Joy Yang

Computational chemist working with medicinal chemists and project team scientists to design potent, property optimized molecules against targets of interest, find new leads, select reagents for molecular series based on computational methods and better understand structure activity relationships between target binding sites and small molecule inhibitors.

Research: Identify and develop a novel class of antibacterials targeting gram negative pathogens Identified novel hit and lead molecules through docking/scoring of focused screening libraries. Evaluated the binding affinity of virtual ligands in MM-PBSA. Studied the binding free energy difference under different pH conditions in FEP. Prioritized compound synthesis based on the evaluation results. Applied Quantum Mechanical methods to study compound stability and reactivity. Designed new synthetically viable chemotypes and optimized the lead compound to balance target potency and toxicity properties

Analyzed the geometric and physical properties of the binding and nonbinding pockets on protein surfaces. Studied the local dynamics of protein binding pockets coupled to the global dynamics in MD simulation. Used structure-based virtual screening techniques to discover and characterize potential binding partners for several target proteins.

Doctoral Supervisor: Prof. Kim A. Sharp Dissertation: New Computational Tools for Rapid Macromolecular Simulation and Modeling Developed a new methodology to rapidly build alternative protein structures with geometrical correctness by using coarse-grained Normal Mode Analysis. Investigated the methodology’s application to protein design, protein structure transition study and homology modeling. Developed a general atomic charge assignment program by enhancing the electronegativity neutralization algorithm to allow charge polarization and increase the number of applicable functional groups.