BCL::MP-Fold: Folding Membrane Proteins through Assembly of Transmembrane Helices

Abstract

Summary Membrane 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 3-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 new symmetry folding mode allows for the prediction of obligate homomultimers, a common property amongst membrane proteins. In a benchmark test of 40 proteins of known structure, the method samples 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.

Pushing the size limit of de novo structure ensemble prediction guided by sparse SDSL-EPR restraints to 200 residues: The monomeric and homodimeric forms of BAX

“…During the refinement stage, the weight for the SDSL-EPR score remains at 50. For homodimeric BAX, the protein structure prediction protocol was slightly altered to assemble and refine the models in C2-symmetry mode (Weiner et al, 2013). …”

Systematic evaluation of CS-Rosetta for membrane protein structure prediction with sparse NOE restraints

“…Our RASREC CS‐Rosetta results for pSRII and DsbB can be compared to the published data obtained with BCL::MP‐Fold . BCL::MP‐Fold employs an efficient algorithm that initially assembles ‐helices into MP topologies at the backbone level; structures are subsequently converted to full‐atom models using the Rosetta CCD loop building and FastRelax protocols .…”

Computational modeling of membrane proteins

“… Comparison of different de novo structure prediction methods using RMSDs to crystal structures versus sequence lengths of the modeled proteins. The data is taken from the following references: RosettaMembrane, RosettaMembrane*, BCL::MP‐Fold, FILM3, EVfold_membrane.…”

“…111 Rosetta uses three and nine residue fragments for assembly and was originally developed for prediction of small soluble proteins. For improved sampling of the extensive conformational search space of larger proteins, the fragment assembly approach of the BioChemicalLibrary used in BCL::MPfold uses complete secondary structure elements and outperforms Rosetta for most MPs and some large soluble proteins. Recently, the concept of correlated mutations (i.e., covariation of amino acid residues) has been applied to de novo MP structure prediction .…”