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Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. Part III: partitioning into torsional groups
File(s)
ra5144.pdf (4.72 MB)
Published version
Author(s)
Sugden, Isaac J
Bowskill, David H
Tan, Benjamin I
Zhang, Yizu
Adjiman, Claire S
Type
Journal Article
Abstract
We present an approach to reduce this computational cost substantially, based on the partitioning of the molecule into geometrically separated torsional groups, with the dependence of the intramolecular energy and atomic point charges and dependent degrees of freedom on molecular conformation being computed as a linear combination of the contributions of these groups. This can lead to large savings in computational cost without a significant impact on accuracy, as demonstrated in the cases of N-acetyl-para-amino­phenol (paracetamol) and methyl 4-hy­droxy­benzoate (methyl paraben). The approach is also applied successfully to two larger molecules, benzyl [4-(4-methyl-5-[(4-methyl­phenyl)­sulfonyl]-1,3-thia­zol-2-yl)phenyl]­carbamate (molecule XX from the fifth CSP blind test) and (2S)-2-[4-(3-fluoro­benzyl­oxy)benzyl­amino]­propionamide (safinamide), for which we conduct the first reported CSP study. In both cases, the use of torsional groups results in over 99% reduction in computational cost, which enables the generation of an initial CSP landscape with high-quality structures found within the standard cutoff of 20 kJ mol−1 for progression to refinement.
Date Issued
2025-02-01
Date Acceptance
2024-10-15
Citation
Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials, 2025, 81 (Part 1), pp.114-127
URI
URL
DOI
ISSN
2052-5192
Publisher
International Union of Crystallography
Start Page
114
End Page
127
Journal / Book Title
Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials
Volume
81
Issue
Part 1
Copyright Statement
© 2025 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/39874186
PII: S2052520624010072
Subjects
BLIND TEST
Chemistry
Chemistry, Multidisciplinary
computational chemistry
crystal structure prediction
Crystallography
DRUG
energy partitioning
flexible molecules
FORCE-FIELD
MOLECULES
Physical Sciences
POLYMORPHS
POTENTIALS
SAFINAMIDE
Science & Technology
STRUCTURE PREDICTION
Publication Status
Published
Coverage Spatial
England
Date Publish Online
2025-01-22