QSSR Modeling of Bacillus Subtilis Lipase A Peptide Collision Cross-Sections in Ion Mobility Spectrometry: Local Descriptor Versus Global Descriptor

2021 ◽  
Vol 40 (1) ◽  
pp. 54-62
Author(s):  
Zhong Ni ◽  
Anlin Wang ◽  
Lingyu Kang ◽  
Tiancheng Zhang
Keyword(s):  
Bacillus Subtilis ◽  
Ion Mobility Spectrometry ◽  
Cross Sections ◽  
Ion Mobility ◽  
Local Descriptor ◽  
Collision Cross Sections ◽  
Lipase A

scholarly journals Effect of Phosphorylation on the Collision Cross Sections of Peptide Ions in Ion Mobility Spectrometry

2020 ◽  
Author(s):  
Kosuke Ogata ◽  
Chih-Hsiang Chang ◽  
Yasushi Ishihama
Keyword(s):  
Ion Mobility Spectrometry ◽  
Cross Sections ◽  
Ion Mobility ◽  
Structural Information ◽  
Peptide Identification ◽  
Intramolecular Interactions ◽  
Peptide Ions ◽  
Large Numbers ◽  
Collision Cross Sections ◽  
Mass Increase

AbstractThe insertion of ion mobility spectrometry (IMS) between LC and MS can improve peptide identification in both proteomics and phosphoproteomics by providing structural information that is complementary to LC and MS, because IMS separates ions on the basis of differences in their shapes and charge states. However, it is necessary to know how phosphate groups affect the peptide collision cross sections (CCS) in order to accurately predict phosphopeptide CCS values and to maximize the usefulness of IMS. In this work, we systematically characterized the CCS values of 4,433 pairs of mono-phosphopeptide and corresponding unphosphorylated peptide ions using trapped ion mobility spectrometry (TIMS). Nearly one-third of the mono-phosphopeptide ions evaluated here showed smaller CCS values than their unphosphorylated counterparts, even though phosphorylation results in a mass increase of 80 Da. Significant changes of CCS upon phosphorylation occurred mainly in structurally extended peptides with large numbers of basic groups, possibly reflecting intramolecular interactions between phosphate and basic groups.

Determining Collision Cross Sections from Differential Ion Mobility Spectrometry

2021 ◽  
Author(s):  
Christian Ieritano ◽  
Arthur Lee ◽  
Jeff Crouse ◽  
Zack Bowman ◽  
Nour Mashmoushi ◽  
...  
Keyword(s):  
Ion Mobility Spectrometry ◽  
Cross Sections ◽  
Ion Mobility ◽  
Differential Ion Mobility Spectrometry ◽  
Collision Cross Sections

scholarly journals A Deep Convolutional Neural Network for Prediction of Peptide Collision Cross Sections in Ion Mobility Spectrometry

Biomolecules ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1904
Author(s):  
Yulia V. Samukhina ◽  
Dmitriy D. Matyushin ◽  
Oksana I. Grinevich ◽  
Aleksey K. Buryak
Keyword(s):  
Neural Network ◽  
Mass Spectrometry ◽  
Convolutional Neural Network ◽  
Cross Section ◽  
Ion Mobility Spectrometry ◽  
Cross Sections ◽  
Ion Mobility ◽  
Collision Cross Section ◽  
Deep Convolutional Neural Network ◽  
Collision Cross Sections

Most frequently, the identification of peptides in mass spectrometry-based proteomics is carried out using high-resolution tandem mass spectrometry. In order to increase the accuracy of analysis, additional information on the peptides such as chromatographic retention time and collision cross section in ion mobility spectrometry can be used. An accurate prediction of the collision cross section values allows erroneous candidates to be rejected using a comparison of the observed values and the predictions based on the amino acids sequence. Recently, a massive high-quality data set of peptide collision cross sections was released. This opens up an opportunity to apply the most sophisticated deep learning techniques for this task. Previously, it was shown that a recurrent neural network allows for predicting these values accurately. In this work, we present a deep convolutional neural network that enables us to predict these values more accurately compared with previous studies. We use a neural network with complex architecture that contains both convolutional and fully connected layers and comprehensive methods of converting a peptide to multi-channel 1D spatial data and vector. The source code and pre-trained model are available online.

scholarly journals A coarse-grained model for assisting the investigation of structure and dynamics of large nucleic acids by ion mobility spectrometry–mass spectrometry

2017 ◽  
Vol 19 (23) ◽  
pp. 14937-14946 ◽  
Author(s):  
S. Vangaveti ◽  
R. J. D'Esposito ◽  
J. L. Lippens ◽  
D. Fabris ◽  
S. V. Ranganathan
Keyword(s):  
Mass Spectrometry ◽  
Nucleic Acids ◽  
Ion Mobility Spectrometry ◽  
Cross Sections ◽  
Ion Mobility ◽  
Structural Elucidation ◽  
Coarse Grained ◽  
Coarse Grained Model ◽  
Structure And Dynamics ◽  
Collision Cross Sections

We developed a five bead model that facilitates calculation of collision cross sections of coarse grained structures of nucleic acids, enabling their structural elucidation using Ion Mobility Spectrometry–Mass Spectrometry (IMS-MS).

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