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An Integrated Framework Advancing Membrane Protein Modeling and Design.

Alford RF, Koehler Leman J, Weitzner BD, Duran AM, Tilley DC, Elazar A, Gray JJ - PLoS Comput. Biol. (2015)

Bottom Line: Preliminary data show that these algorithms can produce meaningful scores and structures.The data also suggest needed improvements to both sampling routines and score functions.Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America; Department of Chemistry, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.

ABSTRACT
Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1) prediction of free energy changes upon mutation; (2) high-resolution structural refinement; (3) protein-protein docking; and (4) assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

No MeSH data available.


Assembly of symmetric protein complexes in the membrane using MPsymdock.(A) FoldTree representation of the homo-tetrameric KcsA potassium channel with the membrane residue (M) at the root (circled). The virtual residues V1,i and V2,i required for the symmetry machinery are described in the text. (B) Native structure in gray (PDB 1bl8) superimposed with the model from MPsymdock with the lowest interface score. The view is from the extracellular side of the membrane. (C) Membrane plane view of (B). (D) Interface score vs. backbone RMSD to the native structure for 1000 models of the KcsA potassium channel. The lowest scoring model, shown in (B) and (C), is indicated in red.
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pcbi.1004398.g008: Assembly of symmetric protein complexes in the membrane using MPsymdock.(A) FoldTree representation of the homo-tetrameric KcsA potassium channel with the membrane residue (M) at the root (circled). The virtual residues V1,i and V2,i required for the symmetry machinery are described in the text. (B) Native structure in gray (PDB 1bl8) superimposed with the model from MPsymdock with the lowest interface score. The view is from the extracellular side of the membrane. (C) Membrane plane view of (B). (D) Interface score vs. backbone RMSD to the native structure for 1000 models of the KcsA potassium channel. The lowest scoring model, shown in (B) and (C), is indicated in red.

Mentions: Many membrane proteins assemble into symmetric complexes in the membrane environment. We developed an application for symmetric assembly of complexes in the membrane bilayer; we achieved this by combining Rosetta’s symmetric docking protocol [64] with RosettaMP (Fig 8 with protocol capture in S5 File). The FoldTree maintains internal symmetry of the complex and its position in the membrane bilayer, with the membrane residue being at its root, hence keeping it fixed (Fig 8A). The subunits are arranged in Cn symmetry around the membrane normal axis (defined consistently in this protocol as the z-axis), where n is the number of subunits in the complex. To account for symmetry in the protein, the FoldTree uses two additional virtual residues per subunit, V1,i and V2,i, where i is the number of the subunit and 1 ≤ i ≤ n. The jump from V1,i to V1,i+1 describes the rotation and translation required to transform the ith subunit to the (i+1)th subunit based on the Cn symmetry, and the jump from V1,i to V2,i describes the rotation and translation between the V1,i and the protein subunit root residue. This setup allows the protocol to respect both symmetry and the membrane environment while allowing efficient sampling moves, side chain packing, and scoring.


An Integrated Framework Advancing Membrane Protein Modeling and Design.

Alford RF, Koehler Leman J, Weitzner BD, Duran AM, Tilley DC, Elazar A, Gray JJ - PLoS Comput. Biol. (2015)

Assembly of symmetric protein complexes in the membrane using MPsymdock.(A) FoldTree representation of the homo-tetrameric KcsA potassium channel with the membrane residue (M) at the root (circled). The virtual residues V1,i and V2,i required for the symmetry machinery are described in the text. (B) Native structure in gray (PDB 1bl8) superimposed with the model from MPsymdock with the lowest interface score. The view is from the extracellular side of the membrane. (C) Membrane plane view of (B). (D) Interface score vs. backbone RMSD to the native structure for 1000 models of the KcsA potassium channel. The lowest scoring model, shown in (B) and (C), is indicated in red.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4556676&req=5

pcbi.1004398.g008: Assembly of symmetric protein complexes in the membrane using MPsymdock.(A) FoldTree representation of the homo-tetrameric KcsA potassium channel with the membrane residue (M) at the root (circled). The virtual residues V1,i and V2,i required for the symmetry machinery are described in the text. (B) Native structure in gray (PDB 1bl8) superimposed with the model from MPsymdock with the lowest interface score. The view is from the extracellular side of the membrane. (C) Membrane plane view of (B). (D) Interface score vs. backbone RMSD to the native structure for 1000 models of the KcsA potassium channel. The lowest scoring model, shown in (B) and (C), is indicated in red.
Mentions: Many membrane proteins assemble into symmetric complexes in the membrane environment. We developed an application for symmetric assembly of complexes in the membrane bilayer; we achieved this by combining Rosetta’s symmetric docking protocol [64] with RosettaMP (Fig 8 with protocol capture in S5 File). The FoldTree maintains internal symmetry of the complex and its position in the membrane bilayer, with the membrane residue being at its root, hence keeping it fixed (Fig 8A). The subunits are arranged in Cn symmetry around the membrane normal axis (defined consistently in this protocol as the z-axis), where n is the number of subunits in the complex. To account for symmetry in the protein, the FoldTree uses two additional virtual residues per subunit, V1,i and V2,i, where i is the number of the subunit and 1 ≤ i ≤ n. The jump from V1,i to V1,i+1 describes the rotation and translation required to transform the ith subunit to the (i+1)th subunit based on the Cn symmetry, and the jump from V1,i to V2,i describes the rotation and translation between the V1,i and the protein subunit root residue. This setup allows the protocol to respect both symmetry and the membrane environment while allowing efficient sampling moves, side chain packing, and scoring.

Bottom Line: Preliminary data show that these algorithms can produce meaningful scores and structures.The data also suggest needed improvements to both sampling routines and score functions.Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America; Department of Chemistry, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.

ABSTRACT
Membrane proteins are critical functional molecules in the human body, constituting more than 30% of open reading frames in the human genome. Unfortunately, a myriad of difficulties in overexpression and reconstitution into membrane mimetics severely limit our ability to determine their structures. Computational tools are therefore instrumental to membrane protein structure prediction, consequently increasing our understanding of membrane protein function and their role in disease. Here, we describe a general framework facilitating membrane protein modeling and design that combines the scientific principles for membrane protein modeling with the flexible software architecture of Rosetta3. This new framework, called RosettaMP, provides a general membrane representation that interfaces with scoring, conformational sampling, and mutation routines that can be easily combined to create new protocols. To demonstrate the capabilities of this implementation, we developed four proof-of-concept applications for (1) prediction of free energy changes upon mutation; (2) high-resolution structural refinement; (3) protein-protein docking; and (4) assembly of symmetric protein complexes, all in the membrane environment. Preliminary data show that these algorithms can produce meaningful scores and structures. The data also suggest needed improvements to both sampling routines and score functions. Importantly, the applications collectively demonstrate the potential of combining the flexible nature of RosettaMP with the power of Rosetta algorithms to facilitate membrane protein modeling and design.

No MeSH data available.