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Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies

The throughput of macromolecular X-ray crystallography experiments has surged over the last decade. This remarkable gain in efficiency has been facilitated by increases in the availability of high-intensity X-ray beams, (ultra)fast detectors and high degrees of automation. These developments have in...

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Autores principales: Pearce, Nicholas M., Skyner, Rachael, Krojer, Tobias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035521/
https://www.ncbi.nlm.nih.gov/pubmed/35480897
http://dx.doi.org/10.3389/fmolb.2022.861491
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author Pearce, Nicholas M.
Skyner, Rachael
Krojer, Tobias
author_facet Pearce, Nicholas M.
Skyner, Rachael
Krojer, Tobias
author_sort Pearce, Nicholas M.
collection PubMed
description The throughput of macromolecular X-ray crystallography experiments has surged over the last decade. This remarkable gain in efficiency has been facilitated by increases in the availability of high-intensity X-ray beams, (ultra)fast detectors and high degrees of automation. These developments have in turn spurred the development of several dedicated centers for crystal-based fragment screening which enable the preparation and collection of hundreds of single-crystal diffraction datasets per day. Crystal structures of target proteins in complex with small-molecule ligands are of immense importance for structure-based drug design (SBDD) and their rapid turnover is a prerequisite for accelerated development cycles. While the experimental part of the process is well defined and has by now been established at several synchrotron sites, it is noticeable that software and algorithmic aspects have received far less attention, as well as the implications of new methodologies on established paradigms for structure determination, analysis, and visualization. We will review three key areas of development of large-scale protein-ligand studies. First, we will look into new software developments for batch data processing, followed by a discussion of the methodological changes in the analysis, modeling, refinement and deposition of structures for SBDD, and the changes in mindset that these new methods require, both on the side of depositors and users of macromolecular models. Finally, we will highlight key new developments for the presentation and analysis of the collections of structures that these experiments produce, and provide an outlook for future developments.
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spelling pubmed-90355212022-04-26 Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies Pearce, Nicholas M. Skyner, Rachael Krojer, Tobias Front Mol Biosci Molecular Biosciences The throughput of macromolecular X-ray crystallography experiments has surged over the last decade. This remarkable gain in efficiency has been facilitated by increases in the availability of high-intensity X-ray beams, (ultra)fast detectors and high degrees of automation. These developments have in turn spurred the development of several dedicated centers for crystal-based fragment screening which enable the preparation and collection of hundreds of single-crystal diffraction datasets per day. Crystal structures of target proteins in complex with small-molecule ligands are of immense importance for structure-based drug design (SBDD) and their rapid turnover is a prerequisite for accelerated development cycles. While the experimental part of the process is well defined and has by now been established at several synchrotron sites, it is noticeable that software and algorithmic aspects have received far less attention, as well as the implications of new methodologies on established paradigms for structure determination, analysis, and visualization. We will review three key areas of development of large-scale protein-ligand studies. First, we will look into new software developments for batch data processing, followed by a discussion of the methodological changes in the analysis, modeling, refinement and deposition of structures for SBDD, and the changes in mindset that these new methods require, both on the side of depositors and users of macromolecular models. Finally, we will highlight key new developments for the presentation and analysis of the collections of structures that these experiments produce, and provide an outlook for future developments. Frontiers Media S.A. 2022-04-11 /pmc/articles/PMC9035521/ /pubmed/35480897 http://dx.doi.org/10.3389/fmolb.2022.861491 Text en Copyright © 2022 Pearce, Skyner and Krojer. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Molecular Biosciences
Pearce, Nicholas M.
Skyner, Rachael
Krojer, Tobias
Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies
title Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies
title_full Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies
title_fullStr Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies
title_full_unstemmed Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies
title_short Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies
title_sort experiences from developing software for large x-ray crystallography-driven protein-ligand studies
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9035521/
https://www.ncbi.nlm.nih.gov/pubmed/35480897
http://dx.doi.org/10.3389/fmolb.2022.861491
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