Artificial antimicrobial peptides could help overcome drug-resistant bacteria

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 During the past several years, many strains of bacteria have become resistant to existing antibiotics, and very few new drugs have been added to the antibiotic arsenal.To help combat this growing public health problem, some scientists are exploring antimicrobial peptides -- naturally occurring peptides found in most organisms. Most of these are not powerful enough to fight off infections in humans, so researchers are trying to come up with new, more potent versions.

        Researchers at MIT and the Catholic University of Brasilia have now developed a streamlined approach to developing such drugs. Their new strategy, which relies on a computer algorithm that mimics the natural process of evolution, has already yielded one potential drug candidate that successfully killed bacteria in mice.

                  Antimicrobial peptides kill microbes in many different ways. They enter microbial cells by damaging their membranes, and once inside, they can disrupt cellular targets such as DNA, RNA, and proteins.

                        In their search for more powerful, artificial antimicrobial peptides, scientists typically synthesize hundreds of new variants, which is a laborious and time-consuming process, and then test them against different types of bacteria.

              De la Fuente-Nunez and his colleagues wanted to find a way to make computers do most of the design work. To achieve that, the researchers created a computer algorithm that incorporates the same principles as Darwin's theory of natural selection. The algorithm can start with any peptide sequence, generate thousands of variants, and test them for the desired traits that the researchers have specified.