Transmembrane β-barrel (TMB) proteins are embedded in the outer
membrane of Gram-negative bacteria, mitochondria and chloroplasts. The
cellular location and functional diversity of β-barrel
outer membrane proteins (omps) makes them an important protein class.
At the present time, very few non-homologous TMB structures have been
determined by X-ray diffraction because of the experimental
difficulty encountered in crystallizing transmembrane proteins. The
transFold web server uses pairwise inter-strand residue
statistical potentials derived from globular (non-outer-membrane)
proteins to predict the supersecondary structure of TMB.
Unlike all previous approaches, transFold does not use machine
learning methods such as hidden Markov models or neural networks;
instead, transFold employs multi-tape S-attribute grammars to
describe all potential conformations, and then applies dynamic
programming to determine the global minimum energy supersecondary
structure. The transFold web server not only predicts
secondary structure and TMB topology, but is the only method which
additionally predicts the side-chain orientation of transmembrane
β-strand residues, inter-strand residue contacts and
transmembrane β-strand inclination with respect to the
membrane. The program transFold currently outperforms all other
methods for accuracy of β-barrel structure prediction.