Abstract

Ion mobility spectrometry (IMS) is a gas-phase separation technique based on ion mobility differences in an electric field. It is largely used for the detection of specific ions such as small molecule explosives. IMS detection system includes the use of e. g. a Faraday cupor mass spectrometry (MS). The presence of interfering ion signals in standalone IMS may lead to the detection of false positives or negatives due to e. g. lacking resolving power. In this case, selective mobility shifts obtained using shift reagents (SR), i. e. ligands complexing a specific target, can bring help. The effectiveness of an SR strategy relies on the SR-target ion selectivity. The crucial step lies in the SR design. The aim of this paper is to present an efficient interplay of experimental ion mobility mass spectrometry (IMMS) and predictive computational chemistry using various levels of computational efforts for rationally designing target-specific SR. Mass spectrometry is used to evaluate the efficiency of the SR selectivity with identification and semi-quantification of free and complexed ions. Minimal computational efforts allow the design of the SR, predicting the SR-target ion relative stabilities, and predicting the ion mobility shifts. We demonstrate our approach using crown ethers and β-cyclodextrin to selectively shift interfering perchlorate, amino acids and diaminonaphthalene isomers. We also release the software ParsIMoS for the straightforward use of ion mobility calculator IMoS.

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