Computational models for predicting substrates or inhibitors of P-glycoprotein.
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Veterinary Medicine Needs New Green Antimicrobial DrugsADMET evaluation in drug discovery: 15. Accurate prediction of rat oral acute toxicity using relevance vector machine and consensus modelingModelling three-dimensional protein structures for applications in drug design.Docking applied to the prediction of the affinity of compounds to P-glycoproteinA highly tumor-targeted nanoparticle of podophyllotoxin penetrated tumor core and regressed multidrug resistant tumors.Afatinib reverses multidrug resistance in ovarian cancer via dually inhibiting ATP binding cassette subfamily B member 1.Classification of P-glycoprotein-interacting compounds using machine learning methods.Overcoming doxorubicin resistance of cancer cells by Cas9-mediated gene disruption.Pharmacokinetics and tolerability of NSC23925b, a novel P-glycoprotein inhibitor: preclinical study in mice and rats.Inhibition of the multidrug resistance P-glycoprotein: time for a change of strategy?In vitro, in vivo and in silico models of drug distribution into the brain.In silico prediction of brain exposure: drug free fraction, unbound brain to plasma concentration ratio and equilibrium half-life.Structure-activity relationships and in silico models of P-glycoprotein (ABCB1) inhibitors.Overview of experimental models of the blood-brain barrier in CNS drug discovery.Influence of multidrug resistance and drug transport proteins on chemotherapy drug metabolism.Modeling of The hERG K+ Channel Blockage Using Online Chemical Database and Modeling Environment (OCHEM).Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitorsComputational approaches for innovative antiepileptic drug discovery.Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP.Bafetinib (INNO-406) reverses multidrug resistance by inhibiting the efflux function of ABCB1 and ABCG2 transporters.Ligand and structure-based classification models for prediction of P-glycoprotein inhibitors.Re-evaluation of the role of P-glycoprotein in in vitro drug permeability studies with the bovine brain microvessel endothelial cells.Maximizing computational tools for successful drug discovery.Molecular insight into conformational transmission of human P-glycoprotein.Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA.Three- and four-class classification models for P-glycoprotein inhibitors using counter-propagation neural networks.Computational classification models for predicting the interaction of drugs with P-glycoprotein and breast cancer resistance protein.Selective targeting and therapy of metastatic and multidrug resistant tumors using a long circulating podophyllotoxin nanoparticle.Using the Variable-Nearest Neighbor Method To Identify P-Glycoprotein Substrates and Inhibitors.Predicting drug resistance related to ABC transporters using unsupervised Consensus Self-Organizing MapsP-glycoprotein (P-gp)-mediated efflux limits intestinal absorption of the Hsp90 inhibitor SNX-2112 in ratsThe flexibility of P-glycoprotein for its poly-specific drug binding from molecular dynamics simulationsOvarian hormones modulate multidrug resistance transporters in the ovary
P2860
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P2860
Computational models for predicting substrates or inhibitors of P-glycoprotein.
description
2011 nî lūn-bûn
@nan
2011年の論文
@ja
2011年学术文章
@wuu
2011年学术文章
@zh-cn
2011年学术文章
@zh-hans
2011年学术文章
@zh-my
2011年学术文章
@zh-sg
2011年學術文章
@yue
2011年學術文章
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2011年學術文章
@zh-hant
name
Computational models for predicting substrates or inhibitors of P-glycoprotein.
@en
Computational models for predicting substrates or inhibitors of P-glycoprotein.
@nl
type
label
Computational models for predicting substrates or inhibitors of P-glycoprotein.
@en
Computational models for predicting substrates or inhibitors of P-glycoprotein.
@nl
prefLabel
Computational models for predicting substrates or inhibitors of P-glycoprotein.
@en
Computational models for predicting substrates or inhibitors of P-glycoprotein.
@nl
P2093
P1433
P1476
Computational models for predicting substrates or inhibitors of P-glycoprotein.
@en
P2093
Huidong Yu
Liling Zhang
P304
P356
10.1016/J.DRUDIS.2011.11.003
P577
2011-11-18T00:00:00Z