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New computational models of natural site mutations are developed that account for the different selective pressures acting on different locations in the protein. The number of adjustable parameters is greatly reduced by basing the models on the underlying physical-chemical properties of the amino acids. This allows us to use our method on small data sets built of specific protein types. We demonstrate that with this approach we can represent the evolutionary patterns in HIV envelope proteins far better than with more traditional methods.
Koshi et al. (Sat,) studied this question.
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