SAR and QSAR in Environmental Research

Papers
(The H4-Index of SAR and QSAR in Environmental Research is 15. 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 2020-03-01 to 2024-03-01.)
ArticleCitations
Development of a simple, interpretable and easily transferable QSAR model for quick screening antiviral databases in search of novel 3C-like protease (3CLpro) enzyme inhibitors against SARS-CoV diseas53
Chemometric methods in antimalarial drug design from 1,2,4,5-tetraoxanes analogues42
Cell-based multi-target QSAR model for design of virtual versatile inhibitors of liver cancer cell lines26
Extending the identification of structural features responsible for anti-SARS-CoV activity of peptide-type compounds using QSAR modelling24
In silico enhancement of azo dye adsorption affinity for cellulose fibre through mechanistic interpretation under guidance of QSPR models using Monte Carlo method with index of ideality correlation23
A Monte Carlo method based QSPR model for prediction of reaction rate constants of hydrated electrons with organic contaminants23
Optimizing cardio, hepato and phospholipidosis toxicity of the Bedaquiline by chemoinformatics and molecular modelling approach22
QSAR modelling of larvicidal phytocompounds against Aedes aegypti using index of ideality of correlation21
Prediction of power conversion efficiency of phenothiazine-based dye-sensitized solar cells using Monte Carlo method with index of ideality of correlation21
Consensus QSAR models estimating acute toxicity to aquatic organisms from different trophic levels: algae, Daphnia and fish19
QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm17
Application of cross-validation strategies to avoid overestimation of performance of 2D-QSAR models for the prediction of aquatic toxicity of chemical mixtures17
Revealing binding selectivity of inhibitors toward bromodomain-containing proteins 2 and 4 using multiple short molecular dynamics simulations and free energy analyses16
Structure-based discovery of interleukin-33 inhibitors: a pharmacophore modelling, molecular docking, and molecular dynamics simulation approach16
The index of ideality of correlation: QSAR studies of hepatitis C virus NS3/4A protease inhibitors using SMILES descriptors15
QSAR and molecular docking modelling of anti-leishmanial activities of organic selenium and tellurium compounds15
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