SAR and QSAR in Environmental Research

Papers
(The median citation count of SAR and QSAR in Environmental Research is 2. 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 2021-11-01 to 2025-11-01.)
ArticleCitations
Quantitative structure-property relationship modelling for predicting retention indices of essential oils based on an improved horse herd optimization algorithm76
Identification of potential inhibitors of hypoxanthine-guanine phosphoribosyl transferase for cancer treatment by molecular docking, dynamics simulation and in vitro studies41
Monte Carlo technique to study the adsorption affinity of azo dyes by applying new statistical criteria of the predictive potential32
Computational investigations of flavonoids as ALDH isoform inhibitors for treatment of cancer28
Discovery of dual-target natural antimalarial agents against DHODH and PMT of Plasmodium falciparum : pharmacophore modelling, molecular docking, quantum mechanics, and 23
Metrics for estimating vapour pressure deviation from ideality in binary mixtures17
In silico package models for deriving values of solute parameters in linear solvation energy relationships17
Classification of ULK1 inhibitors and SAR analysis by machine learning methods16
Two QSAR models for predicting the toxicity of chemicals towards Tetrahymena pyriformis based on topological-norm descriptors and spatial-norm descriptors16
Predicting repurposed drugs targeting the NS3 protease of dengue virus using machine learning-based QSAR, molecular docking, and molecular dynamics simulations15
Machine learning-based predictive models for identifying high active compounds against HIV-1 integrase15
First report on q-RASTR modelling of hazardous dose (HD 5 ) for acute toxicity of pesticides: an efficient and reliable approach towards safeguarding the sensitive a15
In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives14
Utilizing machine learning techniques to predict the blood-brain barrier permeability of compounds detected using LCQTOF-MS in Malaysian Kelulut honey14
MDM-Pred: a freely available web application for predicting the metabolism of drug-like compounds by the gut microbiota13
Identifying SARS-CoV-2 main protease inhibitors by applying the computer screening of a large database of molecules13
Identification of inhibitors for neurodegenerative diseases targeting dual leucine zipper kinase through virtual screening and molecular dynamics simulations11
Molecular mechanism underlying effect of D93 and D289 protonation states on inhibitor-BACE1 binding: exploration from multiple independent Gaussian accelerated molecular dynamics and deep learning11
QSPR models to predict the physical hazards of mixtures: a state of art10
Exploring molecular interactions of potential inhibitors against the spleen tyrosine kinase implicated in autoimmune disorders via virtual screening and molecular dynamics simulations10
A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods10
Synthesis of new benzimidazole derivatives containing 1,3,4-thiadiazole: their in vitro antimicrobial, in silico molecular docking and molecular dynamic simulations studies10
Development of 3D-QSAR and pharmacophoric models to design new anti-Trypanosoma cruzi agents based on 2-aryloxynaphthoquinone scaffold10
iACP-GE: accurate identification of anticancer peptides by using gradient boosting decision tree and extra tree10
Prediction of soil ecotoxicity against Folsomia candida using acute and chronic endpoints10
Multi-epitope vaccine construct against Staphylococcus aureus : insights from immunoinformatics and molecular dynamics simulations9
Theoretically exploring selective-binding mechanisms of BRD4 through integrative computational approaches9
Correction9
Insights from computational studies on the potential of natural compounds as inhibitors against SARS-CoV-2 spike omicron variant9
Prediction of tissue and urine concentrations of 2-phenoxyethanol and its metabolite 2-phenoxyacetic acid in rat and human after oral and dermal exposures via GastroPlusTM physiologically b9
Optimizing cardio, hepato and phospholipidosis toxicity of the Bedaquiline by chemoinformatics and molecular modelling approach9
Classification-based QSARs for predicting dietary biomagnification in fish8
Design of 2-amino-6-methyl-pyrimidine benzoic acids as ATP competitive casein kinase-2 (CK2) inhibitors using structure- and fragment-based design, docking and molecular dynamic simulation studies8
Microwave-assisted organic synthesis, antimycobacterial activity, structure–activity relationship and molecular docking studies of some novel indole-oxadiazole hybrids8
Analysis of oral and inhalation toxicity of per- and polyfluoroalkylated organic compounds in rats and mice using multivariate QSAR8
What is the ecotoxicity of a given chemical for a given aquatic species? Predicting interactions between species and chemicals using recommender system techniques8
Combining QSAR and SSD to predict aquatic toxicity and species sensitivity of pyrethroid and organophosphate pesticides7
Prioritizing pharmaceutically active compounds (PhACs) based on occurrence-persistency-mobility-toxicity (OPMT) criteria: an application to the Brazilian scenario7
Hybrid consensus and k-nearest neighbours (kNN) strategies to classify dual BRD4/PLK1 inhibitors7
Unveiling the potential of Hamigeran-B from marine sponges as a probable inhibitor of Nipah virus RDRP through molecular modelling and dynamics simulation studies7
Correction7
HT_PREDICT: a machine learning-based computational open-source tool for screening HDAC6 inhibitors7
SAR based on self consistent classifier7
Identification, experimental validation, and computational evaluation of potential ALK inhibitors through hierarchical virtual screening7
QSAR assessment of aquatic toxicity potential of diverse agrochemicals7
Structural characterization of length-varying peptide sequences for peptide quantitative structure-activity relationship6
Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning6
First report on machine learning based multiclass classification of Caco-2 permeability using different balancing strategies6
A computational perception of BBOX1-IP3R3 interaction uncovers inhibitors for dysregulated calcium signalling in triple negative breast cancer6
Experimental evaluation and structure–activity relationship analysis of bridged-ring terpenoid derivatives as novel Blattella germanica repellent6
Discovery of Zafirlukast as a novel SARS-CoV-2 helicase inhibitor using in silico modelling and a FRET-based assay6
Steroidal hydrazones as antimicrobial agents: biological evaluation and molecular docking studies6
Structural insights and molecular profiling of a large set of diverse compounds targeting PPARγ: from comprehensive cheminformatics approach to tool development6
Deciphering Cathepsin K inhibitors: a combined QSAR, docking and MD simulation based machine learning approaches for drug design6
Machine learning-based models for accessing thermal conductivity of liquids at different temperature conditions6
Modelling enzyme inhibition toxicity of ionic liquid from molecular structure via convolutional neural network model6
Exploring molecular fragments for fraction unbound in human plasma of chemicals: a fragment-based cheminformatics approach5
Synthesis, biological evaluation and in silico studies of novel thiadiazole-hydrazone derivatives for carbonic anhydrase inhibitory and anticancer activities5
Enhanced prediction of beta-secretase inhibitory compounds with mol2vec technique and machine learning algorithms5
HDAC1 PREDICTOR: a simple and transparent application for virtual screening of histone deacetylase 1 inhibitors5
Structure-based drug design of pre-clinical candidate nanopiperine: a direct target for CYP1A1 protein to mitigate hyperglycaemia and associated microbes5
Unveiling the biophysical basis of DYRK kinase family isoform selectivity mechanism of Abemaciclib using computational approaches5
Modelling lethality and teratogenicity of zebrafish ( Danio rerio ) due to β-lactam antibiotics employing the QSTR approach5
ToxAI_assistant: a web platform for a comprehensive study of the acute toxicity of xenobiotics following oral and intravenous administration in rats4
Priority list of potential endocrine-disrupting chemicals in food chemical contaminants: a docking study and in vitro/epidemiological evidence integration4
Discovery of dual-target natural inhibitors of meprins α and β metalloproteases for inflammation regulation: pharmacophore modelling, molecular docking, ADME prediction, and molecular dynamics studies4
QSAR modelling of organic dyes for their acute toxicity in Daphnia magna using 2D-descriptors4
Potent inhibition of human and rat 17β-hydroxysteroid dehydrogenase 1 by curcuminoids and the metabolites: 3D QSAR and in silico docking analysis4
Harnessing the potential of phytochemicals to design anti-filarial molecules targeting the MurE enzyme of Brugia malayi : a hierarchical virtual screening and molecular 4
Decoding drug resistant mechanism of V32I, I50V and I84V mutations of HIV-1 protease on amprenavir binding by using molecular dynamics simulations and MM-GBSA calculations4
Development of a standardized methodology for transfer learning with QSAR models: a purely data-driven approach for source task selection4
Molecular mechanism of interactions of SPIN1 with novel inhibitors through molecular docking and molecular dynamics simulations4
A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds4
First molecular modelling report on tri-substituted pyrazolines as phosphodiesterase 5 (PDE5) inhibitors through classical and machine learning based multi-QSAR analysis4
Predicting acute toxicity of pesticides towards Daphnia magna with random forest algorithm4
Network-based clustering and statistical evaluation to elucidate structure-activity relationships of EZH2 inhibitors4
q-RASTR modelling for prediction of diverse toxic chemicals towards T. pyriformis4
Selective inhibition mechanism of three inhibitors to BRD4 uncovered by molecular docking and molecular dynamics simulations4
Synthesis and molecular modelling of thiadizole based hydrazone derivatives as acetylcholinesterase and butyrylcholinesterase inhibitory activities4
Development of binary classification models for grouping hydroxylated polychlorinated biphenyls into active and inactive thyroid hormone receptor agonists3
Insight into the structural requirements of gelatinases (MMP-2 and MMP-9) inhibitors by multiple validated molecular modelling approaches: Part II3
Targeting drug-resistant Mycobacterium tuberculosis : an integrated computational approach to identify DprE2 inhibitors3
Novel molecular hybrid geometric-harmonic-Zagreb degree based descriptors and their efficacy in QSPR studies of polycyclic aromatic hydrocarbons3
Prediction of critical micelle concentration for per- and polyfluoroalkyl substances3
Ligand-based discovery of new potential acetylcholinesterase inhibitors for Alzheimer’s disease treatment3
HDAC6 detector: online application for evaluating compounds as potential histone deacetylase 6 inhibitors3
Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation3
Pinpointing prime structural attributes of potential MMP-2 inhibitors comprising alkyl/arylsulfonyl pyrrolidine scaffold: a ligand-based molecular modelling approach validated by molecular dynamics si3
Descriptor generation from Morgan fingerprint using persistent homology3
Comparison of predictions of developmental toxicity for compounds of solvent data set3
An effective machine learning model for rat acute oral toxicity prediction of emerging chemicals: multi-domain applications and structure-activity relationships3
Functionally substituted 2-aminothiazoles as antimicrobial agents: in vitro and in silico evaluation3
Understanding mechanism governing the inflammatory potential of metal oxide nanoparticles using periodic table-based descriptors: a nano-QSAR approach3
Fragment-based QSAR study to explore the structural requirements of DPP-4 inhibitors: a stepping stone towards better type 2 diabetes mellitus management3
Discovery of novel 1,3,4-oxadiazole derivatives as anticancer agents targeting thymidine phosphorylase: pharmacophore modelling, virtual screening, molecular docking, ADMET and DFT analysis3
Exploiting the chemical diversity space of phosphopeptide binding to nasopharyngeal carcinoma PLK1 PBD domain with unnatural amino acid building blocks by using QSAR-based genetic optimization2
Exploration of structural alerts and fingerprints for novel anticancer therapeutics: a robust classification-QSAR dependent structural analysis of drug-like MMP-9 inhibitors2
Pteridine reductase (PTR1): initial structure-activity relationships studies of potential leishmanicidal arylindole derivatives compounds2
Carcinogenicity prediction using the index of ideality of correlation2
QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm2
A holistic molecular modelling approach to design novel indole-2-carboxamide derivatives as potential inhibitors of MmpL32
QSAR analysis and experimental evaluation of new quinazoline-containing hydroxamic acids as histone deacetylase 6 inhibitors2
A quantitative structural analysis of AR-42 derivatives as HDAC1 inhibitors for the identification of promising structural contributors2
Potential antioxidant, α-glucosidase, butyrylcholinesterase and acetylcholinesterase inhibitory activities of major constituents isolated from Alpinia officinarum hance 2
Molecular docking-based interactions in QSAR studies on Mycobacterium tuberculosis ATP synthase inhibitors2
Predictive modelling of peroxisome proliferator-activated receptor gamma (PPARγ) IC50 inhibition by emerging pollutants using light gradient boosting machine2
Essential oil components interacting with insect odorant-binding proteins: a molecular modelling approach2
Read-across-driven binary classification for the developmental and reproductive toxicity of organic compounds tested according to the OECD test guidelines 421/4222
First report on retention time prediction of pesticides and veterinary drugs in cow milk using read-across and intelligent consensus prediction: an alternative for hazard assessment employing food-inf2
Hybrid descriptors–conjoint indices: a case study on imidazole-thiourea containing glutaminyl cyclase inhibitors for design of novel anti-Alzheimer’s candidates2
Machine learning-based q-RASAR modelling for the in silico identification of novel α7nAChR agonists for anti-Alzheimer’s drug discovery2
In silico prediction of mosquito repellents for clothing application2
Identification of novel inhibitors targeting TIRAP interactions with BTK and PKCδ in inflammation through an in silico approach2
QSAR classification model for diverse series of antifungal agents based on binary coyote optimization algorithm2
Exploring different classification-dependent QSAR modelling strategies for HDAC3 inhibitors in search of meaningful structural contributors2
Ranked binding energies of residues and data fusion to identify the active and selective pyrimidine-based Janus kinases 3 (JAK3) inhibitors2
Computational explorations of the interaction between laccase and bisphenol A: influence of surfactant and different organic solvents2
Correction2
Binding modes of GDP, GTP and GNP to NRAS deciphered by using Gaussian accelerated molecular dynamics simulations2
Predicting cytotoxicity of engineered nanoparticles using regularized regression models: an in silico approach2
Development of terpenoid repellents against Aedes albopictus : a combined study of biological activity evaluation and computational modelling2
Investigating potency of TMC-126 against wild-type and mutant variants of HIV-1 protease: a molecular dynamics and free energy study2
Study for the binding affinity of thyroid hormone receptors based on machine learning algorithm2
Exploring crucial structural attributes of quinolinyl methoxyphenyl sulphonyl-based hydroxamate derivatives as ADAM17 inhibitors through classification-dependent molecular modelling approaches2
Targeting MAO-B selectivity: computational screening, docking, and molecular dynamics insights2
Unravelling the molecular recognition mechanism between odorants and PBP1 in Loxostege sticticalis by homology modelling, molecular docking, and MD simulation2
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