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Different pH-sensitivity patterns of 30 sodium channel inhibitors suggest chemically different pools along the access pathway.

Lazar A, Lenkey N, Pesti K, Fodor L, Mike A - Front Pharmacol (2015)

Bottom Line: One-way to probe this is to modify the pH of the extracellular fluid, which alters the ratio of charged vs. uncharged forms of some compounds, thereby changing their interaction with the membrane.We recorded the pH-dependence of potency, reversibility, as well as onset/offset kinetics.Unexpectedly, however, the pH-dependence of reversibility or kinetics showed diverse patterns, not simple correlation.

View Article: PubMed Central - PubMed

Affiliation: Intensive Care Unit, University of Medicine and Pharmacy Tirgu Mures, Romania.

ABSTRACT
The major drug binding site of sodium channels is inaccessible from the extracellular side, drug molecules can only access it either from the membrane phase, or from the intracellular aqueous phase. For this reason, ligand-membrane interactions are as important determinants of inhibitor properties, as ligand-protein interactions. One-way to probe this is to modify the pH of the extracellular fluid, which alters the ratio of charged vs. uncharged forms of some compounds, thereby changing their interaction with the membrane. In this electrophysiology study we used three different pH values: 6.0, 7.3, and 8.6 to test the significance of the protonation-deprotonation equilibrium in drug access and affinity. We investigated drugs of several different indications: carbamazepine, lamotrigine, phenytoin, lidocaine, bupivacaine, mexiletine, flecainide, ranolazine, riluzole, memantine, ritanserin, tolperisone, silperisone, ambroxol, haloperidol, chlorpromazine, clozapine, fluoxetine, sertraline, paroxetine, amitriptyline, imipramine, desipramine, maprotiline, nisoxetine, mianserin, mirtazapine, venlafaxine, nefazodone, and trazodone. We recorded the pH-dependence of potency, reversibility, as well as onset/offset kinetics. As expected, we observed a strong correlation between the acidic dissociation constant (pKa) of drugs and the pH-dependence of their potency. Unexpectedly, however, the pH-dependence of reversibility or kinetics showed diverse patterns, not simple correlation. Our data are best explained by a model where drug molecules can be trapped in at least two chemically different environments: A hydrophilic trap (which may be the aqueous cavity within the inner vestibule), which favors polar and less lipophilic compounds, and a lipophilic trap (which may be the membrane phase itself, and/or lipophilic binding sites on the channel). Rescue from the hydrophilic and lipophilic traps can be promoted by alkalic and acidic extracellular pH, respectively.

No MeSH data available.


Related in: MedlinePlus

Position of compound classes within the chemical space. We attempted to correlate pH-dependent behavior patterns (i.e., Classes A–G) with the chemical properties of the classes (i.e., their location within the chemical space). Classes are color-coded (same colors as in Figure 2), three-letter codes identify individual drugs. The insets are the exact same plots, where we marked the outlines of the areas occupied by specific classes. (A) logD(6.3) vs. logN(pKa) plot, (B) logP vs. aromatic atom count (AAC) plot, and (C) polar surface area (PSA) (Å2) vs. minimal projection area (Å2).
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Figure 3: Position of compound classes within the chemical space. We attempted to correlate pH-dependent behavior patterns (i.e., Classes A–G) with the chemical properties of the classes (i.e., their location within the chemical space). Classes are color-coded (same colors as in Figure 2), three-letter codes identify individual drugs. The insets are the exact same plots, where we marked the outlines of the areas occupied by specific classes. (A) logD(6.3) vs. logN(pKa) plot, (B) logP vs. aromatic atom count (AAC) plot, and (C) polar surface area (PSA) (Å2) vs. minimal projection area (Å2).

Mentions: The areas inhabited by the classes in three projections of the n-dimensional chemical space are illustrated in Figure 3. In Figure 3A we plotted logD(6.0) values against logN(pKa). Considering the areas occupied by different classes (see inset), we can conclude that predominantly neutral compounds with high logD(6.0) are more likely to manifest Class A or Class E type pH-dependence. Class C and Class F type pH-dependence occurred with predominantly charged compounds, with lower logD(6.0) values. Class B, Class D, and Class G mechanisms were not determined by logN(pKa) or logD(6.0, because compounds belonging to these classes were scattered widely. We need, therefore, to try to find descriptors which can differentiate Class A from Class E, as well as Class C from Class F; and which are able to define Classes B, D, and G.


Different pH-sensitivity patterns of 30 sodium channel inhibitors suggest chemically different pools along the access pathway.

Lazar A, Lenkey N, Pesti K, Fodor L, Mike A - Front Pharmacol (2015)

Position of compound classes within the chemical space. We attempted to correlate pH-dependent behavior patterns (i.e., Classes A–G) with the chemical properties of the classes (i.e., their location within the chemical space). Classes are color-coded (same colors as in Figure 2), three-letter codes identify individual drugs. The insets are the exact same plots, where we marked the outlines of the areas occupied by specific classes. (A) logD(6.3) vs. logN(pKa) plot, (B) logP vs. aromatic atom count (AAC) plot, and (C) polar surface area (PSA) (Å2) vs. minimal projection area (Å2).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4585259&req=5

Figure 3: Position of compound classes within the chemical space. We attempted to correlate pH-dependent behavior patterns (i.e., Classes A–G) with the chemical properties of the classes (i.e., their location within the chemical space). Classes are color-coded (same colors as in Figure 2), three-letter codes identify individual drugs. The insets are the exact same plots, where we marked the outlines of the areas occupied by specific classes. (A) logD(6.3) vs. logN(pKa) plot, (B) logP vs. aromatic atom count (AAC) plot, and (C) polar surface area (PSA) (Å2) vs. minimal projection area (Å2).
Mentions: The areas inhabited by the classes in three projections of the n-dimensional chemical space are illustrated in Figure 3. In Figure 3A we plotted logD(6.0) values against logN(pKa). Considering the areas occupied by different classes (see inset), we can conclude that predominantly neutral compounds with high logD(6.0) are more likely to manifest Class A or Class E type pH-dependence. Class C and Class F type pH-dependence occurred with predominantly charged compounds, with lower logD(6.0) values. Class B, Class D, and Class G mechanisms were not determined by logN(pKa) or logD(6.0, because compounds belonging to these classes were scattered widely. We need, therefore, to try to find descriptors which can differentiate Class A from Class E, as well as Class C from Class F; and which are able to define Classes B, D, and G.

Bottom Line: One-way to probe this is to modify the pH of the extracellular fluid, which alters the ratio of charged vs. uncharged forms of some compounds, thereby changing their interaction with the membrane.We recorded the pH-dependence of potency, reversibility, as well as onset/offset kinetics.Unexpectedly, however, the pH-dependence of reversibility or kinetics showed diverse patterns, not simple correlation.

View Article: PubMed Central - PubMed

Affiliation: Intensive Care Unit, University of Medicine and Pharmacy Tirgu Mures, Romania.

ABSTRACT
The major drug binding site of sodium channels is inaccessible from the extracellular side, drug molecules can only access it either from the membrane phase, or from the intracellular aqueous phase. For this reason, ligand-membrane interactions are as important determinants of inhibitor properties, as ligand-protein interactions. One-way to probe this is to modify the pH of the extracellular fluid, which alters the ratio of charged vs. uncharged forms of some compounds, thereby changing their interaction with the membrane. In this electrophysiology study we used three different pH values: 6.0, 7.3, and 8.6 to test the significance of the protonation-deprotonation equilibrium in drug access and affinity. We investigated drugs of several different indications: carbamazepine, lamotrigine, phenytoin, lidocaine, bupivacaine, mexiletine, flecainide, ranolazine, riluzole, memantine, ritanserin, tolperisone, silperisone, ambroxol, haloperidol, chlorpromazine, clozapine, fluoxetine, sertraline, paroxetine, amitriptyline, imipramine, desipramine, maprotiline, nisoxetine, mianserin, mirtazapine, venlafaxine, nefazodone, and trazodone. We recorded the pH-dependence of potency, reversibility, as well as onset/offset kinetics. As expected, we observed a strong correlation between the acidic dissociation constant (pKa) of drugs and the pH-dependence of their potency. Unexpectedly, however, the pH-dependence of reversibility or kinetics showed diverse patterns, not simple correlation. Our data are best explained by a model where drug molecules can be trapped in at least two chemically different environments: A hydrophilic trap (which may be the aqueous cavity within the inner vestibule), which favors polar and less lipophilic compounds, and a lipophilic trap (which may be the membrane phase itself, and/or lipophilic binding sites on the channel). Rescue from the hydrophilic and lipophilic traps can be promoted by alkalic and acidic extracellular pH, respectively.

No MeSH data available.


Related in: MedlinePlus