AUTHOR=Mondal Arup , Perez Alberto 

TITLE=Simultaneous Assignment and Structure Determination of Proteins From Sparsely Labeled NMR Datasets

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 8 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2021.774394

DOI=10.3389/fmolb.2021.774394

ISSN=2296-889X

ABSTRACT=parsely labeled NMR samples provide opportunities to study larger biomolecular assemblies than traditionally done by NMR. This requires new computational tools that can handle the sparsity and ambiguity in the NMR datasets. The MELD (Modeling Employing Limited Data) Bayesian approach was assessed as the best performing in predicting structures from sparsely labeled NMR data in the 13th edition of the critical assessment of structure prediction (CASP) event -- and limitations of the methodology were also noted.   In this report we evaluate the nature and difficulty in modeling unassigned sparsely labeled NMR datasets and  report on an improved methodological pipeline leading to higher accuracy predictions.  We benchmark our methodology against the NMR datasets provided by CASP 13.