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Issue 54, 2017
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Collision cross section predictions using 2-dimensional molecular descriptors

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Abstract

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%.

Graphical abstract: Collision cross section predictions using 2-dimensional molecular descriptors

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Publication details

The article was received on 01 Jun 2017, accepted on 16 Jun 2017 and first published on 22 Jun 2017


Article type: Communication
DOI: 10.1039/C7CC04257D
Citation: Chem. Commun., 2017,53, 7624-7627
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    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 and F. M. Fernández, Chem. Commun., 2017, 53, 7624
    DOI: 10.1039/C7CC04257D

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