Unknown

Dataset Information

0

Efficient merging of data from multiple samples for determination of anomalous substructure.


ABSTRACT: Merging of data from multiple crystals has proven to be useful for determination of the anomalously scattering atomic substructure for crystals with weak anomalous scatterers (e.g. S and P) and/or poor diffraction. Strategies for merging data from many samples, which require assessment of sample isomorphism, rely on metrics of variability in unit-cell parameters, anomalous signal correlation and overall data similarity. Local scaling, anomalous signal optimization and data-set weighting, implemented in phenix.scale_and_merge, provide an efficient protocol for merging data from many samples. The protein NS1 was used in a series of trials with data collected from 28 samples for phasing by single-wavelength anomalous diffraction of the native S atoms. The local-scaling, anomalous-optimization protocol produced merged data sets with higher anomalous signal quality indicators than did standard global-scaling protocols. The local-scaled data were also more successful in substructure determination. Merged data quality was assessed for data sets where the multiplicity was reduced in either of two ways: by excluding data from individual crystals (to reduce errors owing to non-isomorphism) or by excluding the last-recorded segments of data from each crystal (to minimize the effects of radiation damage). The anomalous signal was equivalent at equivalent multiplicity for the two procedures, and structure-determination success correlated with anomalous signal metrics. The quality of the anomalous signal was strongly correlated with data multiplicity over a range of 12-fold to 150-fold multiplicity. For the NS1 data, the local-scaling and anomalous-optimization protocol handled sample non-isomorphism and radiation-induced decay equally well.

SUBMITTER: Akey DL 

PROVIDER: S-EPMC4784661 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

altmetric image

Publications

Efficient merging of data from multiple samples for determination of anomalous substructure.

Akey David L DL   Terwilliger Thomas C TC   Smith Janet L JL  

Acta crystallographica. Section D, Structural biology 20160301 Pt 3


Merging of data from multiple crystals has proven to be useful for determination of the anomalously scattering atomic substructure for crystals with weak anomalous scatterers (e.g. S and P) and/or poor diffraction. Strategies for merging data from many samples, which require assessment of sample isomorphism, rely on metrics of variability in unit-cell parameters, anomalous signal correlation and overall data similarity. Local scaling, anomalous signal optimization and data-set weighting, impleme  ...[more]

Similar Datasets

| S-EPMC2917277 | biostudies-literature
| S-EPMC8251343 | biostudies-literature
| S-EPMC5947775 | biostudies-literature
| S-EPMC4312553 | biostudies-literature
| S-EPMC6554296 | biostudies-literature
| S-EPMC6612806 | biostudies-literature
| S-EPMC5947773 | biostudies-literature
| S-EPMC5668859 | biostudies-literature
| S-EPMC9344479 | biostudies-literature
| S-EPMC4856140 | biostudies-literature