Aggregating Homologous Protein Families in Evolutionary Reconstructions of Herpesviruses

Abstract

Abstract-Protein families can be used to reconstruct evolutionary histories of organisms. The accuracy of protein assignment to such families is critical for the success of such studies. Here we investigate the automatic aggregation of motif-defined homologous protein families for further reconstruction of their evolutionary histories. We propose a method that utilises only parameters that can be adjusted by using the data. The building blocks of the method include: (a) a majority rule for combining protein homologous neighbourhood lists into that for a family, and (b) a robust clustering procedure whose only parameter, the similarity shift, can be estimated from information on proteins with known function. The method is applied to a herpesvirus protein dataset leading to insights into the composition of ancestors of herpesvirus superfamilies. Comparison of the computational reconstructions with more comprehensive analyses also show how alignment-based betweenprotein similarity scoring can be improved by using data on gene arrangements.

The Iterative Extraction Approach to Clustering

“…To define an appropriate similarity shift value, families with known function have been selected and, of those, family pairs have been put into two categories: (I) those whose function is clearly the same (86 pairs), and (II) those whose function clearly differ (279 pairs) [37,38]. The pair-wise similarities should be high in the category (I) and low in the category (II), so that any intermediate value could be taken as the scale shift.…”

A Common Approach to Finding the Optimal Scenarios of a Markov Stochastic Process Over a Phylogenetic Tree

“…This iterative procedure together with the first open problem about it (described below) originates from Mirkin et al (7). The procedure is a part of the algorithm MALS (MAximum Likelihood Scenario) (7), on which some of the following considerations are based.…”