Tripeptide Aggregation Prediction via Hydrophilicity Adjustment
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Solution Overview
Problem
Current methods for predicting the self-assembly behavior of short peptides, such as tripeptides, are limited by the need for serendipitous discovery and lack of amphiphilicity, which restricts their aqueous solubility and applications, and existing virtual screening techniques are not practical for screening all possible tripeptide combinations for aggregation propensity.
Innovation Solution
Development of an improved virtual screening method that uses a hydrophilicity-adjusted measure of aggregation propensity (APH) to identify tripeptides with high aggregation potential, allowing for the selection of peptides that form aggregates and potentially gelate, and the method can account for pH effects on peptide aggregation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional aggregation propensity measures are used to screen tripeptides, then hydrophobic sequences can be identified that form aggregates, but the peptides lack amphiphilicity required for gelation and have limited aqueous solubility
Solution Approach 1:
The patent modifies the aggregation propensity calculation by introducing a hydrophilicity adjustment factor. The APH score is calculated as APH = AP × (1 - logP), where AP is the original aggregation propensity and logP represents hydrophilicity. This parameter change transforms the screening criterion to simultaneously favor both aggregation-prone and sufficiently hydrophilic sequences, resolving the contradiction between aggregation ability and amphiphilicity requirements for gelation.
2Measurement precision
If all 8000 tripeptide combinations are synthesized and tested experimentally to screen for aggregation propensity, then comprehensive data can be obtained, but the process is impractical due to time and resource constraints
Solution Approach 1:
The patent employs computational modeling to create virtual copies of all 8000 tripeptide sequences. Instead of synthesizing and testing each peptide experimentally, the aggregation propensity is calculated in silico using the APH metric. This copying approach allows comprehensive screening of the entire tripeptide space without the time and resource costs of experimental synthesis, dramatically improving productivity while maintaining measurement precision through systematic computational evaluation.
3Reliability
If hydrophobic tripeptides are selected based on high aggregation propensity, then aggregates can be formed, but the peptides have poor aqueous solubility and limited biological applications
Solution Approach 1:
The patent changes the selection parameter from pure aggregation propensity (AP) to hydrophilicity-adjusted aggregation propensity (APH). By incorporating the logP term that represents hydrophilicity, the screening criterion is modified to APH = AP × (1 - logP). This ensures that only peptides with sufficient hydrophilicity are selected, even if they have high aggregation propensity. The result is peptides that can form aggregates while maintaining adequate aqueous solubility for biological applications.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the identification of tripeptides with high aggregation propensity, including those that form hydrogels, and demonstrates the ability to predict self-assembly behaviors, expanding the scope of peptide applications in biological, medical, and nanotechnology fields.
Implementation Method 1
Peptides with the ability to spontaneously assemble into nanostructures of defined size, shape and chemical functionality
Implementation Method 2
largely limited to hydrophobic sequences, which form (nanoscale) aggregates
Implementation Method 3
adjusting a measure of propensity of aggregation (AP) for the peptide in dependence on a measure of hydrophilicity for the peptide
Implementation Method 4
The screening method may be expanded to take account of how other parameters, such a pH, may affect peptide aggregation
Data Source
Figure 1a~1b
Figure 2a
Figure 2b
AI summary
The present invention relates to a method of predicting the propensity of tripeptides to from aggregates in solution. The present invention also provides tripeptides which are able to form aggregates in solution, as well as uses thereof. The present invention also provides nanostructures formed by self-aggregation of tripeptides of the present invention. The present invention also provides pH responsive aggregates as well as methods of screening for the ability of a tripeptide to form a pH dependent aggregate or gel.