Systematic analysis of microorganisms’ metabolism for selective targeting

Abstract

Abstract 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.