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

The interaction between the Staphylococcal Protein A (SpA) domain B (the basis of the Affibody) molecule and the Fc of IgG is key to the use of Affibodies in affinity chromatography and in potential therapies against certain inflammatory diseases. Despite its importance and four-decade history, to our knowledge this interaction has never been affinity matured. We elucidate reasons why single-substitutions in the SpA which improve affinity to Fc may be very rare, and also discover substitutions which potentially serve several engineering purposes. We used a variation of FoldX to predict changes in protein-protein-binding affinity, and produce a list of 41 single-amino acid substitutions on the SpA molecule, of which four are near wild type (wt) and five are at most a factor of four from wt affinity. The nine substitutions include one which removes lysine, and several others which change charge. Subtle modulations in affinity may be useful for modifying column elution conditions. The method is applicable to other protein-protein systems, providing molecular insights with lower workload than existing experimental techniques.

Two-component signaling (TCS) is the primary means by which bacteria sense and respond to the environment. TCS involves two partner proteins working in tandem, which interact to perform cellular functions whereas limiting interactions with non-partners (i.e., cross-talk). We construct a Potts model for TCS that can quantitatively predict how mutating amino acid identities affect the interaction between TCS partners and non-partners. The parameters of this model are inferred directly from protein sequence data. This approach drastically reduces the computational complexity of exploring the sequence-space of TCS proteins. As a stringent test, we compare its predictions to a recent comprehensive mutational study, which characterized the functionality of 20 4 mutational variants of the PhoQ kinase in Escherichia coli. We find that our best predictions accurately reproduce the amino acid combinations found in experiment, which enable functional signaling with its partner PhoP. These predictions demonstrate the evolutionary pressure to preserve the interaction between TCS partners as well as prevent unwanted cross-talk. Further, we calculate the mutational change in the binding affinity between PhoQ and PhoP, providing an estimate to the amount of destabilization needed to disrupt TCS.