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Title: A study on anti-malaria drugs using degree-based topological indices through QSPR analysis
Authors: Zhang1, Xiujun
Reddy, H. G. Govardhana
Usha, Arcot
Shanmukha, M. C.
Reza Farahani, Mohammad
Alaeiyan, Mehdi
Keywords: Degree-based topological indices
regression model
QSPR analysis
Issue Date: 8-Dec-2022
Publisher: AIMS Press
Abstract: The 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.
Appears in Collections:Journal Articles

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