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More general and universally applicable drug discovery assay technologies are needed in order to keep pace with the recent advances in combinatorial chemistry and genomics-based target generation. Ligand-induced conformational stabilization of proteins is a well-understood phenomenon in which substrates, inhibitors, cofactors, and even other proteins provide enhanced stability to proteins on binding. This phenomenon is based on the energetic coupling of the ligand-binding and protein-melting reactions. In an attempt to harness these biophysical properties for drug discovery, fully automated instrumentation was designed and implemented to perform miniaturized fluorescence-based thermal shift assays in a microplate format for the high throughput screening of compound libraries. Validation of this process and instrumentation was achieved by investigating ligand binding to more than 100 protein targets. The general applicability of the thermal shift screening strategy was found to be an important advantage because it circumvents the need to design and retool new assays with each new therapeutic target. Moreover, the miniaturized thermal shift assay methodology does not require any prior knowledge of a therapeutic target's function, making it ideally suited for the quantitative high throughput drug screening and evaluation of targets derived from genomics.

The structural formula of an organic compound, in principle, contains coded within it all of the information which predetermines the chemical, biological, and physical properties of that compound. The molecular formula defines precisely all of the molecular properties and features, including, for example, the compound's rate of oxidation, the equilibrium constant and rate of absorption on any defined surface, the degree to which it will inhibit rust formation in sea water under any defined set of conditions, and so on. If we could only read the code, such properties could be elucidated simply from a knowledge of the molecular formula.There are two main alternative approaches to Edisonian random testing to find compounds with superior properties. One consists of theoretical calculations using quantum and statistical QSPR THE CORRELATION A N D QUANTITATIVE PREDICTION-A R KATRITZKY ET AL 28 1 10 References

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A quantitative structure−property relationship (QSPR) treatment of the normal boiling points was performed for a structurally wide variety of organic compounds using the CODESSA (comprehensive descriptors for structural and statistical analysis) technique. A highly significant two-parameter correlation (R 2 = 0.9544, s = 16.2 K) employs just two molecular parameters, a bulk cohesiveness descriptor, G I 1/3, and the area-weighted surface charge of the hydrogen-bonding donor atom(s) in the molecule. A more refined QSPR model (with R 2 = 0.9732 and s = 12.4 K) includes, in addition, the most negative atomic partial charge and the number of the chlorine atoms in the molecule. The four-parameter equation offers an average predicted error of 2.3% for a standard set of compounds with an average experimental error of 2.1%. The QSPR equations developed allow remarkably accurate predictions of the normal boiling points for a number of simple inorganic compounds, including water.