Coevolutionary information, protein folding landscapes, and the thermodynamics of natural selection

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Revealing evolutionary constraints on proteins through sequence analysis (2018, methodology): “…successfully employed via Direct Coupling Analysis (DCA) to identify strongly coupled residues that are in contact within a folded protein [36–38], to investigate folding [39], and to predict fitness [33, 40–45] and conformational changes [46, 47], as well as protein-protein interactions [48, 49].”
Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1 (2015, background): “[72] Faruck Morcos, Nicholas P Schafer, Ryan R Cheng, José N Onuchic, and Peter G Wolynes.”
Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes (2016, background): “Several studies have reported strong linear correlation between mutational changes in H ð s Þ with mutational changes in protein stability (Lui and Tiana 2013; Morcos et al. 2014; Contini and Tiana 2015).”
Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis (2017, background): “Direct coupling analysis (DCA) (1, 2) and related tools (3, 4) develop a global model mimicking evolutionary fitness landscapes of protein families (5, 6) and quantify the coevolution of amino acid residue positions (7–9).”