An Integrated Framework Advancing Membrane Protein Modeling and Design

PLoS Computational Biology
Rebecca F AlfordJeffrey J Gray

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 t...Continue Reading

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Methods Mentioned

BETA
NMR
PISA
sequence-based prediction

Software Mentioned

OCTOPUS
FoldTree
MEDELLER
MPrelax
AddMembraneMover
RosettaDock
RosettaScripts
RosettaMembrane
PyMOL Mover
LipidAccInfo

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