allowing them to be annotated
• Annotating a large number of toxicity assays would open a universe of possibilities
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Acknowledgments• Biologists
Janice Kranz Haifa Ghandour Karen Featherstone
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• Collaborative Drug Discovery
Barry Bunin Kellan Gregory and the rest of the team
• More information
http://github.com/cdd/bioassay-templatehttp://www.bioassayexpress.com
http://collaborativedrug.com
PeerJ Comp Sci
2:e61 (2016)