Yuan-Ping Pang, Principal Investigator

In Silico Drug Design

The focus of this research is the development and application of computational (in silico) methods for reliable determination of novel pharmaceutical drug leads. Viable drug candidates are predicted through the virtual screening of a database of millions of unique chemical structures against a target enzyme. Computationally identified leads are tested experimentally and optimized using combinatorial chemistry and medicinal chemistry.

In silico (virtual) screening studies are being performing using the researchers’ advanced docking program, EUDOC. This program permits molecular docking studies with metalloproteins and uses “spatial-decomposition” to achieve 100% parallelism. A Mayo in-house database called CHEMIX that consists of about 2.5 million druggable molecules facilitates virtual screening of drug targets. The researchers plan to increase the reliability of docking studies by increasing the number of conformations stored per molecule in the database. This is done by obtaining CM2 atomic charges for all molecules and by taking into account the change in free energy of solvation due to receptorligand complexation. A goal for the virtual screening efforts is to identify better second-generation farnesyltransferase inhibitors as potential cancer drugs.

In addition, this group is studying the dynamic structure of the active site of cofactor-independent phosphoglycerate mutase using a lengthy molecular dynamics simulation. The characterization of this active site will allow for the future in silico screening of this target in the search for novel antibacterial agents, computational study of Sin3- mediated transcriptional repression, and BIR3 inhibitor design.