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Search Publications by: Dmitrii V. Tchekhovskoi (Fed)

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Displaying 1 - 25 of 43

Variation of Site-Specific Glycosylation Profiles of Recombinant Influenza Glycoproteins

August 9, 2024
Author(s)
Zachary Goecker, Meghan Burke Harris, Concepcion Remoroza, Yi Liu, Yuri Mirokhin, Sergey Sheetlin, Dmitrii V. Tchekhovskoi, Xiaoyu (Sara) Yang, Stephen E. Stein
This work presents a detailed determination of site-specific N-glycan distributions of the recombinant influenza glycoproteins hemagglutinin (HA) and neuraminidase. Variation in glycosylation among recombinant glycoproteins is not predictable and can

Comparison of N-glycopeptide to released N-glycan abundances and the influence of glycopeptide mass and charge state on N-linked glycosylation of IgG antibodies

March 7, 2024
Author(s)
Concepcion Remoroza, Meghan Burke Harris, Tytus Mak, Sergey Sheetlin, Yuri Mirokhin, Zachary Goecker, Brian T. Cooper, Mark Lowenthal, Xiaoyu (Sara) Yang, Guanghui Wang, Dmitrii V. Tchekhovskoi, Stephen E. Stein
We report the comparison of mass-spectral-based abundances of tryptic glycopeptides to fluorescence abundances of released labeled glycans and the effects of mass and charge state and in-source fragmentation on glycopeptide abundances. The primary

Determining Site-Specific Glycan Profiles of Recombinant SARS-CoV-2 Spike Proteins from Multiple Sources

August 30, 2023
Author(s)
Meghan Burke Harris, Yi Liu, Concepcion Remoroza, Yuri Mirokhin, Sergey Sheetlin, Dmitrii V. Tchekhovskoi, Guanghui Wang, Xiaoyu (Sara) Yang, Stephen E. Stein
Glycopeptide Abundance Distribution Spectra (GADS) were recently introduced as a means of representing, storing and comparing glycan profiles of intact glycopeptides. Here, using that representation, an extensive analysis is made of multiple commercial

Mass Spectral Library Methods for Analysis of Site-Specific N-Glycosylation: Application to Human Milk Proteins

September 16, 2022
Author(s)
Concepcion Remoroza, Meghan Burke Harris, Xiaoyu (Sara) Yang, Sergey Sheetlin, Yuri Mirokhin, Sanford Markey, Dmitrii V. Tchekhovskoi, Stephen E. Stein
We present a mass-spectral library-based method for analyzing site-specific N-linked protein glycosylation. Its operation and utility are illustrated by applying it to both newly measured and available proteomics data of human milk glycoproteins. It

Representing and Comparing Site-Specific Glycan Abundance Distributions of Glycoproteins

July 30, 2021
Author(s)
Concepcion Remoroza, Meghan Burke Harris, Yi Liu, Yuri Mirokhin, Dmitrii V. Tchekhovskoi, Xiaoyu (Sara) Yang, Stephen E. Stein
A method for representing and comparing distributions of N-linked glycans located at specific sites in proteins is presented. The representation takes the form of a simple mass spectrum for a given peptide sequence, with each peak corresponding to a

MS_Piano: A Software Tool for Annotating Peaks in CID Tandem Mass Spectra of Peptides and N-Glycopeptides

July 15, 2021
Author(s)
Xiaoyu (Sara) Yang, Pedatsur Neta, Yuri Mirokhin, Dmitrii V. Tchekhovskoi, Concepcion Remoroza, Meghan Burke Harris, Yuxue Liang, Sanford Markey, Stephen E. Stein
Annotating product ion peaks in tandem mass spectra is essential for evaluating spectral quality and validating peptide identification. This task is more complex for glycopeptides and is crucial for the confident determination of glycosylation sites in

Sensitive Method for the Confident Identification of Genetically Variant Peptides in Human Hair

October 31, 2019
Author(s)
Zheng Zhang, Meghan Burke, William E. Wallace, Yuxue Liang, Sergey L. Sheetlin, Yuri Mirokhin, Dmitrii Tchekhovskoi, Stephen Stein
Recent reports have demonstrated that genetically variant peptides (GVPs) derived from human hair shaft proteins can be used to differentiate individuals of different biogeographic origin (Parker, G.J.; et al. PLos One. 2016, e0160653). We report a direct

The NISTmAb Tryptic Peptide Spectral Library for Monoclonal Antibody Characterization

March 6, 2018
Author(s)
Qian Dong, Yuxue Liang, Xinjian Yan, Sanford Markey, Yuri Mirokhin, Dmitrii V. Tchekhovskoi, Tallat H. Bukhari, Stephen E. Stein
We describe the creation of a mass spectral library composed of all identifiable spectra derived from the tryptic digest of a therapeutic monoclonal antibody. The NISTmAb library is a unique reference peptide spectral library developed from a total of six

Reverse and Random Decoy Methods for False Discovery Rate Estimation in High Mass Accuracy Peptide Spectral Library Searches

February 2, 2018
Author(s)
Zheng Zhang, Meghan C. Burke, Yuri A. Mirokhin, Dmitrii V. Tchekhovskoi, Sanford P. Markey, Wen Yu, Raghothama Chaerkady, Sonja Hess, Stephen E. Stein
Spectral library searching (SLS) is an attractive alternative to sequence database searching (SDS) for peptide identification due to its speed, sensitivity, and ability to include any selected mass spectra. However, SLS does not have a widely tested and

Combining fragment ion and neutral loss matching during mass spectral library searching: A new general-purpose algorithm applicable to illicit drug identification

November 20, 2017
Author(s)
Arun S. Moorthy, William E. Wallace, Anthony J. Kearsley, Dmitrii V. Tchekhovskoi, Stephen E. Stein
A mass spectral library search algorithm that identifies compounds that differ from library compounds by a single ‘inert’ structural component is described. This algorithm, the Hybrid Similarity Search, generates a similarity score based on matching both

The Hybrid Search: A Mass Spectral Library Search Method for Discovery of Modifications in Proteomics

April 3, 2017
Author(s)
Meghan C. Burke, Yuri A. Mirokhin, Dmitrii V. Tchekhovskoi, Sanford P. Markey, Stephen E. Stein, Jenny Heidbrink Thompson, Christopher Larkin
We present a mass spectral library based method to identify tandem mass spectra of peptides that contain unanticipated modifications and amino acid variants. We describe this as a ‘hybrid’ method since it combines matching both ion m/z and mass losses. The

Mass Spectral Library Quality Assurance by Inter-Library Comparison

April 2, 2017
Author(s)
William E. Wallace, Weihua Ji, Dmitrii V. Tchekhovskoi, Karen W. Phinney, Stephen E. Stein
A method to discover and correct errors in mass spectral libraries is described. Comparing across a set of highly curated reference libraries compounds that have the same chemical structure quickly identifies entries that are outliers. In cases where three