Bioinformatics-driven discovery of novel Clostridioides difficile lysins and experimental comparison with highly active benchmarks.

Clostridioides difficile is the single most deadly bacterial pathogen in the United States, and its global prevalence and outsized health impacts underscore the need for more effective therapeutic options. Towards this goal, a novel group of modified peptidoglycan hydrolases with significant in vitro bactericidal activity have emerged as potential candidates for treating C. difficile infections (CDI).

DisruPPI: structure-based computational redesign algorithm for protein binding disruption.

Motivation: Disruption of protein-protein interactions can mitigate antibody recognition of therapeutic proteins, yield monomeric forms of oligomeric proteins, and elucidate signaling mechanisms, among other applications. While designing affinity-enhancing mutations remains generally quite challenging, both statistically and physically based computational methods can precisely identify affinity-reducing mutations. In order to leverage this ability to design variants of a target protein with disrupted interactions, we developed the DisruPPI protein design method (DISRUpting Protein-Protein Interactions) to optimize combinations of mutations simultaneously for both disruption and stability, so that incorporated disruptive mutations do not inadvertently affect the target protein adversely.