Abstract
[Formula: see text]-Barrel membrane proteins ([Formula: see text]MPs) play important roles, but knowledge of their structures is limited. We have developed a method to predict their 3D structures. We predict strand registers and construct transmembrane (TM) domains of [Formula: see text]MPs accurately, including proteins for which no prediction has been attempted before. Our method also accurately predicts structures from protein families with a limited number of sequences and proteins with novel folds. An average main-chain rmsd of 3.48 Å is achieved between predicted and experimentally resolved structures of TM domains, which is a significant improvement ([Formula: see text]3 Å) over a recent study. For [Formula: see text]MPs with NMR structures, the deviation between predictions and experimentally solved structures is similar to the difference among the NMR structures, indicating excellent prediction accuracy. Moreover, we can now accurately model the extended [Formula: see text]-barrels and loops in non-TM domains, increasing the overall coverage of structure prediction by [Formula: see text]%. Our method is general and can be applied to genome-wide structural prediction of [Formula: see text]MPs.
Highlights
Β-Barrel membrane proteins play important roles, but knowledge of their structures is limited
They form β-barrels, so are known as β-barrel membrane proteins. β-Barrel membrane proteins (βMPs) are involved in outer membrane biogenesis, membrane anchoring, pore formation, translocation of virulence factors, and enzyme activities [2,3,4,5]
To predict structures of βMPs, we proceed in three steps: predicting strand registers, predicting 3D coordinates of TM residues, and modeling nonTM residues (Fig. 1)
Summary
Β-Barrel membrane proteins (βMPs) play important roles, but knowledge of their structures is limited. A recently published βMP-specific method that combines sequence covariation for contact prediction with a machinelearning–based method achieved limited progress, with a mainchain rmsd of 6.66 Afor predicted structures of TM regions, before it was adjusted to a better published value of 4.45 Awhen only a subset of residues were aligned instead of all TM residues [29] Another template-free βMP-specific method, 3DSPoT (3D structure predictor of transmembrane β-barrels), can predict the TM regions of βMPs with an average main-chain rmsd of 4.14 A [30]. Despite such progress, further improvement in prediction methods to generate accurate structural models is required to bridge the gap between identified βMP sequences and resolved βMP structures, so that modeled structures can be used directly for applications such as nanopore engineering and drug design/delivery
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