FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2043113066> ?p ?o ?g. }

• W2043113066 endingPage "127" @default.
• W2043113066 startingPage "117" @default.
• W2043113066 abstract "The human Ether-a-go-go Related Gene (hERG) potassium channel is one of the major critical factors associated with QT interval prolongation and development of arrhythmia called Torsades de Pointes (TdP). It has become a growing concern of both regulatory agencies and pharmaceutical industries who invest substantial effort in the assessment of cardiac toxicity of drugs. The development of in silico tools to filter out potential hERG channel inhibitors in early stages of the drug discovery process is of considerable interest. Here, we describe binary classification models based on a large and diverse library of 495 compounds. The models combine pharmacophore-based GRIND descriptors with a support vector machine (SVM) classifier in order to discriminate between hERG blockers and nonblockers. Our models were applied at different thresholds from 1 to 40 microm and achieved an overall accuracy up to 94% with a Matthews coefficient correlation (MCC) of 0.86 ( F-measure of 0.90 for blockers and 0.95 for nonblockers). The model at a 40 microm threshold showed the best performance and was validated internally (MCC of 0.40 and F-measure of 0.57 for blockers and 0.81 for nonblockers, using a leave-one-out cross-validation). On an external set of 66 compounds, 72% of the set was correctly predicted ( F-measure of 0.86 and 0.34 for blockers and nonblockers, respectively). Finally, the model was also tested on a large set of hERG bioassay data recently made publicly available on PubChem ( http://pubchem.ncbi.nlm.nih.gov/assay/assay.cgi?aid=376) to achieve about 73% accuracy ( F-measure of 0.30 and 0.83 for blockers and nonblockers, respectively). Even if there is still some limitation in the assessment of hERG blockers, the performance of our model shows an improvement between 10% and 20% in the prediction of blockers compared to other methods, which can be useful in the filtering of potential hERG channel inhibitors." @default.
• W2043113066 created "2016-06-24" @default.
• W2043113066 creator A5005294445 @default.
• W2043113066 creator A5046853170 @default.
• W2043113066 creator A5061685157 @default.
• W2043113066 creator A5074122105 @default.
• W2043113066 creator A5075393358 @default.
• W2043113066 date "2008-01-16" @default.
• W2043113066 modified "2023-10-18" @default.
• W2043113066 title "hERG Classification Model Based on a Combination of Support Vector Machine Method and GRIND Descriptors" @default.
• W2043113066 cites W1559072304 @default.
• W2043113066 cites W1963748793 @default.
• W2043113066 cites W1964940342 @default.
• W2043113066 cites W1968138630 @default.
• W2043113066 cites W1968956582 @default.
• W2043113066 cites W1987388257 @default.
• W2043113066 cites W1991739064 @default.
• W2043113066 cites W2006964534 @default.
• W2043113066 cites W2013537099 @default.
• W2043113066 cites W2014746876 @default.
• W2043113066 cites W2014886686 @default.
• W2043113066 cites W2015795498 @default.
• W2043113066 cites W2021049589 @default.
• W2043113066 cites W2025847642 @default.
• W2043113066 cites W2030541138 @default.
• W2043113066 cites W2032734987 @default.
• W2043113066 cites W2033643779 @default.
• W2043113066 cites W2035001688 @default.
• W2043113066 cites W2039166600 @default.
• W2043113066 cites W2040826404 @default.
• W2043113066 cites W2048066067 @default.
• W2043113066 cites W2048975664 @default.
• W2043113066 cites W2051669906 @default.
• W2043113066 cites W2054466265 @default.
• W2043113066 cites W2056593372 @default.
• W2043113066 cites W2058895283 @default.
• W2043113066 cites W2061927735 @default.
• W2043113066 cites W2063821958 @default.
• W2043113066 cites W2066557345 @default.
• W2043113066 cites W2067098334 @default.
• W2043113066 cites W2070624290 @default.
• W2043113066 cites W2071374372 @default.
• W2043113066 cites W2078183328 @default.
• W2043113066 cites W2078257795 @default.
• W2043113066 cites W2083488506 @default.
• W2043113066 cites W2087661061 @default.
• W2043113066 cites W2089468765 @default.
• W2043113066 cites W2092086698 @default.
• W2043113066 cites W2096907369 @default.
• W2043113066 cites W2100905521 @default.
• W2043113066 cites W2101204196 @default.
• W2043113066 cites W2107763854 @default.
• W2043113066 cites W2113927644 @default.
• W2043113066 cites W2123048529 @default.
• W2043113066 cites W2128780696 @default.
• W2043113066 cites W2130566541 @default.
• W2043113066 cites W2134670392 @default.
• W2043113066 cites W2138538314 @default.
• W2043113066 cites W2143070723 @default.
• W2043113066 cites W2151040995 @default.
• W2043113066 cites W2151378419 @default.
• W2043113066 cites W2158965509 @default.
• W2043113066 cites W2164829352 @default.
• W2043113066 cites W2950965966 @default.
• W2043113066 cites W2952142422 @default.
• W2043113066 doi "https://doi.org/10.1021/mp700124e" @default.
• W2043113066 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18197627" @default.
• W2043113066 hasPublicationYear "2008" @default.
• W2043113066 type Work @default.
• W2043113066 sameAs 2043113066 @default.
• W2043113066 citedByCount "86" @default.
• W2043113066 countsByYear W20431130662012 @default.
• W2043113066 countsByYear W20431130662013 @default.
• W2043113066 countsByYear W20431130662014 @default.
• W2043113066 countsByYear W20431130662015 @default.
• W2043113066 countsByYear W20431130662016 @default.
• W2043113066 countsByYear W20431130662017 @default.
• W2043113066 countsByYear W20431130662018 @default.
• W2043113066 countsByYear W20431130662019 @default.
• W2043113066 countsByYear W20431130662020 @default.
• W2043113066 countsByYear W20431130662021 @default.
• W2043113066 countsByYear W20431130662022 @default.
• W2043113066 countsByYear W20431130662023 @default.
• W2043113066 crossrefType "journal-article" @default.
• W2043113066 hasAuthorship W2043113066A5005294445 @default.
• W2043113066 hasAuthorship W2043113066A5046853170 @default.
• W2043113066 hasAuthorship W2043113066A5061685157 @default.
• W2043113066 hasAuthorship W2043113066A5074122105 @default.
• W2043113066 hasAuthorship W2043113066A5075393358 @default.
• W2043113066 hasConcept C103697762 @default.
• W2043113066 hasConcept C104317684 @default.
• W2043113066 hasConcept C118441451 @default.
• W2043113066 hasConcept C119857082 @default.
• W2043113066 hasConcept C12267149 @default.
• W2043113066 hasConcept C126322002 @default.
• W2043113066 hasConcept C134018914 @default.
• W2043113066 hasConcept C154945302 @default.
• W2043113066 hasConcept C158180186 @default.

• next