Sidekick for membrane simulations: automated ensemble molecular dynamics simulations of transmembrane helices
The interactions of transmembrane (TM) α- helices with the phospholipid membrane and with one another are central to understanding the structure and stability of integral membrane proteins. These interactions may be analyzed via coarse grained molecular dynamics (CGMD) simulations. To obtain st...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/59249/ http://irep.iium.edu.my/59249/ http://irep.iium.edu.my/59249/1/KB-sidekick.pdf http://irep.iium.edu.my/59249/7/59249_Sidekick%20for%20membrane%20simulations_SCOPUS.pdf |
| Summary: | The interactions of transmembrane (TM) α-
helices with the phospholipid membrane and with one another
are central to understanding the structure and stability of
integral membrane proteins. These interactions may be
analyzed via coarse grained molecular dynamics (CGMD)
simulations. To obtain statistically meaningful analysis of TM
helix interactions, large (N ca. 100) ensembles of CGMD
simulations are needed. To facilitate the running and analysis
of such ensembles of simulations, we have developed Sidekick,
an automated pipeline software for performing high
throughput CGMD simulations of α-helical peptides in lipid
bilayer membranes. Through an end-to-end approach, which
takes as input a helix sequence and outputs analytical metrics derived from CGMD simulations, we are able to predict the
orientation and likelihood of insertion into a lipid bilayer of a given helix of a family of helix sequences. We illustrate this software
via analyses of insertion into a membrane of short hydrophobic TM helices containing a single cationic arginine residue
positioned at different positions along the length of the helix. From analyses of these ensembles of simulations, we estimate
apparent energy barriers to insertion which are comparable to experimentally determined values. In a second application, we use
CGMD simulations to examine the self-assembly of dimers of TM helices from the ErbB1 receptor tyrosine kinase and analyze
the numbers of simulation repeats necessary to obtain convergence of simple descriptors of the mode of packing of the two
helices within a dimer. Our approach offers a proof-of-principle platform for the further employment of automation in large
ensemble CGMD simulations of membrane proteins. |
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