Peptides: The Next Weapon Against Drug-Resistant Bacteria

Reposting and old post. Discovery of new antibiotics has stagnated in recent years. Peptides offer a new possible option. They can be digitally analyzed and optimised to combat antibiotic resistance using genetic algorithms and machine learning.

Rodrigo M. Ortiz de la Morena

9/20/20191 min read

n 1928, Alexander Fleming's accidental discovery of penicillin marked a milestone in antibiotic development. However, recent years have seen a stagnation in new antibiotic discoveries, leading to a rise in drug-resistant bacteria.

To combat this challenge, researchers are turning to peptides, chains of amino acids with antibiotic properties. Rather than relying solely on natural sources, scientists are leveraging digitalization to expedite peptide discovery. By digitally analyzing peptide structures and using algorithms like genetic and machine learning, scientists can predict and create peptides with enhanced antibacterial activity.

These advancements not only hold promise for fighting drug-resistant infections but also offer potential applications in targeting specific bacteria within the gut microbiota. With growing evidence of the gut-brain axis's impact on neurological disorders, such as autism spectrum disorders, Parkinson's, and Alzheimer's, peptide-based therapies could offer new avenues for treatment.

In conclusion, the convergence of biology, computational science, chemistry, and neurosciences in peptide research presents a compelling and multidisciplinary frontier. As artificial intelligence technologies continue to advance, the pace of discovery is expected to accelerate, offering hope for addressing antibiotic resistance and advancing neurological therapies.

Explore more about peptides and their role in combating drug-resistant bacteria in our engaging explainer video. Explainer videos and scientific illustrations can be highly engaging and useful ways to show the MoA (Mechanism of action) of new therapies. Let me know what you think about this case.