Relationship between the bioavailability and molecular properties of angiotensin II receptor antagonists
In the present study, we investigated the relationships between several molecular properties and bioavailability data for seven of the most commonly prescribed angiotensin II receptor antagonists (also known as angiotensin II receptor blockers (ARBs) or sartans), candesartan, eprosartan, irbesartan,...
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Published in: | Archives of biological sciences Vol. 68; no. 2; pp. 273 - 278 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
University of Belgrade, University of Novi Sad
2016
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Subjects: | |
Online Access: | Get full text |
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Summary: | In the present study, we investigated the relationships between several
molecular properties and bioavailability data for seven of the most commonly
prescribed angiotensin II receptor antagonists (also known as angiotensin II
receptor blockers (ARBs) or sartans), candesartan, eprosartan, irbesartan,
losartan, olmesartan, telmisartan and valsartan. The molecular descriptors of
ARBs are:, aqueous solubility (logS values), polar surface area (PSA),
molecular weight (Mw), volume value (Vol), lipophilicity (logP values) and
the acidity descriptor (pKa1). The respective descriptors were calculated
using four different software packages. The relevant bioavailability data
were obtained from literature. Among calculated molecular descriptors, simple
linear regression analysis showed the best correlation between
bioavailability data and the lipophilicity descriptor, logP (R2 = 0.568).
Multiple linear regression established good correlations between
bioavailability and the lipophilicity descriptor, logP, using the molecular
weight, Mw, or the acidity descriptor, pKa1, as an additional, independent
variable (with R2 0.661 and 0.682, respectively). Finally, excluding
candesartan from the calculations resulted in a very good correlation (R2 =
0.852) between the remaining ARB bioavailability and molecular descriptors
MlogP and Mw as independent variables, determined by multiple linear
regression. |
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ISSN: | 0354-4664 1821-4339 |
DOI: | 10.2298/ABS150915015T |