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The conventional approach to finding structurally similar search models for use in molecular replacement (MR) is to use the sequence of the target to search against those of a set of known structures. Sequence similarity often correlates with structure similarity. Given sufficient similarity, a known structure correctly positioned in the target cell by the MR process can provide an approximation to the unknown phases of the target. An alternative approach to identifying homologous structures suitable for MR is to exploit the measured data directly, comparing the lattice parameters or the experimentally derived structure-factor amplitudes with those of known structures. Here, SIMBAD, a new sequence-independent MR pipeline which implements these approaches, is presented. SIMBAD can identify cases of contaminant crystallization and other mishaps such as mistaken identity (swapped crystallization trays), as well as solving unsequenced targets and providing a brute-force approach where sequence-dependent search-model identification may be nontrivial, for example because of conformational diversity among identifiable homologues. The program implements a three-step pipeline to efficiently identify a suitable search model in a database of known structures. The first step performs a lattice-parameter search against the entire Protein Data Bank (PDB), rapidly determining whether or not a homologue exists in the same crystal form. The second step is designed to screen the target data for the presence of a crystallized contaminant, a not uncommon occurrence in macromolecular crystallography. Solving structures with MR in such cases can remain problematic for many years, since the search models, which are assumed to be similar to the structure of interest, are not necessarily related to the structures that have actually crystallized. To cater for this eventuality, SIMBAD rapidly screens the data against a database of known contaminant structures. Where the first two steps fail to yield a solution, a final step in SIMBAD can be invoked to perform a brute-force search of a nonredundant PDB database provided by the MoRDa MR software. Through early-access usage of SIMBAD, this approach has solved novel cases that have otherwise proved difficult to solve.
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http://dx.doi.org/10.1107/S2059798318005752 | DOI Listing |
Acta Crystallogr F Struct Biol Commun
July 2022
Structural and Functional Biology Laboratory, National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110 067, India.
The unintended crystallization of proteins which generally originate from the expression host instead of the target recombinant proteins is periodically reported. Despite the massive technological advances in the field, assigning a structural model to the corresponding diffraction data is not a trivial task. Here, the structure of acyl-carrier protein synthase (AcpS) from Mycobacterium smegmatis (msAcpS), which crystallized inadvertently in an experimental setup to grow crystals of a Mycobacterium tuberculosis protein using M.
View Article and Find Full Text PDFActa Crystallogr D Struct Biol
January 2020
Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England.
The conventional approach to search-model identification in molecular replacement (MR) is to screen a database of known structures using the target sequence. However, this strategy is not always effective, for example when the relationship between sequence and structural similarity fails or when the crystal contents are not those expected. An alternative approach is to identify suitable search models directly from the experimental data.
View Article and Find Full Text PDFActa Crystallogr D Struct Biol
December 2019
Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England.
Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Where the lack of a suitable homologue precludes conventional MR, one option is to predict the target structure using bioinformatics. Such modelling, in the absence of homologous templates, is called ab initio or de novo modelling.
View Article and Find Full Text PDFActa Crystallogr F Struct Biol Commun
September 2019
National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY 11973-5000, USA.
The crystallization of amidase, the ultimate enzyme in the Trp-dependent auxin-biosynthesis pathway, from Arabidopsis thaliana was attempted using protein samples with at least 95% purity. Cube-shaped crystals that were assumed to be amidase crystals that belonged to space group I4 (unit-cell parameters a = b = 128.6, c = 249.
View Article and Find Full Text PDFActa Crystallogr D Struct Biol
July 2018
Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England.
The conventional approach to finding structurally similar search models for use in molecular replacement (MR) is to use the sequence of the target to search against those of a set of known structures. Sequence similarity often correlates with structure similarity. Given sufficient similarity, a known structure correctly positioned in the target cell by the MR process can provide an approximation to the unknown phases of the target.
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