Structure–activity relationships of new inhibitors of breast cancer resistance protein (ABCG2)

Pick, Anne; Müller, Henrik; Wiese, Michael

doi:10.1016/j.bmc.2008.07.034

Cited by 79 publications

(100 citation statements)

References 52 publications

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“…The authors suggest a log D cutoff of 0.5, above which there is an increased likelihood of a compound-inhibiting ABCG2 (34). Though lipophilicity has been shown to be a good predictor of ABCG2 inhibition in some studies, other investigators have not found this descriptor to be significant (16,27). No correlation was found between log IC 50 and log P or log D for 30 tariquidar analogues (27).…”

Section: Resultsmentioning

confidence: 98%

“…Though lipophilicity has been shown to be a good predictor of ABCG2 inhibition in some studies, other investigators have not found this descriptor to be significant (16,27). No correlation was found between log IC 50 and log P or log D for 30 tariquidar analogues (27). In another study, ten descriptors, including log P, were used to construct a QSAR model for 23 propafenone analogues.…”

Section: Resultsmentioning

confidence: 98%

“…SARs were utilized to design the third-generation ABCB1 inhibitor tariquidar (XR9576) (27). Recently, it was discovered that tariquidar also inhibits ABCG2.…”

Section: Tariquidar Analoguesmentioning

confidence: 99%

“…The q 2 further dropped to 0.681, 0.598, and 0.507 for the leave-manyout method with 4, 3, and 2 groups, respectively. Contour plots were generated by the authors to help visualize the contribution of the different fields to the biological activity of compounds toward ABCG2 inhibition (27).…”

Section: Tariquidar Analoguesmentioning

confidence: 99%

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Structure–Activity Relationships and Quantitative Structure–Activity Relationships for Breast Cancer Resistance Protein (ABCG2)

Gandhi

Morris

2009

AAPS J

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Abstract. Breast cancer resistance protein (ABCG2), the newest ABC transporter, was discovered independently by three groups in the late 1990s. ABCG2 is widely distributed in the body with expression in the brain, intestine, and liver, among others. ABCG2 plays an important role by effluxing drugs at the blood-brain, blood-testis, and maternal-fetal barriers and in the efflux of xenobiotics at the small intestine and kidney proximal tubule brush border and liver canalicular membranes. ABCG2 transports a wide variety of substrates including HMG-CoA reductase inhibitors, antibiotics, and many anticancer agents and is one contributor to multidrug resistance in cancer cells. Quantitative structureactivity relationship (QSAR) models and structure-activity relationships (SARs) are often employed to predict ABCG2 substrates and inhibitors prior to in vitro and in vivo studies. QSAR models correlate in vivo biological activity to physicochemical properties of compounds while SARs attempt to explain chemical moieties or structural features that contribute to or are detrimental to the biological activity. Most ABCG2 datasets available for in silico modeling are comprised of congeneric series of compounds; the results from one series usually cannot be applied to another series of compounds. This review will focus on in silico models in the literature used for the prediction of ABCG2 substrates and inhibitors.KEY WORDS: ABC transporter; ABCG2; breast cancer resistance protein; quantitative structureactivity relationships; structure-activity relationships.

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Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 98%

“…SARs were utilized to design the third-generation ABCB1 inhibitor tariquidar (XR9576) (27). Recently, it was discovered that tariquidar also inhibits ABCG2.…”

Section: Tariquidar Analoguesmentioning

confidence: 99%

Section: Tariquidar Analoguesmentioning

confidence: 99%

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Structure–Activity Relationships and Quantitative Structure–Activity Relationships for Breast Cancer Resistance Protein (ABCG2)

Gandhi

Morris

2009

AAPS J

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“…A structure-activity relationship study of five XR derivatives and 25 structurally related compounds has been reported using data obtained in BCRP-overexpressing tumor cells (40). Three-dimensional QSAR analyses were performed using CoMFA and CoMSIA approaches.…”

Section: Bcrp Inhibitionmentioning

confidence: 99%

Structure–Activity Relationships of Tariquidar Analogs as Multidrug Resistance Modulators

Pajeva

Wiese

2009

AAPS J

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Abstract. The review summarizes the most recent achievements in structure-activity relationship (SAR) studies of tariquidar and its analogs. Tariquidar is one of the most promising representatives of the third generation of multidrug resistance (MDR) modulators created so far. This fact determines the strong interest of different research groups in the development of tariquidar-like structures as selective inhibitors of MDR transporters in resistant human cancer cells. After the discovery of tariquidar, a number of analogs have been synthesized and pharmacologically tested, thus supplying good data for comprehensive analyses of their structure-activity relationships. In the review, the structural and pharmacological data of newly synthesized tariquidar-like compounds are first presented. Next, the main achievements in the SAR studies are described focusing on two main transport proteins: P-glycoprotein and breast cancer resistance protein. The reported results are discussed from the point of view of their significance and importance for future directions in the rational design of effective MDR modulators.

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Transporters in Drug Discovery

2014

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Structure–activity relationships of new inhibitors of breast cancer resistance protein (ABCG2)

Cited by 79 publications

References 52 publications

Structure–Activity Relationships and Quantitative Structure–Activity Relationships for Breast Cancer Resistance Protein (ABCG2)

Structure–Activity Relationships and Quantitative Structure–Activity Relationships for Breast Cancer Resistance Protein (ABCG2)

Structure–Activity Relationships of Tariquidar Analogs as Multidrug Resistance Modulators

Transporters in Drug Discovery

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