Biology subjects

Colby, J. M.

Publications and source records attributed to Colby, J. M..

4 recordsLinked to original sources

bioRxiv2025

Dynamic Gating by the Phenylalanine Clamp Loop Controls Peptide Translocation Through the Anthrax Toxin Nanopore

The {phi}-clamp loop, which contains the key F427 residue, is a critical active site in the anthrax toxin protective antigen (PA) nanopore, yet its precise role in governing the complex, multi-state dynamics of peptide translocation remains debated. Here, we dissect the peptide-clamp interaction mechanism using single-channel electrophysiology and a series of guest-host peptides, which are translocated via either wild-type PA, an ablated F427A mutant, or a polar aromatic F427Y mutant. Mutations to the {phi} clamp dramatically reduce peptide residence times but, critically, preserve the intermediate, partially blocked conductance states observed in the wild-type pore. Thermodynamic analysis reveals that the F427 residue is essential for creating a deep, energetically stable, fully blocked hydrophobic trap (State 0), as its mutation leads to a significant destabilization of this state and a corresponding population shift to shallower intermediates. Kinetic analysis of the state-to-state transitions demonstrates that while the F427A mutation lowers the energetic barrier for escape from this trap, it disrupts the efficient, hydrophobically driven entry. Furthermore, the strong correlations between kinetic parameters and peptide molecular properties (hydrophobicity, aromaticity) that are a hallmark of the wild-type pore are completely abolished in the F427A mutant. These results support a refined model where F427 acts as a specific chemical reader, and the intermediate states arise from larger-scale, dynamic dilation of the entire clamp-containing loop. This detailed mechanistic insight provides a framework for the rational engineering of next-generation nanopore biosensors.

biophysics↗

bioRxiv2025

Peptide hydrophobicity and aromaticity predict multi-state translocation kinetics via protective antigen nanopores

Single-molecule analysis of guest-host peptides translocating through the anthrax toxin protective antigen (PA) nanopore reveals a multi-state kinetic mechanism. Using K-Means clustering, four distinct conductance states, including a fully-blocked state (State 0), two intermediates (States 1 and 2), and a fully open pore (State 3) were identified. Multi-exponential kinetic analysis of state-to-state transitions was performed, and resulting lifetimes and amplitudes were correlated with molecular properties of the guest residue. Our correlation analysis of these kinetic parameters to defined molecular properties of the guest residues reveals which physical properties govern the mechanism. The fully blocked State 0 acts as a hydrophobic trap, with the lifetime of entry transitions (e.g., 1[->]0) strongly predicted by side-chain hydrophobicity. Conversely, escaping this trap is a steric process governed by molecular size, though the probability of a fast escape is uniquely facilitated by aromaticity, suggesting a specific ungating interaction with the pores {phi}-clamp, which is consistent with clamp site dilation. Rearrangements between partially blocked states are also dominated by hydrophobicity, reflecting the side chain exploring different contacts within the pore. Final dissociation to open nanopore is a multi-pathway process where the dominant physical force depends on the starting state: escape from deeper states is an energetic battle against hydrophobicity and aromaticity, while escape from shallower states presents a final steric hurdle. Overall, this work dissects the peptide translocation process, demonstrating how distinct physical forces--hydrophobicity, sterics, and aromaticity--govern specific, sequential steps of intra-pore dynamics and release, providing a detailed energy landscape for peptide-nanopore interactions.

biophysics↗

bioRxiv2025

High-performance machine learning for peptide classification from nanopore translocation events, leveraging event kinetics and duration filtering

Understanding single-molecule translocation dynamics through biological nanopores is fundamental to advancing next-generation biosensing and sequencing technologies. Here, using the anthrax toxin protective antigen nanopore, we describe a high-performance machine learning (ML) framework for classifying a diverse series of guest-host peptides based on individual translocation events. The approach leverages carefully engineered, event-level biophysical features extracted from either scaled current and conductance state sequences. Through systematic UMAP analysis of this feature space, we reveal that filtering away the shortest events effectively enriches the dataset with more discriminative longer events, leading to improved classification. Various deep learning (DL) and traditional ML architectures, including convolutional neural networks (CNN), temporal convolutional networks (TCN), and eXtreme Gradient Boosting (XGBoost), were investigated. The dual-input CNN-Dense model, which utilized current sequences and features, achieved strong classification performance (accuracy [~]0.80). However, the most robust classification was achieved with XGBoost acting solely on the engineered feature set, demonstrating superior performance (accuracy [~]0.90). This ML approach provided a significant computational advantage in both training and inference over DL models. Notably, these models consistently discriminated between peptides differing only in backbone stereochemistry, highlighting the exquisite sensitivity of the nanopore to subtle conformational dynamics. These findings underscore that carefully engineered event-level features, particularly from longer translocations, combined with efficient tree-based models, offer a highly effective and computationally favorable strategy for high-fidelity peptide classification for biosensing applications.

biophysics↗

bioRxiv2025

Comparative study of nanopore phenylalanine clamp variants reveals unique peptide biosensing and classification properties

The rapid, label-free, and low-cost detection of peptides is critical for the development of next-generation diagnostics, drug discovery, and environmental monitoring. Nanopore-based biosensing offers a promising platform to address this need by leveraging single-molecule analysis. In this study, we utilize protein engineering to create a series of novel peptide biosensors from the anthrax toxin protective antigen (PA) nanopore by targeting its central phenylalanine clamp constriction (residue F427), a key site known to interact dynamically with translocating molecules. This series of engineered variants were evaluated for their performance in both unsupervised clustering and supervised classification of a diverse set of seven guest-host peptides. Intriguingly, we found that the engineered variants exhibited a broad range of unique biosensing and classification properties. There was a notable divergence between the ability of the variants to intrinsically separate peptides (unsupervised clustering) and their performance in supervised classification tasks. Notably, PA F427A nanopores showed enhanced specificity for small molecular weight peptides that were challenging for WT nanopores to classify, achieving exceptionally high performance (accuracy of 0.93). These findings challenge the assumption that a single unmodified biosensor is sufficient for complex discrimination. Instead, our results highlight the potential for a more robust approach: leveraging the unique, complementary strengths of multiple sensor variants in an ensemble or multiplexed array. Such a system can achieve high and balanced performance across diverse peptide classes, representing a significant step forward in the development of sophisticated nanopore biosensors.

biophysics↗