QSAR modeling of dihydrofolate reductase inhibitors as a therapeutic target for multiresistant bacteria
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Veselinović, Jovana B.Đorđević, Vukica
Bogdanović, Milena
Morić, Ivana
Veselinović, Aleksandar M.
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Antibacterial resistance is a growing public health threat of major concern around the world so development of new therapeutic approaches to prevent bacterial multidrug resistance has become a primary consideration for medicinal chemistry research. QSAR models for the dihydrofolate reductase inhibition with 2,4-diamino-5-(substituted-benzyle)-pyramidine derivatives were developed with further computer-aided design of new derivatives with desired activity. The Monte Carlo method has been used as a computational tool for QSAR modeling. For the representation of molecular structure and optimal descriptor calculation, the simplified molecular input line entry system (SMILES) together with the molecular graph (hydrogen-suppressed graph-HSG, hydrogen-filled graph-HFG, and the graph of atomic orbitals-GAO) was used. One-variable models have been calculated for one data split into training, test, and validation set. The impact of Morgan's extended connectivity index on built QSAR models and ou...tliers was determined. Statistical parameters for the best QSAR model are satisfying. Structural indicators (molecular fragments) responsible for the increase and the decrease of the stated activity are defined, and with the application of defined structural alerts, the computer-aided design of new derivatives with desired activity is presented. Computational experiments presented and applied in this research can satisfactorily predict desired endpoint and can be used further for computer-aided antibacterial drug design.
Keywords:
SMILES / QSAR / Pyramidine derivatives / Dihydrofolate reductase inhibitions / CORAL softwareSource:
Structural Chemistry, 2018, 29, 2, 541-551Publisher:
- Springer/Plenum Publishers, New York
Funding / projects:
- Production of new dietetic milk products for risk populations based on qualitative and quantitative analysis of health risk markers in milk consumption (RS-MESTD-Technological Development (TD or TR)-31060)
- COST [COST Action CA15135]
DOI: 10.1007/s11224-017-1051-7
ISSN: 1040-0400
WoS: 000427405400017
Scopus: 2-s2.0-85033466391
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Institut za molekularnu genetiku i genetičko inženjerstvoTY - JOUR AU - Veselinović, Jovana B. AU - Đorđević, Vukica AU - Bogdanović, Milena AU - Morić, Ivana AU - Veselinović, Aleksandar M. PY - 2018 UR - https://imagine.imgge.bg.ac.rs/handle/123456789/1189 AB - Antibacterial resistance is a growing public health threat of major concern around the world so development of new therapeutic approaches to prevent bacterial multidrug resistance has become a primary consideration for medicinal chemistry research. QSAR models for the dihydrofolate reductase inhibition with 2,4-diamino-5-(substituted-benzyle)-pyramidine derivatives were developed with further computer-aided design of new derivatives with desired activity. The Monte Carlo method has been used as a computational tool for QSAR modeling. For the representation of molecular structure and optimal descriptor calculation, the simplified molecular input line entry system (SMILES) together with the molecular graph (hydrogen-suppressed graph-HSG, hydrogen-filled graph-HFG, and the graph of atomic orbitals-GAO) was used. One-variable models have been calculated for one data split into training, test, and validation set. The impact of Morgan's extended connectivity index on built QSAR models and outliers was determined. Statistical parameters for the best QSAR model are satisfying. Structural indicators (molecular fragments) responsible for the increase and the decrease of the stated activity are defined, and with the application of defined structural alerts, the computer-aided design of new derivatives with desired activity is presented. Computational experiments presented and applied in this research can satisfactorily predict desired endpoint and can be used further for computer-aided antibacterial drug design. PB - Springer/Plenum Publishers, New York T2 - Structural Chemistry T1 - QSAR modeling of dihydrofolate reductase inhibitors as a therapeutic target for multiresistant bacteria EP - 551 IS - 2 SP - 541 VL - 29 DO - 10.1007/s11224-017-1051-7 ER -
@article{ author = "Veselinović, Jovana B. and Đorđević, Vukica and Bogdanović, Milena and Morić, Ivana and Veselinović, Aleksandar M.", year = "2018", abstract = "Antibacterial resistance is a growing public health threat of major concern around the world so development of new therapeutic approaches to prevent bacterial multidrug resistance has become a primary consideration for medicinal chemistry research. QSAR models for the dihydrofolate reductase inhibition with 2,4-diamino-5-(substituted-benzyle)-pyramidine derivatives were developed with further computer-aided design of new derivatives with desired activity. The Monte Carlo method has been used as a computational tool for QSAR modeling. For the representation of molecular structure and optimal descriptor calculation, the simplified molecular input line entry system (SMILES) together with the molecular graph (hydrogen-suppressed graph-HSG, hydrogen-filled graph-HFG, and the graph of atomic orbitals-GAO) was used. One-variable models have been calculated for one data split into training, test, and validation set. The impact of Morgan's extended connectivity index on built QSAR models and outliers was determined. Statistical parameters for the best QSAR model are satisfying. Structural indicators (molecular fragments) responsible for the increase and the decrease of the stated activity are defined, and with the application of defined structural alerts, the computer-aided design of new derivatives with desired activity is presented. Computational experiments presented and applied in this research can satisfactorily predict desired endpoint and can be used further for computer-aided antibacterial drug design.", publisher = "Springer/Plenum Publishers, New York", journal = "Structural Chemistry", title = "QSAR modeling of dihydrofolate reductase inhibitors as a therapeutic target for multiresistant bacteria", pages = "551-541", number = "2", volume = "29", doi = "10.1007/s11224-017-1051-7" }
Veselinović, J. B., Đorđević, V., Bogdanović, M., Morić, I.,& Veselinović, A. M.. (2018). QSAR modeling of dihydrofolate reductase inhibitors as a therapeutic target for multiresistant bacteria. in Structural Chemistry Springer/Plenum Publishers, New York., 29(2), 541-551. https://doi.org/10.1007/s11224-017-1051-7
Veselinović JB, Đorđević V, Bogdanović M, Morić I, Veselinović AM. QSAR modeling of dihydrofolate reductase inhibitors as a therapeutic target for multiresistant bacteria. in Structural Chemistry. 2018;29(2):541-551. doi:10.1007/s11224-017-1051-7 .
Veselinović, Jovana B., Đorđević, Vukica, Bogdanović, Milena, Morić, Ivana, Veselinović, Aleksandar M., "QSAR modeling of dihydrofolate reductase inhibitors as a therapeutic target for multiresistant bacteria" in Structural Chemistry, 29, no. 2 (2018):541-551, https://doi.org/10.1007/s11224-017-1051-7 . .