3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data
Computational modeling of proteins using evolutionary or de novo approaches offers rapid structural characterization, but often suffers from low success rates in generating high quality models comparable to the accuracy of structures observed in X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. A computational/experimental hybrid approach incorporating sparse experimental restraints in computational modeling algorithms drastically improves reliability and accuracy of 3D...[Show more]
|Collections||ANU Research Publications|
|Book Title:||Methods in Molecular Biology - Bioinformatics: Structure, Function and Applications|
|01_Pilla_3D_Computational_Modeling_of_2017.pdf||6.81 MB||Adobe PDF||Request a copy|
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