Ab initio macromolecular phasing has been so far limited to small proteins diffracting at atomic resolution (beyond 1.2 A) unless heavy atoms are present. We describe a general ab initio phasing method for 2 A data, based on combination of localizing model fragments such as small á-helices with Phaser and density modification with SHELXE. We implemented this approach in the program Arcimboldo to solve a 222-amino-acid structure at 1.95 A.
We describe an algorithm for phasing protein crystal X-ray diffraction data that identifies, retrieves, refines and exploits general tertiary structural information from small fragments available in the Protein Data Bank. The algorithm successfully phased, through unspecific molecular replacement combined with density modification, all-helical, mixed alpha-beta, and all-beta protein structures. The method is available as a software implementation: Borges.
Since its release in September 2009, the structure-solution program ARCIMBOLDO, based on the combination of locating small model fragments such as polyalanine -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 -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 ARCIM-BOLDO within each of these scenarios is described through the distributed test cases.
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