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Cited by 323

The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.

Multipass membrane protein structure prediction using Rosetta

Open access
Yarov‐Yarovoy, Vladimir, Schonbrun, Jack, Baker, David·2006·Proteins: Structure, Function, and Bioinformatics
DOI 10.1002/prot.20817
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Abstract

We describe the adaptation of the Rosetta de novo structure prediction method for prediction of helical transmembrane protein structures. The membrane environment is modeled by embedding the protein chain into a model membrane represented by parallel planes defining hydrophobic, interface, and polar membrane layers for each energy evaluation. The optimal embedding is determined by maximizing the exposure of surface hydrophobic residues within the membrane and minimizing hydrophobic exposure outside of the membrane. Protein conformations are built up using the Rosetta fragment assembly method and evaluated using a new membrane‐specific version of the Rosetta low‐resolution energy function in which residue–residue and residue–environment interactions are functions of the membrane layer in addition to amino acid identity, distance, and density. We find that lower energy and more native‐like structures are achieved by sequential addition of helices to a growing chain, which may mimic some aspects of helical protein biogenesis after translocation, rather than folding the whole chain simultaneously as in the Rosetta soluble protein prediction method. In tests on 12 membrane proteins for which the structure is known, between 51 and 145 residues were predicted with root‐mean‐square deviation <4 Å from the native structure. Proteins 2006. © 2005 Wiley‐Liss, Inc.

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Metadata

Authors
Yarov‐Yarovoy, V., Schonbrun, J., & Baker, D.
Venue
Proteins: Structure, Function, and Bioinformatics
Publisher
Wiley
Published
2005-12-21
Volume
62
Issue
4
Pages
1010-1025
ISSN
  • 0887-3585 (ISSN-L)
  • 1097-0134
DOI
10.1002/prot.20817
OpenAlex
W2101810621
Cited by
323
References
60
FWCI
4.61
Type
journal article
Language
en
Open access
green

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