Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 253

The DOI matches its Crossref record; 126 of the 126 references it cites were found in a registry or an index.

Classification Analysis of P-Glycoprotein Substrate Specificity

Didziapetris, Remigijus, Japertas, Pranas, Avdeef, Alex, Petrauskas, Alanas·2003·Journal of Drug Targeting

Abstract

Prediction of P-glycoprotein substrate specificity (S(PGP)) can be viewed as a constituent part of a compound's "pharmaceutical profiling" in drug design. This task is difficult to achieve due to several factors that raised many contradictory opinions: (i) the disparity between the S(PGP) values obtained in different assays, (ii) the confusion between Pgp substrates and inhibitors, (iii) the confusion between lipophilicity and amphiphilicity of Pgp substrates, and (iv) the dilemma of describing class-specific relationships when Pgp has no binding sites of high ligand specificity. In this work, we compiled S(PGP) data for 1000 compounds. All data were represented in a binary format, assigning S(PGP) = 1 for substrates and S(PGP) = 0 for non-substrates. Each value was ranked according to the reliability of experimental assay. Two data sets were considered. Set 1 included 220 compounds with S(PGP) from polarized transport across MDR1 transfected cell monolayers. Set 2 included the entire list of 1000 compounds, with S(PGP) values of generally lower reliability. Both sets were analysed using a stepwise classification structure-activity relationship (C-SAR) method, leading to derivation of simple rules for crude estimation of S(PGP) values. The obtained rules are based on the following factors: (i) compound's size expressed through molar weight or volume, (ii) H-accepting given by the Abraham's beta (that can be crudely approximated by the sum of O and N atoms), and (iii) ionization given by the acid and base pKa values. Very roughly, S(PGP) can be estimated by the "rule of fours". Compounds with (N + O) > or = 8, MW > 400 and acid pKa > 4 are likely to be Pgp substrates, whereas compounds with (N + O) < or = 4, MW < 400 and base pKa < 8 are likely to be non-substrates. The obtained results support the view that Pgp functioning can be compared to a complex "mini-pharmacokinetic" system with fuzzy specificity. This system can be described by a probabilistic version of Abraham's solvation equation, suggesting a certain similarity between Pgp transport and chromatographic retention. The chromatographic model does not work in the case of "marginal" compounds with properties close to the "global" physicochemical cut-offs. In the latter case various class-specific rules must be considered. These can be associated with the "amphiphilicity" and "biological similarity" of compounds. The definition of class-specific effects entails construction of the knowledge base that can be very useful in ADME profiling of new drugs.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/10611860310001648248

Cites

126 of 126 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 126 references

Cited by

See all 253

Metadata

Authors
Didziapetris, R., Japertas, P., Avdeef, A., & Petrauskas, A.
Venue
Journal of Drug Targeting
Published
2003-08
Volume
11
Issue
7
Pages
391-406
ISSN
  • 1026-7158 (ISSN-L)
  • 1061-186X
  • 1029-2330
OpenAlex
W1976867680
Cited by
253
References
126
FWCI
2.08
Type
journal article
Language
en
Open access
closed

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Classification Analysis of P-Glycoprotein Substrate Specificity. https://app.cochat.ai/papers/10.1080/10611860310001648248
The paper
Didziapetris, R., Japertas, P., Avdeef, A., & Petrauskas, A. (2003). Classification Analysis of P-Glycoprotein Substrate Specificity. Journal of Drug Targeting. https://doi.org/10.1080/10611860310001648248

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.