Poking Holes in Antibiotic Resistance

The problem with antibiotics is that bacteria become resistant.  Researchers at the University of Illinois at Urbana-Champaign set out to tackle this issue by designing “resistance-proof” antibiotics.  Their first candidate, a helical antimicrobial polypeptide, just might fit the bill.  

Antimicrobial peptides (AMPs) are rather widespread in nature (they are found in honey, for example). AMPs typically consist of 12 to 50 positively charged and nonpolar amino acids, and take on numerous secondary structures including alpha helices and beta strands.  The majority of AMPs kill bacteria (as well as some viruses and fungi) by disrupting their cell membranes.  The positively charged amino acids are attracted to the negatively charged membrane, and the nonpolar amino acids allow the AMP to interact with the hydrophobic membrane lipids.  These interactions disrupt the membrane, killing the cells.  
 
The University of Illinois team, let by Jianjun Cheng, faced a number of challenges when designing an AMP for therapeutic use.  For example, human cells are not immune to AMP activity, and many AMPs are quickly degraded by proteases once they enter the body.  

To overcome these issues, the team designed an AMP with a “radially amphiphilic structure” - a so-called “RA polypeptide”.  What this means is that the positively charged amino acids lie on the outside of the polypeptide, and the hydrophobic amino acids lie on the inside.  The team reasoned that such a design would prevent the RA polypeptides from aggregating and interacting with other components in the blood. In addition, the positively charged amino acids on the surface of the polypeptide should attract it to the negatively charged bacterial membranes.

The researchers plan to use their RA polypeptides in conjunction with traditional antibiotics.  According to Cheng, “the polypeptides punch holes in the membrane, which make it very easy for other drugs to go through and bypass some of the drug-resistant mechanisms … together, they work even better than a single agent”.

Sources: PNAS, Phys.org, Wikipedia