Graphical targeting techniques

Simple peak purity analysis is relatively accurate when the impurity is present at significant concentration levels but, as the level of impurity diminishes, its impact on the target analyte spectrum becomes subtler and may require more sophisticated techniques. For this, statistical software routines are available for automated spectral comparisons. In these cases, peak purity determination and analysis of spectral differences are achieved using vector analysis algorithms. The more similar the spectra are, the closer the value is to 0.0° the more spectrally different they are, the larger the value. All the spectral data points across the peak are analyzed the data are converted into vectors, compared, and graphically plotted so that the results can be visualized. These software routines provide both numerical results and graphical representations such as similarity and threshold curves. 

Several groups have used molecular graphics techniques to model ways In which ergosterol biosynthesis Inhibitors might bind to the active site of their target enzyme (13-14) and we have also looked at proehloraz and Its analogues In this way. 

Similarly to energy integration, techniques have been developed for targeting and optimisation of operations based on the exchange of mass. Simple graphical representations are not available yet, but appropriate computer methods could facilitate the application of this concept in the design practice in the future. 

In both of those editions, spectroscopic correlations are presented essentially in tabular form. It is onr conviction, however, that for spectroscopic data, correlation charts are far more easily used than tables. This is especially true of scientists and students who must make use (occasional or freqnent) of spectroscopic methods, while their own areas of specialization may lie elsewhere. We have therefore developed a set of fundamental correlation charts that target the same audience as the tabnlar format adopted in CRC Handbook of Basic Tables for Chemical Analysis. The exception wonld be the tables that we present here for mass spectrometry, a technique that does not lend itself to graphical presentation of data. It is nevertheless important to have data for this important techniqne covered here, since often multiple techniques, including mass spectrometry, are used for analyses and strnctnral determinations. 

---