Prediction of Protein Orientation upon Immobilization on Biological and Nonbiological Surfaces

We report on a rapid simulation method for predicting protein orientation on a surface based on electrostatic interactions. New methods for predicting protein immobilization are needed because of the increasing use of biosensors and protein microarrays, two technologies that use protein immobilizati...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2006-10, Vol.103 (40), p.14773-14778
Main Authors: Talasaz, AmirAli H., Nemat-Gorgani, Mohsen, Liu, Yang, Ståhl, Patrik, Dutton, Robert W., Ronaghi, Mostafa, Davis, Ronald W.
Format: Article
Language:English
Subjects:
Animals
Biological Sciences
Computer Simulation
Creatine Kinase, Mitochondrial Form - chemistry
Creatine Kinase, Mitochondrial Form - metabolism
Cytochromes
Cytochromes c - metabolism
Electric fields
Electrostatics
Enzymes
Enzymes, Immobilized - chemistry
Enzymes, Immobilized - metabolism
Free energy
Hexokinase - chemistry
Hexokinase - metabolism
Mitochondrial membranes
Mitochondrial Membranes - metabolism
Models, Biological
Models, Molecular
Molecular interactions
Molecules
P branes
Physical Sciences
Proteins
Research methodology
Sarcomeres - enzymology
Simulation
Static Electricity
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Summary:We report on a rapid simulation method for predicting protein orientation on a surface based on electrostatic interactions. New methods for predicting protein immobilization are needed because of the increasing use of biosensors and protein microarrays, two technologies that use protein immobilization onto a solid support, and because the orientation of an immobilized protein is important for its function. The proposed simulation model is based on the premise that the protein interacts with the electric field generated by the surface, and this interaction defines the orientation of attachment. Results of this model are in agreement with experimental observations of immobilization of mitochondrial creatine kinase and type I hexokinase on biological membranes. The advantages of our method are that it can be applied to any protein with a known structure; it does not require modeling of the surface at atomic resolution and can be run relatively quickly on readily available computing resources. Finally, we also propose an orientation of membrane-bound cytochrome c, a protein for which the membrane orientation has not been unequivocally determined.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.0605841103