Collision cross section predictions using 2-dimensional molecular descriptors

M. T. Soper-Hopper, A. S. Petrov, J. N. Howard, S. S. Yu, J. G. Forsythe, M. A. Grover, F. M. Fernández

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)


Traditional methods for deriving computationally-generated collision cross sections for comparisons with ion mobility-mass spectrometry data require 3-dimensional energy-minimized structures and are often time consuming, preventing high throughput implementation. Here, we introduce a method to predict ion mobility collision cross sections of lipids and peptide analogs important in prebiotic chemistry and other fields. Using less than 100 2-D molecular descriptors this approach resulted in prediction errors of less than 2%.

Original languageEnglish
Pages (from-to)7624-7627
Number of pages4
JournalChemical Communications
Issue number54
Publication statusPublished - 2017 Jan 1

All Science Journal Classification (ASJC) codes

  • Catalysis
  • Electronic, Optical and Magnetic Materials
  • Ceramics and Composites
  • Chemistry(all)
  • Surfaces, Coatings and Films
  • Metals and Alloys
  • Materials Chemistry


Dive into the research topics of 'Collision cross section predictions using 2-dimensional molecular descriptors'. Together they form a unique fingerprint.

Cite this