From Classification to Regression Multitasking QSAR Modeling Using a Novel Modular Neural Network: Simultaneous Prediction of Anticonvulsant Activity and Neurotoxicity of Succinimides
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2017
Authors
Antanasijević, DavorAntanasijević, Jelena
Trišović, Nemanja
Ušćumlić, Gordana
Pocajt, Viktor
Article (Published version)
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Show full item recordAbstract
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.
Keywords:
succinimides / multitasking / QSAR / regression / modular neural networkSource:
Molecular Pharmaceutics, 2017, 14, 12, 4476-4484Publisher:
- Amer Chemical Soc, Washington
Funding / projects:
- Development and Application of Methods and Materials for Monitoring New Organic Contaminants, Toxic Compounds and Heavy Metals (RS-MESTD-Basic Research (BR or ON)-172007)
- Study of the Synthesis, Structure and Activity of Natural and Synthetic Organic Compounds (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
Institution/Community
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 . .