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Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)
The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends t...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5139988/ https://www.ncbi.nlm.nih.gov/pubmed/27980506 http://dx.doi.org/10.1107/S160057671601517X |
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author | Perkins, Stephen J. Wright, David W. Zhang, Hailiang Brookes, Emre H. Chen, Jianhan Irving, Thomas C. Krueger, Susan Barlow, David J. Edler, Karen J. Scott, David J. Terrill, Nicholas J. King, Stephen M. Butler, Paul D. Curtis, Joseph E. |
author_facet | Perkins, Stephen J. Wright, David W. Zhang, Hailiang Brookes, Emre H. Chen, Jianhan Irving, Thomas C. Krueger, Susan Barlow, David J. Edler, Karen J. Scott, David J. Terrill, Nicholas J. King, Stephen M. Butler, Paul D. Curtis, Joseph E. |
author_sort | Perkins, Stephen J. |
collection | PubMed |
description | The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends the capabilities of solution scattering and provides deeper insights into the physics and chemistry of the systems studied. Realizing this potential, however, requires integrating the experimental data with a new generation of modelling software. To achieve this, the CCP-SAS collaboration (http://www.ccpsas.org/) is developing open-source, high-throughput and user-friendly software for the atomistic and coarse-grained molecular modelling of scattering data. Robust state-of-the-art molecular simulation engines and molecular dynamics and Monte Carlo force fields provide constraints to the solution structure inferred from the small-angle scattering data, which incorporates the known physical chemistry of the system. The implementation of this software suite involves a tiered approach in which GenApp provides the deployment infrastructure for running applications on both standard and high-performance computing hardware, and SASSIE provides a workflow framework into which modules can be plugged to prepare structures, carry out simulations, calculate theoretical scattering data and compare results with experimental data. GenApp produces the accessible web-based front end termed SASSIE-web, and GenApp and SASSIE also make community SAS codes available. Applications are illustrated by case studies: (i) inter-domain flexibility in two- to six-domain proteins as exemplified by HIV-1 Gag, MASP and ubiquitin; (ii) the hinge conformation in human IgG2 and IgA1 antibodies; (iii) the complex formed between a hexameric protein Hfq and mRNA; and (iv) synthetic ‘bottlebrush’ polymers. |
format | Online Article Text |
id | pubmed-5139988 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-51399882016-12-15 Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS) Perkins, Stephen J. Wright, David W. Zhang, Hailiang Brookes, Emre H. Chen, Jianhan Irving, Thomas C. Krueger, Susan Barlow, David J. Edler, Karen J. Scott, David J. Terrill, Nicholas J. King, Stephen M. Butler, Paul D. Curtis, Joseph E. J Appl Crystallogr Research Papers The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends the capabilities of solution scattering and provides deeper insights into the physics and chemistry of the systems studied. Realizing this potential, however, requires integrating the experimental data with a new generation of modelling software. To achieve this, the CCP-SAS collaboration (http://www.ccpsas.org/) is developing open-source, high-throughput and user-friendly software for the atomistic and coarse-grained molecular modelling of scattering data. Robust state-of-the-art molecular simulation engines and molecular dynamics and Monte Carlo force fields provide constraints to the solution structure inferred from the small-angle scattering data, which incorporates the known physical chemistry of the system. The implementation of this software suite involves a tiered approach in which GenApp provides the deployment infrastructure for running applications on both standard and high-performance computing hardware, and SASSIE provides a workflow framework into which modules can be plugged to prepare structures, carry out simulations, calculate theoretical scattering data and compare results with experimental data. GenApp produces the accessible web-based front end termed SASSIE-web, and GenApp and SASSIE also make community SAS codes available. Applications are illustrated by case studies: (i) inter-domain flexibility in two- to six-domain proteins as exemplified by HIV-1 Gag, MASP and ubiquitin; (ii) the hinge conformation in human IgG2 and IgA1 antibodies; (iii) the complex formed between a hexameric protein Hfq and mRNA; and (iv) synthetic ‘bottlebrush’ polymers. International Union of Crystallography 2016-10-14 /pmc/articles/PMC5139988/ /pubmed/27980506 http://dx.doi.org/10.1107/S160057671601517X Text en © Stephen J. Perkins et al. 2016 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. |
spellingShingle | Research Papers Perkins, Stephen J. Wright, David W. Zhang, Hailiang Brookes, Emre H. Chen, Jianhan Irving, Thomas C. Krueger, Susan Barlow, David J. Edler, Karen J. Scott, David J. Terrill, Nicholas J. King, Stephen M. Butler, Paul D. Curtis, Joseph E. Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS) |
title | Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)
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title_full | Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)
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title_fullStr | Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)
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title_full_unstemmed | Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)
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title_short | Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)
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title_sort | atomistic modelling of scattering data in the collaborative computational project for small angle scattering (ccp-sas) |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5139988/ https://www.ncbi.nlm.nih.gov/pubmed/27980506 http://dx.doi.org/10.1107/S160057671601517X |
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