Prof. Dr. Ademir Camargo

The rational design of a new drug or a new material with specific properties has been the long-standing dream of pharmacologists and materials scientists. With the development of computational quantum chemistry algorithms and advancements in computational processing power, the rational design of new bioactive molecules and materials is becoming increasingly achievable. Although we have not yet been able to simulate the entire process of developing a new drug from start to finish, the application of molecular quantum mechanics methods and multivariate statistical analysis has profoundly impacted the development and understanding of the properties of new bioactive molecules. Among the various molecular quantum mechanics methods currently available to us, Density Functional Theory within the Kohn-Sham formalism (DFTKS) stands out. This method offers low computational cost with sufficiently high calculation accuracy to describe intermolecular interactions and chemical bonds. By using DFTKS, we can obtain important information about the interaction between bioactive molecules and their respective receptors. Examples of calculated properties include electrostatic potential, electron density maps, description of frontier molecular orbitals, partial atomic charges, bond orders, and more. The plethora of results from electronic structure calculations can be analyzed using multivariate statistical methods such as Principal Component Analysis (PCA), Partial Least Squares (PLS), and Hierarchical Cluster Analysis (HCA), among others. These statistical analyses help in selecting the molecular descriptors responsible for bioactivity. These descriptors are then used by synthetic chemists to rationalize new molecules with improved activities and fewer side effects. Electronic structure methods also enable the description of chemical reaction mechanisms. Through theoretical characterization of transition structures, we can provide detailed descriptions of the kinetics of chemical reactions, aspects of great importance to synthetic chemists. Another highly relevant aspect of this project is the study of the solvent influence on the geometric and electronic parameters of molecular systems of interest. In this case, we employ ab initio molecular dynamics to study the temporal evolution of interactions between solvent and solute molecules. Our group focuses primarily on Car-Parrinello molecular dynamics (CPMD) due to its ability to simulate long trajectories necessary to describe dynamic physicochemical properties, such as hydrogen bonds, that are extremely important in biological processes. We employ Born-Oppenheimer quantum molecular dynamics (DMBO) with the stochastic surface hopping algorithm to describe photochemical processes. This algorithm allows us to study the temporal evolution of excited states along with the respective photochemical reactions resulting from excitations.