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SCT: Analysis and Modelling of Small Angle Scattering Data

Authors: David W Wright; Stephen J Perkins;

SCT: Analysis and Modelling of Small Angle Scattering Data

Abstract

Small angle X-ray and neutron-scattering techniques (known as SAXS and SANS nrespectively) are low resolution techniques that can characterize protein structure in solution. They are of particular utility when large proteins cannot be crystallized and in systems where solution conditions affect the structure adopted. Atomistic models of the average structure can be generated through constrained modelling, a technique in which known structures (such as domain or subunit crystal structures) are combined with linker models to produce candidate global conformations. Homology modelling techniques and simulation methodologies such as Monte Carlo or molecular dynamics simulations can be used to produce a library of structurally varied, atomistic, candidate models of the target macromolecule. Theoretical scattering curves are then generated for each model and used for trial-and-error fits to the experimental data. From this a small family of best-fit models can be identified. It is to automate this last two steps that SCT was developed. The original SCT software, written in Fortran, has been used in the production of 74 structures (21 antibodies, 27 complement proteins and 24 oligosaccharides) deposited in the Protein Data Bank between 1998 and 2014. All of the same functionality of the classic SCT is now available in an easier to use set of Python scripts. This release version of the software is described in the article submitted to Journal of Applied Crystalography

Related Organizations
Keywords

small angle scattering, structural biology

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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