TY - JOUR
T1 - Expanding the toolkit for membrane protein modeling in Rosetta
AU - Leman, Julia Koehler
AU - Mueller, Benjamin K.
AU - Gray, Jeffrey J.
N1 - Funding Information:
The authors would like to thank Rebecca Alford for the implementation of the mp-viewer and for technical help. We also thank the anonymous reviewers for their suggestions. Funding was provided from NIH R01 GM-078221 to JJG and JKL, NIH T32 NS007491 to BKM and RosettaCommons to JKL.
Publisher Copyright:
© The Author 2016. Published by Oxford University Press. All rights reserved.
PY - 2017
Y1 - 2017
N2 - Motivation: A range of membrane protein modeling tools has been developed in the past 5-10 years, yet few of these tools are integrated and make use of existing functionality for soluble proteins. To extend existing methods in the Rosetta biomolecular modeling suite for membrane proteins, we recently implemented RosettaMP, a general framework for membrane protein modeling. While RosettaMP facilitates implementation of new methods, addressing real-world biological problems also requires a set of accessory tools that are used to carry out standard modeling tasks. Results: Here, we present six modeling tools, including de novo prediction of single trans-membrane helices, making mutations and refining the structure with different amounts of flexibility, transforming a protein into membrane coordinates and optimizing its embedding, computing a Rosetta energy score, and visualizing the protein in the membrane bilayer. We present these methods with complete protocol captures that allow non-expert modelers to carry out the computations.
AB - Motivation: A range of membrane protein modeling tools has been developed in the past 5-10 years, yet few of these tools are integrated and make use of existing functionality for soluble proteins. To extend existing methods in the Rosetta biomolecular modeling suite for membrane proteins, we recently implemented RosettaMP, a general framework for membrane protein modeling. While RosettaMP facilitates implementation of new methods, addressing real-world biological problems also requires a set of accessory tools that are used to carry out standard modeling tasks. Results: Here, we present six modeling tools, including de novo prediction of single trans-membrane helices, making mutations and refining the structure with different amounts of flexibility, transforming a protein into membrane coordinates and optimizing its embedding, computing a Rosetta energy score, and visualizing the protein in the membrane bilayer. We present these methods with complete protocol captures that allow non-expert modelers to carry out the computations.
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U2 - 10.1093/bioinformatics/btw716
DO - 10.1093/bioinformatics/btw716
M3 - Article
C2 - 28011777
AN - SCOPUS:85020130076
VL - 33
SP - 754
EP - 756
JO - Bioinformatics
JF - Bioinformatics
SN - 1367-4803
IS - 5
ER -