Overview of the use of theory to understand infrared and Raman spectra and images of biomolecules: colorectal cancer as an example

J. A. A. C. Piva, J. L. R. Silva, L. Raniero, A. A. Martin, Henrik Bohr, Karl J. Jalkanen

Research output: Contribution to journalJournal articleResearchpeer-review


In this work, we present the state of the art in the use of theory (first principles, molecular dynamics, and statistical methods) for interpreting and understanding the infrared (vibrational) absorption and Raman scattering spectra. It is discussed how they can be used in combination with purely experimental studies to generate infrared and Raman images of biomolecules in biologically relevant solutions, including fluids, cells, and both healthy and diseased tissue. The species and conformers of the individual biomolecules are in many cases not stable structures, species, or conformers in the isolated state or in non-polar non-strongly interacting solvents. Hence, it is better to think of the collective behavior of the system. The collective interaction is not the simple sum of the individual parts. Here, we will show that this is also not true for the infrared and Raman spectra and images and that the models used must take this into account. Hence, the use of statistical methods to interpret and understand the infrared and Raman spectra and images from biological tissues, cells, parts of cells, fluids, and even whole organism should change accordingly. As the species, conformers and structures of biomolecules are very sensitive to their environment and aggregation state, the combined use of infrared and Raman spectroscopy and imaging and theoretical simulations are clearly fields, which can benefit from their joint and mutual development.
Original languageEnglish
JournalTheoretical Chemistry Accounts
Issue number4-6
Pages (from-to)1261-1273
Publication statusPublished - 2011


  • Linear discriminant analysis
  • Principal component analysis
  • Raman
  • Infrared
  • Colorectal cancer diagnosis
  • Raman imaging
  • Cluster analysis
  • Infrared imaging
  • Image generation
  • Statistical methods
  • First principles
  • Molecular mechanics


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