Pore forming toxins (PFTs) are proteins which form unregulated oligomeric pores 
on target plasma membranes to cause ion leakage and cell death and represent the 
largest class of bacterial virulence factors. With increasing 
antibiotic-resistant bacterial strains, alternate therapies are being developed 
to target toxin pore formation rather than the bacteria themselves. One strategy 
is to undermine the stability of these multimeric pores, whose subunits are held 
together by complex amino acid interaction networks, by identifying key residues 
in these networks which could be plausible drug or mutagenesis targets. However, 
this requires a quantitative assessment of per residue contributions towards 
pore stability, which cannot be reliably gleaned from static crystal/cryo-EM 
pore structures. In this study, we overcome this limitation by developing a 
computational screening algorithm that employs fully atomistic molecular 
dynamics simulations coupled with energy-based screening that can predict 
'hot-spot' residues which engage in persistent and stabilizing hydrogen bonds or 
salt bridges across protein-protein interfaces. Application of this algorithm to 
prototypical α-PFT (cytolysin A) and β-PFT (α-hemolysin) membrane-inserted pores 
yielded a small predicted set of highly interacting residues, blocking of which 
could destabilize pore complexes. Previous mutagenesis studies validate some of 
our in silico predictions. The algorithm could be applied to all pores with 
known structures to generate a database of destabilizing mutations, which could 
then serve as a basis for experimental validation and rational structure-based 
inhibitor design.Communicated by Ramaswamy H. Sarma.