HMMs work just as well on membrane proteins as they do on globular proteins. Profile HMMs are are quite effective at identifying and aligning GPCRs, for example, and one of the best transmembrane helix annotation tools is TMHMM. The quality of an HMM is very dependent on the number and diversity of the sequences it is trained on and on details of the training procedure. If you take a poor multiple alignment and build a profile HMM from it, you will get a poor HMM. If you train an HMM on sequences that are not part of the family, you will get a poor HMM. If you train an HMM on only a small subfamily, you will get an HMM that does not generalize well to the full family. All these caveats apply equally to globular and membrane proteins, but there is less structural data available for membrane proteins, so people are often tempted to push the tools into much more distant relationships, often with poor results. Kevin Karplus karplus at soe.ucsc.edu http://www.soe.ucsc.edu/~karplus Senior member, IEEE Board of Directors, ISCB (starting Jan 2005) Professor of Biomolecular Engineering, University of California, Santa Cruz Undergraduate and Graduate Director, Bioinformatics Affiliations for identification only.