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Lu X, Dou P, Li C, Zheng F, Zhou L, Xie X, Wang Z, Xu G. Annotation of Dipeptides and Tripeptides Derivatized via Dansylation Based on Liquid Chromatography-Mass Spectrometry and Iterative Quantitative Structure Retention Relationship. J Proteome Res 2023. [PMID: 37163573 DOI: 10.1021/acs.jproteome.3c00002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Small peptides such as dipeptides and tripeptides show various biological activities in organisms. However, methods for identifying dipeptides/tripeptides from complex biological samples are lacking. Here, an annotation strategy involving the derivatization of dipeptides and tripeptides via dansylation was suggested based on liquid chromatography-mass spectrometry (LC-MS) and iterative quantitative structure retention relationship (QSRR) to choose dipeptides/tripeptides by using a small number of standards. First, the LC-autoMS/MS method and initial QSRR model were built based on 25 selected grid-dipeptides and 18 test-dipeptides. To achieve high-coverage detection, dipeptide/tripeptide pools containing abundant dipeptides/tripeptides were then obtained from four dansylated biological samples including serum, tissue, feces, and soybean paste by using the parameter-optimized LC-autoMS/MS method. The QSRR model was further optimized through an iterative train-by-pick strategy. Based on the specific fragments and tR tolerances, 198 dipeptides and 149 tripeptides were annotated. The dipeptides at lower annotation levels were verified by using authentic standards and grid-correlation analysis. Finally, variation in serum dipeptides/tripeptides of three different liver diseases including hepatitis B infection, liver cirrhosis, and hepatocellular carcinoma was characterized. Dipeptides with N-prolinyl, C-proline, N-glutamyl, and N-valinyl generally increased with disease severity. In conclusion, this study provides an efficient strategy for annotating dipeptides/tripeptides from complex samples.
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Affiliation(s)
- Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116031, China
| | - Peng Dou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116031, China
| | - Chao Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
| | - Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lina Zhou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116031, China
| | - Xiaoyu Xie
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research (Ministry of Education of China), Key Laboratory of Phytochemical R&D of Hunan Province, Hunan Normal University, Changsha 410081, China
| | - Zixuan Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Andries JPM, Goodarzi M, Heyden YV. Improvement of quantitative structure-retention relationship models for chromatographic retention prediction of peptides applying individual local partial least squares models. Talanta 2020; 219:121266. [PMID: 32887157 DOI: 10.1016/j.talanta.2020.121266] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 06/02/2020] [Accepted: 06/03/2020] [Indexed: 10/24/2022]
Abstract
In Reversed-Phase Liquid Chromatography, Quantitative Structure-Retention Relationship (QSRR) models for retention prediction of peptides can be built, starting from large sets of theoretical molecular descriptors. Good predictive QSRR models can be obtained after selecting the most informative descriptors. Reliable retention prediction may be an aid in the correct identification of proteins/peptides in proteomics and in chromatographic method development. Traditionally, global QSRR models are built, using a calibration set containing a representative range of analytes. In this study, a strategy is presented to build individual local Partial Least Squares (PLS) models for peptides, based on selected local calibration samples, most similar to the specific query peptide to be predicted. Similar local calibration peptides are selected from a possible calibration set. The calibration samples with the lowest Euclidian distances to the query peptide are considered as most similar. Two Euclidian distances are investigated as similarity parameter, (i) in the autoscaled descriptor space and, (ii) in the PLS factor space of the global calibration samples, both after variable selection by the Final Complexity Adapted Models (FCAM) method. The predictive abilities of individual local QSRR PLS models for peptides, developed with both Euclidian distances, are found significantly better than those of two global models, i.e. before and after FCAM variable selection. The predictive abilities of the local models, developed with distances calculated in the PLS factor space, were best.
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Affiliation(s)
- Jan P M Andries
- Research Group Analysis Techniques in the Life Sciences, Avans Hogeschool, University of Professional Education, P.O. Box 90116, 4800, RA Breda, the Netherlands.
| | - Mohammad Goodarzi
- Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX, 75390, United States
| | - Yvan Vander Heyden
- Department of Analytical Chemistry, Applied Chemometrics and Molecular Modelling (FABI), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, B-1090, Brussels, Belgium
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Examination of Dimension Reduction Performances of PLSR and PCR Techniques in Data with Multicollinearity. IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY, TRANSACTIONS A: SCIENCE 2018. [DOI: 10.1007/s40995-018-0565-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Zisi C, Sampsonidis I, Fasoula S, Papachristos K, Witting M, Gika HG, Nikitas P, Pappa-Louisi A. QSRR Modeling for Metabolite Standards Analyzed by Two Different Chromatographic Columns Using Multiple Linear Regression. Metabolites 2017; 7:metabo7010007. [PMID: 28208794 PMCID: PMC5372210 DOI: 10.3390/metabo7010007] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Accepted: 02/05/2017] [Indexed: 01/07/2023] Open
Abstract
Modified quantitative structure retention relationships (QSRRs) are proposed and applied to describe two retention data sets: A set of 94 metabolites studied by a hydrophilic interaction chromatography system under organic content gradient conditions and a set of tryptophan and its major metabolites analyzed by a reversed-phase chromatographic system under isocratic as well as pH and/or simultaneous pH and organic content gradient conditions. According to the proposed modification, an additional descriptor is added to a conventional QSRR expression, which is the analyte retention time, tR(R), measured under the same elution conditions, but in a second chromatographic column considered as a reference one. The 94 metabolites were studied on an Amide column using a Bare Silica column as a reference. For the second dataset, a Kinetex EVO C18 and a Gemini-NX column were used, where each of them was served as a reference column of the other. We found in all cases a significant improvement of the performance of the QSRR models when the descriptor tR(R) was considered.
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Affiliation(s)
- Chrysostomi Zisi
- Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (S.F.); (K.P.); (P.N.); (A.P.-L.)
- Correspondence: ; Tel.: +30-231-099-7765
| | - Ioannis Sampsonidis
- Infrastructure and Environment Research Division, School of Engineering, University of Glasgow, Rankine Building, Oakfield Avenue, Glasgow G12 8LT, UK;
| | - Stella Fasoula
- Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (S.F.); (K.P.); (P.N.); (A.P.-L.)
| | - Konstantinos Papachristos
- Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (S.F.); (K.P.); (P.N.); (A.P.-L.)
| | - Michael Witting
- Helmholtz Zentrum München, Research Unit Analytical BioGeoChemistry, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany;
| | - Helen G. Gika
- Department of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Panagiotis Nikitas
- Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (S.F.); (K.P.); (P.N.); (A.P.-L.)
| | - Adriani Pappa-Louisi
- Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (S.F.); (K.P.); (P.N.); (A.P.-L.)
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Barfeii H, Garkani-Nejad Z. A Comparative QSRR Study on Enantioseparation of Ethanol Ester Enantiomers in HPLC Using Multivariate Image Analysis, Quantum Mechanical and Structural Descriptors. J CHIN CHEM SOC-TAIP 2016. [DOI: 10.1002/jccs.201600253] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Hamideh Barfeii
- Chemistry Department, Faculty of Science; Shahid Bahonar University of Kerman; Kerman, 7616914111 Iran
| | - Zahra Garkani-Nejad
- Chemistry Department, Faculty of Science; Shahid Bahonar University of Kerman; Kerman, 7616914111 Iran
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Žuvela P, Liu JJ, Macur K, Bączek T. Molecular Descriptor Subset Selection in Theoretical Peptide Quantitative Structure–Retention Relationship Model Development Using Nature-Inspired Optimization Algorithms. Anal Chem 2015; 87:9876-83. [DOI: 10.1021/acs.analchem.5b02349] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Petar Žuvela
- Department
of Chemical Engineering, Pukyong National University, 365 Sinseon-ro, 608-739 Busan, Korea
| | - J. Jay Liu
- Department
of Chemical Engineering, Pukyong National University, 365 Sinseon-ro, 608-739 Busan, Korea
| | - Katarzyna Macur
- Laboratory
of Mass Spectrometry, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Kładki
24, 80-822 Gdańsk, Poland
| | - Tomasz Bączek
- Department
of Pharmaceutical Chemistry, Medical University of Gdańsk, Hallera
107, 80-416 Gdańsk, Poland
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Fatemi MH, Malekzadeh H. CORAL: predictions of retention indices of volatiles in cooking rice using representation of the molecular structure obtained by combination of SMILES and graph approaches. JOURNAL OF THE IRANIAN CHEMICAL SOCIETY 2014. [DOI: 10.1007/s13738-014-0497-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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8
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Development of Gradient Retention Model in Ion Chromatography. Part II: Artificial Intelligence QSRR Approach. Chromatographia 2014. [DOI: 10.1007/s10337-014-2654-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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D'Hondt M, Gevaert B, Stalmans S, Van Dorpe S, Wynendaele E, Peremans K, Burvenich C, De Spiegeleer B. Reversed-phase fused-core HPLC modeling of peptides. J Pharm Anal 2012; 3:93-101. [PMID: 29403802 PMCID: PMC5760978 DOI: 10.1016/j.jpha.2012.11.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2012] [Accepted: 11/20/2012] [Indexed: 11/17/2022] Open
Abstract
Different fused-core stationary phase chemistries (C18, Amide, Phenyl-hexyl and Peptide ES-C18) were used for the analysis of 21 structurally representative model peptides. In addition, the effects of the mobile phase composition (ACN or MeOH as organic modifier; formic acid or acetic acid, as acidifying component) on the column selectivity, peak shape and overall chromatographic performance were evaluated. The RP-amide column, combined with a formic acid–acetonitrile based gradient system, performed as best. A peptide reversed-phase retention model is proposed, consisting of 5 variables: log SumAA, log Sv, clog P, log nHDon and log nHAcc. Quantitative structure-retention relationship (QSRR) models were constructed for 16 different chromatographic systems. The accuracy of this peptide retention model was demonstrated by the comparison between predicted and experimentally obtained retention times, explaining on average 86% of the variability. Moreover, using an external set of 5 validation peptides, the predictive power of the model was also demonstrated. This peptide retention model includes the novel in-silico calculated amino acid descriptor, AA, which was calculated from log P, 3D-MoRSE, RDF and WHIM descriptors.
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Affiliation(s)
- Matthias D'Hondt
- Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium
| | - Bert Gevaert
- Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium
| | - Sofie Stalmans
- Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium
| | - Sylvia Van Dorpe
- Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium
| | - Evelien Wynendaele
- Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium
| | - Kathelijne Peremans
- Departments of Medical Imaging and Physiology, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, B9820 Merelbeke, Belgium
| | - Christian Burvenich
- Departments of Medical Imaging and Physiology, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, B9820 Merelbeke, Belgium
| | - Bart De Spiegeleer
- Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium
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Durcekova T, Boronova K, Mocak J, Lehotay J, Cizmarik J. QSRR models for potential local anaesthetic drugs using high performance liquid chromatography. J Pharm Biomed Anal 2012; 59:209-16. [DOI: 10.1016/j.jpba.2011.09.035] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2011] [Revised: 09/27/2011] [Accepted: 09/29/2011] [Indexed: 11/24/2022]
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11
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Zhao W, Liang G, Chen Y, Yang L. A new quantitative structure-retention relationship model for predicting chromatographic retention time of oligonucleotides. Sci China Chem 2011. [DOI: 10.1007/s11426-011-4299-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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12
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Correctness of protein identifications of Bacillus subtilis proteome with the indication on potential false positive peptides supported by predictions of their retention times. J Biomed Biotechnol 2009; 2010:718142. [PMID: 20069061 PMCID: PMC2801521 DOI: 10.1155/2010/718142] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2009] [Accepted: 09/24/2009] [Indexed: 01/11/2023] Open
Abstract
The predictive capability of the retention time prediction model based on quantitative structure-retention relationships (QSRR) was tested. QSRR model was derived with the use of set of peptides identified with the highest scores and originated from 8 known proteins annotated as model ones. The predictive ability of the QSRR model was verified with the use of a Bacillus subtilis proteome digest after separation and identification of the peptides by LC-ESI-MS/MS. That ability was tested with three sets of testing peptides assigned to the proteins identified with different levels of confidence. First, the set of peptides identified with the highest scores achieved in the search were considered. Hence, proteins identified on the basis of more than one peptide were taken into account. Furthermore, proteins identified on the basis of just one peptide were also considered and, depending on the possessed scores, both above and below the assumed threshold, were analyzed in two separated sets. The QSRR approach was applied as the additional constraint in proteomic research verifying results of MS/MS ion search and confirming the correctness of the peptides identifications along with the indication of the potential false positives.
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