Overcoming resistance

Binkowski’s computational models analyze the three-dimensional structure of important classes of protein targets – stretches of DNA on a protein that look promising as docking sites for antibiotics and drugs. The National Institutes of Health, DOE and researchers from across the scientific community suggest protein-target nominees. Binkowski also is a member of the Center for Structural Genomics in Infectious Diseases (CSGID), which is supported by the NIH’s National Institute of Allergy and Infectious Diseases. The center applies technologies for rapidly analyzing biological structures to improve drugs attacking organisms that cause infectious diseases. CSGID and Argonne’s Midwest Center for Structural Genomics, which took part in the NDM-1 study, are considered among the world’s most productive hubs of their kind, deciphering and analyzing hundreds of protein structures each year.

Ligands in search of proteins

Binkowski concentrates on protein targets and ligand relationships. A protein is a macromolecule that might have tens of thousands of atoms; the ligand is a smaller molecule with fewer than 100 atoms. Think of the big protein sitting on a sort of dock. The ligand is a boat seeking a favorable place to land and unload goods, such as antibiotics.

When the ligand gets close enough, forces from the protein’s amino acid residues begin to act on it, Binkowski explains. “In normal protein activity this allows enzymes to perform their normal functions, catalyzing chemical reactions. In infectious diseases, we want to prevent or alter the organism’s normal functions, so we want to design a small molecule that will bind more aggressively to the protein. The more we know about the protein structure, the more effective we can be at doing this.”

Running on Intrepid, Binkowski uses an automated pipeline to model many different ligands and their interactions with a protein. It starts with crude docking models and, employing more sophisticated software that asks more stringent questions at each step, concludes with a list of candidate ligands for protein target sites.

“I have a whole suite of software applications that enables me to simulate and analyze the 3-D structure of the protein and to identify possible sites that could be important or capable of binding different small molecules,” he says. “I also speculate what kinds of molecules might be attracted to this particular spot. Moreover, if we find some molecules that should be attracted to the target, we ask, ‘What kinds of modifications can we do to make them even more attracted and better binders?’”

Supercomputer modeling establishes the ground floor for rational drug design – that is, working from a hypothesis based on a drug target’s biology rather than trial and error. Later, when he thinks he has the right match of protein target and ligand, Binkowski and his associates test their computational predictions by measuring binding in living organisms. They also use X-ray crystallography experiments, with the aid of Argonne’s Structural Biology Center at the powerful Advanced Photon Source, to validate their biomolecular simulations.