Leveraging Deep Learning and MD Simulations to Decipher the Molecular Basis of Attenuated Activity in Glycocin F

This is the authors' abstract. We don't add key points for this paper.

The escalating crisis of multi-drug resistant bacteria demand a new generation of antibiotics. Glycocin F (GccF), a potent bacteriocin, is a promising candidate, but its function hinges on unique post-translational glycosylation. Intriguingly, a seemingly minor chemical tweak of α-methylation at Ser18 of GccF destroys its activity, reducing potency by 1000-fold. To quantify how this subtle chemical change leads to profound functional compromise, we used an advanced molecular dynamics framework guided by Variational Autoencoder to unravel GccF’s complex dynamics. Our findings reveal that native glycosylation preserves conformational plasticity to maintain functionally relevant conformations. In stark contrast, α-methylation introduces local rigidity, locking the peptide into fewer metastable basins with significantly slower transition rates. This leads to the disruptions of α-helix structure which perturbs the loop-helix coupling and trapping the peptide into non-functional conformations. Together, these findings provide a critical blueprint for the rational design of next generation antibiotics, demonstrating how precise chemical modifications can dictate a peptide’s function by profoundly altering its structural dynamics.