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Gorshkov AV, Rozdina IG, Evreinov VV. On the Application of the Critical Chromatography Concept for Investigation of the Nucleotide Sequence of Single-Stranded DNA. POLYMER SCIENCE SERIES A 2022. [DOI: 10.1134/s0965545x22010035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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2
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Yang Y, Lin L, Qiao L. Deep learning approaches for data-independent acquisition proteomics. Expert Rev Proteomics 2021; 18:1031-1043. [PMID: 34918987 DOI: 10.1080/14789450.2021.2020654] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
INTRODUCTION Data-independent acquisition (DIA) is an emerging technology for large-scale proteomic studies. DIA data analysis methods are evolving rapidly, and deep learning has cut a conspicuous figure in this field. AREAS COVERED This review discusses and provides an overview of the deep learning methods that are used for DIA data analysis, including spectral library prediction, feature scoring, and statistical control in peptide-centric analysis, as well as de novo peptide sequencing. Literature searches were performed for articles, including preprints, up to December 2021 from PubMed, Scopus, and Web of Science databases. EXPERT OPINION While spectral library prediction has broken through the limitation on proteome coverage of experimental libraries, the statistical burden due to the large query space is the remaining challenge of utilizing proteome-wide predicted libraries. Analysis of post-translational modifications is another promising direction of deep learning-based DIA methods.
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Affiliation(s)
- Yi Yang
- Department of Chemistry, Shanghai Stomatological Hospital, and Minhang Hospital, Fudan University, Shanghai China
| | - Ling Lin
- Department of Chemistry, Shanghai Stomatological Hospital, and Minhang Hospital, Fudan University, Shanghai China
| | - Liang Qiao
- Department of Chemistry, Shanghai Stomatological Hospital, and Minhang Hospital, Fudan University, Shanghai China
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3
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Bouwmeester R, Gabriels R, Hulstaert N, Martens L, Degroeve S. DeepLC can predict retention times for peptides that carry as-yet unseen modifications. Nat Methods 2021; 18:1363-1369. [PMID: 34711972 DOI: 10.1038/s41592-021-01301-5] [Citation(s) in RCA: 77] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 09/13/2021] [Indexed: 11/09/2022]
Abstract
The inclusion of peptide retention time prediction promises to remove peptide identification ambiguity in complex liquid chromatography-mass spectrometry identification workflows. However, due to the way peptides are encoded in current prediction models, accurate retention times cannot be predicted for modified peptides. This is especially problematic for fledgling open searches, which will benefit from accurate retention time prediction for modified peptides to reduce identification ambiguity. We present DeepLC, a deep learning peptide retention time predictor using peptide encoding based on atomic composition that allows the retention time of (previously unseen) modified peptides to be predicted accurately. We show that DeepLC performs similarly to current state-of-the-art approaches for unmodified peptides and, more importantly, accurately predicts retention times for modifications not seen during training. Moreover, we show that DeepLC's ability to predict retention times for any modification enables potentially incorrect identifications to be flagged in an open search of a wide variety of proteome data.
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Affiliation(s)
- Robbin Bouwmeester
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Ralf Gabriels
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Niels Hulstaert
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium. .,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
| | - Sven Degroeve
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
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4
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Gorshkov AV, Rozdina IG, Pridatchenko ML, Evreinov VV. The Effect of Secondary Structures in Peptides and Proteins on Their Chromatographic Separation. POLYMER SCIENCE SERIES A 2020. [DOI: 10.1134/s0965545x20040069] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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5
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Yang Y, Liu X, Shen C, Lin Y, Yang P, Qiao L. In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics. Nat Commun 2020; 11:146. [PMID: 31919359 PMCID: PMC6952453 DOI: 10.1038/s41467-019-13866-z] [Citation(s) in RCA: 102] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2019] [Accepted: 12/04/2019] [Indexed: 11/12/2022] Open
Abstract
Data-independent acquisition (DIA) is an emerging technology for quantitative proteomic analysis of large cohorts of samples. However, sample-specific spectral libraries built by data-dependent acquisition (DDA) experiments are required prior to DIA analysis, which is time-consuming and limits the identification/quantification by DIA to the peptides identified by DDA. Herein, we propose DeepDIA, a deep learning-based approach to generate in silico spectral libraries for DIA analysis. We demonstrate that the quality of in silico libraries predicted by instrument-specific models using DeepDIA is comparable to that of experimental libraries, and outperforms libraries generated by global models. With peptide detectability prediction, in silico libraries can be built directly from protein sequence databases. We further illustrate that DeepDIA can break through the limitation of DDA on peptide/protein detection, and enhance DIA analysis on human serum samples compared to the state-of-the-art protocol using a DDA library. We expect this work expanding the toolbox for DIA proteomics.
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Affiliation(s)
- Yi Yang
- Department of Chemistry, Shanghai Stomatological Hospital, and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200000, China
| | - Xiaohui Liu
- Department of Chemistry, Shanghai Stomatological Hospital, and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200000, China
| | - Chengpin Shen
- Shanghai Omicsolution Co., Ltd., Shanghai, 200000, China
| | - Yu Lin
- College of Engineering and Computer Science, The Australian National University, Canberra, ACT 0200, Australia
| | - Pengyuan Yang
- Department of Chemistry, Shanghai Stomatological Hospital, and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200000, China
| | - Liang Qiao
- Department of Chemistry, Shanghai Stomatological Hospital, and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200000, China.
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6
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Zamora WJ, Campanera JM, Luque FJ. Development of a Structure-Based, pH-Dependent Lipophilicity Scale of Amino Acids from Continuum Solvation Calculations. J Phys Chem Lett 2019; 10:883-889. [PMID: 30741551 DOI: 10.1021/acs.jpclett.9b00028] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Lipophilicity is a fundamental property to characterize the structure and function of proteins, motivating the development of lipophilicity scales. We report a versatile strategy to derive a pH-adapted scale that relies on theoretical estimates of distribution coefficients from conformational ensembles of amino acids. This is accomplished by using an accurately parametrized version of the IEFPCM/MST continuum solvation model as an effective way to describe the partitioning between n-octanol and water, in conjunction with a formalism that combines partition coefficients of neutral and ionic species of residues and the corresponding p Ka values of ionizable groups. Two weighting schemes are considered to derive solvent-like and protein-like scales, which have been calibrated by comparison with other experimental scales developed in different chemical/biological environments and pH conditions as well as by examining properties such as the retention time of small peptides and the recognition of antigenic peptides. A straightforward extension to nonstandard residues is enabled by this efficient methodological strategy.
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Affiliation(s)
- William J Zamora
- Department of Nutrition, Food Science and Gastronomy, Faculty of Pharmacy and Food Science, Institute of Biomedicine (IBUB) and Institute of Theoretical and Computational Chemistry (IQTCUB), Campus Torribera , University of Barcelona , 08921 Santa Coloma de Gramenet , Spain
| | - Josep M Campanera
- Department of Nutrition, Food Science and Gastronomy, Faculty of Pharmacy and Food Science, Institute of Biomedicine (IBUB) and Institute of Theoretical and Computational Chemistry (IQTCUB), Campus Torribera , University of Barcelona , 08921 Santa Coloma de Gramenet , Spain
| | - F Javier Luque
- Department of Nutrition, Food Science and Gastronomy, Faculty of Pharmacy and Food Science, Institute of Biomedicine (IBUB) and Institute of Theoretical and Computational Chemistry (IQTCUB), Campus Torribera , University of Barcelona , 08921 Santa Coloma de Gramenet , Spain
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7
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Tarasova IA, Masselon CD, Gorshkov AV, Gorshkov MV. Predictive chromatography of peptides and proteins as a complementary tool for proteomics. Analyst 2018; 141:4816-4832. [PMID: 27419248 DOI: 10.1039/c6an00919k] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
In the last couple of decades, considerable effort has been focused on developing methods for quantitative and qualitative proteome characterization. The method of choice in this characterization is mass spectrometry used in combination with sample separation. One of the most widely used separation techniques at the front end of a mass spectrometer is high performance liquid chromatography (HPLC). A unique feature of HPLC is its specificity to the amino acid sequence of separated peptides and proteins. This specificity may provide additional information about the peptides or proteins under study which is complementary to the mass spectrometry data. The value of this information for proteomics has been recognized in the past few decades, which has stimulated significant effort in the development and implementation of computational and theoretical models for the prediction of peptide retention time for a given sequence. Here we review the advances in this area and the utility of predicted retention times for proteomic applications.
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Affiliation(s)
- Irina A Tarasova
- Institute for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia.
| | - Christophe D Masselon
- CEA, iRTSV-BGE, Laboratoire d'Etude de la Dynamique des Protéomes, Grenoble, F-38000, France and INSERM, U1038-BGE, F-38000, Grenoble, France
| | - Alexander V Gorshkov
- N.N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow 119991, Russia
| | - Mikhail V Gorshkov
- Institute for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia. and Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow region 141700, Russia
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Bittremieux W, Tabb DL, Impens F, Staes A, Timmerman E, Martens L, Laukens K. Quality control in mass spectrometry-based proteomics. MASS SPECTROMETRY REVIEWS 2018; 37:697-711. [PMID: 28802010 DOI: 10.1002/mas.21544] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2017] [Revised: 07/24/2017] [Accepted: 07/24/2017] [Indexed: 05/21/2023]
Abstract
Mass spectrometry is a highly complex analytical technique and mass spectrometry-based proteomics experiments can be subject to a large variability, which forms an obstacle to obtaining accurate and reproducible results. Therefore, a comprehensive and systematic approach to quality control is an essential requirement to inspire confidence in the generated results. A typical mass spectrometry experiment consists of multiple different phases including the sample preparation, liquid chromatography, mass spectrometry, and bioinformatics stages. We review potential sources of variability that can impact the results of a mass spectrometry experiment occurring in all of these steps, and we discuss how to monitor and remedy the negative influences on the experimental results. Furthermore, we describe how specialized quality control samples of varying sample complexity can be incorporated into the experimental workflow and how they can be used to rigorously assess detailed aspects of the instrument performance.
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Affiliation(s)
- Wout Bittremieux
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium
- Biomedical Informatics Research Center Antwerp (Biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium
| | - David L Tabb
- Division of Molecular Biology and Human Genetics, Stellenbosch University Faculty of Medicine and Health Sciences, Tygerberg Hospital, Cape Town, South Africa
| | - Francis Impens
- VIB Proteomics Core, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Biochemistry, Ghent University, Ghent, Belgium
| | - An Staes
- VIB Proteomics Core, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Biochemistry, Ghent University, Ghent, Belgium
| | - Evy Timmerman
- VIB Proteomics Core, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Biochemistry, Ghent University, Ghent, Belgium
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
- Faculty of Medicine and Health Sciences, Department of Biochemistry, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Zwijnaarde, Belgium
| | - Kris Laukens
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium
- Biomedical Informatics Research Center Antwerp (Biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium
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9
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Lobas AA, Levitsky LI, Fichtenbaum A, Surin AK, Pridatchenko ML, Mitulovic G, Gorshkov AV, Gorshkov MV. Predictive Liquid Chromatography of Peptides Based on Hydrophilic Interactions for Mass Spectrometry-Based Proteomics. JOURNAL OF ANALYTICAL CHEMISTRY 2018. [DOI: 10.1134/s1061934817140076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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10
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Tutorial: Correction of shifts in single-stage LC-MS(/MS) data. Anal Chim Acta 2018; 999:37-53. [DOI: 10.1016/j.aca.2017.09.039] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2016] [Revised: 09/26/2017] [Accepted: 09/27/2017] [Indexed: 11/19/2022]
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11
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Moruz L, Käll L. Peptide retention time prediction. MASS SPECTROMETRY REVIEWS 2017; 36:615-623. [PMID: 26799864 DOI: 10.1002/mas.21488] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Accepted: 11/12/2015] [Indexed: 06/05/2023]
Abstract
Most methods for interpreting data from shotgun proteomics experiments are to large degree dependent on being able to predict properties of peptide-ions. Often such predicted properties are limited to molecular mass and fragment spectra, but here we put focus on a perhaps underutilized property, a peptide's chromatographic retention time. We review a couple of different principles of retention time prediction,and their applications within computational proteomics. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:615-623, 2017.
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Affiliation(s)
- Luminita Moruz
- Science for Life Laboratory, School of Biotechnology, Royal Institute of Technology - KTH, Stockholm, Sweden
| | - Lukas Käll
- Science for Life Laboratory, School of Biotechnology, Royal Institute of Technology - KTH, Stockholm, Sweden
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12
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Gorshkov AV, Goloborodko AA, Pridatchenko ML, Tarasova IA, Rozdina IG, Evreinov VV, Gorshkov MV. Applicability of the critical-chromatography concept to proteomics problems: Separation of peptides modeled by a heterogeneous rod. POLYMER SCIENCE SERIES A 2017. [DOI: 10.1134/s0965545x17030063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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13
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Holman SW, McLean L, Eyers CE. RePLiCal: A QconCAT Protein for Retention Time Standardization in Proteomics Studies. J Proteome Res 2016; 15:1090-102. [PMID: 26775667 DOI: 10.1021/acs.jproteome.5b00988] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
This study introduces a new reversed-phase liquid chromatography retention time (RT) standard, RePLiCal (Reversed-phase liquid chromatography calibrant), produced using QconCAT technology. The synthetic protein contains 27 lysine-terminating calibrant peptides, meaning that the same complement of standards can be generated using either Lys-C or trypsin-based digestion protocols. RePLiCal was designed such that each constituent peptide is unique with respect to all eukaryotic proteomes, thereby enabling integration into a wide range of proteomic analyses. RePLiCal has been benchmarked against three commercially available peptide RT standard kits and outperforms all in terms of LC gradient coverage. RePLiCal also provides a higher number of calibrant points for chromatographic retention time standardization and normalization. The standard provides stable RTs over long analysis times and can be readily transferred between different LC gradients and nUHPLC instruments. Moreover, RePLiCal can be used to predict RTs for other peptides in a timely manner. Furthermore, it is shown that RePLiCal can be used effectively to evaluate trapping column performance for nUHPLC instruments using trap-elute configurations, to optimize gradients to maximize peptide and protein identification rates, and to recalibrate the m/z scale of mass spectrometry data post-acquisition.
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Affiliation(s)
- Stephen W Holman
- Centre for Proteome Research, Department of Biochemistry, Institute of Integrative Biology, University of Liverpool , Crown Street, Liverpool L69 7ZB, United Kingdom
| | - Lynn McLean
- Centre for Proteome Research, Department of Biochemistry, Institute of Integrative Biology, University of Liverpool , Crown Street, Liverpool L69 7ZB, United Kingdom
| | - Claire E Eyers
- Centre for Proteome Research, Department of Biochemistry, Institute of Integrative Biology, University of Liverpool , Crown Street, Liverpool L69 7ZB, United Kingdom
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14
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Gorshkov AV, Pridatchenko ML, Perlova TY, Tarasova IA, Gorshkov MV, Evreinov VV. Applicability of the critical chromatography concept to proteomics problems: I. Effect of the stationary phase and the size of the chromatographic column on the dependence of the retention time of peptides and proteins on the amino acid sequence. JOURNAL OF ANALYTICAL CHEMISTRY 2015. [DOI: 10.1134/s1061934816010056] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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15
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Spicer V, Lao YW, Shamshurin D, Ezzati P, Wilkins JA, Krokhin OV. N-Capping Motifs Promote Interaction of Amphipathic Helical Peptides with Hydrophobic Surfaces and Drastically Alter Hydrophobicity Values of Individual Amino Acids. Anal Chem 2014; 86:11498-502. [DOI: 10.1021/ac503352h] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Vic Spicer
- Manitoba
Centre for Proteomics and Systems Biology, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada
| | - Ying W. Lao
- Department
of Chemistry, University of Manitoba, 360 Parker Building, Winnipeg, Manitoba R3T 2N2, Canada
| | - Dmitry Shamshurin
- Manitoba
Centre for Proteomics and Systems Biology, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada
| | - Peyman Ezzati
- Manitoba
Centre for Proteomics and Systems Biology, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada
| | - John A. Wilkins
- Manitoba
Centre for Proteomics and Systems Biology, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada
- Department
of Internal Medicine, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada
| | - Oleg V. Krokhin
- Manitoba
Centre for Proteomics and Systems Biology, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada
- Department
of Internal Medicine, University of Manitoba, 799 JBRC, 715 McDermot Avenue, Winnipeg, Manitoba R3E 3P4, Canada
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16
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Ivanov MV, Levitsky LI, Lobas AA, Panic T, Laskay ÜA, Mitulovic G, Schmid R, Pridatchenko ML, Tsybin YO, Gorshkov MV. Empirical Multidimensional Space for Scoring Peptide Spectrum Matches in Shotgun Proteomics. J Proteome Res 2014; 13:1911-20. [DOI: 10.1021/pr401026y] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Mark V. Ivanov
- Institute
for Energy Problems of Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia
- Moscow Institute of Physics and Technology (State University), Inststitutskii per., 9, Dolgoprudny 141700, Moscow region, Russia
| | - Lev I. Levitsky
- Institute
for Energy Problems of Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia
- Moscow Institute of Physics and Technology (State University), Inststitutskii per., 9, Dolgoprudny 141700, Moscow region, Russia
| | - Anna A. Lobas
- Institute
for Energy Problems of Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia
- Moscow Institute of Physics and Technology (State University), Inststitutskii per., 9, Dolgoprudny 141700, Moscow region, Russia
| | - Tanja Panic
- Medical University of Vienna, Spitalgasse 23, Vienna 1090, Austria
| | - Ünige A. Laskay
- Biomolecular
Mass Spectrometry Laboratory, Ecole Polytechnique Fédérale de Lausanne, 2 av. Forel, Lausanne 1015, Switzerland
| | - Goran Mitulovic
- Medical University of Vienna, Spitalgasse 23, Vienna 1090, Austria
| | - Rainer Schmid
- Medical University of Vienna, Spitalgasse 23, Vienna 1090, Austria
| | - Marina L. Pridatchenko
- Institute
for Energy Problems of Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia
| | - Yury O. Tsybin
- Biomolecular
Mass Spectrometry Laboratory, Ecole Polytechnique Fédérale de Lausanne, 2 av. Forel, Lausanne 1015, Switzerland
| | - Mikhail V. Gorshkov
- Institute
for Energy Problems of Chemical Physics, Russian Academy of Sciences, 38 Leninsky Pr., Bld. 2, Moscow 119334, Russia
- Moscow Institute of Physics and Technology (State University), Inststitutskii per., 9, Dolgoprudny 141700, Moscow region, Russia
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17
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Grigoryan M, Shamshurin D, Spicer V, Krokhin OV. Unifying Expression Scale for Peptide Hydrophobicity in Proteomic Reversed Phase High-Pressure Liquid Chromatography Experiments. Anal Chem 2013; 85:10878-86. [DOI: 10.1021/ac402310t] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Marine Grigoryan
- Manitoba Centre for Proteomics and Systems
Biology and ‡Department of Internal Medicine, University of Manitoba, 799 JBRC,
715 McDermot Avenue, Winnipeg, R3E 3P4, Canada
| | - Dmitry Shamshurin
- Manitoba Centre for Proteomics and Systems
Biology and ‡Department of Internal Medicine, University of Manitoba, 799 JBRC,
715 McDermot Avenue, Winnipeg, R3E 3P4, Canada
| | - Victor Spicer
- Manitoba Centre for Proteomics and Systems
Biology and ‡Department of Internal Medicine, University of Manitoba, 799 JBRC,
715 McDermot Avenue, Winnipeg, R3E 3P4, Canada
| | - Oleg V. Krokhin
- Manitoba Centre for Proteomics and Systems
Biology and ‡Department of Internal Medicine, University of Manitoba, 799 JBRC,
715 McDermot Avenue, Winnipeg, R3E 3P4, Canada
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