Back to Search
Start Over
QSAR models for describing the toxicological effects of ILs against Candida albicans based on norm indexes
- Source :
- Chemosphere. 201:417-424
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- The quantitative structure–activity relationship (QSAR) model is an effective alternative to traditional experimental toxicity testing, which is undoubtedly important for modern environmental risk assessment and property prediction. Based on this background, the toxicological effects of ionic liquids (ILs) against Candida albicans (C. albicans) were studied via the QSAR method. A large diverse group of 141 and 85 ILs that have a minimal inhibitory concentration (MIC) and a minimum fungicidal concentration (MBC) against C. albicans were used to obtain multiple linear regression models. These two models were developed based on matrix norm indexes and proposed based on the atomic character and position. Matrix norm indexes proposed in our research group were used to calculate the toxicity of these ILs towards C. albicans for the first time. These two models precisely estimated the toxicity of these ILs towards C. albicans with a square of correlation coefficient (R2) of = 0.930 and a standard error of estimate (SE) of = 0.254 for pMIC, and for pMBC, R2 = 0.873 and SE = 0.243.
- Subjects :
- Quantitative structure–activity relationship
Antifungal Agents
Environmental Engineering
Correlation coefficient
Health, Toxicology and Mutagenesis
0211 other engineering and technologies
Matrix norm
Ionic Liquids
Quantitative Structure-Activity Relationship
Microbial Sensitivity Tests
02 engineering and technology
010501 environmental sciences
01 natural sciences
Candida albicans
Linear regression
Environmental Chemistry
Minimum fungicidal concentration
0105 earth and related environmental sciences
Environmental risk assessment
Mathematics
021110 strategic, defence & security studies
biology
Public Health, Environmental and Occupational Health
General Medicine
General Chemistry
biology.organism_classification
Pollution
Linear Models
Biological system
Subjects
Details
- ISSN :
- 00456535
- Volume :
- 201
- Database :
- OpenAIRE
- Journal :
- Chemosphere
- Accession number :
- edsair.doi.dedup.....fa56825bef39fb74a36250d7eeb38cf5
- Full Text :
- https://doi.org/10.1016/j.chemosphere.2018.02.147