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Allosteric communication between distant sites in proteins is central to biological regulation but still poorly characterized, limiting understanding, engineering and drug development1-6. An important reason for this is the lack of methods to comprehensively quantify allostery in diverse proteins. Here we address this shortcoming and present a method that uses deep mutational scanning to globally map allostery. The approach uses an efficient experimental design to infer en masse the causal biophysical effects of mutations by quantifying multiple molecular phenotypes-here we examine binding and protein abundance-in multiple genetic backgrounds and fitting thermodynamic models using neural networks. We apply the approach to two of the most common protein interaction domains found in humans, an SH3 domain and a PDZ domain, to produce comprehensive atlases of allosteric communication. Allosteric mutations are abundant, with a large mutational target space of network-altering 'edgetic' variants. Mutations are more likely to be allosteric closer to binding interfaces, at glycine residues and at specific residues connecting to an opposite surface within the PDZ domain. This general approach of quantifying mutational effects for multiple molecular phenotypes and in multiple genetic backgrounds should enable the energetic and allosteric landscapes of many proteins to be rapidly and comprehensively mapped.
Proteins with important functions are usually 'switchable', and their activities are modulated by the binding of other molecules, covalent modifications or mutations outside of their active sites. This transmission of information spatially from one site to another in a protein is termed allostery, which Monod famously referred to as 'the second secret of life'78. Allosteric regulation is central to nearly all of biology, including signal transduction, transcriptional regulation and metabolic control. Many disease-causing mutations, including numerous cancer driver mutations, are pathological because of their allosteric effects1. Conversely, many of the most effective therapeutic agents do not directly inhibit the active sites of proteins but modify their activities by binding to allosteric sites. Among other benefits, allosteric drugs often have higher specificity than orthosteric drugs that bind active sites that are conserved in protein families2,3.
Allosteric sites are difficult to predict, even for highly studied proteins with known active and inactive states4. Individual proteins may contain a limited number of allosteric sites, which would be consistent with their physiological regulation by a limited number of ligands and...