0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessSince its release in September 2009, the structure-solution program ARCIMBOLDO, based on the combination of locating small model fragments such as polyalanine α-helices with density modification with the program SHELXE in a multisolution frame, has evolved to incorporate other sources of stereochemical or experimental information. Fragments that are more sophisticated than the ubiquitous main-chain α-helix can be proposed by modelling side chains onto the main chain or extracted from low-homology models, as locally their structure may be similar enough to the unknown one even if the conventional molecular-replacement approach has been unsuccessful. In such cases, the program may test a set of alternative models in parallel against a specified figure of merit and proceed with the selected one(s). Experimental information can be incorporated in three ways: searching within ARCIMBOLDO for an anomalous fragment against anomalous differences or MAD data or finding model fragments when an anomalous substructure has been determined with another program such as SHELXD or is subsequently located in the anomalous Fourier map calculated from the partial fragment phases. Both sources of information may be combined in the expansion process. In all these cases the key is to control the workflow to maximize the chances of success whilst avoiding the creation of an intractable number of parallel processes. A GUI has been implemented to aid the setup of suitable strategies within the various typical scenarios. In the present work, the practical application of ARCIMBOLDO within each of these scenarios is described through the distributed test cases.
Dayté D Rodríguez, Massimo Sammito, K. Meindl, Iñaki M. de Ilarduya, Marianus Potratz, In Memory: G.M. Sheldrick (1942–2025), Isabel Usón (2012). Practical structure solution with <i> <i>ARCIMBOLDO</i> </i>. Acta Crystallographica Section D Biological Crystallography, 68(4), pp. 336-343, DOI: 10.1107/s0907444911056071.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2012
Authors
7
Datasets
0
Total Files
0
Language
English
Journal
Acta Crystallographica Section D Biological Crystallography
DOI
10.1107/s0907444911056071
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access