SCA was performed as described in (29) using PySCA 6 ( for two different multiple sequence alignments of the kinase catalytic domain: one specific to the CMGC kinases (635 sequences) and one containing 7128 kinases sampled across the kinome. The CMGC alignment was constructed by searching kinbase ( Sequences were filtered for a length of 250 to 350 amino acids and aligned by Promals3D (39) including the PDB identifiers 2B9H, 1BI8, 1Q97, 2ERK, 2F49, 2F9G, 2IW8, and 2R7I as reference structures. The kinome-wide alignment was previously constructed by the Shokat laboratory and was downloaded from (40). After alignment processing and the application of sequence weights [as described in (29)], the alignments contained 464 and 380 total effective sequences for the CMGC and eukaryotic protein kinase alignments, respectively. Both alignments are restricted to the catalytic domain and do not include regulatory domains. For both alignments, we followed an identical procedure for defining the sector. Briefly, we compute a conservation-weighted covariance matrix between all pairs of amino acid positions (see Supplementary Text for discussion of the relationship between the sector, conservation, and allosteric hotspots). This matrix provides a statistical description of the “evolutionary coupling” between all pairs of amino acid positions. We then analyze this matrix by conducting principal components analysis and rotating the top eigenmodes using independent component (IC) analysis. The top ICs are used to define sectors. For both kinase alignments, we define a single sector that includes all positions contributing to the top four ICs. The group of positions contributing to each IC groups is defined by fitting an empirical statistical distribution to the ICs and choosing positions above a defined cutoff (default, >95% of the continuous distribution function). The full analysis of both families can be downloaded from (

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