December 21, 2020
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Feasibility of Estimating Retention Time of Unmodified Peptides
Repeated results can be obtained using liquid chromatography.Under the same experimental conditions, with the exception of minor changes between each test, the same peptide was eluted approximately simultaneously when the sample was reanalyzed.
The consistency of separation time indicates that the peptides participate in a clear interaction during the separation process, which depends solely on the experimental apparatus used and the nature of the peptide itself (Gutuo biological experiments show that repetitive effects can only occur in similar experiments and cannot be extended to other experimental conditions and instruments).
The nature of the peptide segment is closely related to the amino acid sequence, therefore, under certain chromatographic conditions, the retention time estimation of the peptide should provide all the information needed for the sequence retention time.
Reproducibility of peptide retention time
But in reality, this prediction model is not as direct as it seems.For example, an important part of this model is the three-dimensional structure of the peptide.
Although the current structure prediction methods are very accurate for the three-dimensional conformation prediction of short chain of amino acids, this method cannot flexibly simulate various conditions of chromatographic experiments.
Many peptides change their certainty due to the number of organic solvents in the mobile phase, which may be important for the storage time of each peptide.
So most of the chromatographic processes regard the peptide retention time as a black box.
Based on these observations, different retention time estimation methods are proposed.One of these methods is index-based.The main ideas behind this approach are shown in the figure.
Shelf life estimation method
An index-based approach to retention period estimation.
Index-based prediction method is used to evaluate the effect of amino acid sequence on peptide retention time.The individual contribution of an amino acid is often referred to as the retention coefficient, which consists of a set of retention coefficients.
As long as the retention rate of a given chromatographic system is obtained, the retention period of the peptide can be obtained by a simple calculation of the retention rate of the constituent amino acids.
One way to implement this idea is to use a set of 25 short peptides to calculate the retention coefficients of each amino acid and terminal group in the sequence and to calculate their retention times.
Iterative regression was used to calculate the coefficients, and only the amino acid composition of the peptides was used to estimate the coefficients without knowing the position of each amino acid in the sequence.
However, because recombinant versions of the same peptide sequence have been separated on RPLC columns, Gutuo Biologics suggests that other parameters are needed to predict longer peptide retention times.
Indeed, later studies have shown that even short peptides have different retention rates when amino acids are located at different positions in the sequence.
In that case, Gutuo biologically infers that each position in the peptide sequence requires a different retention coefficient.Although the exact chemical mechanism underlying this observation has not been fully understood, many studies have identified individual factors that affect the retention coefficients of amino acids.
For example, the retention of amino acids is influenced by the overall hydrophobicity of the peptide, the number of positive charges, or the presence of secondary structural elements.
In addition, changes in chromatographic settings, such as changes in mobile phase or stationary phase composition, can also change the way peptides are eluted.
Current studies have shown that interactions involving helical structures are very complex and a complex model is needed to consider the effect of such interactions on the retention time of peptides.
A limitation of index-based methods is that they optimize estimated retention times for specific chromatographic settings.
Therefore, the experimental conditions are different from those set in the optimization algorithm, and their predictive ability is reduced.
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