Computational models for predicting substrates or inhibitors of P-glycoprotein

Chen, Lei; Li, Youyong; Yu, Huidong; Zhang, Liling; Hou, Tingjun

doi:10.1016/j.drudis.2011.11.003

Cited by 124 publications

(101 citation statements)

References 65 publications

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“…Dodatni faktori koje je potrebno uzeti u obzir prilikom formiranja seta podataka jesu hemijska raznovrsnost jedinjenja i relativna zastupljenost supstrata i nesupstrata. Najveći setovi korišćeni za uspostavljanje transportnih modela posredstvom Pgp-a uglavnom sadrže oko 300 jedinjenja [48], što je relativno mali broj koji ne obezbeđuje potpunu pokrivenost hemijskog prostora od značaja za medicinsku hemiju. Kvalitet eksperimentalnih podataka i veličina seta često su suprotstavljeni faktori prilikom formiranja seta podataka; prvi faktor odlučujuće utiče na pouzdanost, ali je drugi faktor presudan za domen primenjivosti modela.…”

Section: (Najniži)unclassified

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Computational models for predicting drug transport mediated by P-glycoprotein

Erić¹,

Kalinić²

2015

Arh farmaciju

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Kratak sadržajP-glikoprotein (Pgp) je transmembranski transporter koji, transportujući strukturno raznovrsne lekove iz unutrašnjosti ćelije u ekstracelularnu sredinu, može uticati na resorpciju, distribuciju i efikasnost većeg broja lekova. Prekomerna ekspresija Pgp-a u ćelijama predstavlja jedan od mehanizama razvoja rezistencije na lekove. Iz ovih razloga, potrebno je u ranoj fazi otkrića leka predvideti da li je potencijalni lek supstrat za Pgp, idealno i pre same sinteze. U tu svrhu, tokom poslednje decenije razvijen je veliki broj računarskih modela koji omogućavaju predviđanje transporta posredstvom Pgp-a samo na osnovu hemijske strukture. U ovom radu prikazan je pregled različitih pristupa koji su korišćeni u razvoju modela, razmotrene su njihove prednosti i nedostaci, kao i faktori koji u najvećoj meri utiču na pouzdanost predviđanja. Polispecifičnost ovog transportera predstavlja značajan izazov za većinu metoda računarske hemije. Ipak, dostignut nivo tačnosti modela koji su prikazani u litearaturi ukazuje na činjenicu da oni mogu doprineti racionalizaciji procesa dizajniranja novih lekova. Šira dostupnost eksperimentalnih podataka, kao i kombinovanje različitih pristupa modelovanju transporta, mogu dodatno unaprediti postojeće modele.Ključne reči: P-glikoprotein, računarski modeli, rezistencija, dizajn lekova.

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Section: (Najniži)unclassified

“…Usled ove činjenice, dostupnost kristalne strukture mišjeg Pgp-a nije značajno doprinela uspešnosti računarskih predviđanja transporta P-glikoproteinom [48,81]. Ipak, metode bazirane na strukturi Pgp-a komplementarne su sa predviđanjima modela zasnovanim na molekulskim deskriptorima.…”

Section: Modeli Zasnovani Na Strukturi Pgp-aunclassified

Computational models for predicting drug transport mediated by P-glycoprotein

Erić¹,

Kalinić²

2015

Arh farmaciju

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“…Modulators interact and bind with allosteric site of p-gp thereby reducing the substrate binding through conformational changes. Thus, inhibitors and modulators exert the same biological effect (Chen et al, 2012). Therefore, identification and characterization of p-gp inhibitors and modulators may provide a useful strategy for circumventing multidrug resistance.…”

Section: Enhancing Activity Of Anticancer Drugs In Multidrug Resistanmentioning

confidence: 99%

“…It has become an established fact now that p-gp mediates MDR by actively transporting a wide range of anticancer drugs including paclitaxel, doxorubicin, daunorubicin, vinca alkaloids and eteposide (Zhang et al, 2003;Yoshida et al, 2005;Ferreira et al, 2006;Nabekura, 2010a;Yang et al, 2014). P-gp can interact and bind with a large number of structurally and functionally unrelated agents which suggests its multiple binding sites (Zhang et al, 2009;Chen et al, 2012). According to the interactions, these agents can be classified into three main groups: substrate, inhibitors, and modulators.…”

Section: Enhancing Activity Of Anticancer Drugs In Multidrug Resistanmentioning

confidence: 99%

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Enhancing Activity of Anticancer Drugs in Multidrug Resistant Tumors by Modulating P-Glycoprotein through Dietary Nutraceuticals

Khan¹,

Maryam²,

Mehmood³

et al. 2015

Asian Pacific Journal of Cancer Prevention

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Multidrug resistance is a principal mechanism by which tumors become resistant to structurally and functionally unrelated anticancer drugs. Resistance to chemotherapy has been correlated with overexpression of p-glycoprotein (p-gp), a member of the ATP-binding cassette (ABC) superfamily of membrane transporters. P-gp mediates resistance to a broad-spectrum of anticancer drugs including doxorubicin, taxol, and vinca alkaloids by actively expelling the drugs from cells. Use of specific inhibitors/blocker of p-gp in combination with clinically important anticancer drugs has emerged as a new paradigm for overcoming multidrug resistance. The aim of this paper is to review p-gp regulation by dietary nutraceuticals and to correlate this dietary nutraceutical induced-modulation of p-gp with activity of anticancer drugs.

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Overview of Experimental Models of the Blood‐Brain Barrier in CNS Drug Discovery

Palmer¹,

Alavijeh

2013

CP Pharmacology

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The blood-brain barrier (BBB) is a physical and metabolic entity that isolates the brain from the systemic circulation. The barrier consists of tight junctions between endothelial cells that contain egress transporters and catabolic enzymes. To cross the BBB, a drug must possess the appropriate physicochemical properties to achieve a sufficient time-concentration profile in brain interstitial fluid (ISF). In this overview, we review techniques to measure BBB permeation, which is evidenced by the free concentration of compound in brain ISF over time. We consider a number of measurement techniques, including in vivo microdialysis and brain receptor occupancy following perfusion. Consideration is also given to the endothelial and nonendothelial cell systems used to assess both the BBB permeation of a test compound and its interactions with egress transporters, and computer models employed for predicting passive permeation and the probability of interactions with BBB transporters.

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Computational models for predicting substrates or inhibitors of P-glycoprotein

Cited by 124 publications

References 65 publications

Computational models for predicting drug transport mediated by P-glycoprotein

Computational models for predicting drug transport mediated by P-glycoprotein

Enhancing Activity of Anticancer Drugs in Multidrug Resistant Tumors by Modulating P-Glycoprotein through Dietary Nutraceuticals

Overview of Experimental Models of the Blood‐Brain Barrier in CNS Drug Discovery

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