scholarly journals Quantitative Structure Toxicity Relationship (QSTR) Models for Predicting Toxicity of Polychlorinated Biphenyls (PCBs) Using Quantum Chemical Descriptors

2020 ◽  
Author(s):  
Sabitu Babatunde Olasupo ◽  
Adamu Uzairu ◽  
Balarabe Sarki Sagagi
Keyword(s):  
Polychlorinated Biphenyls ◽  
Quantum Chemical ◽  
Quantitative Structure ◽  
Quantum Chemical Descriptors ◽  
Chemical Descriptors ◽  
Structure Toxicity Relationship ◽  
Toxicity Relationship

QUANTITATIVE STRUCTURE–PROPERTY RELATIONSHIPS ON DISSOLVABILITY OF PCDD/Fs USING QUANTUM CHEMICAL DESCRIPTORS AND PARTIAL LEAST SQUARES

2010 ◽  
Vol 09 (supp01) ◽  
pp. 9-22 ◽  
Author(s):  
GUI-NING LU ◽  
XUE-QIN TAO ◽  
ZHI DANG ◽  
WEILIN HUANG ◽  
ZHONG LI
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Quantum Chemical ◽  
Good Prediction ◽  
Quantitative Structure ◽  
Structure Property ◽  
Quantum Chemical Descriptors ◽  
Validation Test ◽  
Pls Analysis ◽  
Chemical Descriptors

The environmental fate of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) has become a major issue in recent decades. Quantitative structure–property relationship (QSPR) modeling is a powerful approach for predicting the properties of environmental organic pollutants from their structure descriptors. In this study, QSPR models were established for estimating water solubility (- log S W ) and n-octanol/water partition coefficient ( log KOW) of PCDD/Fs. Quantum chemical descriptors computed with density functional theory at the B3LYP/6-31G(d) level and partial least squares (PLS) analysis with an optimizing procedure were used to generate QSPR models for - log S W and log K OW of PCDD/Fs. Optimized models with high correlation coefficients (R2 > 0.983) were obtained for estimating - log S W and log K OW of PCDD/Fs. Both the internal cross validation test [Formula: see text] and external validation test (R2 > 0.965) results showed that the obtained models had high-precision and good prediction capability. The - log S W } and log K OW values predicted by the obtained models are very close to those observed. The PLS analysis indicated that PCDD/Fs with larger electronic spatial extent (R e ), lower molecular total energy (E T ), and smaller energy gap between the lowest unoccupied and the highest occupied molecular orbitals (E LUMO -E HOMO ) tend to be less soluble in water but more lipophilic.

scholarly journals QUANTUM CHEMICAL STUDY FOR THE TOXICITY PREDICTION OF SULFONAMIDE ANTIBIOTICS WITH QUANTITATIVE STRUCTURE – ACTIVITY RELATIONSHIP

2020 ◽  
Vol 51 (1) ◽  
pp. 7-13
Author(s):  
S. Aydogdu ◽  
Arzu Hatipoglu
Keyword(s):  
Correlation Coefficient ◽  
Quantum Chemical ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Quantum Chemical Descriptors ◽  
Structure Activity ◽  
Qsar Models ◽  
Chemical Descriptors

Sulfonamides are one of the most important classes of chemicals found in the aquatic environment as a pollutant due to excessive consumption. The DFT- B3LYP method with the basis set 6-311++G (d,p) was employed to calculate various quantum chemical descriptors of sulfonamide molecules. A quantitative structure activity relationship (QSAR) study was performed for the toxicity value LD50 of sulfonamides with their quantum chemical descriptors by multi linear regression. The QSAR models were validated by internally and externally. The best multilinear equation with correlation coefficient, R and the cross-validation leave-one-out correlation coefficient, Q2 values were 0.9528 ,0.8556 respectively The results show that the QSAR models have both favourable estimation stability and good prediction power.

Reactivity of fullerenes. Quantum-chemical descriptors versus curvature

1995 ◽  
Vol 338 (1-3) ◽  
pp. 293-301 ◽  
Author(s):  
K. Choho ◽  
W. Langenaeker ◽  
G. Van De Woude ◽  
P. Geerlings
Keyword(s):  
Quantum Chemical ◽  
Quantum Chemical Descriptors ◽  
Chemical Descriptors
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