Name
Abstract | ||
|---|---|---|
We cast the problem of identifying protein-protein interfaces, using only unassigned NMR spectra, into a geometric clustering problem. Identifying protein-protein interfaces is critical to understanding inter- and intra-cellular communication, and NMR allows the study of protein interaction in solution. However it is often the case that NMR studies of a protein complex are very time-consuming, mainly due to the bottleneck in assigning the chemical shifts, even if the apo structures of the constituent proteins are known. We study whether it is possible, in a high-throughput manner, to identify the interface region of a protein complex using only unassigned chemical shifts and residual dipolar coupling (RDC) data. We introduce a geometric optimization problem where we must cluster the cells in an arrangement on the boundary of a 3-manifold, where the arrangement is induced by a spherical quadratic form [corrected] The arrangement is induced by a spherical quadratic form, which in turn is parameterized by a SO(3)xR2. We show that this formalism derives directly from the physics of RDCs. We present an optimal algorithm for this problem that runs in O(n3 log n) time for an n-residue protein. We then use this clustering algorithm as a subroutine in a practical algorithm for identifying the interface region of a protein complex from unassigned NMR data. We present the results of our algorithm on NMR data for seven proteins from five protein complexes, and show that our approach is useful for high-throughput applications in which we seek to rapidly identify the interface region of a protein complex.Contact authors for source code. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1093/bioinformatics/bti1005 | ISMB (Supplement of Bioinformatics) |
Keywords | Field | DocType |
n-residue protein,nmr study,unassigned nmr data,identifying protein,protein interaction,nmr spectrum,protein complex,nmr data,interface region,high-throughput inference,protein interface,constituent protein,residual dipolar coupling,source code,high throughput,chemical shift | Parameterized complexity,Computer science,NMR spectra database,Residual dipolar coupling,Bioinformatics,Chemical shift,Cluster analysis,Optimization problem,Nuclear magnetic resonance spectroscopy,Protein structure | Conference |
Volume | Issue | ISSN |
21 Suppl 1 | 1 | 1367-4803 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramgopal R. Mettu | 1 | 177 | 22.23 |
| Ryan H Lilien | 2 | 166 | 24.40 |
| Bruce Donald | 3 | 1859 | 335.89 |