Creating a High-Throughput Workflow for Automated Peptide Characterization using LC-MS
(2023) KASM01 20231Centre for Analysis and Synthesis
- Abstract
- In the early stage of a drug discovery project, there is a need for efficient methods that can analyse peptides in short time. This includes methods that confirm the peptide’s identity and estimates its relative purity in an efficient and reliable way. The aim was to create a workflow for peptide characterization for AstraZeneca’s in-house peptides that was applicable for a high-throughput analysis. The approach was to develop and optimise an LC-MS method based on 20 therapeutic peptides considering stationary phase, gradient of mobile phase and flow rate. Also, to evaluate different peptide descriptors to see if they could be used to predict the suitability of a peptide for this workflow and to consider the usefulness and different... (More)
- In the early stage of a drug discovery project, there is a need for efficient methods that can analyse peptides in short time. This includes methods that confirm the peptide’s identity and estimates its relative purity in an efficient and reliable way. The aim was to create a workflow for peptide characterization for AstraZeneca’s in-house peptides that was applicable for a high-throughput analysis. The approach was to develop and optimise an LC-MS method based on 20 therapeutic peptides considering stationary phase, gradient of mobile phase and flow rate. Also, to evaluate different peptide descriptors to see if they could be used to predict the suitability of a peptide for this workflow and to consider the usefulness and different features of software for processing of raw data. The result was that an LC-MS method with an acquisition time of 5 minutes was developed. The method comprised a CSH column (1.7 µm, 2.1 x 50 mm), 0.5 mL/minute flow rate and gradient time of 3.5 minutes (slope 14%B/minutes). The descriptors ClogKD and aqueous solubility were useful to predict if this method was applicable for the peptides in question. Three software for processing of raw data was considered and the software Waters Connect with its application Intact Mass was chosen. Intact Mass can deconvolve the neutral mass, yield a purity as a combined UV and mass spectral purity (UVxMS) and perform a simple impurity profiling. In conclusion, an LC-MS method adapted for a high-throughput workflow was accomplished that succeeded to obtain adequate results regarding retention time and separation of potential impurities for a range of peptides. Furthermore, descriptors turned out to be useful for predicting suitability of this workflow and an appropriate software could be applied for processing of raw data. (Less)
- Popular Abstract
- At the early stage of a drug discovery project, several hundreds of compounds are of interest to be profiled for the upcoming steps. At this stage it is crucial to have analysis techniques that can characterize the compounds with high quality. In this case, it means to confirm the compound’s identity and relative purity, to be sure the results are reliable. When considering analysis of a large number of compounds in a short time, it is called high-throughput analysis.
This degree project was performed at the pharmaceutical company AstraZeneca in Gothenburg. The application is in line with AstraZeneca’s research interest. The overall aim was to develop an analytical workflow that could be applied for a high-throughput analysis of a... (More) - At the early stage of a drug discovery project, several hundreds of compounds are of interest to be profiled for the upcoming steps. At this stage it is crucial to have analysis techniques that can characterize the compounds with high quality. In this case, it means to confirm the compound’s identity and relative purity, to be sure the results are reliable. When considering analysis of a large number of compounds in a short time, it is called high-throughput analysis.
This degree project was performed at the pharmaceutical company AstraZeneca in Gothenburg. The application is in line with AstraZeneca’s research interest. The overall aim was to develop an analytical workflow that could be applied for a high-throughput analysis of a class of molecules called peptides. This was achieved by using the analysis technique liquid chromatography connected to mass spectrometry (LC-MS). From liquid chromatography, estimations of relative purity could be obtained and from mass spectrometry confirmation of the peptides’ identity. The reason for a high-throughput workflow is to save solvent and energy during the analysis, save time for the user (shorter runs), and it has more user-friendly manual processing for non-experts to perform the characterization. One key success factor was to obtain a shorter run time, but to still get high-quality results.
During the experimental work, 20 peptides of different sizes and chemical properties were investigated. Initially, they needed to be dissolved to be able to run them on the LC-MS instrument. Then, experiments were performed on the LC-MS. A workflow was developed and then it was optimized. Different analysis parameters were investigated, for example the gradient of mobile phases and flow rate. Additionally, different software for processing of raw data from the workflow were considered. This to find the most suitable one to be used in the workflow that would make it easier to automatically perform processing and reporting of data.
As result, it was seen that a shorter method in runtime of instrument could be applied on a range of peptides and gave a good separation of the peptides and impurities. This was obtained by using a CSH column of 50 mm, flow rate of 0.5 mL/min and a gradient time of 3.5 min with the interval of either 10-60% or 5-55%. To know if this workflow will be suitable for a peptide of interest, limits was set up based on the peptide’s lipophilicity, which means tendency to be in an organic phase instead of an aqueous phase. These limits had to be drawn depending on the peptide’s ion class (base, neutral or zwitterion). As for processing of raw data the application Intact Mass was chosen due to having good opportunities of estimating a combined absorbance and mass spectral purity with high quality. Also, because it can sort out complex spectra with many masses from different peptides.
In conclusion, a more high-throughput friendly workflow for peptide characterization has been developed that can be applied on a range of peptides. Properties of peptides that describes lipophilicity can be used to predict whether this workflow is suitable or not. The application Intact Mass was chosen for processing of raw data since it can estimate a combined relative purity and potential impurities. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9130389
- author
- Forsberg, Sara LU
- supervisor
- organization
- course
- KASM01 20231
- year
- 2023
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- High-throughput analysis, Impurity profiling, UHPLC-HRMS, Peptide characterization, Peptide descriptors, Analytical chemistry
- language
- English
- id
- 9130389
- date added to LUP
- 2023-06-28 10:30:02
- date last changed
- 2023-06-28 10:30:02
@misc{9130389,
abstract = {{In the early stage of a drug discovery project, there is a need for efficient methods that can analyse peptides in short time. This includes methods that confirm the peptide’s identity and estimates its relative purity in an efficient and reliable way. The aim was to create a workflow for peptide characterization for AstraZeneca’s in-house peptides that was applicable for a high-throughput analysis. The approach was to develop and optimise an LC-MS method based on 20 therapeutic peptides considering stationary phase, gradient of mobile phase and flow rate. Also, to evaluate different peptide descriptors to see if they could be used to predict the suitability of a peptide for this workflow and to consider the usefulness and different features of software for processing of raw data. The result was that an LC-MS method with an acquisition time of 5 minutes was developed. The method comprised a CSH column (1.7 µm, 2.1 x 50 mm), 0.5 mL/minute flow rate and gradient time of 3.5 minutes (slope 14%B/minutes). The descriptors ClogKD and aqueous solubility were useful to predict if this method was applicable for the peptides in question. Three software for processing of raw data was considered and the software Waters Connect with its application Intact Mass was chosen. Intact Mass can deconvolve the neutral mass, yield a purity as a combined UV and mass spectral purity (UVxMS) and perform a simple impurity profiling. In conclusion, an LC-MS method adapted for a high-throughput workflow was accomplished that succeeded to obtain adequate results regarding retention time and separation of potential impurities for a range of peptides. Furthermore, descriptors turned out to be useful for predicting suitability of this workflow and an appropriate software could be applied for processing of raw data.}},
author = {{Forsberg, Sara}},
language = {{eng}},
note = {{Student Paper}},
title = {{Creating a High-Throughput Workflow for Automated Peptide Characterization using LC-MS}},
year = {{2023}},
}