title: Modelling for antimicrobial activities of ionic liquids towards Escherichia coli, Staphylococcus aureus and Candida albicans using linear free energy relationship descriptors.
abstract: To predict antimicrobial activities i.e., minimal inhibitory concentration (MIC) and minimal biocidal concentration (MBC) for ionic liquids (ILs) against Escherichia coli, Staphylococcus aureus and Candida albicans, six quantitative structure-activity relationship (QSAR) models were developed using linear free energy relationship (LFER) descriptors calculated by density functional theory and conductor screening model. The LFER descriptors are excess molar refraction, dipolarity/polarizability, H-bonding acidity, H-bonding basicity, McGowan volume, cationic interaction, and anionic interaction. By excluding some descriptors with ignorable contributions to training set, components of the QSAR models were simplified. Their estimated predictabilities were in R(2)=0.900, standard error (SE; in log unit of μM)=0.430 for log 1/MIC of E. coli, R(2)=0.934, SE=0.370 for log 1/MBC of E. coli, R(2)=0.910, SE=0.470 for log 1/MIC of S. aureus, R(2)=0.947, SE=0.350 for log 1/MBC of S. aureus, R(2)=0.892, SE=0.362 for log 1/MIC of C. albicans and R(2)=0.803, SE=0.233 for log 1/MBC of C. albicans. Then, except for log 1/MBC of C. albicans due to lack of data points, the models were validated by comparing between observed and calculated values of test set; its checked correlations were all within R(2) of 0.921.
authors.affiliation: School of Chemical Engineering, Chonbuk National University, 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, Republic of Korea, Republic of Korea.
authors.forename: Chul-Woong
authors.initials: CW
authors.lastname: Cho
authors.affiliation: School of Chemical Engineering, Chonbuk National University, 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, Republic of Korea, Republic of Korea.
authors.forename: Jeong-Soo
authors.initials: JS
authors.lastname: Park
authors.affiliation: Centre for Environmental Research and Sustainable Technology (UFT), University of Bremen, Leobener Straße, 28359 Bremen, Germany; Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, ul.Wita Stwosza 63, 80-308 Gdańsk, Poland. Electronic address: stefan.stolte@uni-bremen.de.
authors.forename: Stefan
authors.initials: S
authors.lastname: Stolte
authors.affiliation: School of Chemical Engineering, Chonbuk National University, 567 Beakje-dearo, Deokjin-gu, Jeonju, Jeonbuk 561-756, Republic of Korea, Republic of Korea. Electronic address: ysyun@jbnu.ac.kr.
authors.forename: Yeoung-Sang
authors.initials: YS
authors.lastname: Yun
mesh_terms: D002176:Candida albicans / Q000187:drug effects* / Q000254:growth & development; D004926:Escherichia coli / Q000187:drug effects* / Q000254:growth & development; D052578:Ionic Liquids / Q000737:chemistry / Q000633:toxicity*; D008826:Microbial Sensitivity Tests; D008962:Models, Theoretical; D021281:Quantitative Structure-Activity Relationship; D013211:Staphylococcus aureus / Q000187:drug effects* / Q000254:growth & development
chemical_list: D052578:Ionic Liquids
keywords: Antimicrobial activity; Conductor-like screening model; DFT; Ionic liquids; LFER; Prediction; Toxicity