The microbiome-restorative potential of ibezapolstat for the treatment of Clostridioides difficile infection is predicted through variant PolC-type DNA polymerase III in Lachnospiraceae and Oscillospiraceae.

Abstract

Ibezapolstat (IBZ), a first-in-class antibiotic targeting the PolC-type DNA polymerase III alpha-subunit (PolC) in low G + C bacteria, is in clinical development for the treatment of Clostridioides difficile infection (CDI). In the phase 2 trials, IBZ had potent activity against C. difficile while sparing or causing regrowth of Lachnospiraceae, Oscillospiraceae, and Erysipelotrichales, common commensal low G + C bacteria. The purpose of this study was to utilize in silico approaches to better interpret the narrower than expected IBZ spectrum of activity. IBZ susceptibility to human commensal microbiota was predicted using genomic analysis and PolC phylogenetic tree construction in relation to C. difficile and commensal low G + C bacteria. Protein structure prediction was performed using AlphaFold2 and binding pocket homology modeling was performed using Schrodinger Maestro and UCSF ChimeraX. An amino acid phylogenetic tree identified certain residues that were phylogenetically variant in Lachnospiraceae, Oscillospiraceae, and Erysipelotrichales and conserved in C. difficile. Chemical modeling showed that these residues ablated key PolC•IBZ predicted interactions including two lysine "gates" (_CdiPolCLys1148 and _CdiPolCLys1327) that "latch" onto the compound; an "anchoring" interaction (_CdiPolCThr1331) to the central moiety; and a stabilized set of C. difficile sensitizer residues (_CdiPolCThr1291 and _CdiPolCLys1292) that resulted in the prolonged inhibition of a catalytic residue (_CdiPolCAsp1090). The observed IBZ sparing of Lachnospiraceae, Oscillospiraceae, and Erysipelotrichaceae/Coprobacillaceae was predicted using in silico techniques. Further studies that confirm a PolC structural basis for the IBZ narrower than expected activity are needed to confirm these in silico phylogenetic and chemical modeling data.