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 2022-08-01 to 2026-08-01.)
ArticleCitations
Identification of potential inhibitors of hypoxanthine-guanine phosphoribosyl transferase for cancer treatment by molecular docking, dynamics simulation and in vitro studies92
Monte Carlo technique to study the adsorption affinity of azo dyes by applying new statistical criteria of the predictive potential46
Computational investigations of flavonoids as ALDH isoform inhibitors for treatment of cancer23
Quantitative structure-property relationship modelling for predicting retention indices of essential oils based on an improved horse herd optimization algorithm21
In silico package models for deriving values of solute parameters in linear solvation energy relationships18
Discovery of dual-target natural antimalarial agents against DHODH and PMT of Plasmodium falciparum : pharmacophore modelling, molecular docking, quantum mechanics, and 18
EGFR affinity and selectivity for the phosphorylation codes of pseudo triad tyrosine (YYY) motif and its extensions in lung cancer-related substrate-inhibitor alignment: an integrated molecular simula18
Metrics for estimating vapour pressure deviation from ideality in binary mixtures16
Computational exploration and discovery of dual EGFR-CDK2 kinase inhibitors: AI-ML powered bioisosteric design, 3D QSAR, docking, DFT and ADMET analysis of novel phthalimide derivatives15
In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives15
Predicting repurposed drugs targeting the NS3 protease of dengue virus using machine learning-based QSAR, molecular docking, and molecular dynamics simulations14
Two QSAR models for predicting the toxicity of chemicals towards Tetrahymena pyriformis based on topological-norm descriptors and spatial-norm descriptors14
Classification of ULK1 inhibitors and SAR analysis by machine learning methods14
Utilizing machine learning techniques to predict the blood-brain barrier permeability of compounds detected using LCQTOF-MS in Malaysian Kelulut honey13
First report on q-RASTR modelling of hazardous dose (HD 5 ) for acute toxicity of pesticides: an efficient and reliable approach towards safeguarding13
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