Digging Deep into the Sequence Space of Electrochemical Debonding of Peptides to Impact Next Generation Polymer Adhesives
Sector: Chemical (Industrial) • Location: Germany
Source: EU Funding & Tenders Portal
Generating novel polymer functions based on rational design criteria, derived from deep statistical analysis of massive experimental data sets, would fundamentally impact materials development and represent the next evolutionary step in macromolecular engineering. The IDefix project establishes a generic information-based design strategy to define polymer–surface interactions that represent the ke
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | forthcoming |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
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Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | Generating novel polymer functions based on rational design criteria, derived from deep statistical analysis of massive experimental data sets, would fundamentally impact materials development and represent the next evolutionary step in macromolecular engineering. The IDefix project establishes a generic information-based design strategy to define polymer–surface interactions that represent the key property in various applications. The project focuses on advancing adhesives, to facilitate material-specific adsorption and triggerable desorption by distinct electrochemical transformations. The rationale of engineering such polymers is extracted from peptide phage display (PD) biopanning with an advanced selection scenario and using next-generation sequencing (NGS). This allows to screen 10^9 sequences and readout of 10^6, providing the data sets to feed machine learning (ML) tools. A new software tool “SurPhage” is developed and tailored to the material-oriented biopanning. Leveraging ML concepts, sequence data interpretation and feature abstraction are combined with sequence-function data of a broad analysis pipeline to learn on the rationale that feeds generative models for in-silico design. The underlying chemistry relies on peptides with L-3,4-Dihydroxyphenylalanin (Dopa)-residues that show potent catechol anchors and a unique debonding mechanism on quinone oxidation. However, the strategy enables to identify hidden champions and discover novel Dopa-free mechanisms. Employing the design rationale an IDefix platform is developed, covering polymers from artificial adhesive proteins to copolymers. These enable the electrochemical manipulation of adhesives, coatings or membranes, facilitating applications of debonding on command or dimming of permeability. Combining IDefix materials with piezoelectric elements leads to self-reinforcing mechano-responsive composites and integrating in near-field communication devices enables remote controlled drug release patches. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
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Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
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Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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