Dataset Information

1H, 13C and 15N backbone resonance assignment of BRCA1 fragment 219-504.

ABSTRACT: The breast cancer susceptibility protein 1 (BRCA1) plays a central role in the suppression of human breast and ovarian cancer. Germ line mutations of the BRCA1 gene are responsible for the hereditary breast and ovarian cancer (HBOC) syndrome. Here were report 1H, 13C, and 15N resonance assignments for the intrinsically disordered BRCA1 fragment 219-504, which contains important interaction sites for the proto-oncogenic transcription factor MYC as well as for p53. A nuclear magnetic resonance assignment was achieved at 18.8 T magnetic field strength using a 5D HN(CA)CONH experiment and its associated 4D H(NCA)CONH and 4D (H)N(CA)CONH experiments. 13C? and 13C? assignments were obtained using a 5D HabCabCONH experiment. With this strategy, 90% of 1H/15N backbone pairs could be assigned. Similarly, 264 C' resonances were assigned corresponding to 86% of the total number of C' atoms. In addition, 252 C? resonances (i.e. 85%) were assigned, together with 461 attached H? nuclei, as well as 264 (i.e. 86%) C? resonances, together with 275 attached H? nuclei.

SUBMITTER: Gorka M

PROVIDER: S-EPMC7462910 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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1H, 13C and 15N backbone resonance assignment of BRCA1 fragment 219-504.

Górka Michał M Żerko Szymon S Konrat Robert R Koźmiński Wiktor W Kurzbach Dennis D

Biomolecular NMR assignments 20200624 2

The breast cancer susceptibility protein 1 (BRCA1) plays a central role in the suppression of human breast and ovarian cancer. Germ line mutations of the BRCA1 gene are responsible for the hereditary breast and ovarian cancer (HBOC) syndrome. Here were report 1H, 13C, and 15N resonance assignments for the intrinsically disordered BRCA1 fragment 219-504, which contains important interaction sites for the proto-oncogenic transcription factor MYC as well as for p53. ...[more]

PMID: 32583165

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Project description:Experimental residual dipolar couplings (RDCs) in combination with structural models have the potential for accelerating the protein backbone resonance assignment process because RDCs can be measured accurately and interpreted quantitatively. However, this application has been limited due to the need for very high-resolution structural templates. Here, we introduce a new approach to resonance assignment based on optimal agreement between the experimental and calculated RDCs from a structural template that contains all assignable residues. To overcome the inherent computational complexity of such a global search, we have adopted an efficient two-stage search algorithm and included connectivity data from conventional assignment experiments. In the first stage, a list of strings of resonances (CA-links) is generated via exhaustive searches for short segments of sequentially connected residues in a protein (local templates), and then ranked by the agreement of the experimental (13)C(α) chemical shifts and (15)N-(1)H RDCs to the predicted values for each local template. In the second stage, the top CA-links for different local templates in stage I are combinatorially connected to produce CA-links for all assignable residues. The resulting CA-links are ranked for resonance assignment according to their measured RDCs and predicted values from a tertiary structure. Since the final RDC ranking of CA-links includes all assignable residues and the assignment is derived from a "global minimum", our approach is far less reliant on the quality of experimental data and structural templates. The present approach is validated with the assignments of several proteins, including a 42 kDa maltose binding protein (MBP) using RDCs and structural templates of varying quality. Since backbone resonance assignment is an essential first step for most of biomolecular NMR applications and is often a bottleneck for large systems, we expect that this new approach will improve the efficiency of the assignment process for small and medium size proteins and will extend the size limits assignable by current methods for proteins with structural models.

Dataset Information

1H, 13C and 15N backbone resonance assignment of BRCA1 fragment 219-504.

Publications

<sup>1</sup>H, <sup>13</sup>C and <sup>15</sup>N backbone resonance assignment of BRCA1 fragment 219-504.

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