Date of Original Version




Abstract or Description

This work attempts to understand and explain positional selection pressure in terms of underlying physical and chemical properties. We propose a set of constraining assumptions about how these pressures behave, then describe a procedure for analyzing and explaining the distribution of residues at a particular position in a multiple sequence alignment. In contrast to previous approaches, our model takes into account both amino acid frequencies and a large number of physical-chemical properties. By analyzing each property separately, we are able to identify positions where an unusual conservation pattern is present. In addition, our model can easily incorporate sequence weights that adjust for bias in the sample sequences. Finally, we provide a measure of statistical significance for our conservation measure. We demonstrate the applicability of our method on two HIV-1 proteins: Nef and Env. Access to the data and results presented in this paper are available at


Later published as an article in Applied Bioinformatics 2004;3(2-3):167-79