SAR and QSAR in Environmental Research

Papers
(The TQCC of SAR and QSAR in Environmental Research is 6. 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 2021-06-01 to 2025-06-01.)
ArticleCitations
Identification of potential inhibitors of hypoxanthine-guanine phosphoribosyl transferase for cancer treatment by molecular docking, dynamics simulation and in vitro studies62
Monte Carlo technique to study the adsorption affinity of azo dyes by applying new statistical criteria of the predictive potential32
Quantitative structure-property relationship modelling for predicting retention indices of essential oils based on an improved horse herd optimization algorithm31
Computational investigations of flavonoids as ALDH isoform inhibitors for treatment of cancer26
Insights into effect of the Asp25/Asp25ʹ protonation states on binding of inhibitors Amprenavir and MKP97 to HIV-1 protease using molecular dynamics simulations and MM-GBSA calculations24
Discovery of dual-target natural antimalarial agents against DHODH and PMT of Plasmodium falciparum : pharmacophore modelling, molecular docking, quantum mechanics, and 22
In silico package models for deriving values of solute parameters in linear solvation energy relationships21
Predicting repurposed drugs targeting the NS3 protease of dengue virus using machine learning-based QSAR, molecular docking, and molecular dynamics simulations17
Machine learning-based predictive models for identifying high active compounds against HIV-1 integrase16
Metrics for estimating vapour pressure deviation from ideality in binary mixtures14
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 a13
Utilizing machine learning techniques to predict the blood-brain barrier permeability of compounds detected using LCQTOF-MS in Malaysian Kelulut honey13
In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives12
Two QSAR models for predicting the toxicity of chemicals towards Tetrahymena pyriformis based on topological-norm descriptors and spatial-norm descriptors12
Molecular mechanism underlying effect of D93 and D289 protonation states on inhibitor-BACE1 binding: exploration from multiple independent Gaussian accelerated molecular dynamics and deep learning12
Identifying SARS-CoV-2 main protease inhibitors by applying the computer screening of a large database of molecules12
Identification of inhibitors for neurodegenerative diseases targeting dual leucine zipper kinase through virtual screening and molecular dynamics simulations12
MDM-Pred: a freely available web application for predicting the metabolism of drug-like compounds by the gut microbiota11
iACP-GE: accurate identification of anticancer peptides by using gradient boosting decision tree and extra tree11
Exploring molecular interactions of potential inhibitors against the spleen tyrosine kinase implicated in autoimmune disorders via virtual screening and molecular dynamics simulations10
QSPR models to predict the physical hazards of mixtures: a state of art10
Development of 3D-QSAR and pharmacophoric models to design new anti-Trypanosoma cruzi agents based on 2-aryloxynaphthoquinone scaffold10
Prediction of soil ecotoxicity against Folsomia candida using acute and chronic endpoints9
Correction9
Theoretically exploring selective-binding mechanisms of BRD4 through integrative computational approaches9
Analysis of oral and inhalation toxicity of per- and polyfluoroalkylated organic compounds in rats and mice using multivariate QSAR9
Optimizing cardio, hepato and phospholipidosis toxicity of the Bedaquiline by chemoinformatics and molecular modelling approach9
Synthesis of new benzimidazole derivatives containing 1,3,4-thiadiazole: their in vitro antimicrobial, in silico molecular docking and molecular dynamic simulations studies9
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
A SAR and QSAR study on 3CLpro inhibitors of SARS-CoV-2 using machine learning methods9
Classification-based QSARs for predicting dietary biomagnification in fish8
What is the ecotoxicity of a given chemical for a given aquatic species? Predicting interactions between species and chemicals using recommender system techniques8
Microwave-assisted organic synthesis, antimycobacterial activity, structure–activity relationship and molecular docking studies of some novel indole-oxadiazole hybrids7
HT_PREDICT: a machine learning-based computational open-source tool for screening HDAC6 inhibitors7
Hybrid consensus and k-nearest neighbours (kNN) strategies to classify dual BRD4/PLK1 inhibitors7
Prioritizing pharmaceutically active compounds (PhACs) based on occurrence-persistency-mobility-toxicity (OPMT) criteria: an application to the Brazilian scenario7
Molecular modelling on SARS-CoV-2 papain-like protease: an integrated study with homology modelling, molecular docking, and molecular dynamics simulations7
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 studies7
Correction6
QSAR assessment of aquatic toxicity potential of diverse agrochemicals6
Combining QSAR and SSD to predict aquatic toxicity and species sensitivity of pyrethroid and organophosphate pesticides6
Steroidal hydrazones as antimicrobial agents: biological evaluation and molecular docking studies6
Enhanced prediction of beta-secretase inhibitory compounds with mol2vec technique and machine learning algorithms6
Discovery of Zafirlukast as a novel SARS-CoV-2 helicase inhibitor using in silico modelling and a FRET-based assay6
Identification, experimental validation, and computational evaluation of potential ALK inhibitors through hierarchical virtual screening6
Machine learning-based models for accessing thermal conductivity of liquids at different temperature conditions6
A computational perception of BBOX1-IP3R3 interaction uncovers inhibitors for dysregulated calcium signalling in triple negative breast cancer6
SAR based on self consistent classifier6
Deciphering Cathepsin K inhibitors: a combined QSAR, docking and MD simulation based machine learning approaches for drug design6
Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning6
Unveiling the potential of Hamigeran-B from marine sponges as a probable inhibitor of Nipah virus RDRP through molecular modelling and dynamics simulation studies6
Experimental evaluation and structure–activity relationship analysis of bridged-ring terpenoid derivatives as novel Blattella germanica repellent6
Modelling enzyme inhibition toxicity of ionic liquid from molecular structure via convolutional neural network model6
0.03561806678772