Prediction of the crystal structures of axitinib, a polymorphic pharmaceutical molecule
File(s)
Published version
Author(s)
Vasileiadis, Manolis
Pantelides, Constantinos C
Adjiman, Claire S
Type
Journal Article
Abstract
Organic molecules can crystallize in multiple structures or polymorphs, yielding crystals with very different physical and mechanical properties. The prediction of the polymorphs that may appear in nature is a challenge with great potential benefits for the development of new products and processes. A multistage crystal structure prediction (CSP) methodology is applied to axitinib, a pharmaceutical molecule with significant polymorphism arising from molecular flexibility. The CSP study is focused on those polymorphs with one molecule in the asymmetric unit. The approach successfully identifies all four known polymorphs within this class, as well as a large number of other low-energy structures. The important role of conformational flexibility is highlighted. The performance of the approach is discussed in terms of both the quality of the results and various algorithmic and computational aspects, and some key priorities for further work in this area are identified.
Date Issued
2014-09-10
Citation
Chemical Engineering Science, 2014, 121, pp.60-76
ISSN
0009-2509
Publisher
Elsevier
Start Page
60
End Page
76
Journal / Book Title
Chemical Engineering Science
Volume
121
Copyright Statement
Copyright © 2014 The Authors. Published by Elsevier Ltd. This article is available under the terms of the Creative Commons Attribution License (CC BY).
You may distribute and copy the article, create extracts, abstracts, and other revised versions, adaptations or derivative works of or from an article (such as a translation), to include in a collective work (such as an anthology), to text or data mine the article, including for commercial purposes without permission from Elsevier. The original work must always be appropriately credited.
You may distribute and copy the article, create extracts, abstracts, and other revised versions, adaptations or derivative works of or from an article (such as a translation), to include in a collective work (such as an anthology), to text or data mine the article, including for commercial purposes without permission from Elsevier. The original work must always be appropriately credited.
License URL
Identifier
http://www.sciencedirect.com/science/article/pii/S0009250914004904
Publication Status
Published