tailieunhanh - Design, virtual screening and in silico QSPR modeling for the development of new thiosemicarbazone-based complexes

This modeling is performed on an experimental data set of complexes, where the metal ions of these complexes include transition ion metals and lanthanide ion metals. We use these models to develop a series of new thiosemicarbazone and their complexes; simultaneously, the complexes are worked out the stability constants from the novel models. | Cite this paper Vietnam J. Chem. 2023 61 S1 8-16 Research article DOI Design virtual screening and in silico QSPR modeling for the development of new thiosemicarbazone-based complexes Nguyen Minh Quang1 Huynh Ngoc Chau1 Tran Thai Hoa2 Vu Thi Bao Ngoc4 Pham Van Tat3 1 Faculty of Chemical Engineering Industrial University of Ho Chi Minh City 12 Nguyen Van Bao Go Vap Ho Chi Minh City 70000 Viet Nam 2 Faculty of Chemistry Hue University of Sciences Hue University 77 Nguyen Hue Hue City 49100 Viet Nam 3 Department of Sciences and Journal Management Hoa Sen University 8 Nguyen Van Trang Dist. 1 Ho Chi Minh City 70000 Viet Nam 4 Faculty of Chemistry and Environment University of Dalat 01 Phu Dong Thien Vuong Da Lat City 66000 Viet Nam Submitted November 16 2022 Revised January 16 2023 Accepted February 14 2023 Abstract Eighteen new thiosemicarbazone ligands and 30 new ligand-based complexes were developed from quantitative structure-property relationships QSPR methods. Stability constants log 12 of complexes were calculated on QSPR models that were built by methods of multivariate linear regression MLR and artificial neural network ANN . Six descriptors including dipole 5C 4N fw xc3 and ka1 were discovered in the best QSPRMLR model with the good statistical criteria R2train Q2CV and SE . Besides the ANN model with architecture I 6 -HL 3 - O 1 was built from the descriptors of the MLR model with excellent results as R2train Q2CV and Q2test . Also the models were externally validated on the other experimental dataset. Consequently the resulting QSPR models could be applied to develop new complexes for chemically related fields. Keywords. Machine learning MLR QSPR stability constants log 12 thiosemicarbazone. 1. INTRODUCTION thiosemicarbazones leads to a variety of practical applications. Some have therapeutic activity used as Recently a new theoretical method is emerging as a antivirals and antibiotics 2 some have .

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