Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. Notably, amino-acids located at the surface of proteins are known to evolve more rapidly than those in the core. In particular, amino-acids at the N- and C-termini of protein sequences are likely to be more exposed than those at the core of the folded protein due to their location in the peptidic chain, and they are known to be less structured. Because of these reasons, we would expect that amino-acids located at protein termini would evolve faster than residues located inside the chain. Here we test this hypothesis and found that amino acids evolve almost twice as fast at protein termini compared to those in the centre, hinting at a strong topological bias along the sequence length. We further show that the distribution of solvent-accessible residues and functional domains in proteins readily explain how structural and functional constraints are weaker at their termini, leading to the observed excess of amino-acid substitutions. Finally, we show that the specific evolutionary rates at protein termini may have direct consequences, notably misleading in silico methods used to infer sites under positive selection within genes. These results suggest that accounting for positional information should improve evolutionary models.

Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. However, the position of an amino-acid within the sequence is not known to influence this evolutionary speed. Here we discovered that amino-acid evolve almost twice faster at protein termini than in their centre, hinting at a strong topological bias along the sequence length. We further show that the distribution of functional domains and of solvent-accessible residues in proteins readily explain how functional constrains are weaker at their termini, leading to the observed excess of amino-acid substitutions. Finally, we show that methods inferring sites under positive selection are strongly biased towards protein termini, suggesting that they may confound positive selection with weak negative selection. These results suggest that accounting for positional information should improve evolutionary models.