In this chapter, firstly, we briefly review aspects of the approximation of quantum chemistry, molecular electrostatic potential (MEP), and chemometrics techniques, which are accredited as important tools in the development of chemical science and are frequently used in the study and design of bioactive compounds. Ultimately, we use MEP and pattern recognition (PR) techniques as tools to design nitrofuran compounds with biological activity against Trypanosoma cruzi (T. cruzi). PR models (PCA, HCA, KNN, SDA, and SIMCA) were constructed and demonstrated that 23 nitrofurans can be classified into two classes or groups: more active and less active according to their degrees of activity against T. cruzi. Properties such as charge on the N atom of the nitro group (QN1); the difference between the highest occupied molecular orbital (HOMO) energy and the lowest unoccupied molecular orbital (LUMO) energy (GAP energy); molecular representation of structure based on electron diffraction code of signal 5, unweighted (Mor05u); and Moriguchi water–octanol partition coefficient (MlogP) are responsible for the classification into more active and less active studied nitrofurans. It is interesting to notice that these properties represent three distinct classes of interactions between the nitrofurans and the biological receptor: electronic (QN1 and GAP energy), steric (Mor05u), and hydrophobic (MlogP). The results of the application of PR models on the validation set evidenced two nitrofuran compounds (compounds 25 and 30) as more promising for synthesis and biological assays, which in the future can be used to validate our PR models.
Part of the book: Cheminformatics and its Applications