Abstract
In this work, belonging to the field of comparative analysis of protein sequences, we focus on detection of functional specialization on the residue level. As the input, we take a set of sequences divided into groups of orthologues, each group known to be responsible for a different function.This provides two independent pieces of information: within group conservation and overlap in amino acid type across groups. We build our discussion around the set of scoring functions that keep the two separated and the source of the signal easy to trace back to its source.We propose a heuristic description of functional divergence that includes residue type exchangeability, both in the conservation and in the overlap measure, and does not make any assumptions on the rate of evolution in the groups other than the one under consideration. Residue types acceptable at a certain position within an orthologous group are described as a distribution which evolves in time, starting from a single ancestral type, and is subject to constraints that can be inferred only indirectly. To estimate the strength of the constraints, we compare the observed degrees of conservation and overlap with those expected in the hypothetical case of a freely evolving distribution.Our description matches the experiment well, but we also conclude that any attempt to capture the evolutionary behavior of specificity determining residues in terms of a scalar function will be tentative, because no single model can cover the variety of evolutionary behavior such residues exhibit. Especially, models expecting the same type of evolutionary behavior across functionally divergent groups tend to miss a portion of information otherwise retrievable by the conservation and overlap measures they use.
Highlights
In the standard approach to computational analysis of proteins, the first step is detection of their functional parts through comparative analysis of homologous sequences
Our choice of the test set is guided by the following limiting criteria: (i) The functional divergence has experimental backup, through a systematic and unbiased study at the residue level, Figure 2
In this work we have argued that a heuristic method to detect specificity in a set of paralogous proteins can be broken down to several independent components: (i) conservation scoring function, (ii) overlap scoring function, (iii) the rule to add them together in a combined score, and, last but not least, (iv) the underlying model of evolution, specifying which groups are expected to be conserved, and which groups are expected to overlap in the amino acid type choice
Summary
In the standard approach to computational analysis of proteins, the first step is detection of their functional parts through comparative analysis of homologous sequences. Two types of evolutionary behavior are typically sought in a comparative analysis of a protein family: conservation across several groups of homologues, and specialization within each group The former is of interest for understanding structural and folding features of the class of proteins as a whole, while the latter becomes interesting in an attempt to control a particular set of paralogues, such as in designing a highly specific drug. The latter is the topic of this work. We discuss a class of heuristic methods designed to detect functional specialization without reconstructing the underlying sequence of evolutionary events
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