Publication Date

2015

Document Type

Thesis

Committee Members

Rachel Aga (Committee Member), Eric Fossum (Advisor), Paul Seybold (Advisor), Kenneth Turnbull (Committee Member)

Degree Name

Master of Science (MS)

Abstract

The acid dissociation value pKa of a compound provides important information regarding the neutral and ionic forms of the compound present under different conditions. However, for many compounds experimental pKa values are not available, and for others the measured values are sometimes uncertain. Consequently, having a computational means for estimating pKa values can be of benefit for biochemical, pharmaceutical, polymer, and many other studies. Purines form a key group of bioactive compounds whose acid/base activities are of considerable interest. The purine class includes such diverse compounds as the nucleic acid bases adenine and guanine, the gout-related compound uric acid, the stimulant caffeine, and the leukemia drug 6-mercaptopurine. We have developed a computational method for estimating purine pKas using a quantitative structure property relationship (QSAR) approach. A group of 31 purines and related compounds was first assembled and then examined using the semi-empirical quantum chemical method RM1. This was followed by an ab initio analysis based on density functional theory at the B3LYP/ 6-31+G** level.

Page Count

101

Department or Program

Department of Chemistry

Year Degree Awarded

2015


Included in

Chemistry Commons

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