Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds
Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cappelli, Claudia Ileana [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013transfer abstract |
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| Umfang: |
9 |
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| Übergeordnetes Werk: |
Enthalten in: SPG-56 from Sweet potato Zhongshu-1 delayed growth of tumor xenografts in nude mice by modulating gut microbiota - Wang, Meimei ELSEVIER, 2018, an international journal for scientific research into the environment and its relationship with man, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:463 ; year:2013 ; day:1 ; month:10 ; pages:781-789 ; extent:9 |
| Links: |
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| DOI / URN: |
10.1016/j.scitotenv.2013.06.081 |
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| 520 | |a Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. | ||
| 520 | |a Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. | ||
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10.1016/j.scitotenv.2013.06.081 doi GBVA2013022000028.pica (DE-627)ELV01195258X (ELSEVIER)S0048-9697(13)00733-X DE-627 ger DE-627 rakwb eng 333.7 610 333.7 DE-600 610 DE-600 630 640 610 VZ Cappelli, Claudia Ileana verfasserin aut Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds 2013transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. Manganelli, Serena oth Lombardo, Anna oth Gissi, Andrea oth Benfenati, Emilio oth Enthalten in Elsevier Science Wang, Meimei ELSEVIER SPG-56 from Sweet potato Zhongshu-1 delayed growth of tumor xenografts in nude mice by modulating gut microbiota 2018 an international journal for scientific research into the environment and its relationship with man Amsterdam [u.a.] (DE-627)ELV001360035 volume:463 year:2013 day:1 month:10 pages:781-789 extent:9 https://doi.org/10.1016/j.scitotenv.2013.06.081 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 463 2013 1 1001 781-789 9 045F 333.7 |
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10.1016/j.scitotenv.2013.06.081 doi GBVA2013022000028.pica (DE-627)ELV01195258X (ELSEVIER)S0048-9697(13)00733-X DE-627 ger DE-627 rakwb eng 333.7 610 333.7 DE-600 610 DE-600 630 640 610 VZ Cappelli, Claudia Ileana verfasserin aut Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds 2013transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. Manganelli, Serena oth Lombardo, Anna oth Gissi, Andrea oth Benfenati, Emilio oth Enthalten in Elsevier Science Wang, Meimei ELSEVIER SPG-56 from Sweet potato Zhongshu-1 delayed growth of tumor xenografts in nude mice by modulating gut microbiota 2018 an international journal for scientific research into the environment and its relationship with man Amsterdam [u.a.] (DE-627)ELV001360035 volume:463 year:2013 day:1 month:10 pages:781-789 extent:9 https://doi.org/10.1016/j.scitotenv.2013.06.081 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 463 2013 1 1001 781-789 9 045F 333.7 |
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10.1016/j.scitotenv.2013.06.081 doi GBVA2013022000028.pica (DE-627)ELV01195258X (ELSEVIER)S0048-9697(13)00733-X DE-627 ger DE-627 rakwb eng 333.7 610 333.7 DE-600 610 DE-600 630 640 610 VZ Cappelli, Claudia Ileana verfasserin aut Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds 2013transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. Manganelli, Serena oth Lombardo, Anna oth Gissi, Andrea oth Benfenati, Emilio oth Enthalten in Elsevier Science Wang, Meimei ELSEVIER SPG-56 from Sweet potato Zhongshu-1 delayed growth of tumor xenografts in nude mice by modulating gut microbiota 2018 an international journal for scientific research into the environment and its relationship with man Amsterdam [u.a.] (DE-627)ELV001360035 volume:463 year:2013 day:1 month:10 pages:781-789 extent:9 https://doi.org/10.1016/j.scitotenv.2013.06.081 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 463 2013 1 1001 781-789 9 045F 333.7 |
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10.1016/j.scitotenv.2013.06.081 doi GBVA2013022000028.pica (DE-627)ELV01195258X (ELSEVIER)S0048-9697(13)00733-X DE-627 ger DE-627 rakwb eng 333.7 610 333.7 DE-600 610 DE-600 630 640 610 VZ Cappelli, Claudia Ileana verfasserin aut Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds 2013transfer abstract 9 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. Manganelli, Serena oth Lombardo, Anna oth Gissi, Andrea oth Benfenati, Emilio oth Enthalten in Elsevier Science Wang, Meimei ELSEVIER SPG-56 from Sweet potato Zhongshu-1 delayed growth of tumor xenografts in nude mice by modulating gut microbiota 2018 an international journal for scientific research into the environment and its relationship with man Amsterdam [u.a.] (DE-627)ELV001360035 volume:463 year:2013 day:1 month:10 pages:781-789 extent:9 https://doi.org/10.1016/j.scitotenv.2013.06.081 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 463 2013 1 1001 781-789 9 045F 333.7 |
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330 - Economics 610 - Medicine & health 630 - Agriculture 640 - Home & family management |
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SPG-56 from Sweet potato Zhongshu-1 delayed growth of tumor xenografts in nude mice by modulating gut microbiota |
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Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds |
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(DE-627)ELV01195258X (ELSEVIER)S0048-9697(13)00733-X |
| title_full |
Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds |
| author_sort |
Cappelli, Claudia Ileana |
| journal |
SPG-56 from Sweet potato Zhongshu-1 delayed growth of tumor xenografts in nude mice by modulating gut microbiota |
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SPG-56 from Sweet potato Zhongshu-1 delayed growth of tumor xenografts in nude mice by modulating gut microbiota |
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eng |
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300 - Social sciences 600 - Technology |
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2013 |
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Cappelli, Claudia Ileana |
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Elektronische Aufsätze |
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Cappelli, Claudia Ileana |
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10.1016/j.scitotenv.2013.06.081 |
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333.7 610 630 640 |
| title_sort |
validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds |
| title_auth |
Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds |
| abstract |
Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. |
| abstractGer |
Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. |
| abstract_unstemmed |
Water-solubility is an important physicochemical property in pharmaceutical and environmental studies. We assessed the performance of five predictive computer models: ACD/PhysChem History, ADMET Predictor, T.E.S.T., EPI Suite-WSKOWWIN and EPI Suite-WATERNT; two of them are commercial, the others are free. We used more than 4000 compounds with experimental values to evaluate the models, considering the chemicals inside and outside the applicability domain of the models, those used to build up the model (training set) and those not present in it (prediction set). We also evaluated their ability to predict continuous solubility values, and solubility classes. Overall, considering the whole data set, some models gave a good statistical performance, with R2 up to 0.88. |
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| title_short |
Validation of quantitative structure–activity relationship models to predict water-solubility of organic compounds |
| url |
https://doi.org/10.1016/j.scitotenv.2013.06.081 |
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true |
| author2 |
Manganelli, Serena Lombardo, Anna Gissi, Andrea Benfenati, Emilio |
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Manganelli, Serena Lombardo, Anna Gissi, Andrea Benfenati, Emilio |
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10.1016/j.scitotenv.2013.06.081 |
| up_date |
2024-07-06T21:08:49.369Z |
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