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Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR
Published on: December 16, 2013
High-throughput 3D structural homology detection via NMR resonance assignment
Christopher James Langmead1, Bruce Randall Donald
1Carnegie Mellon Dept. of Computer Science, Pittsburgh, PA 15213, USA.
Proceedings. IEEE Computational Systems Bioinformatics Conference
|February 2, 2006
Summary
Identifying similar protein folds from dissimilar sequences is crucial for structural genomics. A new automated method, HD, uses sparse NMR data to rapidly detect 3D structural homologies without relying on sequence similarity.
Area of Science:
- Structural biology
- Bioinformatics
- Genomics
Background:
- Structural genomics aims to identify novel protein folds.
- Sequence-based methods struggle with detecting structural homology between proteins with dissimilar sequences.
- Rapid identification of protein folds is essential for high-throughput structure determination.
Purpose of the Study:
- To develop an automated procedure for detecting 3D structural homologies from sparse, unassigned protein NMR data.
- To address the challenge of identifying similar protein folds from proteins with highly dissimilar sequences.
- To provide a method that can confirm or refute structural predictions from other techniques.
Main Methods:
- An automated procedure called HD was developed.
- HD detects 3D structural homologies by matching 3D models from a structural database to unassigned experimental NMR data.
- The method utilizes novel algorithms for analyzing sparse, unassigned protein NMR data.
Main Results:
- The HD method successfully identified closely related protein folds, including sub-domains, with as little as 10-30% sequence homology.
- Experiments on real NMR data against a database of 4,500 folds showed no false-negatives or false-positives.
- The method demonstrated effectiveness despite significant percentages of missing experimental data.
Conclusions:
- HD is an effective automated procedure for detecting 3D structural homologies from sparse, unassigned protein NMR data.
- The method overcomes limitations of sequence-based homology prediction and is valuable for structural genomics.
- HD can rapidly identify structural similarities even with low sequence homology and missing data.
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