The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
GABAA receptor activity modulating piperine analogs: In vitro metabolic stability, metabolite identification, CYP450 reaction phenotyping, and protein binding
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“with an average CLint value of 24.2 μL/min/mg protein, calculated from both in-house and reported literature values [31,32]”
From Predicting Food–Drug Interactions between Piperine and CYP3A4 Substrate Drugs Using PBPK Modeling (2024) · cites this paper as [31]
In the citing paper
“Reported values in the literature include 10.3 μL/min/mg protein from Zabela et al. [31] and 44.2 μL/min/mg protein from Gou et al. [32], both measured under the same conditions of HLM 0.5 mg/mL and piperine 1 μM.”
From Predicting Food–Drug Interactions between Piperine and CYP3A4 Substrate Drugs Using PBPK Modeling (2024) · cites this paper as [31]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Beyond classical benzodiazepines: novel therapeutic potential of GABAA receptor subtypes
Rudolph, U., & Knoflach, F. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3502 · Cited by 733
Erve, J. C. L., Gauby, S., Maynard, J. W., Svensson, M. A., Tonn, G., & Quinn, K. P. (2013) · Chemical Research in Toxicology · doi:10.1021/tx4001144 · Cited by 48
Research works printed but not linked: 16
- Zaugg, 2010, HPLC-based activity profiling: discovery of piperine as a positive GABAA receptor modulator targeting a benzodiazepine-independent binding site, J. Nat. Prod., 73, 185, 10.1021/np900656g · DOI
- McNamara, 2005, Effects of piperine the pungent component of black pepper, at the human vanilloid receptor (TRPV1), Br. J. Pharmacol., 144, 781, 10.1038/sj.bjp.0706040 · DOI · Paper page
- Khom, 2013, GABAA receptor modulation by piperine and a non-TRPV1 activating derivative, Biochem. Pharmacol., 85, 1827, 10.1016/j.bcp.2013.04.017 · DOI
- Schöffmann, 2014, Efficient modulation of γ-aminobutyric acid type A receptors by piperine derivatives, J. Med. Chem., 57, 5602, 10.1021/jm5002277 · DOI
- Attia, 2010, Deleterious effects of reactive metabolites, Oxid. Med. Cell Longev., 3, 238, 10.4161/oxim.3.4.13246 · DOI
- Wimmer, 2015, Developing piperine towards TRPV1 and GABAA receptor ligands–synthesis of piperine analogs via Heck-coupling of conjugated dienes, Org. Biomol. Chem., 13, 990, 10.1039/C4OB02242D · DOI
- Giuliano, 2005, Direct determination of unbound intrinsic drug clearance in the microsomal stability assay, Drug Metab. Dispos., 33, 1319, 10.1124/dmd.105.005033 · DOI
- Obach, 1999, Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: an examination of in vitro half-life approach and nonspecific binding to microsomes, Drug Metab. Dispos., 27, 1350, 10.1016/S0090-9556(24)14938-0 · DOI · Paper page
- Gillette, 1971, Factors affecting drug metabolism, Ann. N.Y. Acad. Sci., 179, 43, 10.1111/j.1749-6632.1971.tb46890.x · DOI
- Rowland, 1973, Clearance concepts in pharmacokinetics, J. Pharmacokinet. Biopharm., 1, 123, 10.1007/BF01059626 · DOI · Paper page
- Wilkinson, 1975, A physiological approach to hepatic drug clearance, Clin. Pharmacol. Ther., 18, 377, 10.1002/cpt1975184377 · DOI · Paper page
- Lau, 2002, The use of in vitro metabolic stability for rapid selection of compounds in early discovery based on their expected hepatic extraction ratios, Pharm. Res., 19, 1606, 10.1023/A:1020765025857 · DOI
- Parmentier, 2017, Direct and quantitative evaluation of the human CYP3A4 contribution (fm) to drug clearance using the in vitro SILENSOMES model, Xenobiotica, 47, 562, 10.1080/00498254.2016.1208854 · DOI
- Eigenmann, 2016, In vitro blood-brain barrier permeability predictions for GABAA receptor modulating piperine analogs, Eur. J. Pharm. Biopharm., 103, 118, 10.1016/j.ejpb.2016.03.029 · DOI
- Zhou, 2009, Polymorphism of human cytochrome P450 enzymes and its clinical impact, Drug Metab. Rev., 41, 89, 10.1080/03602530902843483 · DOI
- Tomalik-Scharte, 2008, The clinical role of genetic polymorphisms in drug-metabolizing enzymes, Pharmacogenomics J., 8, 4, 10.1038/sj.tpj.6500462 · DOI
Cited by
Predicting Food–Drug Interactions between Piperine and CYP3A4 Substrate Drugs Using PBPK Modeling
Lin, F., Hu, Y., Zhang, Y., Zhao, L., Zhong, D., & Liu, J. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252010955 · Cited by 20
Metadata
- Authors
- Zabela, V., Hettich, T., Schlotterbeck, G., Wimmer, L., Mihovilovic, M. D., Guillet, F., Bouaita, B., Shevchenko, B., Hamburger, M., & Oufir, M.
- Venue
- Journal of Chromatography B
- Publisher
- Elsevier BV
- Published
- 2018-01
- Volume
- 1072
- Pages
- 379-389
- ISSN
- 1570-0232
- Cited by
- 10
- References
- 2
- Language
- en
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 355 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Funders
- Swiss National Science Foundation (205320_126888)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
