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ABSTRACT

     Angiotensin Receptor Blockers (ARBs) are among the most common drugs used to treat various cardiovascular diseases, primarily hypertension. Eight ARBs are clinically available, and two, Losartan and Valsartan, are among the most prescribed medications in the United States. ARBs target the Angiotensin Type 1 Receptor (AT1R). Multiple genetic studies have identified more than 100 polymorphisms in the AT1R. Polymorphisms can alter drug affinity to a receptor. Therefore, a plausible hypothesis is that polymorphisms within the AT1R affects ARB affinity. Fortunately, the AT1R was recently crystallized, providing a template for molecular modeling and ligand docking to predict the affinity of each ARB to each polymorphic AT1R. Unfortunately, the first docking run to wildtype AT1R did not match known experimental values; the mean deviation from the experimental medians was 504 ± 1116 nM. After altering and interpolating the docking parameters, parameters were optimized to produce affinities within   2 ± 2 nM of experimental values. With acceptable parameters, 103 polymorphisms present within the AT1R model were generated individually in Molecular Operating Environment software; each of the eight ARBs were docked in six trials with 100 dockings per trial to each polymorphic AT1R to test if individual polymorphisms differentially alter ARB affinity. Findings indicated that polymorphisms rarely affect all ARB affinities and even more rarely have no effect whatsoever; however, polymorphisms were commonly found to affect select ARB binding affinities. These results suggest that ARB therapy can be improved with personalized medicine via a tailored ARB therapy established upon a patient’s AT1R sequence.

Computational Prediction of Angiotensin Receptor Blocker Affinity to

Polymorphic Angiotensin Type 1 Receptor for Personalized Therapy

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