Jacob Durrant

  • Assistant Professor
  • Computer-aided drug design

Contact

Office: (801) 613-2277
103C Clapp Hall
4249 Fifth Avenue
Pittsburgh, PA 15260

Petascale, GPU, and cloud computing are transforming computational biology into an even more powerful tool for both medical and basic-science research. The mission of the Durrant lab is to develop broadly applicable, innovative computer-aided drug design (CADD) techniques and to apply those techniques to further infectious-disease, neurological, and cancer drug discovery. The biologically active molecules we identify also serve as small-molecule probes that shed light on protein function in cells.

PROTEIN-TARGET IDENTIFICATION

We use directed evolution in the ABC16 Green Monster yeast strain to identify proteins with important biological and disease-relevant functions. Both yeast and human cells have molecular pumps that expel toxins before they can bind to critical protein targets. Green-monster yeast is unique in that it lacks 16 of these pumps and so is especially susceptible to toxins. To survive, its critical protein targets must evolve/change so that the toxins no longer bind. We use whole-genome sequencing to identify these essential, altered yeast protein(s). Given that human and yeast cells are so similar, the human protein target is often closely related. Aside from identifying new targets in house, we also study known targets through collaborations with other experimentalist researchers.

SMALL-MOLECULE LIGAND IDENTIFICATION

We next use computational and experimental techniques to design small-molecule ligands--chemicals that bind to protein grooves and pockets--that can interfere with these proteins’ functions. By altering the activity of our protein targets, we aim to find new ways to treat disease and to learn more about basic microbiology. Computer-aided drug design (CADD) accelerates ligand identification by predicting protein binding in a computer. Using these predictions, scientists can test fewer molecules before finding one that is effective.

We also develop improved ligand-identification methods that draw on computer docking, molecular dynamics simulations, and big-data/machine-learning.

MOLECULAR VISUALIZATION

Proteins and ligands are invisible to the eye, so visualizing the results of virtual experiments requires modeling, scientific illustration, and 3D artistry. Molecular visualizations provide scientific insights and can serve as powerful educational tools. Blender, a 3D computer-graphics program used in the film and video-game industries, provides careful control over lighting and materials, allowing for photo-realistic protein images.
 
Beyond creating these visualizations, Durrant-lab students also develop techniques to improve molecular graphics. For example, we’re developing virtual-reality (VR) software so we can walk around–and through–our favorite proteins. ProteinVR will be a useful educational and collaborative tool.

 

Visit http://durrantlab.com/computational-biology-research/ to learn more.