Discovering Plastic-Binding Peptides with Favorable Affinity, Water Solubility, and Binding Specificity Through Deep
Tianhong Tan1, Michael Bergman2, Carol K Hall2
1Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14853, USA.
Biorxiv : the Preprint Server for Biology
|April 10, 2026
Summary
Scientists developed artificial intelligence and biophysics methods to discover plastic-binding peptides (PBPs) for microplastic (MP) remediation. These novel PBPs show high affinity, solubility, and specificity, offering a promising solution for environmental cleanup.
Area of Science:
- Environmental Science
- Biotechnology
- Computational Chemistry
Background:
- Microplastic (MP) pollution poses significant environmental and health risks.
- Effective MP detection and capture methods are crucial for mitigation.
- Existing plastic-binding peptides (PBPs) lack desired properties like high solubility and specificity.
Purpose of the Study:
- To discover novel short linear PBPs with high affinity, water solubility, and binding specificity for MP remediation.
- To develop an in-silico pipeline combining deep learning and biophysical modeling for PBP discovery.
- To address the scarcity of suitable PBPs for common plastics like polyethylene and polystyrene.
Main Methods:
- Trained a long short-term memory (LSTM) network on biophysical modeling data to predict peptide-plastic affinity.
- Utilized a Monte Carlo tree search (MCTS) algorithm paired with LSTM for high-affinity peptide generation.
- Incorporated CamSol solubility scores and competitive MCTS for enhanced solubility and plastic-specific binding.
Main Results:
- Discovered PBPs for polyethylene with 15% lower binding free energy compared to traditional methods.
- Increased average peptide solubility score from 0.2 to 0.9 while maintaining high affinity.
- Identified PBPs with high binding specificity for polystyrene and polyethylene using competitive MCTS.
Conclusions:
- The AI-biophysics framework successfully discovered high-affinity PBPs with desirable properties for MP remediation.
- These novel PBPs offer a valuable tool for mitigating microplastic pollution.
- The developed framework is adaptable for designing PBPs targeting other plastic types.
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