SAR and QSAR in Environmental Research

Papers
(The H4-Index of SAR and QSAR in Environmental Research is 13. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Novel molecular hybrid geometric-harmonic-Zagreb degree based descriptors and their efficacy in QSPR studies of polycyclic aromatic hydrocarbons33
Optimizing cardio, hepato and phospholipidosis toxicity of the Bedaquiline by chemoinformatics and molecular modelling approach29
A Monte Carlo method based QSPR model for prediction of reaction rate constants of hydrated electrons with organic contaminants24
Prediction of power conversion efficiency of phenothiazine-based dye-sensitized solar cells using Monte Carlo method with index of ideality of correlation22
Application of cross-validation strategies to avoid overestimation of performance of 2D-QSAR models for the prediction of aquatic toxicity of chemical mixtures21
Structure-based discovery of interleukin-33 inhibitors: a pharmacophore modelling, molecular docking, and molecular dynamics simulation approach17
The index of ideality of correlation: QSAR studies of hepatitis C virus NS3/4A protease inhibitors using SMILES descriptors17
QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds17
CORAL: Monte Carlo based global QSAR modelling of Bruton tyrosine kinase inhibitors using hybrid descriptors17
Molecular mechanism concerning conformational changes of CDK2 mediated by binding of inhibitors using molecular dynamics simulations and principal component analysis15
QSAR modelling of organic dyes for their acute toxicity in Daphnia magna using 2D-descriptors13
Sample-size dependence of validation parameters in linear regression models and in QSAR13
Monte Carlo technique to study the adsorption affinity of azo dyes by applying new statistical criteria of the predictive potential13
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