Journal article
Computational studies of membrane proteins: from sequence to structure to simulation.
- Abstract:
- In this review, I discuss the recent advances in computational approaches to studying membrane protein structures, covering the latest methods for predicting a protein structure from its amino acid sequence, through to methods for assessing the structural dynamics and lipid interactions within molecular simulations of complex biological membranes. These approaches have not only benefited from advances in the computational software and architectures, but have also been assisted by a prodigious rise in the number of both the molecular sequences and experimentally determined membrane protein structures. The former, in part stimulated by metagenomics sequencing techniques, has led to an increased prediction accuracy for the computationally folded protein structures. The latter, assisted by improvements in structural biology approaches, has led to longer, larger and more complex molecular simulations of membrane proteins; many of which have greater relevance to human disease. Here I describe the methods for predicting a membrane protein structure from sequence, discuss the approaches to configure membrane protein simulations and detail the techniques used to identify and characterize specific lipid binding sites to membrane protein structures.
- Publication status:
- Published
- Peer review status:
- Reviewed (other)
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 447.4KB, Terms of use)
-
- Publisher copy:
- 10.1016/j.sbi.2017.04.004
Authors
- Publisher:
- Elsevier
- Journal:
- Current Opinion in Structural Biology More from this journal
- Volume:
- 45
- Pages:
- 133-141
- Publication date:
- 2017-05-13
- Acceptance date:
- 2017-04-07
- DOI:
- EISSN:
-
1879-033X
- ISSN:
-
0959-440X
- Pmid:
-
28511148
- Language:
-
English
- Keywords:
- Pubs id:
-
pubs:697634
- UUID:
-
uuid:7d0f5667-7f1d-4038-bee3-6b39aa6c1ddc
- Local pid:
-
pubs:697634
- Source identifiers:
-
697634
- Deposit date:
-
2018-03-13
Terms of use
- Copyright holder:
- Elsevier
- Copyright date:
- 2017
- Notes:
- © 2017 Published by Elsevier Ltd. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: http://dx.doi.org/10.1016/j.sbi.2017.04.004
If you are the owner of this record, you can report an update to it here: Report update to this record