Screening Of Peptide Libraries Research Articles

Electron-rich anilines as cleavable linkers for peptides.

We report the development of a new electron-rich aniline (ERA)-based cleavable linker. Anilines can be incorporated into peptides during SPPS and are stable to most reaction conditions. ERA-containing peptides can be cleaved rapidly in the presence of oxidants, such as DDQ, CAN, and NaIO4, in 30min at room temperature. The compatibility of these conditions is demonstrated on peptides containing natural and unnatural amino acids. While the cleavages of other oxidatively labile linkers is known to cause decomposition of Tyr and Trp, these sensitive residues are stable to DDQ oxidations. An ERA-linker also enables the capture and release of a biotinylated peptide from immobilized streptavidin. ERA-linkers may serve as an excellent tool for peptide library screening applications.

Discovery of Selective Cyclic d-Sulfopeptide Ligands of the Chemokine CCL22 via Mirror-Image mRNA Display with Genetic Reprogramming.

Chemokines are small proteins involved in recruiting leukocytes to sites of inflammation via interactions with specific cell surface receptors. CCL22 is a chemokine known to play a critical role in inflammatory diseases such as atopic dermatitis and asthma; inhibition of this chemokine therefore represents an attractive therapeutic strategy. Herein, we describe the discovery of cyclic d-sulfopeptide inhibitors of CCL22 identified through mirror-image mRNA display with genetic reprogramming. Chemical synthesis of mirror-image d-CCL22 enabled screening of a cyclic peptide library comprised of all l-amino acids, with reprogramming of l-sulfotyrosine to mimic the presence of this post-translational modification on native chemokine receptors. Enriched macrocyclic peptides were prepared in their mirror-image d-form and assessed for binding against native l-CCL22. The most potent ligand, a plasma-stable d-cyclic peptide bearing four d-sulfotyrosine residues, exhibited nanomolar affinity for CCL22, high selectivity over other chemokines, and nanomolar inhibition of CCL22 signaling through CCR4. This work highlights the vast potential of mirror-image mRNA display technology for discovering proteolytically stable d-peptide inhibitors of protein-protein interactions relevant across a range of therapeutic indications.

HLA A*24:02-restricted T cell receptors cross-recognize bacterial and preproinsulin peptides in type 1 diabetes.

CD8+ T cells destroy insulin-producing pancreatic β cells in type 1 diabetes through HLA class I-restricted presentation of self-antigens. Combinatorial peptide library screening was used to produce a preferred peptide recognition landscape for a patient-derived T cell receptor (TCR) that recognized the preproinsulin-derived (PPI-derived) peptide sequence LWMRLLPLL in the context of disease risk allele HLA A*24:02. Data were used to generate a strong superagonist peptide, enabling production of an autoimmune HLA A*24:02-peptide-TCR structure by crystal seeding. TCR binding to the PPI epitope was strongly focused on peptide residues Arg4 and Leu5, with more flexibility at other positions, allowing the TCR to strongly engage many peptides derived from pathogenic bacteria. We confirmed an epitope from Klebsiella that was recognized by PPI-reactive T cells from 3 of 3 HLA A*24:02+ patients. Remarkably, the same epitope selected T cells from 7 of 8 HLA A*24+ healthy donors that cross-reacted with PPI, leading to recognition and killing of HLA A*24:02+ cells expressing PPI. These data provide a mechanism by which molecular mimicry between pathogen and self-antigens could have resulted in the breaking of self-tolerance to initiate disease.

Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.

Peptide-based drug discovery has surged with the development of peptide hormone-derived analogs for the treatment of diabetes and obesity. Machine learning (ML)-enabled quantitative structure-activity relationship (QSAR) approaches have shown great promise in small molecule drug discovery but have been less successful in peptide drug discovery due to limited data availability. We have developed a peptide drug discovery platform called streaMLine, enabling rigorous design, synthesis, screening, and ML-driven analysis of large peptide libraries. Using streaMLine, this study systematically explored secretin as a peptide backbone to generate potent, selective, and long-acting GLP-1R agonists with improved physicochemical properties. We synthesized and screened a total of 2688 peptides and applied ML-guided QSAR to identify multiple options for designing stable and potent GLP-1R agonists. One candidate, GUB021794, was profiled in vivo (S.C., 10 nmol/kg QD) and showed potent body weight loss in diet-induced obese mice and a half-life compatible with once-weekly dosing.

Optimization of quenched fluorescent peptide substrates of SARS-CoV-2 3CLpro main protease (Mpro) from proteomic identification of P6-P6' active site specificity.

SARS-CoV-2 3C-like main protease (3CLpro) is essential for protein excision from the viral polyprotein. 3CLpro inhibitor drug development to block SARS-CoV-2 replication focuses on the catalytic non-prime (P) side for specificity and potency, but the importance of the prime (P') side in substrate specificity and for drug development remains underappreciated. We determined the P6-P6' specificity for 3CLpro from >800 cleavage sites that we identified using Proteomic Identification of Cleavage site Specificity (PICS). Cleavage occurred after the canonical P1-Gln and non-canonical P1-His and P1-Met residues. Moreover, P3 showed a preference for Arg/Lys and P3' for His. Essential H-bonds between the N-terminal Ser1 of protomer-B in 3CLpro dimers form with P1-His, but not with P1-Met. Nonetheless, cleavage occurs at P1-Met456 in native MAP4K5. Elevated reactive oxygen species in SARS-CoV-2 infection oxidize methionines. Molecular simulations revealed P1-MetOX forms an H-bond with Ser1 and notably, strong positive cooperativity between P1-Met with P3'-His was revealed, which enhanced peptide-cleavage rates. The highly plastic S3' subsite accommodates P3'-His that displays stabilizing backbone H-bonds with Thr25 lying central in a "'threonine trio" (Thr24-Thr25-Thr26) in the P'-binding domain I. Molecular docking simulations unveiled structure-activity relationships impacting 3CLpro-substrate interactions, and the role of these structural determinants was confirmed by MALDI-TOF-MS cleavage assays of P1'- and P3'-positional scanning peptide libraries carrying a 2nd optimal cut-site as an internal positive control. These data informed the design of two new and highly soluble 3CLproquenched-fluorescent peptide substrates for improved FRET monitoring of 3CLpro activity with 15× improved sensitivity over current assays.IMPORTANCEFrom global proteomics identification of >800 cleavage sites, we characterized the P6-P6' active site specificity of SARS-CoV-2 3CLpro using proteome-derived peptide library screens, molecular modeling simulations, and focussed positional peptide libraries. In P1', we show that alanine and serine are cleaved 3× faster than glycine and the hydrophobic small amino acids Leu, Ile, or Val prevent cleavage of otherwise optimal non-prime sequences. In characterizing non-canonical non-prime P1 specificity, we explored the unusual P1-Met specificity, discovering enhanced cleavage when in the oxidized state (P1-MetOX). We unveiled unexpected amino acid cooperativity at P1-Met with P3'-His and noncanonical P1-His with P2-Phe, and the importance of the threonine trio (Thr24-Thr25-Thr26) in the prime side binding domain I in defining prime side binding in SARS-CoV-2 3CLpro. From these analyses, we rationally designed quenched-fluorescence natural amino acid peptide substrates with >15× improved sensitivity and high peptide solubility, facilitating handling and application for screening of new antiviral drugs.

Diversification of Phage-Displayed Peptide Libraries with Noncanonical Amino Acid Mutagenesis and Chemical Modification.

Sitting on the interface between biologics and small molecules, peptides represent an emerging class of therapeutics. Numerous techniques have been developed in the past 30 years to take advantage of biological methods to generate and screen peptide libraries for the identification of therapeutic compounds, with phage display being one of the most accessible techniques. Although traditional phage display can generate billions of peptides simultaneously, it is limited to expression of canonical amino acids. Recently, several groups have successfully undergone efforts to apply genetic code expansion to introduce noncanonical amino acids (ncAAs) with novel reactivities and chemistries into phage-displayed peptide libraries. In addition to biological methods, several different chemical approaches have also been used to install noncanonical motifs into phage libraries. This review focuses on these recent advances that have taken advantage of both biological and chemical means for diversification of phage libraries with ncAAs.

A Tag‐Free Platform for Synthesis and Screening of Cyclic Peptide Libraries

AbstractIn the realm of high‐throughput screening (HTS), macrocyclic peptide libraries traditionally necessitate decoding tags, essential for both library synthesis and identifying hit peptide sequences post‐screening. Our innovation introduces a tag‐free technology platform for synthesizing cyclic peptide libraries in solution and facilitates screening against biological targets to identify peptide binders through unconventional intramolecular CyClick and DeClick chemistries (CCDC) discovered through our research. This combination allows for the synthesis of diverse cyclic peptide libraries, the incorporation of various amino acids, and facile linearization and decoding of cyclic peptide binder sequences. Our sensitivity‐enhancing derivatization method, utilized in tandem with nano LC‐MS/MS, enables the sequencing of peptides even at exceedingly low picomolar concentrations. Employing our technology platform, we have successfully unearthed novel cyclic peptide binders against a monoclonal antibody and the first cyclic peptide binder of HIV capsid protein responsible for viral infections as validated by microscale thermal shift assays (TSA), biolayer interferometry (BLI) and functional assays.

A Tag-Free Platform for Synthesis and Screening of Cyclic Peptide Libraries.

In the realm of high-throughput screening (HTS), macrocyclic peptide libraries traditionally necessitate decoding tags, essential for both library synthesis and identifying hit peptide sequences post-screening. Our innovation introduces a tag-free technology platform for synthesizing cyclic peptide libraries in solution and facilitates screening against biological targets to identify peptide binders through unconventional intramolecular CyClick and DeClick chemistries (CCDC) discovered through our research. This combination allows for the synthesis of diverse cyclic peptide libraries, the incorporation of various amino acids, and facile linearization and decoding of cyclic peptide binder sequences. Our sensitivity-enhancing derivatization method, utilized in tandem with nano LC-MS/MS, enables the sequencing of peptides even at exceedingly low picomolar concentrations. Employing our technology platform, we have successfully unearthed novel cyclic peptide binders against a monoclonal antibody and the first cyclic peptide binder of HIV capsid protein responsible for viral infections as validated by microscale thermal shift assays (TSA), biolayer interferometry (BLI) and functional assays.

The physiological interactome of TCR-like antibody therapeutics in human tissues.

Selective binding of TCR-like antibodies that target a single tumour-specific peptide antigen presented by human leukocyte antigens (HLA) is the absolute prerequisite for their therapeutic suitability and patient safety. To date, selectivity assessment has been limited to peptide library screening and predictive modeling. We developed an experimental platform to de novo identify interactomes of TCR-like antibodies directly in human tissues using mass spectrometry. As proof of concept, we confirm the target epitope of a MAGE-A4-specific TCR-like antibody. We further determine cross-reactive peptidesequences for ESK1, a TCR-like antibody with known off-target activity, in human liver tissue. We confirm off-target-induced T cell activation and ESK1-mediated liver spheroid killing. Off-target sequences feature an amino acid motif that allows a structural groove-coordination mimicking that of the target peptide, therefore allowing the interaction with the engager molecule. We conclude that our strategy offers an accurate, scalable route for evaluating the non-clinical safety profile of TCR-like antibody therapeutics prior to first-in-human clinical application.

The Trimeric Autotransporter Adhesin SadA from Salmonella spp. as a Novel Bacterial Surface Display System.

Bacterial surface display platforms have been developed for applications such as vaccine delivery and peptide library screening. The type V secretion system is an attractive anchoring motif for the surface expression of foreign proteins in gram-negative bacteria. SadA belongs to subtype C of the type V secretion system derived from Salmonella spp. and promotes biofilm formation and host cell adherence. The inner membrane lipoprotein SadB is important for SadA translocation. In this study, SadA was used as an anchoring motif to expose heterologous proteins in Salmonella typhimurium using SadB. The ability of SadA to display heterologous proteins on the S. typhimurium surface in the presence of SadB was approximately three-fold higher than that in its absence of SadB. Compared to full-length SadA, truncated SadAs (SadA877 and SadA269) showed similar display capacities when exposing the B-cell epitopes of urease B from Helicobacter pylori (UreB158-172aa and UreB349-363aa). We grafted different protein domains, including mScarlet (red fluorescent protein), the urease B fragment (UreBm) from H. pylori SS1, and/or protective antigen domain 4 from Bacillus anthracis A16R (PAD4), onto SadA877 or SadA1292. Whole-cell dot blotting, immunofluorescence, and flow cytometric analyses confirmed the localization of Flag×3-mScarlet (~30 kDa) and Flag×3-UreBm-mScarlet (~58 kDa) to the S. typhimurium surface using truncated SadA877 or SadA1292 as an anchoring motif. However, Flag×3-UreBm-PAD4-mScarlet (~75 kDa) was displayed on S. typhimurium using SadA1292. The oral administrated pSadBA1292-FUM/StmΔygeAΔmurI and pSadBA877-FUM/StmΔygeAΔmurI could elicit a significant mucosal and humoral immunity response. SadA could thus be used as an anchoring motif for the surface expression of large heterologous proteins as a potential strategy for attenuated bacterial vaccine development.

Identification of a potent PCNA-p15-interaction inhibitor by autodisplay-based peptide library screening.

Proliferating cell nuclear antigen (PCNA) is an essential factor for DNA metabolism. The influence of PCNA on DNA replication and repair, combined with the high expression rate of PCNA in various tumours renders PCNA a promising target for cancer therapy. In this context, an autodisplay-based screening method was developed to identify peptidic PCNA interaction inhibitors. A 12-mer randomized peptide library consisting of 2.54 × 106 colony-forming units was constructed and displayed at the surface of Escherichia coli BL21 (DE3) cells by autodisplay. Cells exhibiting an enhanced binding to fluorescent mScarlet-I-PCNA were enriched in four sorting rounds by flow cytometry. This led to the discovery of five peptide variants with affinity to mScarlet-I-PCNA. Among these, P3 (TCPLRWITHDHP) exhibited the highest binding signal. Subsequent flow cytometric analysis revealed a dissociation constant of 0.62 μM for PCNA-P3 interaction. Furthermore, the inhibition of PCNA interactions was investigated using p15, a PIP-box containing protein involved in DNA replication and repair. P3 inhibited the PCNA-p1551-70 interaction with a half maximal inhibitory activity of 16.2 μM, characterizing P3 as a potent inhibitor of the PCNA-p15 interaction.

KcsA-Kv1.x chimeras with complete ligand-binding sites provide improved predictivity for screening selective Kv1.x blockers

Despite significant advances in the development of therapeutic interventions targeting autoimmune diseases and chronic inflammatory conditions, lack of effective treatment still poses a high unmet need. Modulating chronically activated T cells through the blockade of the Kv1.3 potassium channel is a promising therapeutic approach, however, developing selective Kv1.3 inhibitors is still an arduous task. Phage display-based high throughput peptide library screening is a rapid and robust approach to develop promising drug candidates; however, it requires solid-phase immobilization of target proteins with their binding site preserved. Historically, the KcsA bacterial channel chimera harboring only the turret region of the human Kv1.3 channel was used for screening campaigns. Nevertheless, literature data suggest that binding to this type of chimera does not correlate well with blocking potency on the native Kv1.3 channels. Therefore, we designed and successfully produced advanced KcsA-Kv1.3, -Kv1.1 and -Kv1.2 chimeric proteins in which both the turret and part of the filter regions of the human Kv1.x channels were transferred. These T+F (turret-filter) chimeras showed superior peptide ligand binding predictivity compared to their T-only versions in novel phage ELISA assays. Phage ELISA binding and competition results supported with electrophysiological data confirmed that the filter region of KcsA-Kv1.x is essential for establishing adequate relative affinity order among selected peptide toxins (Vm24 toxin, Hongotoxin-1, Kaliotoxin-1, Maurotoxin, Stichodactyla toxin) and consequently obtaining more reliable selectivity data. These new findings provide a better screening tool for future drug development efforts and offer insight into the target-ligand interactions of these therapeutically relevant ion channels.

Buffalo colostrum peptide mitigates Parkinson's disease pathophysiology through Cullin-3 inhibition

Colostrum/Milk is a chief repertoire of antioxidant peptides. Nuclear factor-erythroid 2 related factor 2 (Nrf2) is a viable target for Parkinson’s Disease (PD), as this pathway deduced to be impaired in PD. Cullin-3 is one of the crucial E3 ligase responsible for its regulation. The present study screened peptide libraries of buffalo colostrum & milk peptides for Cullin-3 inhibition, thus ensuing activation of Nrf2 to alleviate the molecular etiopathology in PD using the C. elegans as a model. The structure was modelled, binding sites analyzed and peptide-interactions analyzed by docking. Among the 55 sequences (≤1 kDa), the peptide SFVSEVPEL having the highest dock score (-16.919) was synthesized and evaluated for its effects on oxidative stress markers, antioxidant enzymes, neurochemical marker and Nrf2/Skn-1 levels. The lead peptide alleviated the oxidative pathophysiology and behavioural deficits associated with PD in C. elegans.

Using explainable machine learning to uncover the kinase-substrate interaction landscape.

Phosphorylation, a post-translational modification regulated by protein kinase enzymes, plays an essential role in almost all cellular processes. Understanding how each of the nearly 500 human protein kinases selectively phosphorylates their substrates is a foundational challenge in bioinformatics and cell signaling. Although deep learning models have been a popular means to predict kinase-substrate relationships, existing models often lack interpretability and are trained on datasets skewed toward a subset of well-studied kinases. Here we leverage recent peptide library datasets generated to determine substrate specificity profiles of 300 serine/threonine kinases to develop an explainable Transformer model for kinase-peptide interaction prediction. The model, trained solely on primary sequences, achieved state-of-the-art performance. Its unique multitask learning paradigm built within the model enables predictions on virtually any kinase-peptide pair, including predictions on 139 kinases not used in peptide library screens. Furthermore, we employed explainable machine learning methods to elucidate the model's inner workings. Through analysis of learned embeddings at different training stages, we demonstrate that the model employs a unique strategy of substrate prediction considering both substrate motif patterns and kinase evolutionary features. SHapley Additive exPlanation (SHAP) analysis reveals key specificity determining residues in the peptide sequence. Finally, we provide a web interface for predicting kinase-substrate associations for user-defined sequences and a resource for visualizing the learned kinase-substrate associations. All code and data are available at https://github.com/esbgkannan/Phosformer-ST. Web server is available at https://phosformer.netlify.app.

Solid-phase peptide synthesis in 384-well plates.

Newer solid-phase peptide synthesis and release strategies enable the production of short peptides with high purity, allowing direct screening for desired bioactivity without prior chromatographic purification. However, the maximum number of peptides that can currently be synthesized per microplate reactor is 96, allowing the parallel synthesis of 384 peptides in modern devices that have space for 4 microplate reactors. To synthesize larger numbers of peptides, we modified a commercially available peptide synthesizer to enable the production of peptides in 384-well plates, which allows the synthesis of 1,536 peptides in one run (4× 384 peptides). We report new hardware components and customized software that allowed for the synthesis of 1,536 short peptides in good quantity (average > 0.5μmol), at high concentration (average > 10 mM), and decent purity without purification (average > 80%). The high-throughput peptide synthesis, which we developed with peptide drug development in mind, may be widely used for peptide library synthesis and screening, antibody epitope scanning, epitope mimetic development, or protease/kinase substrate screening.

Non-immunoglobulin synthetic binding proteins for oncology

Extensive application of technologies like phage display in screening peptide and protein combinatorial libraries has not only facilitated creation of new recombinant antibodies but has also significantly enriched repertoire of the protein binders that have polypeptide scaffolds without homology to immunoglobulins. These innovative synthetic binding protein (SBP) platforms have grown in number and now encompass monobodies/adnectins, DARPins, lipocalins/anticalins, and a variety of miniproteins such as affibodies and knottins, among others. They serve as versatile modules for developing complex affinity tools that hold promise in both diagnostic and therapeutic settings. An optimal scaffold typically has low molecular weight, minimal immunogenicity, and demonstrates resistance against various challenging conditions, including proteolysis - making it potentially suitable for peroral administration. Retaining functionality under reducing intracellular milieu is also advantageous. However, paramount to its functionality is the scaffold’s ability to tolerate mutations across numerous positions, allowing for the formation of a sufficiently large target binding region. This is achieved through the library construction, screening, and subsequent expression in an appropriate system. Scaffolds that exhibit high thermodynamic stability are especially coveted by the developers of new SBPs. These are steadily making their way into clinical settings, notably as antagonists of oncoproteins in signaling pathways. This review surveys the diverse landscape of SBPs, placing particular emphasis on the inhibitors targeting the oncoprotein KRAS, and highlights groundbreaking opportunities for SBPs in oncology.

A library-derived peptide inhibitor of the BZLF1 transcription factor.

Transcription factor dysregulation is associated with many diseases, including cancer. Peptide-based molecules are increasingly recognised as important modulators of difficult intracellular protein-protein interaction targets, with peptide library screening consequently proven to be a viable strategy in developing inhibitors against a wide range of transcription factors (TFs). However, current strategies simply select the highest affinity of binding to a target TF rather than the ability to inhibit TF function. Here, we utilise our Transcription Block Survival (TBS) screening platform to enable high-throughput identification of peptides that inhibit TFs from binding to cognate DNA sites, hence inhibiting functionality. In this study, we explore whether the TBS can be expanded to derive a potent and functional peptide inhibitor of the BZLF1 transcription factor. The library-derived peptide, AcidicW, is shown to form a more stable dimer with BZLF1 than the BZLF1 homodimer, with a thermal denaturation temperature exceeding 80°C. AcidicW can also functionally inhibit the BZLF1:TRE DNA interaction with high potency and an IC50 of 612 nM.

Construction of Nonnatural Cysteine-Cross-Linked Phage Libraries.

Phage display is a powerful technique for rapid construction and screening of peptide libraries with over 109 sequence diversity. The M13 bacteriophage genome can be edited to incorporate randomized amino acids, which will be displayed on its minor coat protein (pIII). To enable screening of nonnatural cyclic peptides on phage, the minor coat protein can be modified with a chemical cross-linker. By taking advantage of the nucleophilicity and low abundance of free cysteines on phage, a variety of cysteine cross-linkers can be installed on the pIII protein. Here, we describe the construction of a chemically modified cyclic phage library through a cysteine cross-linking reagent, 1,3-dichloroacetone (DCA).

Death-associated protein kinase 1 phosphorylates MDM2 and inhibits its protein stability and function.

Breast cancer is one of the major malignancies in women, and most related deaths are due to recurrence, drug resistance, and metastasis. The expression of the mouse double minute 2 (MDM2) oncogene is upregulated in breast cancer; however, its regulatory mechanism has yet to be fully elucidated. Herein, we identified the tumor suppressor death-associated protein kinase 1 (DAPK1) as a novel MDM2 regulator by unbiased peptide library screening. DAPK1 is directly bound to MDM2 and phosphorylates it at Thr419. DAPK1-mediated MDM2 phosphorylation promoted its protein degradation via the ubiquitin-proteasome pathway, resulting in upregulated p53 expression. DAPK1 overexpression, but not its kinase activity-deficient form, decreased colony formation and increased doxorubicin-induced cell death; however, DAPK1 knockdown produced the opposite effects in human breast cancer cells. In a xenograft tumorigenesis assay, DAPK1 overexpression significantly reduced tumor formation, whereas inhibition of DAPK1 kinase activity reduced its antitumorigenic effect. Finally, DAPK1 expression was negatively correlated with MDM2 levels in human breast cancer tissues. Thus, these results suggest that DAPK1-mediated MDM2 phosphorylation and its protein degradation may contribute to its antitumorigenic function in breast cancer.

In Silico Design and Analysis of Plastic-Binding Peptides.

Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist in interfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores were found to improve with increasing van der Waals interactions, although strengthening the intermolecular van der Waals interactions comes at the cost of introducing unfavorable electrostatic interactions. The best designs are enriched in amino acids with bulky side chains and possess hydrophobic and hydrophilic patches whose location depends on the adsorbed conformation. Future work will evaluate the top peptide designs in molecular dynamics simulations and experiment, enabling their application in microplastic pollution remediation and plastic-based biosensors.