Multiscale Modeling of the Bacterial Ribosome to Identify Potential Peptide Modulators and Their Allosteric Effects

The bacterial ribosome is a key antibiotic target, yet peptide-based modulation from its functional and allosteric sites is underexplored. We developed a computational pipeline combining SiteMap-derived binding-site detection, consensus docking with Glide and rDock, all-atom truncated molecular dynamics (MD), and coarse-grained MD (CGMD) simulations to identify peptide candidates against fourE. coliribosomal sites: the decoding center, peptidyl transferase center, a putative binding pocket on 30S, and the intersubunit bridge B8. Consensus-selected peptides recapitulated hallmark contacts of the native inhibitors viomycin and dalfopristin, and their interaction fingerprints delineate site-specific scaffolds that enable prioritization of inhibitor candidates with enhanced ribosomal affinity, thereby guiding the rational design of novel and effective peptide-based therapeutics. Notably, the peptide CycPeptMPDB_2508 exhibited binding affinity across all investigated sites, nominating it as a versatile lead core for antimicrobial peptide design. Dynamic cross-correlation matrices derived from CGMD simulations captured coupled motions between distal regions of the ribosome, while residue interaction network analysis identified hub residues enriched near the putative binding pocket and B8 bridge, outlining putative allosteric pathways linking local pockets to global motions relevant to decoding and domain closure. This work provides a concise, testable framework for ribosome-targeted peptide discovery and, to the best of our knowledge, constitutes the first ribosome-peptide virtual screening study to employ the viparr module for truncated ribosome-peptide complexes, suggesting the potential applicability of this approach to complex systems and broadening its scope.