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Pharmaceutical Research

, 35:170 | Cite as

Naïve Bayesian Models for Vero Cell Cytotoxicity

  • Alexander L. Perryman
  • Jimmy S. Patel
  • Riccardo Russo
  • Eric Singleton
  • Nancy Connell
  • Sean Ekins
  • Joel S. Freundlich
Research Paper

Abstract

Purpose

To advance translational research of potential therapeutic small molecules against infectious microbes, the compounds must display a relative lack of mammalian cell cytotoxicity. Vero cell cytotoxicity (CC50) is a common initial assay for this metric. We explored the development of naïve Bayesian models that can enhance the probability of identifying non-cytotoxic compounds.

Methods

Vero cell cytotoxicity assays were identified in PubChem, reformatted, and curated to create a training set with 8741 unique small molecules. These data were used to develop Bayesian classifiers, which were assessed with internal cross-validation, external tests with a set of 193 compounds from our laboratory, and independent validation with an additional diverse set of 1609 unique compounds from PubChem.

Results

Evaluation with independent, external test and validation sets indicated that cytotoxicity Bayesian models constructed with the ECFP_6 descriptor were more accurate than those that used FCFP_6 fingerprints. The best cytotoxicity Bayesian model displayed predictive power in external evaluations, according to conventional and chance-corrected statistics, as well as enrichment factors.

Conclusions

The results from external tests demonstrate that our novel cytotoxicity Bayesian model displays sufficient predictive power to help guide translational research. To assist the chemical tool and drug discovery communities, our curated training set is being distributed as part of the Supplementary Material.

Graphical Abstract

Naive Bayesian models have been trained with publically available data and offer a useful tool for chemical biology and drug discovery to select for small molecules with a high probability of exhibiting acceptably low Vero cell cytotoxicity.

Key Words

Bayesian model machine learning predicting mammalian cytotoxicity translational research vero cell CC50 

Abbreviations

ADME/Tox

Absorption, metabolism, distribution, excretion and toxicity

AID

Assay Identification number on PubChem BioAssay

ECFP_6

Extended class fingerprints of maximum diameter 6

FCFP_6

Molecular function class fingerprints of maximum diameter 6

NPV

Negative predictive value (filtering rate)

PPV

Positive predictive value (hit rate)

QSAR

Quantitative Structure-Activity Relationships

ROC

Receiver-operator characteristic

SAR

Structure-Activity Relationship

SMILES

Simplified molecular-input line-entry system

Vero CC50

Vero cell (African green monkey kidney cell) 50% cytotoxicity value

Notes

Compliance with Ethical Standards

Conflicts of Interest

S.E. is the Founder and CEO of Collaborations Pharmaceuticals Inc.

Supplementary material

11095_2018_2439_MOESM1_ESM.docx (1.3 mb)
ESM 1 (DOCX 1.29 mb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Pharmacology, Physiology and Neuroscience, and MedicineRutgers University-New Jersey Medical SchoolNewarkUSA
  2. 2.Division of Infectious Diseases, Department of Medicine, and the Ruy V. Lourenço Center for the Study of Emerging and Re-emerging PathogensRutgers University–New Jersey Medical SchoolNewarkUSA
  3. 3.Collaborations Pharmaceuticals, Inc.RaleighUSA

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