Applications of graph theory, network theory, and chemotopology to structure-activity relationships and characterization of metabolic processes.

摘要

Understanding how drugs cause the desired effect on the organism is of utmost importance for drug design. This is not only a scientific motto, but also an economic issue which pharmaceutical companies have comprehended quite well. Understanding the relationship between the structure of a substance and its biological activity is critical for drug discovery. A wealth of knowledge has been generated to grasp such relationships mainly from quantum chemical and mathematical description of molecules. Due to the large number of chemical substances with potential biological activity, which are normally collected in real or virtual libraries, the first step in the search for new drugs is to screen the chemical libraries which may lead to new drugs with less side effects and desirable therapeutic activity. Screening large libraries with quantum chemical tools normally can be very demanding on computer resources. In contrast, the use of mathematical characterization of molecules allows screening within a reasonable time and with low computational costs. This kind of relationship between mathematics and chemistry is one of the interests of the field of theoretical chemistry currently known as Mathematical Chemistry.