Behrendt, Annika ; Golchin, Pegah ; König, Filip ; Mulnaes, Daniel ; Stalke, Amelie ; Dröge, Carola ; Keitel, Verena ; Gohlke, Holger (2022)
Vasor: Accurate prediction of variant effects for amino acid substitutions in multidrug resistance protein 3.
In: Hepatology Communications, 6 (11)
doi: 10.1002/hep4.2088
Artikel, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
The phosphatidylcholine floppase multidrug resistance protein 3 (MDR3) is an essential hepatobiliary transport protein. MDR3 dysfunction is associated with various liver diseases, ranging from severe progressive familial intrahepatic cholestasis to transient forms of intrahepatic cholestasis of pregnancy and familial gallstone disease. Single amino acid substitutions are often found as causative of dysfunction, but identifying the substitution effect in in vitro studies is time and cost intensive. We developed variant assessor of MDR3 (Vasor), a machine learning‐based model to classify novel MDR3 missense variants into the categories benign or pathogenic. Vasor was trained on the largest data set to date that is specific for benign and pathogenic variants of MDR3 and uses general predictors, namely Evolutionary Models of Variant Effects (EVE), EVmutation, PolyPhen‐2, I‐Mutant2.0, MUpro, MAESTRO, and PON‐P2 along with other variant properties, such as half‐sphere exposure and posttranslational modification site, as input. Vasor consistently outperformed the integrated general predictors and the external prediction tool MutPred2, leading to the current best prediction performance for MDR3 single‐site missense variants (on an external test set: F1‐score, 0.90; Matthew's correlation coefficient, 0.80). Furthermore, Vasor predictions cover the entire sequence space of MDR3. Vasor is accessible as a webserver at https://cpclab.uni‐duesseldorf.de/mdr3_predictor/ for users to rapidly obtain prediction results and a visualization of the substitution site within the MDR3 structure. The MDR3‐specific prediction tool Vasor can provide reliable predictions of single‐site amino acid substitutions, giving users a fast way to initially assess whether a variant is benign or pathogenic.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Behrendt, Annika ; Golchin, Pegah ; König, Filip ; Mulnaes, Daniel ; Stalke, Amelie ; Dröge, Carola ; Keitel, Verena ; Gohlke, Holger |
| Art des Eintrags: | Bibliographie |
| Titel: | Vasor: Accurate prediction of variant effects for amino acid substitutions in multidrug resistance protein 3 |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Ort: | Darmstadt |
| Verlag: | Wiley |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Hepatology Communications |
| Jahrgang/Volume einer Zeitschrift: | 6 |
| (Heft-)Nummer: | 11 |
| DOI: | 10.1002/hep4.2088 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | The phosphatidylcholine floppase multidrug resistance protein 3 (MDR3) is an essential hepatobiliary transport protein. MDR3 dysfunction is associated with various liver diseases, ranging from severe progressive familial intrahepatic cholestasis to transient forms of intrahepatic cholestasis of pregnancy and familial gallstone disease. Single amino acid substitutions are often found as causative of dysfunction, but identifying the substitution effect in in vitro studies is time and cost intensive. We developed variant assessor of MDR3 (Vasor), a machine learning‐based model to classify novel MDR3 missense variants into the categories benign or pathogenic. Vasor was trained on the largest data set to date that is specific for benign and pathogenic variants of MDR3 and uses general predictors, namely Evolutionary Models of Variant Effects (EVE), EVmutation, PolyPhen‐2, I‐Mutant2.0, MUpro, MAESTRO, and PON‐P2 along with other variant properties, such as half‐sphere exposure and posttranslational modification site, as input. Vasor consistently outperformed the integrated general predictors and the external prediction tool MutPred2, leading to the current best prediction performance for MDR3 single‐site missense variants (on an external test set: F1‐score, 0.90; Matthew's correlation coefficient, 0.80). Furthermore, Vasor predictions cover the entire sequence space of MDR3. Vasor is accessible as a webserver at https://cpclab.uni‐duesseldorf.de/mdr3_predictor/ for users to rapidly obtain prediction results and a visualization of the substitution site within the MDR3 structure. The MDR3‐specific prediction tool Vasor can provide reliable predictions of single‐site amino acid substitutions, giving users a fast way to initially assess whether a variant is benign or pathogenic. |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin, Gesundheit |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Multimedia Kommunikation |
| Hinterlegungsdatum: | 02 Aug 2024 12:47 |
| Letzte Änderung: | 02 Aug 2024 12:47 |
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| Suche nach Titel in: | TUfind oder in Google |
Verfügbare Versionen dieses Eintrags
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Vasor: Accurate prediction of variant effects for amino acid substitutions in multidrug resistance protein 3. (deposited 23 Dez 2022 13:09)
- Vasor: Accurate prediction of variant effects for amino acid substitutions in multidrug resistance protein 3. (deposited 02 Aug 2024 12:47) [Gegenwärtig angezeigt]
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