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Extending NMR for Functional and Structural Genomics | ||||||||||||||||
| TopSpin | MDD | PRODECOMP | AUREMOL | CCPN | ARIA | ISD | HADDOCK | CING | Deposition | ||||||||
PRODECOMP: Analysis of 'Fast' NMR DataProteins pose a variety of challenges in NMR studies in terms of their size, native disorder, stability etc. 'Fast' NMR is motivated by the resulting, but contradicting, requirements on spectrum dimensionality, resolution and experiment time. Projection spectroscopy may speed up the recording of very high-dimensional data (4-7 D) by factors of a thousand or more while maintaining high resolution. Decompositions provide an optimal tool to analyze 2D projections of high-dimensional experiments (Fig. A, B): signal-to-noise is not compromised, projections from several experiments can be combined (Fig. C), and the output is well suited for automated interpretation, e.g. assignment by the SHABBA protocol (Fig. D top), and structure determination (Fig. D bottom). The PRODECOMP tool for decomposition of NMR projections is based on a solid mathematical procedure, warranting its robustness and efficiency. PRODECOMP is tightly interweaved with the TopSpin (Bruker) recording and processing software, and fully integrated into the CCPN data model. Its Python code is freely available.
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Features
D) Typical goals for the combination of projection spectroscopy and
decomposition analysis: resonance assignments (top) or 3D structures (bottom:
azurin structure from projection data only).
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