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Since narrow-spectrum antibiotics specifically target the infection-causing organism, their negative side effects are reduced compared with their broad-spectrum counterparts. However, the design of these narrow-spectrum antibiotics requires accurate knowledge about drug targets in different microorganisms and their selectivity. Constraint-based metabolic models can provide this required knowledge using a mathematical framework for in-silico cell metabolism analysis and rewiring. Furthermore, competing against infectious pathogens, especially drug-resistant organisms, is more efficient by targeting multiple targets in each individual microorganism. Here, we combined the idea of synthetic lethality with selective drug targeting to obtain multi-target and organism-specific potential drug candidates for six different microorganisms and their various combinations. By considering each organism as targeted, conserved, or not included, we obtained 665 different cases for single essential reactions as well as double, triple, and quadruple synthetic lethal reaction sets. We found that conserving even one microorganism while attacking some targets reduces the number of potential cases tremendously. The number of solutions depends on how genomically far or close the microorganisms are in the phylogenetic tree. Furthermore, we statistically investigated how these potential drug targets attack different pathways in our studied cases, which reveals the importance of key routes such as cell envelope biosynthesis, glycerophospholipid metabolism, membrane lipid metabolism, and nucleotide salvage pathway.

The multidrug resistance of numerous pathogenic microorganisms is a serious challenge that raises global healthcare concerns. Multi-target medications and combinatorial therapeutics are much more effective than single-target drugs due to their synergistic impact on the systematic activities of microorganisms. A synthetic lethal (SL) is a set of non-essential targets (i.e., reactions or genes) that prevent the proliferation of a microorganism when they are “knocked out” simultaneously. To facilitate the identification of SLs, we introduce Rapid-SL, a new multimodal implementation of the Fast-SL method, using the depth-first search algorithm. The advantages of Rapid-SL over Fast-SL include: (a) the enumeration of all SLs that have an arbitrary cardinality, (b) a shorter runtime due to search space reduction, (c) embarrassingly parallel computations, and (d) the targeted identification of SLs. Targeted identification is important because the enumeration of higher order SLs demands the examination of too many reaction sets. Accordingly, we present specific applications of Rapid-SL for the efficient targeted identification of SLs. In particular, we found up to 67% of all quadruple SLs by investigating about 1% of the search space. Furthermore, 307 sextuples, 476 septuples, and over 9,000 octuples are found for Escherichia coli genome-scale model, iAF1260.