Combining protein modeling and 6D-QSAR. Simulating the binding of structurally diverse ligands to the estrogen receptor.
about
Is conformation a fundamental descriptor in QSAR? A case for halogenated anestheticsDual activities of odorants on olfactory and nuclear hormone receptors.Discovery of estrogen receptor modulators: a review of virtual screening and SAR efforts.A molecular-modeling toolbox aimed at bridging the gap between medicinal chemistry and computational sciences.An index for characterization of natural and non-natural amino acids for peptidomimeticsComputational ligand-based rational design: Role of conformational sampling and force fields in model development.The challenge of predicting drug toxicity in silico.In Silico Design and Evaluation of Carboxylesterase Inhibitors.In silico-aided prediction of biological properties of chemicals: oestrogen receptor-mediated effects.Recent advances in fragment-based QSAR and multi-dimensional QSAR methods.Persistence and dioxin-like toxicity of carbazole and chlorocarbazoles in soil.The advancement of multidimensional QSAR for novel drug discovery - where are we headed?Comparative Occupancy Analysis (CoOAn) - A Straightforward and Directly Applicable 3D-QSAR Formalism to Extract Molecular Features Obligatory for Designing Potent Leads.4D-QSAR investigation and pharmacophore identification of pyrrolo[2,1-c][1,4]benzodiazepines using electron conformational-genetic algorithm method.Improved, selective, human intestinal carboxylesterase inhibitors designed to modulate 7-ethyl-10-[4-(1-piperidino)-1-piperidino]carbonyloxycamptothecin (Irinotecan; CPT-11) toxicity.Molecular fingerprint-based artificial neural networks QSAR for ligand biological activity predictions.How good are ensembles in improving QSAR models? The case with eCoRIA.Quantitative structure-activity relationships for organophosphates binding to trypsin and chymotrypsin.Chemoinformatics Taking Biology into Account: ProteochemometricsEmploying conformational analysis in the molecular modeling of agrochemicals: insights on QSAR parameters of 2,4-D
P2860
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P2860
Combining protein modeling and 6D-QSAR. Simulating the binding of structurally diverse ligands to the estrogen receptor.
description
2005 nî lūn-bûn
@nan
2005 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2005 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2005年の論文
@ja
2005年論文
@yue
2005年論文
@zh-hant
2005年論文
@zh-hk
2005年論文
@zh-mo
2005年論文
@zh-tw
2005年论文
@wuu
name
Combining protein modeling and ...... ands to the estrogen receptor.
@ast
Combining protein modeling and ...... ands to the estrogen receptor.
@en
type
label
Combining protein modeling and ...... ands to the estrogen receptor.
@ast
Combining protein modeling and ...... ands to the estrogen receptor.
@en
prefLabel
Combining protein modeling and ...... ands to the estrogen receptor.
@ast
Combining protein modeling and ...... ands to the estrogen receptor.
@en
P2093
P356
P1476
Combining protein modeling and ...... ands to the estrogen receptor.
@en
P2093
Angelo Vedani
Markus A Lill
Max Dobler
P304
P356
10.1021/JM050185Q
P407
P577
2005-06-01T00:00:00Z