Literature DB >> 21604687

Toward a better pharmacophore description of P-glycoprotein modulators, based on macrocyclic diterpenes from Euphorbia species.

Ricardo J Ferreira1, Daniel J V A dos Santos, Maria-José U Ferreira, Rita C Guedes.   

Abstract

Multidrug resistance related to the increased expression of P-glycoprotein (P-gp) by cancer cells is the major contributor for the failure of chemotherapeutic treatments. Starting from pharmacophores and data already published and in macrocyclic diterpenes isolated from Euphorbia species, a comprehensive study of pharmacophore definitions of features was performed in order to obtain a new improved four-point pharmacophore able to detect literature and in-house modulators and simultaneously specific enough to avoid the detection of most nonactive molecules in a universe of 152 (literature), 74 (in-house), and 46 (inactive) molecules. This pharmacophore detects 84.2% of the molecules described in the literature, along with 100% detection of in-house isolated compounds and 19.5% of false positives. The importance of the hydrophobic and electron acceptor moieties as essential features for recognition of different molecules by the P-gp drug-binding site is clarified. The best combination of acceptor, donor, hydrophobic, and aromatic characteristics that contribute for the increased selectivity shown by the described pharmacophore is evaluated, and the protonation state of the molecules is also addressed.

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Year:  2011        PMID: 21604687     DOI: 10.1021/ci200145p

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  13 in total

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Review 2.  In Silico Studies in Drug Research Against Neurodegenerative Diseases.

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3.  Design, Synthesis, and Evaluation of Tetrasubstituted Pyridines as Potent 5-HT2C Receptor Agonists.

Authors:  Guy Rouquet; Dianna E Moore; Malcolm Spain; Daniel M Allwood; Claudio Battilocchio; David C Blakemore; Paul V Fish; Stephen Jenkinson; Alan S Jessiman; Steven V Ley; Gordon McMurray; R Ian Storer
Journal:  ACS Med Chem Lett       Date:  2015-01-20       Impact factor: 4.345

4.  Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors.

Authors:  Vijaya Kumar Hinge; Dipankar Roy; Andriy Kovalenko
Journal:  J Comput Aided Mol Des       Date:  2019-11-19       Impact factor: 3.686

5.  In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression.

Authors:  Ming-Han Lee; Giang Huong Ta; Ching-Feng Weng; Max K Leong
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Review 6.  Jatrophane and rearranged jatrophane-type diterpenes: biogenesis, structure, isolation, biological activity and SARs (1984-2019).

Authors:  Maryam Fattahian; Mustafa Ghanadian; Zulfiqar Ali; Ikhlas A Khan
Journal:  Phytochem Rev       Date:  2020-04-13       Impact factor: 7.741

7.  Pharmacophore modeling of nilotinib as an inhibitor of ATP-binding cassette drug transporters and BCR-ABL kinase using a three-dimensional quantitative structure-activity relationship approach.

Authors:  Suneet Shukla; Abdul Kouanda; Latoya Silverton; Tanaji T Talele; Suresh V Ambudkar
Journal:  Mol Pharm       Date:  2014-06-05       Impact factor: 4.939

8.  Theoretical Prediction of the Complex P-Glycoprotein Substrate Efflux Based on the Novel Hierarchical Support Vector Regression Scheme.

Authors:  Chun Chen; Ming-Han Lee; Ching-Feng Weng; Max K Leong
Journal:  Molecules       Date:  2018-07-22       Impact factor: 4.411

Review 9.  Prediction of drug-ABC-transporter interaction--Recent advances and future challenges.

Authors:  Floriane Montanari; Gerhard F Ecker
Journal:  Adv Drug Deliv Rev       Date:  2015-03-11       Impact factor: 15.470

Review 10.  Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases.

Authors:  Teresa Kaserer; Katharina R Beck; Muhammad Akram; Alex Odermatt; Daniela Schuster
Journal:  Molecules       Date:  2015-12-19       Impact factor: 4.411

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