Peptide Recognition Research Articles

Molecular recognition characteristics of co-assembled peptides on atomically flat graphite surfaces

Molecular recognition, involving the binding of two or more molecules, is widely found in multiple disciplines. It plays a crucial role in driving specific molecular functionalization or biological activities such as antigen–antibody interactions. Recently, the molecular recognition of single peptides self-assembly at interfaces has been widely investigated since their broad applications in biosensors and bioelectronics. However, the recognition characteristics of peptide-peptide co-assembly on solids have not been investigated yet, which provides a basis for potential multi-probes biosensing or structure-intermingled functionalized bioelectronic applications. Here, we explored the molecular recognition characteristics of co-assembled peptides on two-dimensional (2D) layered nanomaterials, specifically graphite. Our findings showed distinct surface characteristics of peptide co-assembly in comparison to the independent peptide self-assembly. Peptide co-assembly exhibited the nucleation and growth heterogeneities with reduced nucleation and growth rates, dominated by a diffusion-limited step as confirmed via carrying out the sequential assembly experiments. Moreover, molecular dynamics simulation reveals a slowdown binding process of co-assembled peptides to graphite. Furthermore, the misattachment of one peptide to arrays of another type of peptide with distinct structural ordering orientations severely postponed peptide elongation. Therefore, our work provides valuable insight into the fundamental surface characteristics of two co-assembled peptides as they specifically recognize graphite surface via undergoing continuous surface behaviors from binding to diffusion until final ordering process. The formation of co-assembled peptide patterns on 2D layered nanomaterials incorporates multiple functions, enabling to provide potential applications in intermingled peptide-based biosensing or bioelectronic nanodevices.

Integrating recognition peptide into a nanozyme to mimic uricase binding pocket as a multifunctional nanoplatform for highly selective uric acid recognition, sensing and degrading

Nanozyme based colorimetric sensor for physiological biomarkers detection is becoming an increasingly influential technology in diagnosis, but the selective discrimination of biomarkers using single nanozyme without natural enzyme is greatly challenging. Here, a colorimetric detection platform for biomarker is successfully constructed by integrating recognition peptide (RGPT) into a nanozyme to mimic the binding pocket in natural enzyme. Firstly, RGPT-ultrafine palladium nanoparticles (PdNPs)@reduced graphene oxide (rGO) composite was facilely prepared using an arginine-rich RGPT. RGPT-PdNP@rGO composite displays outstanding laccase-like activity with Km being 0.075 mM at significantly low dosage used, which is one magnitude lower than that of natural enzyme. RGPT-PdNP@rGO nanozyme based one-step sensor can selectively detect uric acid (UA) with a comprehensive linear range from 0.2 to 110 μM and a limit of detection of 120 nM. Moreover, RGPT-PdNP@rGO composite displays an outstanding activity for UA oxidation with Km being 0.024 mM, revealing the nanozyme exhibits a similar affinity towards UA as natural uricase due to the cooperation of the three components. Compared with our previous work, these extremely improved UA recognition, sensing and degrading performances not only support the role of RGPT in enhancing with the recognition ability of the composite nanozyme for targeted UA, but also reveal the recognition role of RGPT is associated closely with inorganic components in the composite. This work provides more definitive and comprehensive information about multifunctional nanozymes for precise biomarker recognition by introducing recognition peptide, which is highly significant for applications beyond mimic-enzyme catalyst, including theranostic, sensing, and energy fields.

Molecular recognition of peptides and proteins by cucurbit[n]urils: systems and applications.

The development of methodology for attaching ligand binding sites to proteins of interest has accelerated biomedical science. Such protein tags have widespread applications as well as properties that significantly limit their utility. This review describes the mechanisms and applications of supramolecular systems comprising the synthetic receptors cucurbit[7]uril (Q7) or cucurbit[8]uril (Q8) and their polypeptide ligands. Molecular recognition of peptides and proteins occurs at sites of 1-3 amino acids with high selectivity and affinity via several distinct mechanisms, which are supported by extensive thermodynamic and structural studies in aqueous media. The commercial availability, low cost, high stability, and biocompatibility of these synthetic receptors has led to the development of myriad applications. This comprehensive review compiles the molecular recognition studies and the resulting applications with the goals of providing a valuable resource to the community and inspiring the next generation of innovation.

Non-enzymatic cholesterol biosensor: Electrochemical sensing based on peptide-polylactic acid thin film

Cholesterol is a fundamental lipid prevalent in eukaryotic cell membranes and circulating in the bloodstream bound to lipoproteins. It serves as a precursor to steroid hormones and is regarded as a biomarker for cardiovascular disease and other metabolic disorders. Numerous cholesterol detection methods predominantly rely on enzymes, which suffer from instability, leading to non-cost-effective biosensors with low sensitivity and poor reusability. Therefore, monitoring cholesterol levels with a feasible, rapid, and stable biosensor is critical for diagnosing and treating various disorders. This study aimed to develop a non-enzymatic cholesterol biosensor based on a selected cholesterol recognition peptide as the detection element. Screen-printed carbon electrodes (SPEs) modified with biocompatible poly-L-lactic acid (PLLA) porous nanomembranes (NMs) were utilized as support for the covalent immobilization of the peptide. Data obtained from electrochemical impedance spectroscopy (EIS) demonstrated the peptide's effective binding affinity towards cholesterol, paving the way for its implementation. The determination of cholesterol with the proposed biosensor exhibited a low limit of detection of 6.31 μM with linear responses ranging from 2–15 μM and 20–40 μM. These findings present an alternative method for cholesterol sensing by integrating novel peptides as biorecognition motifs with biocompatible polymeric materials, potentially useful as biocompatible and future point-of-care sensors.

9377 Exploring Strategies To Reverse Cellular Characteristics Of Succinate Dehydrogenase B-loss Immortalized Chromaffin Cells

Abstract Disclosure: L. Rahimi: None. F. Al-Khazal: None. N. Becker: None. L. Maher, III: None. Carriers of loss-of-function alleles in genes encoding the four succinate dehydrogenase (SDH) subunits exhibit a heightened risk for pheochromocytoma/paraganglioma (PPGL), a rare neuroendocrine tumor of chromaffin cells. Tumorigenesis begins with the somatic loss of the remaining functional gene copy, resulting in a cell devoid of functional SDH. Compared to wild-type immortalized chromaffin cells (WT imCCs), SDHB-KO immortalized chromaffin cells (SDHB-KO imCCs) are larger, grow more slowly, display deformed mitochondria, show strikingly heightened succinate accumulation, and altered metabolism. Among several mechanisms proposed to link SDH deficiency with PPGL tumorigenesis, the accumulation of succinate as an oncometabolite is a leading hypothesis. We describe two attempts to suppress succinate accumulation in SDHB-KO imCCs. First, riboflavin has previously been shown to enhance residual SDHA flavinylation and enzymatic function, possibly reducing succinate levels by supporting conversion of accumulated succinate to fumarate in the absence of SDHB. We tested this by treating WT and SDHB-KO imCCs with 5 µM riboflavin for 2 weeks. Metabolomic analysis did not show decreased succinate, suggesting that enzyme activity of any remaining SDHA subunit was not rescued by increased flavinylation. Second, we envisioned a gene therapy approach to replace defective SDHB with a rescuing transgene. SDHB-KO imCCs received DNA encoding SDHB or SDHC cDNAs via transposon technology, confirmed by PCR and analyzed by western blot analyses. These studies showed that whereas WT imCCs successfully expressed processed transgene products in mitochondria, SDHB-KO imCCs could not process or transport rescuing SDH subunits into mitochondria. This shows that transposed SDHB-KO imCCs cannot properly express a rescuing SDHB subunit and do not revert to a wild-type phenotype. It is likely that the severely damaged mitochondria of SDHB-KO imCCs are incompetent to process and import rescuing SDHB subunits, so unprocessed protein accumulates without effect. This defect may lie in the mitochondrial targeting peptide recognition system because the targeting peptide of rescuing SDHB protein is not removed in SDHB-KO imCCs as judged by western blotting. In summary, we show the failure of two conceptually simple tactics to suppress succinate accumulation in SDHB-KO imCCs with highly defective mitochondria: rescue of SDHA by supporting flavinylation, or rescue of SDHB with a replacement gene copy. Further research may allow screening for small molecules that suppress succinate accumulation by other mechanisms. It remains to be determined if blocking succinate accumulation would be therapeutic in SDH-loss PPGL tumors. Presentation: 6/1/2024

ELLA: Modeling Subcellular Spatial Variation of Gene Expression within Cells in High-Resolution Spatial Transcriptomics.

Spatial transcriptomic technologies are becoming increasingly high-resolution, enabling precise measurement of gene expression at the subcellular level. Here, we introduce a computational method called subcellular expression localization analysis (ELLA), for modeling the subcellular localization of mRNAs and detecting genes that display spatial variation within cells in high-resolution spatial transcriptomics. ELLA creates a unified cellular coordinate system to anchor diverse cell shapes and morphologies, utilizes a nonhomogeneous Poisson process to model spatial count data, leverages an expression gradient function to characterize subcellular expression patterns, and produces effective control of type I error and high statistical power. We illustrate the benefits of ELLA through comprehensive simulations and applications to four spatial transcriptomics datasets from distinct technologies, where ELLA not only identifies genes with distinct subcellular localization patterns but also associates these patterns with unique mRNA characteristics. Specifically, ELLA shows that genes enriched in the nucleus exhibit an abundance of long noncoding RNAs or protein-coding mRNAs, often characterized by longer gene lengths. Conversely, genes containing signal recognition peptides, encoding ribosomal proteins, or involved in membrane related activities tend to enrich in the cytoplasm or near the cellular membrane. Furthermore, ELLA reveals dynamic subcellular localization patterns during the cell cycle, with certain genes showing decreased nuclear enrichment in the G1 phase while others maintain their enrichment patterns throughout the cell cycle. Overall, ELLA represents a calibrated, powerful, robust, scalable, and versatile tool for modeling subcellular spatial expression variation across diverse high-resolution spatial transcriptomic platforms.

Structural dynamics of the TPR domain of the peroxisomal cargo receptor Pex5 in Trypanosoma

Peroxisomal protein import has been identified as a valid target in trypanosomiases, an important health threat in Central and South America. The importomer is built of multiple peroxins (Pex) and structural characterization of these proteins facilitates rational inhibitor development. We report crystal structures of the Trypanosoma brucei and T. cruzi tetratricopeptide repeat domain (TPR) of the cytoplasmic peroxisomal targeting signal 1 (PTS1) receptor Pex5. The structure of the TPR domain of TbPex5 represents an apo-form of the receptor which, together with the previously determined structure of the complex of TbPex5 TPR and PTS1 demonstrate significant receptor dynamics associated with signal peptide recognition. The structure of the complex of TPR domain of TcPex5 with PTS1 provided in this study details the molecular interactions that guide signal peptide recognition at the atomic level in the pathogenic species currently perceived as the most relevant among Trypanosoma. Small – angle X – ray scattering (SAXS) data obtained in solution supports the crystallographic findings on the compaction of the TPR domains of TbPex5 and TcPex5 upon interaction with the cargo.

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.

Antigenic peptide–thioredoxin fusion chimeras for <i>in vitro</i> stimulus of CD4<sup>+</sup> TCR<sup>+</sup> Jurkat T-cells

Study of CD4+ T-cell response and T-cell receptor (TCR) specificity is crucial for understanding etiology of immune-mediated diseases and developing targeted therapies. However, solubility, accessibility, and stability of synthetic antigenic peptides used in T-cell assays may be a critical point in such studies. Here we present a T-cell activation reporter system using recombinant proteins containing antigenic epitopes fused with bacterial thioredoxin (trx-peptides) and obtained by bacterial expression. We report that co-incubation of CD4+ HA1.7 TCR+ reporter Jurkat 76 TRP-cells with CD80+ HLA-DRB1*01:01+ HeLa-cells or CD4+ Ob.1A12 TCR+ Jurkat 76 TRP with CD80+ HLA-DRB1*15:01+ HeLa-cells resulted in activation of reporter Jurkat 76 TPR after addition of recombinant trx-peptide fusion proteins, containing TCR-specific epitopes. Trx-peptides were comparable with corresponding synthetic peptides in their capacity to activate Jurkat 76 TPR. These data demonstrate that thioredoxin as a carrier protein (trx) for antigenic peptides exhibits minimal interference with recognition of MHC-specific peptides by TCRs and consequent T-cell activation. Our findings highlight potential feasibility of trx-peptides as a reagent for assessing the immunogenicity of antigenic fragments.

Molecular mechanism of prolactin-releasing peptide recognition and signaling via its G protein-coupled receptor

Prolactin-releasing peptide (PrRP) is an RF-amide neuropeptide that binds and activates its cognate G protein-coupled receptor, prolactin-releasing peptide receptor (PrRPR), also known as GPR10. PrRP and PrRPR are highly conserved across mammals and involved in regulating a range of physiological processes, including stress response, appetite regulation, pain modulation, cardiovascular function, and potentially reproductive functions. Here we present cryo-electron microscopy structures of PrRP-bound PrRPR coupled to Gq or Gi heterotrimer, unveiling distinct molecular determinants underlying the specific recognition of the ligand’s C-terminal RF-amide motif. We identify a conserved polar pocket that accommodates the C-terminal amide shared by RF-amide peptides. Structural comparison with neuropeptide Y receptors reveals both similarities and differences in engaging the essential RF/RY-amide motifs. Our findings demonstrate the general mechanism governing RF-amide motif recognition by PrRPR and RF-amide peptide receptors, and provide a foundation for elucidating activation mechanisms and developing selective drugs targeting this important peptide–receptor system.

HybAVPnet: A Novel Hybrid Network Architecture for Antiviral Peptides Prediction.

Viruses pose a great threat to human production and life, thus the research and development of antiviral drugs is urgently needed. Antiviral peptides play an important role in drug design and development. Compared with the time-consuming and laborious wet chemical experiment methods, it is critical to use computational methods to predict antiviral peptides accurately and rapidly. However, due to limited data, accurate prediction of antiviral peptides is still challenging and extracting effective feature representations from sequences is crucial for creating accurate models. This study introduces a novel two-step approach, named HybAVPnet, to predict antiviral peptides with a hybrid network architecture based on neural networks and traditional machine learning methods. We adopted a stacking-like structure to capture both the long-term dependencies and local evolution information to achieve a comprehensive and diverse prediction using the predicted labels and probabilities. Using an ensemble technique with the different kinds of features can reduce the variance without increasing the bias. The experimental result shows HybAVPnet can achieve better and more robust performance compared with the state-of-the-art methods, which makes it useful for the research and development of antiviral drugs. Meanwhile, it can also be extended to other peptide recognition problems because of its generalization ability.

Glutathione and its structural modifications recognized by Raman Optical Activity and Circularly Polarized Luminescence

Raman Optical Activity combined with Circularly Polarized Luminescence (ROA-CPL) was used in the spectral recognition of glutathione peptide (GSH) and its model post-translational modifications (PTMs). We demonstrate the potential of ROA spectroscopy and CPL probes (EuCl3, Na3[Eu(DPA)3], NaEuEDTA) in the study of unmodified peptide, i.e. GSH, and its derivatives, i.e. glutathione oxidized (GSSG), S-acetylglutathione (GSAc) and S-nitrosoglutathione (GSNO). ROA spectral features of GSH, GSSG, and GSAc were determined along with thier changes upon the different pH conditions. Apart from the ROA, induced CPL signals of Eu(III) probes also proved to be sensitive to the structural modifications of GSH-based model PTMs, enabling their spectral recognition, especially by the NaEuEDTA probe.

Multi-layered heterochromatin interaction as a switch for DIM2-mediated DNA methylation

Functional crosstalk between DNA methylation, histone H3 lysine-9 trimethylation (H3K9me3) and heterochromatin protein 1 (HP1) is essential for proper heterochromatin assembly and genome stability. However, how repressive chromatin cues guide DNA methyltransferases for region-specific DNA methylation remains largely unknown. Here, we report structure-function characterizations of DNA methyltransferase Defective-In-Methylation-2 (DIM2) in Neurospora. The DNA methylation activity of DIM2 requires the presence of both H3K9me3 and HP1. Our structural study reveals a bipartite DIM2-HP1 interaction, leading to a disorder-to-order transition of the DIM2 target-recognition domain that is essential for substrate binding. Furthermore, the structure of DIM2-HP1-H3K9me3-DNA complex reveals a substrate-binding mechanism distinct from that for its mammalian orthologue DNMT1. In addition, the dual recognition of H3K9me3 peptide by the DIM2 RFTS and BAH1 domains allosterically impacts the DIM2-substrate binding, thereby controlling DIM2-mediated DNA methylation. Together, this study uncovers how multiple heterochromatin factors coordinately orchestrate an activity-switching mechanism for region-specific DNA methylation.

PairK: Pairwise k-mer alignment for quantifying protein motif conservation in disordered regions.

Protein-protein interactions are often mediated by a modular peptide recognition domain binding to a short linear motif (SLiM) in the disordered region of another protein. The ability to predict domain-SLiM interactions would allow researchers to map protein interaction networks, predict the effects of perturbations to those networks, and develop biologically meaningful hypotheses. Unfortunately, sequence database searches for SLiMs generally yield mostly biologically irrelevant motif matches or false positives. To improve the prediction of novel SLiM interactions, researchers employ filters to discriminate between biologically relevant and improbable motif matches. One promising criterion for identifying biologically relevant SLiMs is the sequence conservation of the motif, exploiting the fact that functional motifs are more likely to be conserved than spurious motif matches. However, the difficulty of aligning disordered regions has significantly hampered the utility of this approach. We present PairK (pairwise k-mer alignment), an MSA-free method to quantify motif conservation in disordered regions. PairK outperforms both standard MSA-based conservation scores and a modern LLM-based conservation score predictor on the task of identifying biologically important motif instances. PairK can quantify conservation over wider phylogenetic distances than MSAs, indicating that SLiMs may be more conserved than is implied by MSA-based metrics. PairK is available as open-source code at https://github.com/jacksonh1/pairk.

The mechanism of mammalian proton-coupled peptide transporters.

Proton-coupled oligopeptide transporters (POTs) are of great pharmaceutical interest owing to their promiscuous substrate binding site that has been linked to improved oral bioavailability of several classes of drugs. Members of the POT family are conserved across all phylogenetic kingdoms and function by coupling peptide uptake to the proton electrochemical gradient. Cryo-EM structures and alphafold models have recently provided new insights into different conformational states of two mammalian POTs, SLC15A1, and SLC15A2. Nevertheless, these studies leave open important questions regarding the mechanism of proton and substrate coupling, while simultaneously providing a unique opportunity to investigate these processes using molecular dynamics (MD) simulations. Here, we employ extensive unbiased and enhanced-sampling MD to map out the full SLC15A2 conformational cycle and its thermodynamic driving forces. By computing conformational free energy landscapes in different protonation states and in the absence or presence of peptide substrate, we identify a likely sequence of intermediate protonation steps that drive inward-directed alternating access. These simulations identify key differences in the extracellular gate between mammalian and bacterial POTs, which we validate experimentally in cell-based transport assays. Our results from constant-PH MD and absolute binding free energy (ABFE) calculations also establish a mechanistic link between proton binding and peptide recognition, revealing key details underpining secondary active transport in POTs. This study provides a vital step forward in understanding proton-coupled peptide and drug transport in mammals and pave the way to integrate knowledge of solute carrier structural biology with enhanced drug design to target tissue and organ bioavailability.

The mechanism of mammalian proton-coupled peptide transporters

Proton-coupled oligopeptide transporters (POTs) are of great pharmaceutical interest owing to their promiscuous substrate binding site that has been linked to improved oral bioavailability of several classes of drugs. Members of the POT family are conserved across all phylogenetic kingdoms and function by coupling peptide uptake to the proton electrochemical gradient. Cryo-EM structures and alphafold models have recently provided new insights into different conformational states of two mammalian POTs, SLC15A1, and SLC15A2. Nevertheless, these studies leave open important questions regarding the mechanism of proton and substrate coupling, while simultaneously providing a unique opportunity to investigate these processes using molecular dynamics (MD) simulations. Here, we employ extensive unbiased and enhanced-sampling MD to map out the full SLC15A2 conformational cycle and its thermodynamic driving forces. By computing conformational free energy landscapes in different protonation states and in the absence or presence of peptide substrate, we identify a likely sequence of intermediate protonation steps that drive inward-directed alternating access. These simulations identify key differences in the extracellular gate between mammalian and bacterial POTs, which we validate experimentally in cell-based transport assays. Our results from constant-PH MD and absolute binding free energy (ABFE) calculations also establish a mechanistic link between proton binding and peptide recognition, revealing key details underpining secondary active transport in POTs. This study provides a vital step forward in understanding proton-coupled peptide and drug transport in mammals and pave the way to integrate knowledge of solute carrier structural biology with enhanced drug design to target tissue and organ bioavailability.

Electrochemical detection of atrial natriuretic peptide-coated nanocarriers based on a molecularly imprinted polymer receptor thin film

Molecularly imprinted polymers (MIPs) are biomimetic materials of great interest in the scientific and industrial fields for the development of innovative sensing strategies. Herein, we proposed a new sensing application by developing an electrochemical sensor using molecular imprinting (MI) technology for recognition of atrial natriuretic peptide (ANP) both as a free molecule in solution and attached to nanoparticle-based drug delivery systems (DDSs), aiming to provide fast and reliable information on the cell uptake of nanoparticles (NPs). As proof of concept, poly(lactic-co-glycolic acid) (PLGA) NPs were synthesized and used as nanocarriers for ischemic heart disease therapy were synthesized and then functionalized with ANP (named here as PLGA-NPs@ANP). The MIP receptor film was prepared by electrochemical polymerization of dopamine over the working area of a gold screen-printed electrode (AuSPE), using cyclic voltammetry (CV) technique. The construction of the ANP sensor was carefully optimized to enhance its performance, including the film thickness and the procedures for effective template extraction from the MIP matrix. The MIP biosensor presented a linear response against polymeric NPs (PLGA-NPs@ANP) concentration logarithm ranging from 4.0 μg mL-1 to 100 μg mL-1, with a sensitivity of – 0.0129 mA mL μg-1 decade-1 and an LOD < 4.0 μg mL-1. Furthermore, the developed MIP receptor film was able to discriminate ANP-functionalized nanocarriers from non-functionalized NPs.

Sequence-specific targeting of intrinsically disordered protein regions.

A general approach to design proteins that bind tightly and specifically to intrinsically disordered regions (IDRs) of proteins and flexible peptides would have wide application in biological research, therapeutics, and diagnosis. However, the lack of defined structures and the high variability in sequence and conformational preferences has complicated such efforts. We sought to develop a method combining biophysical principles with deep learning to readily generate binders for any disordered sequence. Instead of assuming a fixed regular structure for the target, general recognition is achieved by threading the query sequence through diverse extended binding modes in hundreds of templates with varying pocket depths and spacings, followed by RFdiffusion refinement to optimize the binder-target fit. We tested the method by designing binders to 39 highly diverse unstructured targets. Experimental testing of ∼36 designs per target yielded binders with affinities better than 100 nM in 34 cases, and in the pM range in four cases. The co-crystal structure of a designed binder in complex with dynorphin A is closely consistent with the design model. All by all binding experiments for 20 designs binding diverse targets show they are highly specific for the intended targets, with no crosstalk even for the closely related dynorphin A and dynorphin B. Our approach thus could provide a general solution to the intrinsically disordered protein and peptide recognition problem.

Molecular dynamics simulations in pre-polymerization mixtures for peptide recognition.

Molecularly imprinted polymers (MIPs) have promising applications as synthetic antibodies for protein and peptide recognition. A critical aspect of MIP design is the selection of functional monomers and their adequate proportions to achieve materials with high recognition capacity toward their targets. To contribute to this goal, we calibrated a molecular dynamics protocol to reproduce the experimental trends in peptide recognition of 13 pre-polymerization mixtures reported in the literature for the peptide toxin melittin. Three simulation conditions were tested for each mixture by changing the box size and the number of monomers and cross-linkers surrounding the template in a solvent-explicit environment. Fully atomistic MD simulations of 350 ns were conducted with the AMBER20 software, with ff19SB parameters for the peptide, gaff2 parameters for the monomers and cross-linkers, and the OPC water model. Template-monomer interaction energies under the LIE approach showed significant differences between high-affinity and low-affinity mixtures. Simulation systems containing 100 monomers plus cross-linkers in a cubic box of 90 Å3 successfully ranked the mixtures according to their experimental performance. Systems with higher monomer densities resulted in non-specific intermolecular contacts that could not account for the experimental trends in melittin recognition. The mixture with the best recognition capacity showed preferential binding to the 13-26-α-helix, suggesting a relevant role for this segment in melittin imprinting and recognition. Our findings provide insightful information to assist the computational design of molecularly imprinted materials with a validated protocol that can be easily extended to other templates.

Antigen Delivery Controlled by an On‐Demand Photorelease

AbstractTo eliminate infected and cancerous cells, antigen processing and presentation play a pivotal role through the recognition of antigenic peptides displayed on Major Histocompatibility Complex class I (MHC I) molecules. Here, we developed a photostimulated antigen release system that enables the temporal inception of antigen flux. Simple and effective photocaging of the human immunodeficiency virus (HIV)‐Nef73‐derived epitope, a representative high‐affinity MHC I ligand, was provided by steric hindrance to block the recognition by the transporter associated with antigen processing (TAP) in the peptide loading complex (PLC). In response to light, a heteronomous release of antigens and subsequent translocation in various scenarios is demonstrated, including a TAP‐related ATP‐binding cassette (ABC) transporter reconstituted in liposomes and the native PLC in the endoplasmic reticulum (ER) membrane of human cells. The photochemically induced ‘burst’ of antigens opens new opportunities for a mechanistic analysis of the antigen translocation machinery and will help to provide insights into antigen processing pathways via an on‐demand, subcellular pulse‐chase release of antigens.