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How drugs get into cells: tested and testable predictions to help discriminate between transporter-mediated uptake and lipoidal bilayer diffusion.

Kell DB, Oliver SG - Front Pharmacol (2014)

Bottom Line: One approach to experimental science involves creating hypotheses, then testing them by varying one or more independent variables, and assessing the effects of this variation on the processes of interest.One (BDII) asserts that lipoidal phospholipid Bilayer Diffusion Is Important, while a second (PBIN) proposes that in normal intact cells Phospholipid Bilayer diffusion Is Negligible (i.e., may be neglected quantitatively), because evolution selected against it, and with transmembrane drug transport being effected by genetically encoded proteinaceous carriers or pores, whose "natural" biological roles, and substrates are based in intermediary metabolism.Consequently, the view that Phospholipid Bilayer diffusion Is Negligible (PBIN) provides a starting hypothesis for assessing cellular drug uptake that is much better supported by the available evidence, and is both more productive and more predictive.

View Article: PubMed Central - PubMed

Affiliation: School of Chemistry, The University of Manchester Manchester, UK ; Manchester Institute of Biotechnology, The University of Manchester Manchester, UK.

ABSTRACT
One approach to experimental science involves creating hypotheses, then testing them by varying one or more independent variables, and assessing the effects of this variation on the processes of interest. We use this strategy to compare the intellectual status and available evidence for two models or views of mechanisms of transmembrane drug transport into intact biological cells. One (BDII) asserts that lipoidal phospholipid Bilayer Diffusion Is Important, while a second (PBIN) proposes that in normal intact cells Phospholipid Bilayer diffusion Is Negligible (i.e., may be neglected quantitatively), because evolution selected against it, and with transmembrane drug transport being effected by genetically encoded proteinaceous carriers or pores, whose "natural" biological roles, and substrates are based in intermediary metabolism. Despite a recent review elsewhere, we can find no evidence able to support BDII as we can find no experiments in intact cells in which phospholipid bilayer diffusion was either varied independently or measured directly (although there are many papers where it was inferred by seeing a covariation of other dependent variables). By contrast, we find an abundance of evidence showing cases in which changes in the activities of named and genetically identified transporters led to measurable changes in the rate or extent of drug uptake. PBIN also has considerable predictive power, and accounts readily for the large differences in drug uptake between tissues, cells and species, in accounting for the metabolite-likeness of marketed drugs, in pharmacogenomics, and in providing a straightforward explanation for the late-stage appearance of toxicity and of lack of efficacy during drug discovery programmes despite macroscopically adequate pharmacokinetics. Consequently, the view that Phospholipid Bilayer diffusion Is Negligible (PBIN) provides a starting hypothesis for assessing cellular drug uptake that is much better supported by the available evidence, and is both more productive and more predictive.

No MeSH data available.


Related in: MedlinePlus

Relative lack of relationship between the aqueous solubility of a drug and c log P for various drugs, marked by their BCS classes. We used pdfx (Constantin et al., 2013; http://pdfx.cs.man.ac.uk) to extract the data from Table 2 of Kasim et al. (2004). BCS class is encoded in the color of the symbols: 1, green; 2, blue; 3, red; 4, yellow.
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Figure 7: Relative lack of relationship between the aqueous solubility of a drug and c log P for various drugs, marked by their BCS classes. We used pdfx (Constantin et al., 2013; http://pdfx.cs.man.ac.uk) to extract the data from Table 2 of Kasim et al. (2004). BCS class is encoded in the color of the symbols: 1, green; 2, blue; 3, red; 4, yellow.

Mentions: While it is not obvious which actual measurements (as opposed to assumptions) of passive lipoidal permeability in biological membranes are being claimed (and we know of none), the above statement would also predict that if lipoidal bilayer permeability of drugs were a dominant means of drug uptake there should thus be a good correlation between cellular uptake and log P. This is a very important and testable prediction. Our very first review (Dobson and Kell, 2008) displayed a typical example taken from a paper by Corti et al. (2006), showing that there is not, and we would like to stress that this paper was not specifically selected—it just happened to be the first paper we looked at for this question. We here discuss another, rather famous, dataset. The Biopharmaceutics Classification System (BCS), based on the work of Amidon and colleagues (e.g., Amidon et al., 1995; Dahan et al., 2009; Chen et al., 2011), was developed to indicate a “bioequivalence,” and divides drugs into four classes based on their solubility and presumed (human jejunal) permeability, with “class 1” drugs that display high solubility and permeability deemed favorable and a waiver given http://www.fda.gov/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDER/ucm128219.htm (and see Lennernäs et al., 2014). The experimental jejunal permeability is not always available, and so it is estimated based on a “correlation” between the permeability of a drug's neutral form and c log P determined for a small number of drugs. The data for 27 or 29 such drugs vs. “estimated log P” and c log P are re-plotted from Table 4 and Figures 5, 6 of Kasim et al. (2004) (who very helpfully provided data in both tabular and graphical forms) in our Figure 6. We note there the extremely modest extent of the correlation between the experimental permeability and either the “estimated log P” or c log P. We also note that six of the eight “false negative” drugs (D-glucose, L-leucine, L-Dopa, L-phenylalanine, cephalexin, and valacyclovir) that were predicted to have low permeability but in fact had high permeability were recognized by the original authors as having transporters (Kasim et al., 2004). It is not clear whether it was assumed that the other drugs in Table 4 of Kasim et al. (2004) crossed passively by lipoidal bilayer diffusion (as opposed to facilitated diffusion through a transporter, that is also passive, Figure 3). At all events, whether it was so assumed or not, we can find evidence for interactions with transporters for each of the other drugs except for antipyrine, carbamazepine, and terbutaline. These are: α-methyldopa (Uchino et al., 2002), amoxicillin (Li et al., 2006; Sala-Rabanal et al., 2006; Fujiwara et al., 2011, 2012), atenolol (Kato et al., 2009), cimetidine (Collett et al., 1999; Burckhardt et al., 2003; Motohashi et al., 2004; Pavek et al., 2005; Matsushima et al., 2009; Tsuda et al., 2009), creatinine (Schömig et al., 2006; Chen et al., 2009; Zhou et al., 2009; Hosoya and Tachikawa, 2011; Tachikawa and Hosoya, 2011; Torres et al., 2011), desipramine (Wu et al., 2000; Haenisch et al., 2012), enalapril (Pang et al., 1998), enalaprilat (Ishizuka et al., 1998), fluvastatin (Varma et al., 2011; Sharma et al., 2012), furosemide (Uwai et al., 2000a; Eraly et al., 2006; Vallon et al., 2008), hydrochlorothiazide (Race et al., 1999; Uwai et al., 2000a; Hasannejad et al., 2004; Han et al., 2011), ketoprofen (Khamdang et al., 2002; Morita et al., 2005), Lisinopril (Knütter et al., 2008), losartan (Edwards et al., 1999; Race et al., 1999; Knütter et al., 2009; Sato et al., 2010), metoprolol (Dudley et al., 2000), naproxen (Apiwattanakul et al., 1999; Mulato et al., 2000; Khamdang et al., 2002; El-Sheikh et al., 2007), piroxicam (Jung et al., 2001; Khamdang et al., 2002), propranolol (Dudley et al., 2000; Wang et al., 2010a; Kubo et al., 2013b; Zheng et al., 2013), ranitidine (Collett et al., 1999; Müller et al., 2005; Ming et al., 2009), and verapamil (Döppenschmitt et al., 1999; Kubo et al., 2013a). We have also plotted (Figure 7) data from the Oral Drugs in the Core WHO Essential Medicines List (Table 2 of Kasim et al., 2004). These show the essential lack of a major relationship between solubility and c log P (and neither is well-correlated with bioavailability; Sutherland et al., 2012). A more recent predictive modeling study (Ghosh et al., 2014), in which the word “transporter” does not appear once, developed a theoretical framework for “passive permeability” and applied it to nine substances; these are, with some references indicating that they each have known transporter interactions, as follows: testosterone (Hamada et al., 2008; Sharifi et al., 2008), warfarin (Marchetti et al., 2007), dexamethasone (Polli et al., 2001; Schwab et al., 2003; Uchida et al., 2011a), raffinose (Tyx et al., 2011), metoprolol (Dudley et al., 2000), propranolol (Wang et al., 2010a; Zheng et al., 2013), verapamil (Döppenschmitt et al., 1999; Kubo et al., 2013a), ibuprofen (Uwai et al., 2000b) and (the lipophilic cation) crystal violet (Burse et al., 2004a,b).


How drugs get into cells: tested and testable predictions to help discriminate between transporter-mediated uptake and lipoidal bilayer diffusion.

Kell DB, Oliver SG - Front Pharmacol (2014)

Relative lack of relationship between the aqueous solubility of a drug and c log P for various drugs, marked by their BCS classes. We used pdfx (Constantin et al., 2013; http://pdfx.cs.man.ac.uk) to extract the data from Table 2 of Kasim et al. (2004). BCS class is encoded in the color of the symbols: 1, green; 2, blue; 3, red; 4, yellow.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4215795&req=5

Figure 7: Relative lack of relationship between the aqueous solubility of a drug and c log P for various drugs, marked by their BCS classes. We used pdfx (Constantin et al., 2013; http://pdfx.cs.man.ac.uk) to extract the data from Table 2 of Kasim et al. (2004). BCS class is encoded in the color of the symbols: 1, green; 2, blue; 3, red; 4, yellow.
Mentions: While it is not obvious which actual measurements (as opposed to assumptions) of passive lipoidal permeability in biological membranes are being claimed (and we know of none), the above statement would also predict that if lipoidal bilayer permeability of drugs were a dominant means of drug uptake there should thus be a good correlation between cellular uptake and log P. This is a very important and testable prediction. Our very first review (Dobson and Kell, 2008) displayed a typical example taken from a paper by Corti et al. (2006), showing that there is not, and we would like to stress that this paper was not specifically selected—it just happened to be the first paper we looked at for this question. We here discuss another, rather famous, dataset. The Biopharmaceutics Classification System (BCS), based on the work of Amidon and colleagues (e.g., Amidon et al., 1995; Dahan et al., 2009; Chen et al., 2011), was developed to indicate a “bioequivalence,” and divides drugs into four classes based on their solubility and presumed (human jejunal) permeability, with “class 1” drugs that display high solubility and permeability deemed favorable and a waiver given http://www.fda.gov/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDER/ucm128219.htm (and see Lennernäs et al., 2014). The experimental jejunal permeability is not always available, and so it is estimated based on a “correlation” between the permeability of a drug's neutral form and c log P determined for a small number of drugs. The data for 27 or 29 such drugs vs. “estimated log P” and c log P are re-plotted from Table 4 and Figures 5, 6 of Kasim et al. (2004) (who very helpfully provided data in both tabular and graphical forms) in our Figure 6. We note there the extremely modest extent of the correlation between the experimental permeability and either the “estimated log P” or c log P. We also note that six of the eight “false negative” drugs (D-glucose, L-leucine, L-Dopa, L-phenylalanine, cephalexin, and valacyclovir) that were predicted to have low permeability but in fact had high permeability were recognized by the original authors as having transporters (Kasim et al., 2004). It is not clear whether it was assumed that the other drugs in Table 4 of Kasim et al. (2004) crossed passively by lipoidal bilayer diffusion (as opposed to facilitated diffusion through a transporter, that is also passive, Figure 3). At all events, whether it was so assumed or not, we can find evidence for interactions with transporters for each of the other drugs except for antipyrine, carbamazepine, and terbutaline. These are: α-methyldopa (Uchino et al., 2002), amoxicillin (Li et al., 2006; Sala-Rabanal et al., 2006; Fujiwara et al., 2011, 2012), atenolol (Kato et al., 2009), cimetidine (Collett et al., 1999; Burckhardt et al., 2003; Motohashi et al., 2004; Pavek et al., 2005; Matsushima et al., 2009; Tsuda et al., 2009), creatinine (Schömig et al., 2006; Chen et al., 2009; Zhou et al., 2009; Hosoya and Tachikawa, 2011; Tachikawa and Hosoya, 2011; Torres et al., 2011), desipramine (Wu et al., 2000; Haenisch et al., 2012), enalapril (Pang et al., 1998), enalaprilat (Ishizuka et al., 1998), fluvastatin (Varma et al., 2011; Sharma et al., 2012), furosemide (Uwai et al., 2000a; Eraly et al., 2006; Vallon et al., 2008), hydrochlorothiazide (Race et al., 1999; Uwai et al., 2000a; Hasannejad et al., 2004; Han et al., 2011), ketoprofen (Khamdang et al., 2002; Morita et al., 2005), Lisinopril (Knütter et al., 2008), losartan (Edwards et al., 1999; Race et al., 1999; Knütter et al., 2009; Sato et al., 2010), metoprolol (Dudley et al., 2000), naproxen (Apiwattanakul et al., 1999; Mulato et al., 2000; Khamdang et al., 2002; El-Sheikh et al., 2007), piroxicam (Jung et al., 2001; Khamdang et al., 2002), propranolol (Dudley et al., 2000; Wang et al., 2010a; Kubo et al., 2013b; Zheng et al., 2013), ranitidine (Collett et al., 1999; Müller et al., 2005; Ming et al., 2009), and verapamil (Döppenschmitt et al., 1999; Kubo et al., 2013a). We have also plotted (Figure 7) data from the Oral Drugs in the Core WHO Essential Medicines List (Table 2 of Kasim et al., 2004). These show the essential lack of a major relationship between solubility and c log P (and neither is well-correlated with bioavailability; Sutherland et al., 2012). A more recent predictive modeling study (Ghosh et al., 2014), in which the word “transporter” does not appear once, developed a theoretical framework for “passive permeability” and applied it to nine substances; these are, with some references indicating that they each have known transporter interactions, as follows: testosterone (Hamada et al., 2008; Sharifi et al., 2008), warfarin (Marchetti et al., 2007), dexamethasone (Polli et al., 2001; Schwab et al., 2003; Uchida et al., 2011a), raffinose (Tyx et al., 2011), metoprolol (Dudley et al., 2000), propranolol (Wang et al., 2010a; Zheng et al., 2013), verapamil (Döppenschmitt et al., 1999; Kubo et al., 2013a), ibuprofen (Uwai et al., 2000b) and (the lipophilic cation) crystal violet (Burse et al., 2004a,b).

Bottom Line: One approach to experimental science involves creating hypotheses, then testing them by varying one or more independent variables, and assessing the effects of this variation on the processes of interest.One (BDII) asserts that lipoidal phospholipid Bilayer Diffusion Is Important, while a second (PBIN) proposes that in normal intact cells Phospholipid Bilayer diffusion Is Negligible (i.e., may be neglected quantitatively), because evolution selected against it, and with transmembrane drug transport being effected by genetically encoded proteinaceous carriers or pores, whose "natural" biological roles, and substrates are based in intermediary metabolism.Consequently, the view that Phospholipid Bilayer diffusion Is Negligible (PBIN) provides a starting hypothesis for assessing cellular drug uptake that is much better supported by the available evidence, and is both more productive and more predictive.

View Article: PubMed Central - PubMed

Affiliation: School of Chemistry, The University of Manchester Manchester, UK ; Manchester Institute of Biotechnology, The University of Manchester Manchester, UK.

ABSTRACT
One approach to experimental science involves creating hypotheses, then testing them by varying one or more independent variables, and assessing the effects of this variation on the processes of interest. We use this strategy to compare the intellectual status and available evidence for two models or views of mechanisms of transmembrane drug transport into intact biological cells. One (BDII) asserts that lipoidal phospholipid Bilayer Diffusion Is Important, while a second (PBIN) proposes that in normal intact cells Phospholipid Bilayer diffusion Is Negligible (i.e., may be neglected quantitatively), because evolution selected against it, and with transmembrane drug transport being effected by genetically encoded proteinaceous carriers or pores, whose "natural" biological roles, and substrates are based in intermediary metabolism. Despite a recent review elsewhere, we can find no evidence able to support BDII as we can find no experiments in intact cells in which phospholipid bilayer diffusion was either varied independently or measured directly (although there are many papers where it was inferred by seeing a covariation of other dependent variables). By contrast, we find an abundance of evidence showing cases in which changes in the activities of named and genetically identified transporters led to measurable changes in the rate or extent of drug uptake. PBIN also has considerable predictive power, and accounts readily for the large differences in drug uptake between tissues, cells and species, in accounting for the metabolite-likeness of marketed drugs, in pharmacogenomics, and in providing a straightforward explanation for the late-stage appearance of toxicity and of lack of efficacy during drug discovery programmes despite macroscopically adequate pharmacokinetics. Consequently, the view that Phospholipid Bilayer diffusion Is Negligible (PBIN) provides a starting hypothesis for assessing cellular drug uptake that is much better supported by the available evidence, and is both more productive and more predictive.

No MeSH data available.


Related in: MedlinePlus