Abstract
Site rate and profile mixture models capture the heterogeneity of the amino acid substitution process across sites. However, these models typically use a single matrix of amino acid exchangeabilities and ignore potential heterogeneities of these exchangeabilities across sites. Simply combining multiple exchangeability matrices with rate and profile mixtures leads to a combinatorial explosion of mixture components and a prohibitive increase in free parameters. Here, we introduce GTRspmix, a novel framework that incorporates multiple exchangeability matrices into profile and site rate mixture models while effectively managing model complexity. GTRspmix employs a clustering-based strategy that groups profiles and assigns a distinct exchangeability matrix to each profile cluster. Evaluations using both empirical and simulated datasets demonstrate that GTRspmix fits empirical data significantly better than conventional models, and that overparameterization does not present a problem for sufficiently large alignments. Based on these results, we estimated general-purpose empirical models (SXXpfamCYY series available in IQ-TREE3) from the Pfam database. These general-purpose models not only fit data much better, but they also influence branch length and tree topology estimates, effectively mitigating long-branch attraction artifacts. Because the total number of rate matrices remains manageable, the computational efficiency of the inference is identical to that of conventional profile mixture models (e.g., LG+C60+G4). GTRspmix provides a more realistic and flexible model of protein evolution, offering a robust foundation for the inference of reliable phylogenetic trees.