Isolation of MDCK cells with low expression of <i>mdr1</i> gene and their use in membrane permeability screening

Bokulić, Ana; Padovan, Jasna; Stupin-Polančec, Darija; Milić, Astrid

doi:10.2478/acph-2022-0003

Cited by 6 publications

(2 citation statements)

References 30 publications

(40 reference statements)

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“…However, a considerable chance of MDCK permeability exists. The MDCK cell line is also used for permeability screening in drug discovery ( BOKULIĆ et al, 2022 ). However, both ADMETLab 2.0 and SwissADME are in favor of better gastrointestinal absorption and bioavailability, indicated by the boiled-egg plot as well.…”

Section: Discussionmentioning

confidence: 99%

Computational pharmacology and computational chemistry of 4-hydroxyisoleucine: Physicochemical, pharmacokinetic, and DFT-based approaches

et al. 2023

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Computational pharmacology and chemistry of drug-like properties along with pharmacokinetic studies have made it more amenable to decide or predict a potential drug candidate. 4-Hydroxyisoleucine is a pharmacologically active natural product with prominent antidiabetic properties. In this study, ADMETLab 2.0 was used to determine its important drug-related properties. 4-Hydroxyisoleucine is compliant with important drug-like physicochemical properties and pharma giants’ drug-ability rules like Lipinski’s, Pfizer, and GlaxoSmithKline (GSK) rules. Pharmacokinetically, it has been predicted to have satisfactory cell permeability. Blood–brain barrier permeation may add central nervous system (CNS) effects, while a very slight probability of being CYP2C9 substrate exists. None of the well-known toxicities were predicted in silico, being congruent with wet lab results, except for a “very slight risk” for respiratory toxicity predicted. The molecule is non ecotoxic as analyzed with common indicators such as bioconcentration and LC50 for fathead minnow and daphnia magna. The toxicity parameters identified 4-hydroxyisoleucine as non-toxic to androgen receptors, PPAR-γ, mitochondrial membrane receptor, heat shock element, and p53. However, out of seven parameters, not even a single toxicophore was found. The density functional theory (DFT) study provided support to the findings obtained from drug-like property predictions. Hence, it is a very logical approach to proceed further with a detailed pharmacokinetics and drug development process for 4-hydroxyisoleucine.

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Section: Discussionmentioning

confidence: 99%

Computational pharmacology and computational chemistry of 4-hydroxyisoleucine: Physicochemical, pharmacokinetic, and DFT-based approaches

et al. 2023

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“…As alternative approaches, a short-term growing-cell assay with Madin-Darby canine kidney (MDCK) cells and parallel artificial membrane permeability assays (PAMPAs) have been used for permeability screening in drug discovery [24,25]. Given that wild-type (WT) MDCK cells are genetically heterogeneous, Bokulic et al [26] developed an assay system for assessing passive permeability based on a subclone of MDCK cells, which lowly expressed P-gp. Consequently, in silico permeability prediction models have been developed in accordance with various assay methods.…”

Section: General Assessmentmentioning

confidence: 99%

The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery

Komura,

Watanabe,

Mizuguchi

2023

Pharmaceutics

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Drug discovery and development are aimed at identifying new chemical molecular entities (NCEs) with desirable pharmacokinetic profiles for high therapeutic efficacy. The plasma concentrations of NCEs are a biomarker of their efficacy and are governed by pharmacokinetic processes such as absorption, distribution, metabolism, and excretion (ADME). Poor ADME properties of NCEs are a major cause of attrition in drug development. ADME screening is used to identify and optimize lead compounds in the drug discovery process. Computational models predicting ADME properties have been developed with evolving model-building technologies from a simplified relationship between ADME endpoints and physicochemical properties to machine learning, including support vector machines, random forests, and convolution neural networks. Recently, in the field of in silico ADME research, there has been a shift toward evaluating the in vivo parameters or plasma concentrations of NCEs instead of using predictive results to guide chemical structure design. Another research hotspot is the establishment of a computational prediction platform to strengthen academic drug discovery. Bioinformatics projects have produced a series of in silico ADME models using free software and open-access databases. In this review, we introduce prediction models for various ADME parameters and discuss the currently available academic drug discovery platforms.

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In vitro-in silico pharmacology and chemistry of Stercularin, isolated from Sterculia diversifolia

Ahmad,

Rabbi,

Nisar

et al. 2024

Computational Biology and Chemistry

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Isolation of MDCK cells with low expression of mdr1 gene and their use in membrane permeability screening

Cited by 6 publications

References 30 publications

Computational pharmacology and computational chemistry of 4-hydroxyisoleucine: Physicochemical, pharmacokinetic, and DFT-based approaches

Computational pharmacology and computational chemistry of 4-hydroxyisoleucine: Physicochemical, pharmacokinetic, and DFT-based approaches

The Trends and Future Prospective of In Silico Models from the Viewpoint of ADME Evaluation in Drug Discovery

In vitro-in silico pharmacology and chemistry of Stercularin, isolated from Sterculia diversifolia

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