Native mass spectrometry (MS) allows the interrogation of structural aspects of macromolecules in the gas phase, under the premise of having initially maintained their solution-phase noncovalent interactions intact. In the more than 25 years since the first reports, the utility of native MS has become well established in the structural biology community. The experimental and technological advances during this time have been rapid, resulting in dramatic increases in sensitivity, mass range, resolution, and complexity of possible experiments. As experimental methods have improved, there have been accompanying developments in computational approaches for analyzing and exploiting the profusion of MS data in a structural and biophysical context. In this perspective, we consider the computational strategies currently being employed by the community, aspects of best practice, and the challenges that remain to be addressed. Our perspective is based on discussions within the European Cooperation in Science and Technology Action on Native Mass Spectrometry and Related Methods for Structural Biology (EU COST Action BM1403), which involved participants from across Europe and North America. It is intended not as an in-depth review but instead to provide an accessible introduction to and overview of the topic - to inform newcomers to the field and stimulate discussions in the community about addressing existing challenges. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05792) focuses on software tools available to help researchers tackle some of the challenges enumerated here.

Allison, T., Barran, P., Cianferani, S., Degiacomi, M., Gabelica, V., Grandori, R., et al. (2020). Computational Strategies and Challenges for Using Native Ion Mobility Mass Spectrometry in Biophysics and Structural Biology. ANALYTICAL CHEMISTRY, 92(16), 10872-10880 [10.1021/acs.analchem.9b05791].

Computational Strategies and Challenges for Using Native Ion Mobility Mass Spectrometry in Biophysics and Structural Biology

Grandori R.;
2020

Abstract

Native mass spectrometry (MS) allows the interrogation of structural aspects of macromolecules in the gas phase, under the premise of having initially maintained their solution-phase noncovalent interactions intact. In the more than 25 years since the first reports, the utility of native MS has become well established in the structural biology community. The experimental and technological advances during this time have been rapid, resulting in dramatic increases in sensitivity, mass range, resolution, and complexity of possible experiments. As experimental methods have improved, there have been accompanying developments in computational approaches for analyzing and exploiting the profusion of MS data in a structural and biophysical context. In this perspective, we consider the computational strategies currently being employed by the community, aspects of best practice, and the challenges that remain to be addressed. Our perspective is based on discussions within the European Cooperation in Science and Technology Action on Native Mass Spectrometry and Related Methods for Structural Biology (EU COST Action BM1403), which involved participants from across Europe and North America. It is intended not as an in-depth review but instead to provide an accessible introduction to and overview of the topic - to inform newcomers to the field and stimulate discussions in the community about addressing existing challenges. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05792) focuses on software tools available to help researchers tackle some of the challenges enumerated here.
Articolo in rivista - Articolo scientifico
ion mobility
English
10872
10880
9
Allison, T., Barran, P., Cianferani, S., Degiacomi, M., Gabelica, V., Grandori, R., et al. (2020). Computational Strategies and Challenges for Using Native Ion Mobility Mass Spectrometry in Biophysics and Structural Biology. ANALYTICAL CHEMISTRY, 92(16), 10872-10880 [10.1021/acs.analchem.9b05791].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/349322
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