Site interdependence attributed to tertiary structure in amino acid sequence evolution

Standard likelihood-based frameworks in phylogenetics consider the process of evolution of a sequence site by site. Assuming that sites evolve independently greatly simplifies the required calculations. However, this simplification is known to be incorrect in many cases. Here, a computational method that allows for general dependence between sites of a sequence is investigated. Using this method, measures acting as sequence fitness proxies can be considered over a phylogenetic tree. In this work, a set of statistically derived amino acid pairwise potentials, developed in the context of protein threading, is used to account for what we call the structural fitness of a sequence. We describe a model combining statistical potentials with an empirical amino acid substitution matrix. We propose such a combination as a useful way of capturing the complexity of protein evolution. Finally, we outline features of the model using three datasets and show the approach's sensitivity to different tree topologies.