Works matching DE "COMPARATIVE molecular field analysis"
Results: 149
www.3d-qsar.com: a web portal that brings 3-D QSAR to all electronic devices—the Py-CoMFA web application as tool to build models from pre-aligned datasets.
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- Journal of Computer-Aided Molecular Design, 2019, v. 33, n. 9, p. 855, doi. 10.1007/s10822-019-00231-x
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A probabilistic method to report predictions from a human liver microsomes stability QSAR model: a practical tool for drug discovery.
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- Journal of Computer-Aided Molecular Design, 2015, v. 29, n. 4, p. 327, doi. 10.1007/s10822-015-9838-3
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Pyridones as NNRTIs against HIV-1 mutants: 3D-QSAR and protein informatics.
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- Journal of Computer-Aided Molecular Design, 2013, v. 27, n. 7, p. 637, doi. 10.1007/s10822-013-9667-1
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Computational Investigation with Toxicophore Study of 1,2,3-Triazole Derivatives as an Effective Inhibitor Against Prostate Cancer.
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- Russian Journal of General Chemistry, 2024, v. 94, n. 9, p. 2445, doi. 10.1134/S1070363224090238
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Generalized fragmental approach in QSAR/QSPR studies.
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- Doklady Chemistry, 2015, v. 463, n. 1, p. 185, doi. 10.1134/S0012500815070071
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Discovery of MAO-B Inhibitor with Machine Learning, Topomer CoMFA, Molecular Docking and Multi-Spectroscopy Approaches.
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- Biomolecules (2218-273X), 2022, v. 12, n. 10, p. N.PAG, doi. 10.3390/biom12101470
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Developing a CoMSIA Model for Inhibition of COX-2 by Resveratrol Derivatives.
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- Iranian Journal of Pharmaceutical Research, 2016, v. 15, n. 3, p. 459
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Studies of febuxostat analogues as xanthine oxidase inhibitors through 3D-QSAR, Topomer CoMFA and molecular modeling.
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- Journal of the Iranian Chemical Society, 2019, v. 16, n. 12, p. 2659, doi. 10.1007/s13738-019-01726-y
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3D-QSAR modeling of maximum steady-state fluxes of some substituted benzenes and quinolone derivatives through polydimethylsiloxane membrane.
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- Journal of the Iranian Chemical Society, 2018, v. 15, n. 6, p. 1293, doi. 10.1007/s13738-018-1328-9
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Pharmacophore elucidation and 3D-QSAR analysis of a new class of highly potent inhibitors of acid ceramidase based on maximum common substructure and field fit alignment methods.
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- Journal of the Iranian Chemical Society, 2014, v. 11, n. 5, p. 1329, doi. 10.1007/s13738-013-0402-6
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3D-QSAR, Scaffold Hopping, Virtual Screening, and Molecular Dynamics Simulations of Pyridin-2-one as mIDH1 Inhibitors.
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- International Journal of Molecular Sciences, 2024, v. 25, n. 13, p. 7434, doi. 10.3390/ijms25137434
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Exploration of N -Arylsulfonyl-indole-2-carboxamide Derivatives as Novel Fructose-1,6-bisphosphatase Inhibitors by Molecular Simulation.
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- International Journal of Molecular Sciences, 2022, v. 23, n. 18, p. N.PAG, doi. 10.3390/ijms231810259
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Computer-Aided and AILDE Approaches to Design Novel 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors.
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- International Journal of Molecular Sciences, 2022, v. 23, n. 14, p. 7822, doi. 10.3390/ijms23147822
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Binding Studies and Lead Generation of Pteridin-7(8 H)-one Derivatives Targeting FLT3.
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- International Journal of Molecular Sciences, 2022, v. 23, n. 14, p. 7696, doi. 10.3390/ijms23147696
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Molecular Modeling Studies of N -phenylpyrimidine-4-amine Derivatives for Inhibiting FMS-like Tyrosine Kinase-3.
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- International Journal of Molecular Sciences, 2021, v. 22, n. 22, p. 12511, doi. 10.3390/ijms222212511
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Docking-Based 3D-QSAR Studies for 1,3,4-oxadiazol-2-one Derivatives as FAAH Inhibitors.
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- International Journal of Molecular Sciences, 2021, v. 22, n. 11, p. 6108, doi. 10.3390/ijms22116108
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Design, Synthesis, and Evaluation of Novel 3-Carboranyl-1,8-Naphthalimide Derivatives as Potential Anticancer Agents.
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- International Journal of Molecular Sciences, 2021, v. 22, n. 5, p. 2772, doi. 10.3390/ijms22052772
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The Universal 3D QSAR Model for Dopamine D2 Receptor Antagonists.
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- International Journal of Molecular Sciences, 2019, v. 20, n. 18, p. 4555, doi. 10.3390/ijms20184555
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Molecular Modeling Study for the Design of Novel Peroxisome Proliferator-Activated Receptor Gamma Agonists Using 3D-QSAR and Molecular Docking.
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- International Journal of Molecular Sciences, 2018, v. 19, n. 2, p. 630, doi. 10.3390/ijms19020630
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Chemical Structure-Biological Activity Models for Pharmacophores' 3D-Interactions.
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- International Journal of Molecular Sciences, 2016, v. 17, n. 7, p. 1087, doi. 10.3390/ijms17071087
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Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations.
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- International Journal of Molecular Sciences, 2015, v. 16, n. 9, p. 20118, doi. 10.3390/ijms160920118
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Prediction of octanol-water partition coefficient for polychlorinated naphthalenes through three-dimensional QSAR models.
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- Human & Ecological Risk Assessment, 2017, v. 23, n. 1, p. 40, doi. 10.1080/10807039.2016.1219650
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Structural Insights on Hyp-Gly-Containing Peptides as Antiplatelet Compounds through Topomer CoMFA and CoMSIA Analysis.
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- Foods, 2023, v. 12, n. 4, p. 777, doi. 10.3390/foods12040777
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Quantitative Structure-Activity Relationships: Linear Regression Modelling and Validation Strategies by Example.
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- Biomath, 2013, v. 2, n. 1, p. 1, doi. 10.11145/j.biomath.2013.09.089
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THREE-DIMENSIONAL QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP AND COMPARATIVE MOLECULAR FIELD ANALYSIS OF CYP450 ENZYME SYSTEM INHIBITORS.
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- Pharma Science Monitor, 2013, v. 4, n. 2, p. 3890
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3D-QSAR COMFA, COMSIA STUDIES ON PYRAZOLO-FUSED AZADECALINS DERIVATIVES AS SELECTIVE GLUCOCORTICOID RECEPTOR ANTAGONISTS.
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- Pharma Science Monitor, 2012, v. 3, n. 4, p. 2027
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QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS OF MAP KINASE INHIBITOR.
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- Pharma Science Monitor, 2012, v. 3, n. 4, p. 1952
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3D-QSAR COMFA, COMSIA AND DOCKING STUDIES ON AMINOPYRIMIDINE IKK2 INHIBITORS.
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- Pharma Science Monitor, 2012, v. 3, n. 4, p. 1907
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Quinoxalinones Based Aldose Reductase Inhibitors: 2D and 3D-QSAR Analysis.
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- Molecular Informatics, 2019, v. 38, n. 8/9, p. 1, doi. 10.1002/minf.201800149
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Integrative Modeling Strategies for Predicting Drug Toxicities at the eTOX Project.
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- Molecular Informatics, 2015, v. 34, n. 6/7, p. 477, doi. 10.1002/minf.201400193
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A Combinational Strategy of Model Disturbance and Outlier Comparison to Define Applicability Domain in Quantitative Structural Activity Relationship.
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- Molecular Informatics, 2014, v. 33, n. 8, p. 503, doi. 10.1002/minf.201300161
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Quantitative structure activity relationship (QSAR) studies on nitazoxanide-based analogues against Clostridium difficile In vitro.
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- Pakistan Journal of Pharmaceutical Sciences, 2016, v. 29, n. 5, p. 1681
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QSAR studies on benzothiophene derivatives as Plasmodium falciparum N‐myristoyltransferase inhibitors: Molecular insights into affinity and selectivity.
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- Drug Development Research, 2022, v. 83, n. 2, p. 264, doi. 10.1002/ddr.21646
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Structural Insights from Molecular Modeling of Isoindolin-1-One Derivatives as PI3Kγ Inhibitors against Gastric Carcinoma.
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- Biomedicines, 2022, v. 10, n. 4, p. 813, doi. 10.3390/biomedicines10040813
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Thermal Resilience of Citizens: Comparison between Thermal Sensation and Objective Estimation in Outdoor Spaces: A Case Study in Seville, Spain.
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- Applied Sciences (2076-3417), 2022, v. 12, n. 22, p. 11676, doi. 10.3390/app122211676
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In-silico design of novel 4-aminoquinolinyl analogs as potential anti-malaria agents using quantitative structure-activity relationships and ADMET approach.
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- Tropical Journal of Pharmaceutical Research, 2020, v. 19, n. 1, p. 169, doi. 10.4314/tjpr.v19i1.25
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(–)-cleistenolide and its Analogs as New Potential Antitumor Compounds Against PC-3 Cells.
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- Pharmaceutical Chemistry Journal, 2022, v. 56, n. 5, p. 619, doi. 10.1007/s11094-022-02686-z
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3D-QSAR and Molecular Docking Studies of Novel GPR52 Agonists.
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- Journal of Computational Biophysics & Chemistry, 2023, v. 22, n. 5, p. 615, doi. 10.1142/S2737416523500308
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QSAR analysis of VEGFR-2 inhibitors based on machine learning, Topomer CoMFA and molecule docking.
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- BMC Chemistry, 2024, v. 18, n. 1, p. 1, doi. 10.1186/s13065-024-01165-8
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保健食品中添加地平类降压药急性毒性的 3D-QSAR模型建立.
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- Food Research & Development, 2023, v. 44, n. 11, p. 7, doi. 10.12161/j.issn.1005-6521.2023.11.002
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Estimating antiwear properties of esters as potential lubricant-based oils using QSTR models with CoMFA and CoMSIA.
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- Friction (2223-7704), 2018, v. 6, n. 3, p. 289, doi. 10.1007/s40544-017-0175-5
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Isosteric design of friction-reduction and anti-wear lubricant additives with less sulfur content.
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- Friction (2223-7704), 2018, v. 6, n. 2, p. 164, doi. 10.1007/s40544-017-0162-x
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3D-QSAR Study of the Chalcone Derivatives as Anticancer Agents.
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- Journal of Chemistry, 2020, p. 1, doi. 10.1155/2020/5268985
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Using Topomer Comparative Molecular Field Analysis to Elucidate Activity Differences of Aminomethylenethiophene Derivatives as Lysyl Oxidase Inhibitors: Implications for Rational Design of Antimetastatic Agents for Cancer Therapy.
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- Journal of Chemistry, 2020, p. 1, doi. 10.1155/2020/2036585
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The Application of CoMFA Approach for the Design of 1,4-Dihydropyridines as Calcium Channel Blockers.
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- Chemistry & Biology Interface, 2016, v. 6, n. 5, p. 350
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3D-QSAR, Molecular Docking, and MD Simulations of Anthraquinone Derivatives as PGAM1 Inhibitors.
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- Frontiers in Pharmacology, 2021, v. 12, p. 1, doi. 10.3389/fphar.2021.764351
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4‐Methyl morpholinium bis‐(thio)barbiturates: Synthesis, structure, anticancer evaluation, and CoMFA study.
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- Journal of the Chinese Chemical Society, 2020, v. 67, n. 9, p. 1679, doi. 10.1002/jccs.202000057
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Is it possible to improve the quality of predictions from an “intelligent” use of multiple QSAR/QSPR/QSTR models?
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- Journal of Chemometrics, 2018, v. 32, n. 4, p. 1, doi. 10.1002/cem.2992
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Quionolone carboxylic acid derivatives as HIV-1 integrase inhibitors: Docking-based HQSAR and topomer CoMFA analyses.
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- Journal of Chemometrics, 2017, v. 31, n. 12, p. 1, doi. 10.1002/cem.2934
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Studies on Substituted Thienopyridine Carbonitriles as Src Inhibitors Using a Comprehensive In Silico Method.
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- Indian Journal of Pharmaceutical Sciences, 2020, v. 82, n. 2, p. 270, doi. 10.36468/pharmaceutical-sciences.647
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