ABSTRACT
Chemistry is “rst and foremost an experimental science relying more on empirical work carried out by trial and error than on theory where careful observation of both successes and failures in the laboratory guides the practitioners’ thinking on their current research problem. The intervention of theoretical and computational tools has been a recent addition in the evolution of the subject. Other disciplines such as physics, mathematics, computer science, and engineering have played huge roles in developing theories in chemistry and increasing the power of prediction in the subject. This has propelled it to have a “rm grounding and it has thus evolved to be a central science that connects with all other scienti“c “elds. One of the great triumphs was quantum mechanics whose practical offspring, spectroscopy, played an immeasurable role in speeding up the process of structure elucidation compared to traditional methods of degradation and analyzing the fragments. Another triumph is the great suite of analytical tools now available to detect molecules and to purify them. Still, despite all these advances, chemists’ ability to predict chemical properties of new molecules relies heavily on comparative analysis using the vast database of known compounds. Of course, predictions improve when there is a large enough database available. In the early days when only a few compounds were known, predictive powers were limited. Modern endeavors relying on the existence of large databases, database mining, and pattern recognition are the search for lead pharmaceutical compounds by combinatorial methods and structure determination of large biomolecules such as proteins.
