QSAR study and theoretical investigation on the lethality of halogenated aliphatic hydrocarbons toward <i>Aspergillus</i> (<i>A.</i>) <i>Nidulans</i>

The prediction of Aspergillus (A.) nidulans toxicities (log1/D37) for a set of 55 halogenated aliphatic hydrocarbons (HAHs) was thoroughly investigated using density functional theory (DFT) computations. Different multiple linear regression (MLR)methods were employed to assess the reliability of the proposed quantitative structure-activity relationships (QSAR) model. The obtained ELUMO, Egap, molecular polarizability (α), and molar refractivity (MR) values offered informative indications in determining the toxicity of the HAHs. A promising three-descriptor linear model was constructed using 41 molecules as a training set; then, the model was validated on the remaining 14 molecules. Statistical comparisons between these models and others quoted from the literature were presented. Furthermore, the potential causes of the outlier molecules in the proposed QSAR models were explored. The most preferable interactions were obviously noticed within the 1-bromo-2-methylpropane…α-glucan complex, followed by 2-bromo-2-methylpropane…α-glucan and 2-chloro-2-methylpropane…α-glucan complexes. Compared to other analogs, the higher number of bond paths and bond critical points within the 1-bromo-2-methylpropane…α-glucan complex highlighted its high preferability.

Authors

Institutions

Publication Details

Journal
AIMS environmental science
Published
2025-01-01
DOI
https://doi.org/10.3934/environsci.2025019
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

QSAR study and theoretical investigation on the lethality of halogenated aliphatic hydrocarbons toward Aspergillus (A.) Nidulans

E. A. M. Gad, Jabir H. Al‐Fahemi, Mahmoud A. A. Ibrahim, Faten A. Aljiffrey
AIMS environmental science
Computational Drug Discovery Methods
article

QSAR study and theoretical investigation on the lethality of halogenated aliphatic hydrocarbons toward Aspergillus (A.) Nidulans

E. A. M. Gad, Jabir H. Al‐Fahemi, Mahmoud A. A. Ibrahim, Faten A. Aljiffrey
article en

Abstract

The prediction of Aspergillus (A.) nidulans toxicities (log1/D37) for a set of 55 halogenated aliphatic hydrocarbons (HAHs) was thoroughly investigated using density functional theory (DFT) computations. Different multiple linear regression (MLR)methods were employed to assess the reliability of the proposed quantitative structure-activity relationships (QSAR) model. The obtained ELUMO, Egap, molecular polarizability (α), and molar refractivity (MR) values offered informative indications in determining the toxicity of the HAHs. A promising three-descriptor linear model was constructed using 41 molecules as a training set; then, the model was validated on the remaining 14 molecules. Statistical comparisons between these models and others quoted from the literature were presented. Furthermore, the potential causes of the outlier molecules in the proposed QSAR models were explored. The most preferable interactions were obviously noticed within the 1-bromo-2-methylpropane…α-glucan complex, followed by 2-bromo-2-methylpropane…α-glucan and 2-chloro-2-methylpropane…α-glucan complexes. Compared to other analogs, the higher number of bond paths and bond critical points within the 1-bromo-2-methylpropane…α-glucan complex highlighted its high preferability.

AIMS environmental scienceVol. 12(3)
Umm al-Qura University (SA), College of Applied Sciences, Nizwa (OM), Egyptian Petroleum Research Institute (EG), Minia University (EG), University of KwaZulu-Natal (ZA)
Openalex Percentile: Top 88%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.