Im's bad bugs beware-bacterial membrane simulations earn researcher Bessel Award

CAPTION This photo was taken at the Annual Meeting of the Alexander von Humboldt Foundation 2017 on June 29th of this. CREDIT Alexander von Humboldt Foundation

Award supports Wonpil Im's collaboration with Jacobs University faculty members on modeling bacterial membrane channels and the transport of antibiotic molecules by proteins, using Im's online, open-source, biomolecular modeling tool CHARMM-GUI

Bacteria has a formidable enemy in Wonpil Im.

As researchers race against bacteria's growing resistance to antibiotics, Im is fighting back by accelerating knowledge about how antibiotics permeate bacterial membranes and target it for destruction. His weapon: computational biophysics.

Im, Presidential Endowed Chair in Health and Professor of Biological Sciences and Bioengineering at Lehigh University, is a pioneer in the development of new computer-aided biophysics methods. Biophysics aims to examine the processes in biological systems using the laws of physics and its measurement methods. He has been integral to the development of CHARMM-GUI an open-source tool that enables researchers throughout the world to generate simulations of complex biomolecular systems more simply and more precisely than previously possible. The National Science Foundation's Advances in Bio Informatics program is providing funding support for the maintenance and expansion of the web-based interface.

On June 29, 2017, Im was awarded a prestigious Friedrich Wilhelm Bessel Research Award by the Humboldt Foundation to support his antibiotic research with two collaborators from Jacobs University in Bremen, Germany: Dr. Ulrich Kleinekathöfer, Professor in Theoretical Physics, and biophysicist Prof. Dr. Mathias Winterhalter. The project will use computational biophysics to model bacterial membrane channels and the transport of molecules, in particular antibiotic molecules, by proteins. Im will use a specialized CHARMM-GUI module to build a simulation of Gram-negative bacteria's complex outer membrane.

"With the foundation awarding only 20 Bessel Research Awards each year, the award is evidence of Wonpil's accomplishments in the field and his international colleagues' eagerness to work with him," said Alan J. Snyder, Lehigh's vice president and associate provost for research and graduate studies.

Gram-negative bacteria are more resistant to antibiotics than Gram-positive bacteria because of their impenetrable cell wall made up of both an inner and outer membrane. Diseases caused by Gram-negative bacteria include cholera, typhoid, meningitis and various kinds of gastrointestinal distresses, including Escherichia coli, also known as E. coli.

"The work we are doing is aligned with one of the top drug development priorities identified by the European Commission's 'New Drugs for Bad Bugs' initiative: translocation, which focuses on understanding the molecular basis of bacterial cell wall permeability. Of particular concern is how antibiotic substances are transported across bacterial cell walls into the pathogens with the help of highly specialized transport proteins," says Im. "We don't really know the mechanics of how molecules penetrate the outer bacterial membrane. By understanding this process thoroughly, researchers could more easily predict what kinds of molecular structures could target specific bacterial proteins and kill the cell."

Im's group recently figured out how to use lipopolysaccharide, a simple phospholipid, to mimic the outer membrane of E. coli. It was the first major step for his lab to simulate a Gram-negative pathogen for drug discovery. Im's CHARMM-GUI can model lipopolysaccharide structures' various bacteria in less than 10 minutes.

Im's ultimate goal is to model complex biomolecular systems that will further scientific understanding of the structure and functions of 10 different superbugs. CHARMM-GUI is designed to advance such understanding.

"I hope that widespread access to this free graphical user interface will enable researchers worldwide to model any number of bacterial cells efficiently, pushing the boundaries of our modeling capabilities and leading to a greater understanding of how these complex systems actually work."

More about: |