Homology modeling of larger proteins guided by chemical shifts

基于化学位移的大型蛋白质同源建模

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Abstract

We describe an approach to the structure determination of large proteins that relies on experimental NMR chemical shifts, plus sparse nuclear Overhauser effect (NOE) data if available. Our alignment method, POMONA (protein alignments obtained by matching of NMR assignments), directly exploits pre-existing bioinformatics algorithms to match experimental chemical shifts to values predicted for the crystallographic database. Protein templates generated by POMONA are subsequently used as input for chemical shift-based Rosetta comparative modeling (CS-RosettaCM) to generate reliable full-atom models.

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