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  • Brief Communication
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Homology modeling of larger proteins guided by chemical shifts

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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Figure 1: POMONA–CS-RosettaCM structure generation.
Figure 2: Comparison of protein-structure alignments obtained by different methods for the 16 proteins listed in Table 1.

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Acknowledgements

This work was funded by the Intramural Research Program of the NIDDK, US National Institutes of Health (NIH). We thank Y. Song, N. Sgourakis and D. Baker for help and advice on the use of RosettaCM. We also gratefully acknowledge use of the NIH high-performance computational Biowulf Linux cluster.

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Authors and Affiliations

Authors

Contributions

Y.S. and A.B. designed the methods and protocol and wrote the manuscript. Y.S. developed the code, optimized the parameterization of the protocol and analyzed the resulting data.

Corresponding authors

Correspondence to Yang Shen or Ad Bax.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Quality of protein structure alignments obtained by various methods.

Structural quality is represented by the MaxSub score, with alignments identified by POMONA in red and by the sequence alignment method HHsearch in black, while the DALI-based structure alignment method (blue) shows the best possible alignments available in the PDB. Results are shown for each of the test proteins in Table 1, using a PDB from which all proteins with ≥20% sequence identity were removed. DALI and HHsearch results correspond to default thresholds of Z > 2 and Prob < 10%, respectively, used by these programs to identify homologs. Positive POMONA alignments are taken from the first 10 clusters (solid red bars) within the top 1,000 alignments (solid + transparent red) selected on the basis of highest Hʹ score (equation (10)).

Supplementary Figure 2 Comparison of alignment quality obtained by sequence searching (HHsearch) and chemical shift–based alignment (POMONA).

MaxSub score of alignments obtained by HHsearch versus those obtained by POMONA (using a <20% sequence identity cutoff for both). The HHSearch alignments correspond to a setting of Prob ≥ 10%.

Supplementary Figure 3 Results of POMONA alignment for the 12 test proteins not shown in Figure 1.

For each protein, the database proteins with the top 1,000 POMONA alignment scores are shown as a function of Cα r.m.s. deviation relative to the experimental structures, with the Cα r.m.s. deviation restricted to the aligned parts in the target protein. Gray and black dots correspond to database proteins with a sequence identities of <20% and ≥20%, respectively. For the database hits with 20% sequence identity to the query protein, the ten clusters containing the highest alignment scores are colored according to the cluster number (red, purple, blue, magenta, light blue, yellow, cyan, orange, dark gray and brown for clusters 1–10, respectively). No NOEs were used.

Supplementary information

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Supplementary Figures 1–3, Supplementary Table 1 and Supplementary Results (PDF 3933 kb)

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Shen, Y., Bax, A. Homology modeling of larger proteins guided by chemical shifts. Nat Methods 12, 747–750 (2015). https://doi.org/10.1038/nmeth.3437

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