Approaches towards the automated interpretation and prediction of ES-MS/MS spectra of non-peptidic, pharmaceutical, combinatorial compounds
Approaches towards the automated interpretation and prediction of ES-MS/MS spectra of non-peptidic, pharmaceutical, combinatorial compounds
Electrospray tandem mass spectrometry is currently widely used in protein sequencing. The knowledge of the dissociation trends of peptides molecules allows detailed identification of the amino acid residues and to a certain extent successful characterisation of unknown peptidic compounds. The process of protein identification is frequently aided by interpretive A1 software packages that offer fast and simple ways for manipulating the ES-MS/MS data.
Identification of non-peptide molecules using a similar automated approach is, at the moment, a challenge. The dissociation pathways of non-peptidic compounds vary for each class of molecules and general rules have not been established. The isonisation and fragmentation mechanisms taking place under ES-MS/MS conditions have also not been identified and therefore electron ionisation rules are often employed by the A1 packages in order to overcome this problem. This approach leads to a very low success rate when it comes to identifying an unknown non-peptide molecule from its ES-MS/MS spectrum.
The aim of this investigation was to develop existing interpretive software packages such that they take account of the specific fragmentation pathways and mechanisms involved in ES-MS/MS. Sub-libraries of non-peptidic, combinatorial molecules were studied and specific rules for their dissociation were established. This allowed pattern recognition methods to be used. Throughout this work, detailed mechanisms and fragmentation pathways together with the sites of ionisation have been investigated. Incorporation of the findings into an A1 software package should enable the rapid characterisation of the components of combinatorial libraries using ES-MS/MS only.
University of Southampton
Klagkou, Aikaterini Maria
054df800-0ed2-471b-a3b5-854b4d902f7c
2003
Klagkou, Aikaterini Maria
054df800-0ed2-471b-a3b5-854b4d902f7c
Klagkou, Aikaterini Maria
(2003)
Approaches towards the automated interpretation and prediction of ES-MS/MS spectra of non-peptidic, pharmaceutical, combinatorial compounds.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
Electrospray tandem mass spectrometry is currently widely used in protein sequencing. The knowledge of the dissociation trends of peptides molecules allows detailed identification of the amino acid residues and to a certain extent successful characterisation of unknown peptidic compounds. The process of protein identification is frequently aided by interpretive A1 software packages that offer fast and simple ways for manipulating the ES-MS/MS data.
Identification of non-peptide molecules using a similar automated approach is, at the moment, a challenge. The dissociation pathways of non-peptidic compounds vary for each class of molecules and general rules have not been established. The isonisation and fragmentation mechanisms taking place under ES-MS/MS conditions have also not been identified and therefore electron ionisation rules are often employed by the A1 packages in order to overcome this problem. This approach leads to a very low success rate when it comes to identifying an unknown non-peptide molecule from its ES-MS/MS spectrum.
The aim of this investigation was to develop existing interpretive software packages such that they take account of the specific fragmentation pathways and mechanisms involved in ES-MS/MS. Sub-libraries of non-peptidic, combinatorial molecules were studied and specific rules for their dissociation were established. This allowed pattern recognition methods to be used. Throughout this work, detailed mechanisms and fragmentation pathways together with the sites of ionisation have been investigated. Incorporation of the findings into an A1 software package should enable the rapid characterisation of the components of combinatorial libraries using ES-MS/MS only.
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Published date: 2003
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Local EPrints ID: 465167
URI: http://eprints.soton.ac.uk/id/eprint/465167
PURE UUID: 72b0fbdd-e442-49b9-aab6-6dca5b83eb0c
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Date deposited: 05 Jul 2022 00:27
Last modified: 16 Mar 2024 19:59
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Author:
Aikaterini Maria Klagkou
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