From Classification to Regression Multitasking QSAR Modeling Using a Novel Modular Neural Network: Simultaneous Prediction of Anticonvulsant Activity and Neurotoxicity of Succinimides
Samo za registrovane korisnike
2017
Autori
Antanasijević, DavorAntanasijević, Jelena
Trišović, Nemanja
Ušćumlić, Gordana
Pocajt, Viktor
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Succinimides, which contain a pharmacophore responsible for anticonvulsant activity, are frequently used antiepileptic drugs and the synthesis of their new derivatives with improved efficacy and tolerability presents an important task. Nowadays, multitarget/tasking methodologies focused on quantitative-structure activity relationships (mt-QSAR/mtk-QSAR) have an important role in the rational design of drugs since they enable simultaneous prediction of several standard measures of biological activities at diverse experimental conditions and against different biological targets. Relating to this very topic, the mt-QSAR/mtk-QSAR methodology can give only binary classification models, and as such, in this study a regression mtk-QSAR (rmtk-QSAR) model based on a novel modular neural network (MNN) has been proposed. The MNN uses standard classification mtk-QSAR models as input modules, while the regression is performed by the output module. The rmtk-QSAR model has been successfully developed... for the simultaneous prediction of anticonvulsant activity and neurotoxicity of succinimides, with a satisfactory accuracy in testing (R-2 = 0.87). Thus, the proposed mtk-QSAR regression method can be regarded as a viable alternative to the standard QSAR methodology.
Ključne reči:
succinimides / multitasking / QSAR / regression / modular neural networkIzvor:
Molecular Pharmaceutics, 2017, 14, 12, 4476-4484Izdavač:
- Amer Chemical Soc, Washington
Finansiranje / projekti:
- Razvoj i primena metoda i materijala za monitoring novih zagađujućih i toksičnih organskih materija i teških metala (RS-MESTD-Basic Research (BR or ON)-172007)
- Proučavanje sinteze, strukture i aktivnosti organskih jedinjenja prirodnog i sintetskog porekla (RS-MESTD-Basic Research (BR or ON)-172013)
DOI: 10.1021/acs.molpharmaceut.7b00582
ISSN: 1543-8384
PubMed: 29130688
WoS: 000417342400034
Scopus: 2-s2.0-85037633229
Institucija/grupa
Tehnološko-metalurški fakultetTY - JOUR AU - Antanasijević, Davor AU - Antanasijević, Jelena AU - Trišović, Nemanja AU - Ušćumlić, Gordana AU - Pocajt, Viktor PY - 2017 UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/3614 AB - Succinimides, which contain a pharmacophore responsible for anticonvulsant activity, are frequently used antiepileptic drugs and the synthesis of their new derivatives with improved efficacy and tolerability presents an important task. Nowadays, multitarget/tasking methodologies focused on quantitative-structure activity relationships (mt-QSAR/mtk-QSAR) have an important role in the rational design of drugs since they enable simultaneous prediction of several standard measures of biological activities at diverse experimental conditions and against different biological targets. Relating to this very topic, the mt-QSAR/mtk-QSAR methodology can give only binary classification models, and as such, in this study a regression mtk-QSAR (rmtk-QSAR) model based on a novel modular neural network (MNN) has been proposed. The MNN uses standard classification mtk-QSAR models as input modules, while the regression is performed by the output module. The rmtk-QSAR model has been successfully developed for the simultaneous prediction of anticonvulsant activity and neurotoxicity of succinimides, with a satisfactory accuracy in testing (R-2 = 0.87). Thus, the proposed mtk-QSAR regression method can be regarded as a viable alternative to the standard QSAR methodology. PB - Amer Chemical Soc, Washington T2 - Molecular Pharmaceutics T1 - From Classification to Regression Multitasking QSAR Modeling Using a Novel Modular Neural Network: Simultaneous Prediction of Anticonvulsant Activity and Neurotoxicity of Succinimides EP - 4484 IS - 12 SP - 4476 VL - 14 DO - 10.1021/acs.molpharmaceut.7b00582 ER -
@article{ author = "Antanasijević, Davor and Antanasijević, Jelena and Trišović, Nemanja and Ušćumlić, Gordana and Pocajt, Viktor", year = "2017", abstract = "Succinimides, which contain a pharmacophore responsible for anticonvulsant activity, are frequently used antiepileptic drugs and the synthesis of their new derivatives with improved efficacy and tolerability presents an important task. Nowadays, multitarget/tasking methodologies focused on quantitative-structure activity relationships (mt-QSAR/mtk-QSAR) have an important role in the rational design of drugs since they enable simultaneous prediction of several standard measures of biological activities at diverse experimental conditions and against different biological targets. Relating to this very topic, the mt-QSAR/mtk-QSAR methodology can give only binary classification models, and as such, in this study a regression mtk-QSAR (rmtk-QSAR) model based on a novel modular neural network (MNN) has been proposed. The MNN uses standard classification mtk-QSAR models as input modules, while the regression is performed by the output module. The rmtk-QSAR model has been successfully developed for the simultaneous prediction of anticonvulsant activity and neurotoxicity of succinimides, with a satisfactory accuracy in testing (R-2 = 0.87). Thus, the proposed mtk-QSAR regression method can be regarded as a viable alternative to the standard QSAR methodology.", publisher = "Amer Chemical Soc, Washington", journal = "Molecular Pharmaceutics", title = "From Classification to Regression Multitasking QSAR Modeling Using a Novel Modular Neural Network: Simultaneous Prediction of Anticonvulsant Activity and Neurotoxicity of Succinimides", pages = "4484-4476", number = "12", volume = "14", doi = "10.1021/acs.molpharmaceut.7b00582" }
Antanasijević, D., Antanasijević, J., Trišović, N., Ušćumlić, G.,& Pocajt, V.. (2017). From Classification to Regression Multitasking QSAR Modeling Using a Novel Modular Neural Network: Simultaneous Prediction of Anticonvulsant Activity and Neurotoxicity of Succinimides. in Molecular Pharmaceutics Amer Chemical Soc, Washington., 14(12), 4476-4484. https://doi.org/10.1021/acs.molpharmaceut.7b00582
Antanasijević D, Antanasijević J, Trišović N, Ušćumlić G, Pocajt V. From Classification to Regression Multitasking QSAR Modeling Using a Novel Modular Neural Network: Simultaneous Prediction of Anticonvulsant Activity and Neurotoxicity of Succinimides. in Molecular Pharmaceutics. 2017;14(12):4476-4484. doi:10.1021/acs.molpharmaceut.7b00582 .
Antanasijević, Davor, Antanasijević, Jelena, Trišović, Nemanja, Ušćumlić, Gordana, Pocajt, Viktor, "From Classification to Regression Multitasking QSAR Modeling Using a Novel Modular Neural Network: Simultaneous Prediction of Anticonvulsant Activity and Neurotoxicity of Succinimides" in Molecular Pharmaceutics, 14, no. 12 (2017):4476-4484, https://doi.org/10.1021/acs.molpharmaceut.7b00582 . .