Research output: Contribution to journal › Article › peer-review
QSPR modeling of potentiometric sensitivity towards heavy metal ions for polymeric membrane sensors. / Soloviev, Vitaly; Varnek, Alexandre; Babain, Vasily; Polukeev, Valery; Ashina, Julia; Legin, Evgeny; Legin, Andrey; Kirsanov, Dmitry.
In: Sensors and Actuators, B: Chemical, Vol. 301, 126941, 12.2019.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - QSPR modeling of potentiometric sensitivity towards heavy metal ions for polymeric membrane sensors
AU - Soloviev, Vitaly
AU - Varnek, Alexandre
AU - Babain, Vasily
AU - Polukeev, Valery
AU - Ashina, Julia
AU - Legin, Evgeny
AU - Legin, Andrey
AU - Kirsanov, Dmitry
PY - 2019/12
Y1 - 2019/12
N2 - Potentiometric electrodes with plasticized membranes containing various ligands are widely employed as ion-selective sensors and as cross-sensitive sensors in multisensor systems. The design and testing of the appropriate ligands to make the sensors with required properties is a long and tedious process, which is not always successful. The concept of quantitative structure-property relationship (QSPR) seems to be an attractive complement to the ordinary ligand testing and design in potentiometric sensing. In this study we explore the feasibility of QSPR as a tool for in silico prediction of sensor performance of various ligands in PVC-plasticized potentiometric sensor membranes. The data on potentiometric sensitivity towards Cu2+, Zn2+, Cd2+, Pb2+ of membranes based on 35 nitrogen-containing ligands were employed for QSPR modeling. In spite of the limited dataset the derived models relating the chemical structures of the ligands with their electrochemical sensitivities have reasonable precision of sensitivity prediction with root mean squared errors RMSE around 5 mV/dec and squared determination coefficient R2det about 0.8 in external 10-fold cross-validation for zinc, cadmium and lead. This shows a good promise for further research in this area.
AB - Potentiometric electrodes with plasticized membranes containing various ligands are widely employed as ion-selective sensors and as cross-sensitive sensors in multisensor systems. The design and testing of the appropriate ligands to make the sensors with required properties is a long and tedious process, which is not always successful. The concept of quantitative structure-property relationship (QSPR) seems to be an attractive complement to the ordinary ligand testing and design in potentiometric sensing. In this study we explore the feasibility of QSPR as a tool for in silico prediction of sensor performance of various ligands in PVC-plasticized potentiometric sensor membranes. The data on potentiometric sensitivity towards Cu2+, Zn2+, Cd2+, Pb2+ of membranes based on 35 nitrogen-containing ligands were employed for QSPR modeling. In spite of the limited dataset the derived models relating the chemical structures of the ligands with their electrochemical sensitivities have reasonable precision of sensitivity prediction with root mean squared errors RMSE around 5 mV/dec and squared determination coefficient R2det about 0.8 in external 10-fold cross-validation for zinc, cadmium and lead. This shows a good promise for further research in this area.
KW - COMBINATORIAL LIBRARY
KW - COMPLEXATION STABILITIES
KW - Consensus model
KW - Electrochemical sensitivity
KW - Ensemble structure-property modeling
KW - FRAGMENT
KW - GENERATION
KW - IN-SILICO DESIGN
KW - ISIDA
KW - Ionophores
KW - Molecular fragment descriptors
KW - ORGANIC-LIGANDS
KW - PREDICTION
KW - Potentiometric sensors
KW - QSPR
KW - STRUCTURE-PROPERTY RELATIONSHIP
UR - http://www.scopus.com/inward/record.url?scp=85072206562&partnerID=8YFLogxK
U2 - 10.1016/j.snb.2019.126941
DO - 10.1016/j.snb.2019.126941
M3 - Article
AN - SCOPUS:85072206562
VL - 301
JO - Sensors and Actuators, B: Chemical
JF - Sensors and Actuators, B: Chemical
SN - 0925-4005
M1 - 126941
ER -
ID: 48638947