Crossref journal-article
AIP Publishing
The Journal of Chemical Physics (317)
Abstract

In order to characterize molecular structures we introduce configurational fingerprint vectors which are counterparts of quantities used experimentally to identify structures. The Euclidean distance between the configurational fingerprint vectors satisfies the properties of a metric and can therefore safely be used to measure dissimilarities between configurations in the high dimensional configuration space. In particular we show that these metrics are a perfect and computationally cheap replacement for the root-mean-square distance (RMSD) when one has to decide whether two noise contaminated configurations are identical or not. We introduce a Monte Carlo approach to obtain the global minimum of the RMSD between configurations, which is obtained from a global minimization over all translations, rotations, and permutations of atomic indices.

Bibliography

Sadeghi, A., Ghasemi, S. A., Schaefer, B., Mohr, S., Lill, M. A., & Goedecker, S. (2013). Metrics for measuring distances in configuration spaces. The Journal of Chemical Physics, 139(18).

Authors 6
  1. Ali Sadeghi (first)
  2. S. Alireza Ghasemi (additional)
  3. Bastian Schaefer (additional)
  4. Stephan Mohr (additional)
  5. Markus A. Lill (additional)
  6. Stefan Goedecker (additional)
References 48 Referenced 128
  1. {'volume-title': 'Modern Methods of Crystal Structure Prediction', 'year': '2010', 'key': '2023070203444836100_c1'} / Modern Methods of Crystal Structure Prediction (2010)
  2. 10.1063/1.1724816 / J. Chem. Phys. (2004)
  3. 10.1063/1.3512900 / J. Chem. Phys. (2010)
  4. 10.1002/anie.200704247 / Angew. Chem., Int. Ed. (2008)
  5. 10.1063/1.3079326 / J. Chem. Phys. (2009)
  6. 10.1002/9780470125847.ch1 / Rev. Comput. Chem. (1996)
  7. {'first-page': '261', 'volume-title': 'IEEE Symposium on BionInformatics and BioEngineering', 'year': '2006', 'key': '2023070203444836100_c7'} / IEEE Symposium on BionInformatics and BioEngineering (2006)
  8. 10.1093/bioinformatics/btl259 / Bioinformatics (2006)
  9. 10.1021/ar00041a001 / Acc. Chem. Res. (1994)
  10. 10.1021/ci00021a011 / J. Chem. Inf. Comput. Sci. (1994)
  11. 10.1016/j.sbi.2008.02.004 / Curr. Opin. Strut. Biol. (2008)
  12. 10.1093/comjnl/41.8.547 / Comput. J. (1998)
  13. 10.1016/S1359-6446(02)02411-X / Drug Discovery Today (2002)
  14. 10.1023/A:1008059505361 / J. Comput.-Aided Mol. Des. (1999)
  15. 10.1023/A:1008194019144 / J. Comput.-Aided Mol. Des. (2000)
  16. 10.1021/ci970437z / J. Chem. Inf. Comput. Sci. (1998)
  17. 10.1021/ci0003956 / J. Chem. Inf. Comput. Sci. (2001)
  18. 10.1145/640075.640110 / Proceedings of RECOMB'03 (2003)
  19. 10.1103/PhysRevLett.108.058301 / Phys. Rev. Lett. (2012)
  20. {'volume-title': 'Molecular Descriptors for Chemoinformatics', 'year': '2009', 'key': '2023070203444836100_c20'} / Molecular Descriptors for Chemoinformatics (2009)
  21. 10.1021/ci200386x / J. Chem. Inf. Model. (2012)
  22. 10.1007/s00214-003-0552-1 / Theor. Chem. Acc. (2004)
  23. 10.1103/PhysRevLett.91.080201 / Phys. Rev. Lett. (2003)
  24. 10.1107/S0108767310026395 / Acta Crystallogr., Sect. A: Found. Crystallogr. (2010)
  25. 10.1063/1.2949547 / J. Chem. Phys. (2008)
  26. 10.1107/s0567739478001680 / Acta Crystallogr. (1978)
  27. 10.1364/JOSAA.5.001127 / J. Opt. Soc. Am. (1988)
  28. 10.1002/jcc.20110 / J. Comput. Chem. (2004)
  29. 10.1107/S0108767305015266 / Acta Cryst. A (2005)
  30. 10.1002/nav.3800020109 / Naval Res. Logistics Quart. (1955)
  31. 10.1021/ct3004832 / J. Chem. Theory Comput. (2012)
  32. 10.1021/c160017a018 / J. Chem. Doc. (1965)
  33. 10.1021/ci9800918 / J. Chem. Inf. Comput. Sci. (1999)
  34. 10.1002/jcc.21925 / J. Comput. Chem. (2012)
  35. 10.1007/BF02288323 / Ann. Operat. Res. (1988)
  36. {'key': '2023070203444836100_c36'}
  37. 10.1038/143939b0 / Nature (London) (1939)
  38. 10.1016/S0009-2614(03)00820-0 / Chem. Phys. Lett. (2003)
  39. 10.1098/rspa.1962.0066 / Proc. R. Soc. London, Ser. A (1962)
  40. 10.1103/PhysRevLett.107.085504 / Phys. Rev. Lett. (2011)
  41. 10.1103/PhysRevB.28.784 / Phys. Rev. B (1983)
  42. 10.1103/PhysRevB.87.184115 / Phys. Rev. B (2013)
  43. 10.1103/PhysRevLett.109.059801 / Phys. Rev. Lett. (2012)
  44. {'key': '2023070203444836100_c44'}
  45. 10.1107/S0021889811038970 / J. Appl. Crystallogr. (2011)
  46. 10.1016/0021-9991(66)90004-0 / J. Comput. Phys. (1966)
  47. 10.1063/1.455717 / J. Chem. Phys. (1988)
  48. {'volume-title': 'A Practical Introduction to the Simulation of Molecular Systems', 'year': '1999', 'key': '2023070203444836100_c48'} / A Practical Introduction to the Simulation of Molecular Systems (1999)
Dates
Type When
Created 11 years, 9 months ago (Nov. 14, 2013, 6:45 p.m.)
Deposited 2 years, 1 month ago (July 1, 2023, 11:44 p.m.)
Indexed 1 day, 18 hours ago (Aug. 27, 2025, 11:55 a.m.)
Issued 11 years, 9 months ago (Nov. 14, 2013)
Published 11 years, 9 months ago (Nov. 14, 2013)
Published Online 11 years, 9 months ago (Nov. 14, 2013)
Published Print 11 years, 9 months ago (Nov. 14, 2013)
Funders 0

None

@article{Sadeghi_2013, title={Metrics for measuring distances in configuration spaces}, volume={139}, ISSN={1089-7690}, url={http://dx.doi.org/10.1063/1.4828704}, DOI={10.1063/1.4828704}, number={18}, journal={The Journal of Chemical Physics}, publisher={AIP Publishing}, author={Sadeghi, Ali and Ghasemi, S. Alireza and Schaefer, Bastian and Mohr, Stephan and Lill, Markus A. and Goedecker, Stefan}, year={2013}, month=nov }