Research Themes
Molecular Design and Modeling, Chemistry Data Science
Assoc. Prof. Somsak Pianwanit
Computational Drug Discovery
Various computational drug discovery techniques are systematically employed, leveraging available experimental data to provide valuable insights for drug development across a diverse spectrum of diseases, with a primary emphasis on tropical diseases. For instance, the molecular docking technique facilitates the prediction of enzyme-inhibitor complex structures, while precise exploration of their interactions is achieved through rigorous quantum chemical calculations. Additionally, quantitative structure-activity relationship (QSAR) analysis yields robust mathematical models that predict the activity of novel compounds and offers guidelines for enhancing their efficacy by strategically modifying their chemical structures.
Keywords: QSAR, molecular docking, virtual screening, homology modeling, quantum chemical calculation
Dr. Pongphak Chidchob
Supramolecular polymerization approaches toward novel electroactive materials
Our research focuses on the design, functionalization, and fabrication of electroactive supramolecular polymers using electroactive π-conjugated oligomers as building blocks. Unlike traditional covalent polymers, supramolecular polymers are composed of monomers linked through directional supramolecular interactions such as hydrogen bonding, host-guest interactions, and metal coordination. These diverse supramolecular interactions endow the materials with attractive properties, including stimuli-responsiveness, self-healing capabilities, tunable processability as well as mechanical properties. The complex assembly process inherent in molecular self-assembly also provides promising avenues to achieve unprecedented material properties. Our goal is to utilize the concept of supramolecular polymerization to develop innovative materials for potential applications in electronics, energy, and biointerfaces.
Keywords: self-assembly, supramolecular polymers, electronic materials