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New insights and innovation from a million crystal structures in the Cambridge Structural Database

The Cambridge Structural Database (CSD) is the world's largest and most comprehensive collection of organic, organometallic, and metal-organic crystal structure information. Analyses using the data have wide impact across the chemical sciences in allowing understanding of structural preferences...

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Detalles Bibliográficos
Autores principales: Cole, Jason C., Wiggin, Seth, Stanzione, Francesca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Crystallographic Association 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713555/
https://www.ncbi.nlm.nih.gov/pubmed/31489338
http://dx.doi.org/10.1063/1.5116878
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author Cole, Jason C.
Wiggin, Seth
Stanzione, Francesca
author_facet Cole, Jason C.
Wiggin, Seth
Stanzione, Francesca
author_sort Cole, Jason C.
collection PubMed
description The Cambridge Structural Database (CSD) is the world's largest and most comprehensive collection of organic, organometallic, and metal-organic crystal structure information. Analyses using the data have wide impact across the chemical sciences in allowing understanding of structural preferences. In this short review, we illustrate the more common methods by which CSD data influence molecular design. We show how more data could lead to more refined insights into the future using a simple example of trifluoromethylphenyl fragments, highlighting how with sufficient data one can build a reasonable model of geometric change in a chemical fragment with torsional rotation, and show some recent examples where the CSD has been used in conjunction with other methods to provide design ideas and more computationally tractable workflows for derivation of useful insights into structural design.
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spelling pubmed-67135552019-09-05 New insights and innovation from a million crystal structures in the Cambridge Structural Database Cole, Jason C. Wiggin, Seth Stanzione, Francesca Struct Dyn ARTICLES The Cambridge Structural Database (CSD) is the world's largest and most comprehensive collection of organic, organometallic, and metal-organic crystal structure information. Analyses using the data have wide impact across the chemical sciences in allowing understanding of structural preferences. In this short review, we illustrate the more common methods by which CSD data influence molecular design. We show how more data could lead to more refined insights into the future using a simple example of trifluoromethylphenyl fragments, highlighting how with sufficient data one can build a reasonable model of geometric change in a chemical fragment with torsional rotation, and show some recent examples where the CSD has been used in conjunction with other methods to provide design ideas and more computationally tractable workflows for derivation of useful insights into structural design. American Crystallographic Association 2019-08-28 /pmc/articles/PMC6713555/ /pubmed/31489338 http://dx.doi.org/10.1063/1.5116878 Text en © 2019 Author(s). 2329-7778/2019/6(5)/054301/6 All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle ARTICLES
Cole, Jason C.
Wiggin, Seth
Stanzione, Francesca
New insights and innovation from a million crystal structures in the Cambridge Structural Database
title New insights and innovation from a million crystal structures in the Cambridge Structural Database
title_full New insights and innovation from a million crystal structures in the Cambridge Structural Database
title_fullStr New insights and innovation from a million crystal structures in the Cambridge Structural Database
title_full_unstemmed New insights and innovation from a million crystal structures in the Cambridge Structural Database
title_short New insights and innovation from a million crystal structures in the Cambridge Structural Database
title_sort new insights and innovation from a million crystal structures in the cambridge structural database
topic ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6713555/
https://www.ncbi.nlm.nih.gov/pubmed/31489338
http://dx.doi.org/10.1063/1.5116878
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