A method pioneered by MIT researchers might offer hope in finding a new generation of antibiotics, made of antimicrobial peptides.
Antimicrobial peptides act by attaching to bacterial membranes and punching holes in them, an attack that is general to many different types of bacteria and is difficult for them to defend against. “There’s no quick easy mutation fix for a bacteria to get around this non-specific membrane attack,” said Loose. [Christopher Loose is a graduate student at MIT –ed.]
The peptides are generally short, consisting of about 20 amino acid building blocks. The molecules naturally fold into a helix, with positively charged areas running along one side of the helix and hydrophobic (water-resisting) areas along the other side. The charged ends allow the peptides to latch onto the bacteria by attracting the negative charges of the bacterial membrane, while the hydrophobic ends punch holes in the membrane.
Because there are 20 naturally occurring amino acids, there are about 1026 possible peptide sequences of length 20. Some of those kill microbes with varying levels of effectiveness; the overwhelming majority have no effect.
With such a mind-boggling number of possible combinations, it is extremely difficult to find effective antimicrobial peptides by using traditional methods such as testing random sequences or slightly tweaking naturally existing peptides. “Designing them from scratch is quite difficult,” said Loose.
Instead, the researchers decided to take a more strategic approach, based on grammatical patterns in the peptide sequences.
At its essence, a “grammar” is a simple rule that describes the allowed arrangements of words in a given language. As it applies to peptides, the sequence can be thought of as a sentence, while the individual amino acids are the words. For example, the sequence QxEAGxLxKxxK, where x is any amino acid and Q, E, A, etc. are specific amino acids, is a pattern that occurs in more than 90 percent of a certain class of insect antimicrobial proteins known as cecropins.
In this case, the researchers, led by Jensen and Isidore Rigoutsos of IBM Research (Rigoutsos is also a visiting lecturer in the Department of Chemical Engineering), used a pattern discovery tool to find about 700 grammatical patterns in the sequences of 526 naturally occurring antimicrobial peptides.
To design their new peptides, the researchers first came up with all possible 20-amino acid sequences in which each overlapping string of 10 amino acids conformed to one of the grammars. They then removed any peptides that had six or more amino acids in a row in common with naturally occurring peptides. Then, they threw out sequences that were very similar to each other and chose 42 peptides to test.
About half of the peptides displayed significant antimicrobial activity against two common strains of bacteria — Escherichia coli and Bacillus cereus. That is a much higher success rate than one would expect from testing randomly generated sequences, and much higher than the success rate for peptides with the same amino acids as the designed sequences, but in a shuffled order.