Sequence classification of water channels and related proteins in view of functional predictions

We have worked with a classification method based upon a notion of probabil istic similarity or "likelihood of similarity" between aligned sequences. O ne important parameter, among others, affecting the sequence similarities a nd hence the classification results is the amino acid similarity matrix. We present a method for choosing the most adapted matrix to classify protein sequences. This method has been applied to the transmembrane channels of th e major intrinsic protein (MIP) family. At present, two functional subgroup s have been well characterized in this family: (1) specific water transport by the aquaporins and (2) small neutral solutes transport. The aim of the present study is to show the usefulness of the classification method in the prediction of sequence segments important for substrate selectivity. Moreo ver, we show that this method can also be used to predict the function of u ndetermined MIP proteins. The method could be applied to other protein fami lies as well.