The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Pred‐hERG: A Novel web‐Accessible Computational Tool for Predicting Cardiac Toxicity
Open accessAbstract
The blockage of the hERG K+ channels is closely associated with lethal cardiac arrhythmia. The notorious ligand promiscuity of this channel earmarked hERG as one of the most important antitargets to be considered in early stages of drug development process. Herein we report on the development of an innovative and freely accessible web server for early identification of putative hERG blockers and non‐blockers in chemical libraries. We have collected the largest publicly available curated hERG dataset of 5,984 compounds. We succeed in developing robust and externally predictive binary (CCR≈0.8) and multiclass models (accuracy≈0.7). These models are available as a web‐service freely available for public at http://labmol.farmacia.ufg.br/predherg/. Three following outcomes are available for the users: prediction by binary model, prediction by multi‐class model, and the probability maps of atomic contribution. The Pred‐hERG will be continuously updated and upgraded as new information became available.
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Self-citationDoes Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?
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Self-citationJSME: a free molecule editor in JavaScript
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Interpretation of Quantitative Structure-Activity Relationship Models: Past, Present, and Future
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eToxPred: a machine learning-based approach to estimate the toxicity of drug candidates
Pu, L., Naderi, M., Liu, T., Wu, H.-C., Mukhopadhyay, S., & Brylinski, M. (2019) · BMC Pharmacology and Toxicology · doi:10.1186/s40360-018-0282-6 · Cited by 212
“A recently developed method, Pred-hERG, estimates the cardiac toxicity with a set of features based on statistically significant and externally predictive QSAR models of the hERG blockage [26].”
MethodAlarms about structural alerts
Alves, V. M., Muratov, E. N., Capuzzi, S. J., Politi, R., Low, Y., Braga, R. C., Zakharov, A. V., Sedykh, A., Mokshyna, E., Farag, S., et al. (2016) · Green Chemistry · doi:10.1039/c6gc01492e · Cited by 133
Self-citationHancox, J. C., Wang, Y., Copeland, C. S., Zhang, H., Harmer, S. C., & Henderson, G. (2024) · Journal of Molecular and Cellular Cardiology Plus · doi:10.1016/j.jmccpl.2024.100118 · Cited by 5
Metadata
- Authors
- Braga, R. C., Alves, V. M., Silva, M. F. B., Muratov, E., Fourches, D., Lião, L. M., Tropsha, A., & Andrade, C. H.
- Venue
- Molecular Informatics
- Publisher
- Wiley
- Published
- 2015-07-20
- Volume
- 34
- Issue
- 10
- Pages
- 698-701
- ISSN
- 1868-1743 (ISSN-L)
- 1868-1751
- OpenAlex
- W2160305962
- Cited by
- 256
- References
- 19
- FWCI
- 8.98
- Type
- journal article
- Language
- en
- Open access
- green
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- Braga, R. C., Alves, V. M., Silva, M. F. B., Muratov, E., Fourches, D., Lião, L. M., Tropsha, A., & Andrade, C. H. (2015). Pred‐hERG: A Novel web‐Accessible Computational Tool for Predicting Cardiac Toxicity. Molecular Informatics. https://doi.org/10.1002/minf.201500040
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