Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/566
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dc.contributor.authorZhang1, Xiujun-
dc.contributor.authorReddy, H. G. Govardhana-
dc.contributor.authorUsha, Arcot-
dc.contributor.authorShanmukha, M. C.-
dc.contributor.authorReza Farahani, Mohammad-
dc.contributor.authorAlaeiyan, Mehdi-
dc.date.accessioned2023-03-07T10:31:22Z-
dc.date.available2023-03-07T10:31:22Z-
dc.date.issued2022-12-08-
dc.identifier.otherhttps://doi.org/10.3934/mbe.2023167-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/566-
dc.description.abstractThe use of topological descriptors is the key method, regardless of great advances taking place in the field of drug design. Descriptors portray the chemical characteristic of a molecule in numerical form, that is used for QSAR/QSPR models. The numerical values related with chemical constitutions that correlate the chemical structure with the physical properties refer to topological indices. The study of chemical structure with chemical reactivity or biological activity is termed quantitative structure activity relationship, in which topological index plays a significant role. Chemical graph theory is one such significant branch of science which plays a key role in QSAR/QSPR/QSTR studies. This work is focused on computing various degree-based topological indices and regression model of nine anti-malaria drugs. Regression models are fitted for computed indices values with 6 physicochemical properties of the anti-malaria drugs are studied. Based on the results obtained, an analysis is carried out for various statistical parameters for which conclusions are drawn.en_US
dc.language.isoenen_US
dc.publisherAIMS Pressen_US
dc.subjectDegree-based topological indicesen_US
dc.subjectregression modelen_US
dc.subjectQSPR analysisen_US
dc.titleA study on anti-malaria drugs using degree-based topological indices through QSPR analysisen_US
dc.typeArticleen_US
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