Machine Learning-based Prediction of Enzyme Substrate Scope: Application to Bacterial Nitrilases Article Swipe
Zhongyu Mou
,
Jason Eakes
,
Connor J. Cooper
,
Carmen M. Foster
,
Robert F. Standaert
,
Mircea Podar
,
Mitchel J. Doktycz
,
J. E. Parks
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.22541/au.158888180.03951231
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.22541/au.158888180.03951231
Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequence- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (linear regression, random forest, gradient-boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset. The approach is intended to be highly modular with respect to physicochemical property calculations and software used for docking and modeling.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.22541/au.158888180.03951231
- https://papers.cociwg.org/doi/pdf/10.22541/au.158888180.03951231
- OA Status
- gold
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4243595344
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4243595344Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.22541/au.158888180.03951231Digital Object Identifier
- Title
-
Machine Learning-based Prediction of Enzyme Substrate Scope: Application to Bacterial NitrilasesWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2020Year of publication
- Publication date
-
2020-05-07Full publication date if available
- Authors
-
Zhongyu Mou, Jason Eakes, Connor J. Cooper, Carmen M. Foster, Robert F. Standaert, Mircea Podar, Mitchel J. Doktycz, J. E. ParksList of authors in order
- Landing page
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https://doi.org/10.22541/au.158888180.03951231Publisher landing page
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https://papers.cociwg.org/doi/pdf/10.22541/au.158888180.03951231Direct link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://papers.cociwg.org/doi/pdf/10.22541/au.158888180.03951231Direct OA link when available
- Concepts
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Support vector machine, Machine learning, Artificial intelligence, Docking (animal), Computer science, Scope (computer science), Random forest, Substrate (aquarium), Chemistry, Combinatorial chemistry, Biology, Programming language, Medicine, Nursing, EcologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2021: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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