Connecting the sequence-space of bacterial signaling proteins to phenotypes using coevolutionary landscapes

摘要: Two-component signaling (TCS) is the primary means by which bacteria sense and respond to environment. TCS involves two partner proteins working in tandem, interact perform cellular functions while limiting interactions with non-partners (i.e., ″cross-talk"). We construct a Potts model for that can quantitatively predict how mutating amino acid identities affect interaction between partners non-partners. The parameters of this are inferred directly from protein sequence data. This approach drastically reduces computational complexity exploring sequence-space proteins. As stringent test, we compare its predictions recent comprehensive mutational study, characterized functionality 204 variants PhoQ kinase Escherichia coli. find our best accurately reproduce combinations found experiment, enable functional PhoP. These demonstrate evolutionary pressure preserve as well prevent unwanted ″cross-talk". Further, calculate change binding affinity PhoP, providing an estimate amount destabilization needed disrupt TCS.