Published on July 13, 2009
Company Products Support Services News & Events Downloads Search Automating pKa Curve Fitting Using Origin Summary Brian Bissett, a scientist at Pfizer Global Research & Development, has performed research related to the development of new medicinal drugs. His research involved the analysis of chemical compounds in order to determine their pKa values. These pKa values were then, in turn, used to predict whether or not a specific compound has or does not have drug-like properties. The Problem Calculating the pKa values was an arduous task. Absorbance vs. pH data was captured on a scanning plate reader spectrophotometer. A typical assay utilized a standard 96 well microplate column-wise, resulting in an analysis of 12 compounds per plate, each with 8 data points. Each row of the microplate had a different value pH buffer in it (typically from pH 3.0 - pH 10.0). A set amount of compound in Dimethyl Sulfoxide (DMSO), a common pharmaceutical industry solvent, was then dispensed down an entire column providing absorbance values across the entire pH range for each compound. A pKa could be determined provided the compound for analysis had a perturbable pH induced chromophore*. The real bottleneck was the fact that it took so much time to individually curve fit each dataset to obtain a resultant pKa. First the scientist had to choose "the best" wavelength from which to try and curve fit a pKa. (The particular spectrophotometer being used scanned from 250nm to 750nm in 5nm increments.) Once the optimal wavelength was determined, the scientist would specify initial conditions (usually "reasonable" guesses for a parameter's starting value which would be optimized during the fitting process) for a curve fit. When a fit was then obtained from a set of data, a decision had to be made as to whether the fitted curve was returning a valid result. How Origin Was Used To circumvent these difficulties and free up time, algorithms were written in LabTalk™, Origin's scripting language, to accomplish the following tasks: 1. determine the best wavelength from which to extract data for a pKa curve fit
2. set up the curve fitter with reasonable initial conditions and trigger a curve fit of the data at the chosen wavelength 3. determine if the pKa returned from the fitting session was indeed reasonable The scripts were then hooked up to a graphical user interface, or GUI. Figures 1 and 2 depict the tool for an early (circa 1995) pKa assay developed by Mr. Bissett and a colleague, Dr. Chris Lipinski, in what was then the Physical Measurements Laboratory at Pfizer.
Figure 1: A solved single (or monotonic) pKa system utilizing Origin. The figure above shows the two tabs of the tool designed in Origin for analyzing the pKa data. In this example, a monotonic (or single) pKa system is solved. Pressing the "Do It" button in the lower right corner of the Run & Settings tab caused the software to automatically fit the data for all 12 samples using a rules based system. It was also possible for the operator to hand fit the data to any wavelength using either the bis or mono pKa equation by using the Fitting tab. The
fitted pKa's are shown as well as the r^2 (or cod) value (which represents the "goodness" of the fit). This option was typically only utilized if the automatic curve fitting algorithms were incapable of settling on a solution. The plot shows the raw data points in black with the fitted curve in red. Below (Fig 2) is the identical screen but run on a dual (or bis) pKa system.
The figure above shows the two tabs of the tool designed in Origin for analyzing the pKa data. In this example, a monotonic (or single ...
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