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SummaryMembrane protein structure determination remains a challenging endeavor. Computational methods that predict membrane protein structure from sequence can potentially aid structure determination for such difficult target proteins. The de novo protein structure prediction method BCL::Fold rapidly assembles secondary structure elements into three-dimensional models. Here, we describe modifications to the algorithm, named BCL::MP-Fold, in order to simulate membrane protein folding. Models are built into a static membrane object and are evaluated using a knowledge-based energy potential, which has been modified to account for the membrane environment. Additionally, a symmetry folding mode allows for the prediction of obligate homomultimers, a common property among membrane proteins. In a benchmark test of 40 proteins of known structure, the method sampled the correct topology in 34 cases. This demonstrates that the algorithm can accurately predict protein topology without the need for large multiple sequence alignments, homologous template structures, or experimental restraints.

Electron density maps of membrane proteins or large macromolecular complexes are frequently only determined at medium resolution between 4 Å and 10 Å, either by cryo-electron microscopy (cryoEM) or X-ray crystallography. In these density maps the general arrangement of secondary structure elements is revealed while their directionality and connectivity remain elusive. We demonstrate that the topology of proteins with up to 250 amino acids can be determined from such density maps when combined with a computational protein folding protocol. Furthermore, we accurately reconstruct atomic detail in loop regions and amino acid side chains not visible in the experimental data. The EM-Fold algorithm assembles the secondary structure elements de novo before atomic detail is added using Rosetta. In a benchmark of 27 proteins the protocol consistently and reproducibly achieves models with RMSD values smaller than 3 Å.