T.N. Wells, P.L. Alonso, W.E. Gutteridge, New medicines to improve control and contribute to the eradication of malaria, Nature reviews Drug discovery, 8 (2009) 879.
 W.H. Organization, W.E.C.o. Malaria, WHO expert committee on malaria: twentieth report, World Health Organization, 2000.
 J.N. Domínguez, Chemotherapeutic agents against malaria: what next after chloroquine?, Current topics in medicinal chemistry, 2 (2002) 1173-1185.
 A. Mital, D. Murugesan, M. Kaiser, C. Yeates, I.H. Gilbert, Discovery and optimisation studies of antimalarial phenotypic hits, European journal of medicinal chemistry, 103 (2015) 530-538.
 L.H. Hall, L.B. Kier, The molecular connectivity chi indexes and kappa shape indexes in structure‐property modeling, Reviews in computational chemistry, (1991) 367-422.
 V.N. Chandrashekar, K. Punnath, K.K. Dayanand, R.N. Achur, S.B. Kakkilaya, P. Jayadev, S.N. Kumari, D.C. Gowda, Malarial anemia among pregnant women in the south-western coastal city of Mangaluru in India, Informatics in Medicine Unlocked, 15 (2019) 100159.
 D. Murugesan, M. Kaiser, K.L. White, S. Norval, J. Riley, P.G. Wyatt, S.A. Charman, K.D. Read, C. Yeates, I.H. Gilbert, Structure–Activity Relationship Studies of Pyrrolone Antimalarial Agents, ChemMedChem, 8 (2013) 1537-1544.
 C. Hansch, J.F. Sinclair, P.R. Sinclair, Induction of Cytochrome P450 by Barbiturates in Chick Embryo Hepatocytes: A Quantitative Structure‐Activity Analysis, Quantitative Structure‐Activity Relationships, 9 (1990) 223-226.
 S. Asadpour, M. CHamsaz, J.H. Md, Application of MLR, PLS and artificial neural networks for prediction of GC/ECD retention times of chlorinated pesticides, herbicides, and organohalides, Research Journal of Pharmaceutical, Biological and Chemical Sciences, 3 (2012) 850-860.
 P.M. Khan, K. Roy, Current approaches for choosing feature selection and learning algorithms in quantitative structure–activity relationships (QSAR), Expert opinion on drug discovery, 13 (2018) 1075-1089.
 S.G. Nasab, A. Semnani, F. Marini, A. Biancolillo, Prediction of viscosity index and pour point in ester lubricants using quantitative structure-property relationship (QSPR), Chemometrics and Intelligent Laboratory Systems, 183 (2018) 59-78.
 J. Ghasemi, A. Abdolmaleki, S. Asadpour, F. Shiri, Prediction of solubility of nonionic solutes in anionic micelle (SDS) using a QSPR model, QSAR & Combinatorial Science, 27 (2008) 338-346.
 P. Gramatica, V. Consonni, R. Todeschini, QSAR study on the tropospheric degradation of organic compounds, Chemosphere, 38 (1999) 1371-1378.
 M. Nendza, R. Kühne, A. Lombardo, S. Strempel, G. Schüürmann, PBT assessment under REACH: screening for low aquatic bioaccumulation with QSAR classifications based on physicochemical properties to replace BCF in vivo testing on fish, Science of the Total Environment, 616 (2018) 97-106.
 S. Chtita, M. Larif, M. Ghamali, M. Bouachrine, T. Lakhlifi, DFT-based QSAR Studies of MK801 derivatives for non competitive antagonists of NMDA using electronic and topological descriptors, Journal of taibah university for chemistry, 9 (2014) 143-154.
 A. Adad, M. Larif. R. Hmamouchi. M. Bouachrine& T. Lakhlifi. Two different antibacterial activities against Staphylococcus aureus and Bacillus subtilis of 1.3-disubstituted-1H-naphtho [1.2-e][1.3] oxazine derivatives. Studies by combining DFT and QSAR results, J. Comp. Meth. Mol. Des, 4 (2014) 72-83.