Engineering repressors with coevolutionary cues facilitates toggle switches with a master reset

Engineering allosteric transcriptional repressors containing an environmental sensing module (ESM) and a DNA recognition module (DRM) has the potential to unlock a combinatorial set of rationally designed biological responses. We demonstrated that constructing hybrid repressors by fusing distinct ESMs and DRMs provides a means to flexibly rewire genetic networks for complex signal processing. We have used coevolutionary traits among LacI homologs to develop a model for predicting compatibility between ESMs and DRMs. Our predictions accurately agree with the performance of 40 engineered repressors. We have harnessed this framework to develop a system of multiple toggle switches with a master OFF signal that produces a unique behavior: each engineered biological activity is switched to a stable ON state by different chemicals and returned to OFF in response to a common signal. One promising application of this design is to develop living diagnostics for monitoring multiple parameters in complex physiological environments and it represents one of many circuit topologies that can be explored with modular repressors designed with coevolutionary information

Direct-coupling analysis of residue co-evolution captures native contacts across many protein families

The similarity in the three-dimensional structures of homologous proteins imposes strong constraints on their sequence variability. It has long been suggested that the resulting correlations among amino acid compositions at different sequence positions can be exploited to infer spatial contacts within the tertiary protein structure. Crucial to this inference is the ability to disentangle direct and indirect correlations, as accomplished by the recently introduced Direct Coupling Analysis (DCA) (Weigt et al. (2009) Proc Natl Acad Sci 106:67). Here we develop a computationally efficient implementation of DCA, which allows us to evaluate the accuracy of contact prediction by DCA for a large number of protein domains, based purely on sequence information. DCA is shown to yield a large number of correctly predicted contacts, recapitulating the global structure of the contact map for the majority of the protein domains examined. Furthermore, our analysis captures clear signals beyond intra- domain residue contacts, arising, e.g., from alternative protein conformations, ligand- mediated residue couplings, and inter-domain interactions in protein oligomers. Our findings suggest that contacts predicted by DCA can be used as a reliable guide to facilitate computational predictions of alternative protein conformations, protein complex formation, and even the de novo prediction of protein domain structures, provided the existence of a large number of homologous sequences which are being rapidly made available due to advances in genome sequencing.Comment: 28 pages, 7 figures, to appear in PNA

Modeling Conformational Ensembles of Slow Functional Motions in Pin1-WW

Protein-protein interactions are often mediated by flexible loops that experience conformational dynamics on the microsecond to millisecond time scales. NMR relaxation studies can map these dynamics. However, defining the network of inter-converting conformers that underlie the relaxation data remains generally challenging. Here, we combine NMR relaxation experiments with simulation to visualize networks of inter-converting conformers. We demonstrate our approach with the apo Pin1-WW domain, for which NMR has revealed conformational dynamics of a flexible loop in the millisecond range. We sample and cluster the free energy landscape using Markov State Models (MSM) with major and minor exchange states with high correlation with the NMR relaxation data and low NOE violations. These MSM are hierarchical ensembles of slowly interconverting, metastable macrostates and rapidly interconverting microstates. We found a low population state that consists primarily of holo-like conformations and is a “hub” visited by most pathways between macrostates. These results suggest that conformational equilibria between holo-like and alternative conformers pre-exist in the intrinsic dynamics of apo Pin1-WW. Analysis using MutInf, a mutual information method for quantifying correlated motions, reveals that WW dynamics not only play a role in substrate recognition, but also may help couple the substrate binding site on the WW domain to the one on the catalytic domain. Our work represents an important step towards building networks of inter-converting conformational states and is generally applicable

DCA for FliN homodimer model

Coevolution couplings derived from Direct-Coupling Analysis used to predict the dimerization interface of FliN C-terminal domain (validation of methodology)

Chemical Cross-Links observed in the CCW state of FliN/FliM C-terminal dimer

Chemical Cross-Links in FliN/FliM C-terminal dimerization that are observed only in CCW rotational states of flagellar motor. This dataset from literature was used to support predicted model for FliN/FliM C-terminal heterodimer

DCA for FliM models

Coevolution couplings derived from Direct-Coupling Analysis used to predict FliM middle domain homodimers (parallel and twisted models)