ArticleMolecular biology and evolution2016
Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes.
Article in Molecular biology and evolution, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Co-evolution of RcsD and RcsF shapes signal transduction in the enterobacteriaceae Rcs system.PloS one · 2026Article
- Thermal Adaptation of Cytosolic Malate Dehydrogenase Revealed by Deep Learning and Coevolutionary Analysis.Journal of chemical theory and computation · 2025Article
- Impact of phylogeny on the inference of functional sectors from protein sequence data.PLoS computational biology · 2024Article
- Machine learning in biological physics: From biomolecular prediction to design.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Functional effects of mutations in proteins can be predicted and interpreted by guided selection of sequence covariation information.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Residue coevolution and mutational landscape for OmpR and NarL response regulator subfamilies.Biophysical journal · 2024Article
- Coevolutionary Information Captures Catalytic Functions and Reveals Divergent Roles of Terpene Synthase Interdomain Connections.Biochemistry · 2024Article
- In vivo functional phenotypes from a computational epistatic model of evolution.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Is Novelty Predictable?Cold Spring Harbor perspectives in biology · 2024Review
- pycofitness-Evaluating the fitness landscape of RNA and protein sequences.Bioinformatics (Oxford, England) · 2024Article
- Evolution shapes interaction patterns for epistasis and specific protein binding in a two-component signaling system.Communications chemistry · 2024Article
- Selection pressures on evolution of ribonuclease H explored with rigorous free-energy-based design.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Latent generative landscapes as maps of functional diversity in protein sequence space.Nature communications · 2023Article
- Undersampling and the inference of coevolution in proteins.Cell systems · 2023Article
- Article
- Impact of phylogeny on structural contact inference from protein sequence data.Journal of the Royal Society, Interface · 2023Article
- Computational compensatory mutation discovery approach: Predicting a PARP1 variant rescue mutation.Biophysical journal · 2022Article
- Article
- Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences.PLoS computational biology · 2022Article
- Coupling a Live Cell Directed Evolution Assay with Coevolutionary Landscapes to Engineer an Improved Fluorescent Rhodopsin Chloride Sensor.ACS synthetic biology · 2022Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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
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