<figure><img src="image_1.png" /></figure>

HAL
open science

# Discrimination of Oxytocin, a Behavioral Neuropeptide Hormone, and Its Structural Variants by Nanopore

Nathan Meyer, Laura Ratinho, Sandra J Greive, Laurent Bacri, Bénédicte

Thiebot, Blasco Morozzo Della Rocca, Mauro Chinappi, Juan Pelta, Benjamin

Cressiot

► To cite this version:

Nathan Meyer, Laura Ratinho, Sandra J Greive, Laurent Bacri, Bénédicte Thiebot, et al. Discrimination of Oxytocin, a Behavioral Neuropeptide Hormone, and Its Structural Variants by Nanopore. ACS Nano, 2025, 19 (31), pp.28690-28701. 10.1021/acsnano.5c08031. hal-05265158

HAL Id: hal-05265158

https://hal.science/hal-05265158v1

Submitted on 17 Sep 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Discrimination of oxytocin, a behavioral neuropeptide hormone, and its structural variants by nanopore

Nathan Meyer<fnref n="1" />, Laura Ratinho<fnref n="1" />, Sandra J. Greive<fnref n="2" />, Laurent Bacri<fnref n="3" />, Bénédicte Thiebot<fnref n="1" />, Blasco Morozzo della Rocca<fnref n="4" />, Mauro Chinappi<fnref n="5" />, Juan Pelta<fnref n="3" />* and Benjamin Cressiot<fnref n="1" />*

## Abstract

Oxytocin, a neurohormone peptide, is implicated in various physiological processes, such as functions related to social behavior, reproduction, and emotional regulation. Recently, this peptide has been identified as a potential biomarker of human psychiatric disorders. Until now, no analytical tool has been able to routinely detect oxytocin and its variants, which can have different effects on their receptor binding and activity. This work uses an aerolysin nanopore and two mutants to detect oxytocin (OXT) and oxytocin-free acid (OXT-FA) differing by a single amine group. Several oxytocin variants were used to understand the effect of structure and conformational changes of the peptides on the electric signal. We identify two conformations in native conditions, allowing their discrimination. Nanopore mutants showed improved discrimination of these peptides. MD simulation allowed us to rationalize the competition between electroosmosis and electrophoresis on OXT and OXT-FA transport through aerolysin. This work demonstrates the potential for analyzing conformational biomarkers for diagnostic purposes.

**Keywords:** Aerolysin, mutant, mental health biomarker, peptide conformation, electroosmotic flow.

## Introduction

Oxytocin (OXT) is a key neuropeptide in social bonding, parturition, and lactation<fnref n="1" />,<fnref n="2" />. Recent research highlights its involvement in various neuropsychiatric disorders such as depression<fnref n="3" />,<fnref n="4" />,

<footnote n="1">¹ Université Paris-Saclay, Univ Evry, CY Cergy Paris Université, CNRS, LAMBE, 95000 Cergy, France</footnote>

<footnote n="2">² DreamPore S.A.S., 95000 Cergy, France</footnote>

<footnote n="3">³ Université Paris-Saclay, Univ Evry, CY Cergy Paris Université, CNRS, LAMBE, 91025 Evry-Courcouronnes, France</footnote>

<footnote n="4">⁴ Dipartimento di Biologia, Università di Roma Tor Vergata, 00133 Roma, Italia</footnote>

<footnote n="5">⁵ Dipartimento di ingegneria industriale, Università di Roma Tor Vergata, 00133 Roma, Italia</footnote>

<footnote>* Corresponding authors: juan.pelta@univ-evry.fr, benjamin.cressiot@cyu.fr</footnote>
schizophrenia⁵⁻⁷, and autism spectrum disorders⁸,⁹ (ASD) (Figure 1a). These effects could be
due to OXT's involvement in social cognition, emotional regulation, and stress response¹⁰. It
is estimated that 5% of the world's population suffers from significant depressive disorders¹¹.
Concerning ASD, it is thought that 1 in 100 children is affected¹². However, these values could
be higher because of a lack of analytical tools, leading to undiagnosed cases of autism¹²,
depression¹³, and schizophrenia¹⁴.

OXT, primarily produced in the paraventricular and supraoptic nuclei of the hypothalamus, is released by the posterior pituitary gland¹⁵,¹⁶ into the bloodstream, acting as a neurohormone in peripheral tissues. In parallel, a distinct population of paraventricular neurons projects directly to various brain regions, allowing OXT to act as a neurotransmitter and neuromodulator¹⁷,¹⁸. Its effects are primarily mediated through the oxytocin receptor (OXTR)¹⁹, a G-protein-coupled receptor whose expression, desensitization, or local variations in OXT levels. Additionally, OXT can interact with vasopressin receptors (AVPR), which may contribute to its roles in social behavior regulation, stress modulation, and emotional processing. The polymorphism and localization of this receptor may also explain the various functions of the OXTR-OXT complex²⁰,²¹.

Notably, the functional diversity of OXT may also be determined by structural modifications of the peptide itself²². OXT is a nonapeptide featuring two key secondary structural elements: a disulfide bridge conferred by the presence of two cysteines (Cys1 and Cys6) and a beta-turn favored by the presence of proline (Pro7)²³,²⁴. Together, these elements create a tailed ring that is stabilized by a hydrogen bond between the Cys6 and the Gly9 (Figure 1b). Structural modifications of OXT can significantly alter its function²⁵⁻²⁷. For instance, the loss of the disulfide bridge induces a conformational change, enabling binding to alpha 2-adrenoreceptors and reducing spontaneous motor activity and stress response²⁸. Another key variant, the C-terminally extended form (OXT-GKR, derived from processing OXT-neurophysin precursors), is implicated in ASD²⁹. Additionally, OXT can undergo C-terminal deamidification by a carboxy-aminopeptidase, yielding oxytocin-free acid (OXT-FA). This form, suspected to biologically inactive, could serve as a regulatory mechanism³⁰,³¹ (Figure 1b), and has been found in the developmental stages of nonmammalian vertebrates and, presumably, given its evolutionary conservation, also in human fetal development. Consequently, these structural variations highlight the complexity of OXT signaling. Distinguishing between these various forms remains challenging.
Mass spectrometry and immunoassays are the standard methods³² to detect the peptides. However, both present limitations. Traditional immunoassays, such as ELISA and RIA, are widely used for quantifying OXT, but they suffer from several limitations³³. First, they rely on antibody-antigen interactions that can exhibit cross-reactivity³⁴ between OXT and structurally related forms such as OXT-free acid (OXT-FA), compromising specificity. Moreover, antibody affinity is batch-dependent and can vary significantly between production lots, impacting reproducibility. ELISA-based quantification also suffers from environmental sensitivity, as variations in temperature, matrix complexity, or enzymatic stability can influence the assay's performance and lead to inconsistent results. While RIA provides better reproducibility due to the stability of the radiolabel, it requires prior extraction steps to remove interfering substances. It is also constrained by regulatory and safety concerns associated with the use of radioactivity. Mass spectrometry remains the gold standard in research for characterizing both known and unknown forms of molecules, as well as for their quantification, due to its sensitivity and specificity. However, it typically requires multi-step sample preparation, which may affect molecular integrity or introduce variability. On the other hand, the peptides are not easily detected in biological fluids. Identifying molecules with similar properties, notably charge and molecular weight, can be challenging, as OXT and OXT-FA differ by a single charge at neutral pH and only 0.99 Da³²,³⁵. Finally, its complexity and cost limit its routine use.

These technical limitations have resulted in conflicting and confusing findings about the physiological concentrations of OXT and OXT-FA in blood, making it difficult to understand their function and impeding the development of routine clinically diagnostic assays³²,³⁶,³⁷. Reported baseline OXT concentrations often differ significantly (by one order of magnitude), primarily due to differences in analytical methods and sample preparation. In healthy adults, typical concentrations are 10 pg/mL in blood, excluding significant physiological variations such as lactation and parturition, which can lead to transient but substantial increases (> 100 pg/mL). In contrast, cerebrospinal fluid (CSF) OXT measurements provide a more direct representation of central OXT dynamics and show stronger correlations with psychiatric conditions. While this approach enhances diagnostic accuracy, CSF sampling remains highly invasive, limiting its use in routine clinical practice. To overcome these limitations, advanced analytical methods are needed to reliably quantify OXT and its structural variants from blood samples. By enabling high-resolution discrimination of OXT isoforms, nanopore-based techniques could improve the
reliability of peripheral measurements, such as abnormal levels of OXT-FA and desulfurized
OXT found in the blood, which could indirectly reflect OXT dynamics in the CNS.

Nanopore technology is emerging as an analytical technique for detecting single-molecule-level peptides. This technique has allowed the discrimination of subtle chemical differences, such as post-translational modifications (PTMs)⁵³⁻⁵⁷, enantiomeric amino acids in peptides⁴⁸⁻⁵¹, and conformational changes⁵²,⁵³ linked to the biomolecule activity⁵⁴. Recently, nanopores have been used to detect peptide biomarkers directly in biofluids⁵⁵, paving the way to developing point-of-care tests⁵⁴. The detection principle consists of two reservoirs filled with electrolytes and separated by a membrane containing a nanometric hole (nanopore). When a potential bias is applied, it will cause the movement of ions through the pore, creating an open pore current (I₀). The analytes passing through the nanopore cause current blockages. The blockage characteristics (Figure 1b), the depth Dlₕ (I₀-Iₕₐ₉₆₇ₐ₆₇), and duration Tₜ, provide information on the analyte properties, such as volume, charge, shape, etc⁵⁶,⁵⁷. Several forces are responsible for the transport of analytes through the pores. The electrophoretic force (EP) enables the driving of a charged analyte when a voltage is applied, with the EP direction depending on the analyte charge⁵⁸,⁵⁹. Instead, the electroosmotic flow (EOF, i.e., the flow of water due to the application of the external electric field)⁶⁰ can push the analytes into the pore regardless of their charge⁶¹. EOF is often associated with pore selectivity, and it may be modulated by altering the fixed charges exposed towards the pore lumen, although more subtle mechanisms are possible, such as induced charge EOF that may result in EOF also in uncharged nanopores⁶².
<figure><img src="image_3.png" /><figcaption>**Figure 1:** a) The structure of OXT and its role in lactation, childbirth, and social behavior, as well as its potential involvement in various neuropsychological disorders. b) Principle of electrical detection of OXT and analogs using an AeL nanopore. Top left, sequences and structural motifs (disulfide bond and beta-turn) of OXT and an analog OXT-FA with a variation in one chemical group (amidation of the C-terminal group). Detection was performed in 4 M KCl, 25 mM Tris (pH 7.4) buffer with a peptide concentration of 2 µM. Top right, sequence and structures of mutant peptides with no disulfide bridge (OXT-S, OXT-FA-S) and without beta turn or disulfide bridge (OXT-S-A, OXT-FA-S-A). Detection of mutant peptides was carried out in 3.5 M KCl, 25 mM Tris, 1 M Gdn-HCl (pH 7.4) buffer with a peptide concentration of 2 µM. On the bottom left, the traces of OXT and OXT-FA were recorded using AeL WT. The electrical parameters ($D_{I_b}$, $T_i$, and $T_f$) are shown for the dynamics study. The AeL mutants (D222K and E258R) used, along with the nature and position of the mutations, are illustrated in the sketch. Experiments were performed in 4 M KCl, 25 mM Tris, pH 7.5. Bottom right: Examples of part of current traces for mutant peptides carrying different structural motifs. In all experiments, peptides were driven from cis to trans by applying a positive voltage. Created in BioRender.</figcaption></figure>
In this study, we work with an Aerolysin (AeL) nanopore with an internal diameter of 1.1 nm, compatible with detecting short peptides and subtle modifications. This pore has already shown its potential to detect the size of peptides⁶³, identify amino acids, and detect biological peptides⁶⁴. Because of its excellent sensitivity, it has enabled the discrimination between peptides that differ by just one amino acid⁶⁵, the identification of different peptide biomarker conformations in solution⁴⁹,⁶⁶,⁶⁷, and the detection of various PTMs⁴¹,⁴³,⁴⁵–⁴⁷,⁶⁸. In addition, the compatibility with biofluids proves the relevance of this pore in the clinical field⁶⁶.

Our results show the ability to detect the subtle chemical difference between OXT and OXT-FA by the specific electrical signatures. We further demonstrate the influence of the peptide charge and specific conformations on the dynamics through the nanopore. We can sense two peptide conformations in native conditions that allow us to discriminate between the two molecules. Furthermore, we can identify structural modifications (disulfide bond and beta-turn) using OXT and OXT-FA variants. To follow the influence of the secondary structure on the electrical signal, we performed experiments using a chaotropic agent for these variants. We show that improved discrimination is obtained using aerolysin mutants. All-atom MD simulation provides insights into understanding the transport process and the competition between EP and EOF.

## Results/discussion

### OXT and OXT-FA dynamics

OXT and OXT-FA were driven from the cis to the trans compartment by applying a positive voltage (30 to 130 mV) on the trans side (Figure 2a). Blocking events were observed at all voltages (Figures 2b, c, d, e), with longer blockages at higher applied voltage for both peptides. This shows that the peptides do not translocate but remain trapped at the pore entrance, as described previously for biological nanopores⁴⁷,⁴⁹,⁶⁹,⁷⁰.

At an intermediate voltage (70 mV), two distinct levels of blockage are observed for OXT-FA (0.38 ± 0.01 and 0.41 ± 0.01), while only one is observed for OXT (0.42 ± 0.01) (Figure 2f, h). Since OXT-FA is neutral, only EOF from the cis to the trans side contributes to its trapping. In contrast, OXT has an overall positive charge, experiencing an opposing EP force to the EOF. At lower voltages, this scenario results in decreased trapping of OXT compared to OXT-FA, thereby
limiting the detection of its potential conformations within the pore, explaining the presence
of only one population⁷¹,⁷². At a higher voltage (130 mV), the two OXT-FA populations are still
present but are better separated (Figure 2 g, i). Two populations are now visible for OXT (0.41
± 0.01 and 0.42 ± 0.01). The appearance of this additional population could be due to a higher
EOF, which partially counteracts the EP force on OXT allowing for better entrapment inside the
pore, as shown by the dwell time increase for both peptides. By pushing the peptide strongly
into the pore, we show that we have increased the conformational sensing resolution of OXT.

The capture frequency of both peptides increases linearly with the applied voltage<sup>73</sup>, showing
that the main force driving the peptides into the pore is EOF (Figure 2j). The values are
comparable for both peptides, from 1.31 Hz ± 0.16 at 30 mV to 14.45 Hz ± 0.54 at 130 mV. This
suggests that the charge difference between the two molecules does not alter their entrance
into the pore. More specifically, a plausible interpretation is that EOF dominates the capture
process. This is coherent with the estimation of EOF by MD simulation reported at the end of
the experimental section.

The dwell times for both molecules increase with the voltage, confirming that the peptides
remain trapped at the pore entrance instead of translocating (Figure 2k). For OXT-FA, the dwell
times are significantly longer than those for OXT: 1.4 ± 0.15 ms at 30 mV and 27 ± 1.5 ms at
130 mV. The shorter dwell times for OXT can be attributed to the additional antagonistic EP
force contributing to the peptide's exit toward the *cis* reservoir. In contrast, OXT-FA is neutral,
relying solely on EOF for its entrapment. Additional discussion on this subtle effect is reported
in Supplementary Information Figure SI-1.

The blocking levels of the main peak for each peptide are constant between 30 and 130 mV (Figure 2l), suggesting the absence of significant structural modification. OXT-FA blocks the pore less (0.39 ± 0.01) than OXT (0.42 ± 0.01). This difference could be attributed to the distinct conformations of these two peptides. The main peak of blockade level for both peptides could be a helpful parameter for discriminating between them in the solution. However, the presence of overlapping subpeaks could complicate their precise identification. We performed discrimination experiments both in an equimolar mix (Supplementary Information Figure SI-2a, b, c) and also varying the ratio of concentrations OXT-FA/OXT (Supplementary Information
Figure SI-2d, e) to confirm their identification in a mix. We naturally observe the same peaks as in independent experiments. Furthermore, we can sense the increase in the number of OXT-FA events when we increase the concentration of OXT-FA compared to OXT.

<figure><img src="image_4.png" /></figure>
Figure 2: a) Detection of OXT and OXT-FA using an AeL WT nanopore. The different forces (EP, EOF) responsible for the capture and dynamics are shown. The experiments were conducted in 4 M KCl, 25 mM Tris pH 7.5, with a peptide concentration of 2 µM. b) c) d) e) Current traces of OXT (red) and OXT-FA (blue) recorded at 70 mV and 130 mV. f) Normalized event count versus the blockade level for OXT (n = 3463) and OXT-FA (n = 4895) at 70 mV. g) Normalized event count versus blockade level for OXT (n = 7335) and OXT-FA (n = 4425) at 130 mV. The figures illustrate the distribution of blockade levels, along with their corresponding Gaussian peak values. h) Scatter plots of dwell time versus the blockade level for OXT (red) and OXT-FA at 70 mV. i) Scatter plots of dwell time versus the blockade level for OXT and OXT-FA at 130 mV. j) Frequency of event, k) dwell time, and l) blockade level versus the applied voltage for OXT (red) and OXT-FA (blue), respectively. The means and standard deviations were extracted from at least a duplicate. Created in BioRender.

## Role of OXT and OXT-FA secondary structures on the electrical signal

To understand the contribution of the disulfide bond and beta-turn on the peptide conformation, we designed OXT mutants without disulfide bridges (OXT-S) and beta-turns (OXT-S-A).

For OXT-S and OXT-FA-S, we observe the same level of signal blockage for both molecules in 1 M Gdn-HCl (Figures 3a, c, e, g). There are two distinct populations, one centered at 0.41 ± 0.01 and the other at 0.43 ± 0.01, comparable to the results obtained for OXT and OXT-FA. This shows that the peptide can adopt two main conformations likely caused by the beta-turn, not the disulfide bond. To prove this result, we used peptides where the proline is substituted with alanine, thus preventing the beta-turn formation. OXT-S-A and OXT-FA-S-A exhibit only one population centered at 0.38 ± 0.01 for both molecules in 1 M Gdn-HCl (Figures 3b, d, f, h), showing that the two conformations observed are due to the presence of the beta-turn.

As described above for the WT peptides, the dynamics of these modified peptides also do not translocate into the pore but instead get trapped at the entrance. The dwell time increases as the voltage increases (Supplementary Information Figure SI-3a-b), with durations for all the modified peptides ranging from 0.2 ms (at 30 mV) to 3.75 ms (at 130 mV).
<figure><img src="image_5.png" /><figcaption>Figure 3: a) Current traces recorded at 130 mV for OXT-S and c) OXT-FA-S in the presence of 1 M of Gdn-HCl. b) Current traces recorded at 130 mV for OXT-S-A and d) OXT-FA-S-A, respectively, in 1 M Gdn-HCl. e) Histogram of blockade levels for OXT-S (red) and OXT-FA-S (cyan) at 130 mV in 1 M Gdn-HCl. The centers of the distributions of Gaussian fits are indicated in the figure. f) Histogram of blockade levels for OXT-S-A and OXT-FA-S-A recorded at 130 mV in 1 M Gdn-HCl. The centers of the distributions of Gaussian fits are indicated in the figure. g) Scatter plot of blocking levels versus times for OXT-S (n = 1253) and OXT-FA-S (n = 1949) at 130 mV in the presence of 1 M Gdn-HCl. h) Scatter plot of blocking levels versus times for OXT-S-A (n = 1679) and OXT-FA-S-A (n = 2151) at 130 mV in</figcaption></figure>
## Use of AeL Mutants to discriminate OXT and OXT-FA

The AeL WT nanopore experiments showed that the peptides did not translocate but remained trapped at the pore entrance. To explore this further, we generated AeL mutants where the acidic residues (E258 and D222) were substituted with basic residues E258R and D222K (Figures 4a and Supplementary Information Figure SI-4). We expected an increase in EOF by enhancing AeL's selectivity to anions.

Blocking events for OXT and OXT-FA were measured between 30 mV and 130 mV for both mutants, and the blocking signals are shown in Figure 4b (D222K) and Figure 4c (E258R). At 130 mV, there is now only one population per peptide, centered at 0.48 ± 0.03 and 0.65 ± 0.1 for OXT and OXT-FA, respectively (Figures 4d and e). The mutants allow better discrimination and better separation of the blockade levels for each peptide. The results are similar for both mutants, see Figure SI-2f-o, indicating that the mutation's nature and position do not influence this trend. Additionally, the distributions are broader than those obtained with a WT nanopore. The widths at mid-height exceed 0.03, whereas they were less than 0.01 previously. At 70 mV, the results for both pores are still similar, with only one population of blockade levels per peptide visible, centered at 0.46 ± 0.2 and 0.55 ± 0.5 for OXT and OXT-FA, respectively (Supplementary Information Figure SI-5). Compared to the AeL WT, the different surface charge distribution might alter the possible interactions between the peptide and the pore, limiting the ability to orient the peptides into the pore properly.

Similar capture frequencies are observed for both pores (Figure 4f), with no noticeable difference between OXT and OXT-FA. The additional negative charge in OXT-FA does not affect the capture, as observed with AeL WT. The values increase linearly for both peptides as a function of the applied voltage, regardless of the pore used, showing that EOF is the dominant force. However, there are significant differences in dwell times compared to the AeL WT (Figure 4g). We observe two regimes for dwell time evolution as a function of the applied voltage. Dwell times increase with voltage up to 60 mV for OXT and up to 40 mV for OXT-FA. After these two threshold voltages, we observe a drastic decrease in dwell times, indirectly showing that the peptides translocate the pore. Indeed, the reduction in dwell times occurs at a lower
voltage for OXT-FA (40 mV) than for OXT (60 mV), presumably due to the additional charge for
OXT.

We observe similar blocking levels for both mutant pores (Figure 4h). For OXT, the values are
constant between 30 and 130 mV, centered at 0.48 ± 0.01. This result could be due to the
antagonistic forces of EOF and EP. On the other hand, for OXT-FA, the blocking levels increase
from 0.48 ± 0.01 at 30 mV to 0.65 ± 0.01 at 130 mV. This increase is presumably due to the
different conformation (and locations) explored by the OXT-FA at different voltages; however,
a precise interpretation is not possible, as is common when flexible peptides interact with
nanopores.

We confirm this increase in discrimination between the two peptides by using the two mutant
pores and varying the peptide stoichiometry. At 70 mV, two peaks were observed for both
pores, one at 0.47 ± 0.02 and the other at 0.55 ± 0.05 (Supplementary Information Figures SI-
2h, j, m, and o). These values are the same as those previously found for OXT and OXT-FA. At
130 mV, both peaks were still present but with broader distributions and centered at 0.48 ±
0.03 and 0.62 ± 0.12. As previously discussed, each peak corresponds to those observed from
independent experiments in Figure 4. As expected, the relative amount of OXT-FA compared
to OXT increased when we varied the stoichiometry accordingly.
<figure><img src="image_6.png" /><figcaption>Figure 4: a) Detection of OXT and OXT-FA using the AeL D222K and E258R mutants. The different forces (EP, EOF) responsible for the capture and dynamics are shown. b) Current traces recorded at 130 mV for OXT (green) and OXT-FA (purple) with the AeL D222K mutant. c) Current traces recorded at 130 mV for OXT (magenta) and OXT-FA (cyan) with the AeL E258R mutant. d) Scatter plot of the dwell time versus blockade level for OXT (green, n = 873) and OXT-FA (purple, n = 1912) recorded at 130 mV with the D222K mutant. The histogram of the blockade level and the values of the Gaussian centers are also indicated in the figure. e) Scatter plot of the dwell time and blockade level for OXT (magenta, n = 2050) and OXT-FA (cyan, n = 2398) recorded at 130 mV with the E258R mutant. The histogram of the blockade level and the values of the Gaussian centers are also indicated in the figure. f) The frequency of the event, g) dwell time, and h) blockade level were compared to the applied voltage for OXT and OXT-FA detected with D222K (top) and E258R (bottom) pores, respectively. The buffer consisted of 4 M KCl and 25 mM Tris (pH 7.5), with a peptide concentration of 2 µM. Created in BioRender.</figcaption></figure>

As discussed throughout the paper, interpreting the capture frequency dependency and the dwell time on the applied voltage calls for competition between EOF and EP. However, EOF cannot be directly measured from experiments. Hence, to support our hypothesis on the role of EOF, we ran MD simulations of Ael WT and its two mutants to quantify the EOF at 1M KCl.
Under a positive voltage, the EOF for Ael WT is directed from cis to trans, see Figure 5a. The flow rate at 250 mV is ~4.5 molecules/ns, Figure 5b, which is relatively low compared with more charged pores, such as some MspA mutants⁶¹ and CytK⁵⁸ or aHL. This is expected since Ael WT does not present large uniformly charged regions, and, consequently, there is not a net prevalence of cation or anion accumulation in the pore as shown in Figure 5c, where mild accumulation of chloride ions is present just close to R220 and K238. Ael WT is also slightly anion-selective, in agreement with reversal potential experiments reported in the literature⁷⁰,⁷⁴, Supplementary Figure SI-6. Simulations at 4M confirm the direction of EOF, although high salt concentration makes interpreting anion selectivity less straightforward (see Supplementary Information Figure SI-7). However, as noted in previous publications⁷⁵,⁷⁶, at 4M, the molecular force field exhibits ion-pairing artifacts that strongly affect the transport properties of the solution. The same simulation protocol for the E258R and D222K mutants indicates a similar EOF (Figure 5b). Despite the charge accumulation, the mutation strongly alters the pore (Figure 5c), reflecting a complex connection between charge accumulation, pore shape, and EOF, as shown also by other MD studies on biological nanopores⁶¹. Among the possible causes of this nontrivial behavior, we note that the size of Arg and Lys, being larger than Glu and Asp, reduce the pore lumen. Additionally, particularly for D220R, the additional accumulation of chloride ions with respect to Ael WT is located in a region just after a constriction, potentially reducing the effectiveness of the electrohydrodynamic force in pushing the fluid through the pore.

The EOF estimation from MD can be used to understand if EOF or EP dominates the capture of OXT. To this purpose, we calculated $b_{eo/ep} = v_{eo}/v_{ep}$, the ratio between the EOF velocity $v_{eo}$ and the particle velocity due to EP ($v_{ep}$), via a simplified capture model⁷⁷. Assuming that in the cis compartment, both the electric field and the electroosmotic velocity are radial, their intensities go as follows:

$$v_{eo} = \frac{Q_{eo}}{2\pi r^2}, \quad E = \frac{l}{2\pi r^2 \sigma}$$

where $\sigma$ is the conductivity of the solution, $Q_{eo}$ the EOF volumetric flow rate, $l$ the electric current, and $r$ the distance from the pore entrance, so that $2\pi r^2$ is the area of a hemisphere centered in the pore entrance⁷⁷,⁷⁸. Estimating the electrophoretic velocity $v_{ep}$ is not straightforward since the molecule's charge is partially screened in a high salt concentration.
Consequently, the intensity of the EP is not simply $F = qE$ with $q$ the molecule's charge. One possibility to take into account the screening is to consider the Smoluchowski expression for electrophoretic mobility $u_{ep}$ that reads:

$$v_{ep} = \frac{\epsilon\zeta}{\mu} = \frac{q\lambda_D}{4\pi a^2\mu}$$

where $\epsilon$ is the dielectric constant and $\mu$ the viscosity of the solution. In the last equation, we used $\zeta = qw\lambda_D/\epsilon$ with $qw = q/(4\pi a^2)$, the average surface charge of the molecule modeled as a sphere of radius $a$. Once the electrophoretic mobility is given, the ratio of velocities reduces to

$$b_{eo/ep} = \frac{\sigma Q_{eo}}{v_{ep} I}$$

When applied to our 4M simulations for Ael WT, we get $b_{eo/ep} \approx 4.5$, i.e., EOF dominates the transport.

Despite the simplifying assumption, this theoretical argument provides a plausible explanation of the experimentally observed capture frequencies, Figure 2j. Since EOF dominates the capture, the difference in charge between OXT and OXT-FA does not affect the capture frequency. This argument also applies to the D222K and E258K mutants: the capture frequencies are very similar to Ael WT, see Figures 2j and 4f, consistent with the slight differences in EOF among the three nanopores estimated by our MD, see Figure 5b. The dwell times increase with the voltage for Ael WT, indicating that OXT does not translocate but exits from the cis side, Figure 2k. In contrast to frequencies, the dwell times for OXT and OXT-FA are quite different. This can also be tentatively explained in terms of EP and EOF. Since OXT-FA is neutral, only EOF is active. The larger the voltage, the larger the EOF that pushes the particle into the pore. Consequently, the OXT-FA requires more time to exit from the cis side as the voltage increases. EOF is also present for OXT, but, in addition to this, an EP directed from trans to cis is also active, so, again, there is a competition between EOF and EP. However, unlike what happens in the cis reservoir, EP is not negligible compared to EOF inside the pore. Indeed, when a molecule is in the nanopore, the EOF reduces and, consequently, EP becomes more relevant. EP facilitates the exit from the cis side, shortening the dwell time for OXT compared to OXT-FA. The dwell times for the D222K and the E258R mutants exhibit completely different behavior (see Figure 4g). The dwell time decreases for $\Delta V > 60$ mV, indicating that the particle now translocates. Simple arguments cannot describe this qualitative change in the transport process. It is presumably due to some internal rearrangements of the pore lumen that our
atomistic model does not capture. Nevertheless, the differences between OXT and OXT-FA may
still be interpreted in terms of EOF and EP. Indeed, the dwell time for OXT is longer than OXT-
FA because now the EP (that, as in the Ael WT, is directed from *trans* to *cis*) hinders the exit of
the molecules from the *trans* side.

<figure><img src="image_7.png" /><figcaption>Figure 5. a) Scheme of the MD simulation set-up. Ael is embedded in a lipid membrane. Cis and trans compartments contain an electrolyte solution (water and 1 M KCl, not shown), and periodic boundary conditions are applied in all three directions. Some charged residues exposed towards the pore lumen are highlighted in blue (Arg, R), light blue (Lys, K), red (Asp, D), and dark red (Glu, E). An electric field is applied parallel to the pore axis. b) EOF measured for ΔV = 250 mV. The electric field is directed from trans to cis, while the EOF from cis to trans suggests that the nanopores are anion-selective. c) Equilibrium (ΔV = 0) distribution of Chloride ions along a cross section of the pore lumen. For Ael WT, accumulation is evident close to R220 and K238. The two mutants exhibit additional accumulations near the two mutations.</figcaption></figure>

Conclusions

Oxytocin is a neuropeptide known for its role in lactation and social behavior. It is increasingly
recognized as potentially implicated in various pathologies, such as schizophrenia and autism.
However, the need for analytical techniques to routinely detect, study, and differentiate
oxytocin from analogs limits its use as a biomarker.

This work used AeL nanopores to detect, study, and differentiate between oxytocin and an
analog varying only by one chemical group (amidation) called oxytocin-free acid. For wt AeL,
the results showed that these two peptides do not translocate but instead remain trapped at
the entrance and are mainly transported by electroosmotic flow (EOF). Although the single
chemical difference between the two peptides did not affect their capture, it did influence
their dynamics because of the addition of the EP due to the net charge of OXT. When the
molecule is in the pore, the EOF is drastically reduced (Figure SI-1). Consequently, the total
force acting on the OXT is now the result of a competition between EP and this reduced EOF.
Since the neutral OXT-FA is not affected by the *trans-cis* EP, this reduced EOF continues to
dominate, resulting in longer dwell times. Voltage-mediated tuning of the relative intensity of
these opposing forces allowed different populations of blockade levels to be observed for both
molecules, which could be due to specific conformations. Mutant peptides lacking specific
secondary structural features (disulfide bond, beta-turn) were also used to understand the
signals observed. We then employed two Ael mutants (D222K, E258R), showing improved
discrimination between OXT and OXT-FA. Finally, the possibility of identifying both molecules
with WT, D222K, and E258R Ael in a mix with different peptide concentrations demonstrates
the feasibility of our approach to identifying OXT and its analogs accurately. This study
demonstrates that nanopore technology can characterize and study oxytocin and its
conformational analogs in single-molecule form without labeling. This could pave the way for
studying these molecules' roles in pathological contexts and their potential use as biomarkers
for related diseases.

**Methods/Experimental**

Chemicals

Tris(hydroxymethyl)aminomethane (ThermoFisher, J65594), guanidine hydrochloride (Sigma, G4505), Potassium chloride (ThermoFisher, 11595), Trypsin beads (ThermoFisher, 20230), Zeba spin desalting column (ThermoFisher, 89882), Nickel Beads (Protino, 2203). Diphytanoylphosphatidylcholine (Avanti Polar Lipids, Alabaster, AL, USA)

Peptides

The following peptides were purchased from ProteoGenix or Clinisience: oxytocin (MW: 1007.19 Da, sequence: CYIQNCPLG-NH₂), oxytocin free acid (MW: 1008.18 Da, sequence: CYIQNCPLG), OXT Serine (977.07 Da, sequence: SYIQNSPLG-NH₂), OXT-FA Serine (978.06 Da, sequence: SYIQNSPLG), OXT Pro7ala (No S-S) (MW: 951.03 Da, sequence: SYIQNSALG-NH₂), and OXT-FA Pro7Ala (No S-S) (MW: 952.02 Da, sequence: SYIQNSALG). They were solubilized in 25 mM Tris (pH 7.4) to 1 mM and 10 mM concentrations and then stored at -20°C.

Protein Production

Proaerolysin was produced by DreamPore SAS (Cergy, France), and the complete protocol was described previously with slight differences. BL21 Ros 2 Cells from MiliporeSigma were used to express the C-terminal histagged protein in the periplasm. The proteins were harvested using an 18% sucrose solution to induce osmotic shock. Nickel affinity and buffer exchange chromatography were used to purify proaerolysin in standard buffers (350 mM NaCl, Cytiva, Malborough, MA, USA). The proaerolysin was stored at 4°C before activation with trypsin-bound beads (Thermo Scientific, Waltham, MA, USA). The activated aerolysin was used in nanopore experiments with a final concentration between 0.5 and 4 nM (monomers equivalent). After activation, aerolysin was used for a maximum of one month. This protocol is the same for Aerolysin WT, D222K, and E258R.

Nanopore Experiments
A vertical planar lipid bilayer setup (Warner Instruments, Hamden, CT, USA) with a 150 µM aperture was used to conduct nanopore experiments. Diphytanoylphosphatidylcholine (DphPC, Avanti Polar Lipids, Alabaster AL USA) lipids were dissolved in decane at a final concentration of 10 mg/ml to form a planar lipid bilayer separating the two reservoirs containing electrolyte solution (1 ml of 4 M KCl, 25 mM Tris, pH 7.4 or 1 ml of 3.5 M KCl, 25 mM Tris, 1 M Gdn-HCl, pH 7.4). The different peptides were added to both reservoirs at the beginning of the experiments. Once a single aerolysin was inserted into the membrane, recordings at different voltages were conducted using Ag/AgCl electrodes.

## Data Acquisition and Analysis

Axopatch 200B and Digidata 1440 were used to conduct electrical measurements. The data were recorded using a sampling frequency of 250 kHz, a 5 kHz Bessel filter, and Clampex software (Axon Instruments, Union City, CA, USA). Subsequently, Igor Pro software (Wavemetrics, Portland, OR, USA) was used to process the recorded data. Homemade protocols were employed to clean the data and identify and extract event parameters, such as baseline level ($I_0$), average blockade fraction (DI), noise intra-event ($\sigma$), dwell time (DT), and the location of the event in the dataset. These parameters were then used to analyze the peptide dynamics further. The open current ($I_0$) was determined statistically for each recording. Blockage events were defined using a threshold of $I_0$ -5$S_{current}$. Multiple recordings were concatenated in cases of low event frequency to ensure robust statistics. Events of interest were selected, excluding those caused by electrical noise or enzymatic digestion during activation. Only events with a duration longer than 120 µs and a blockade level above 0.3 were chosen for frequency analysis (Supplementary Information Figure SI-8). This analysis shows a classical linear frequency increase with peptide concentration (Supplementary Information Figure SI-9). The blockade level histograms (DI/$I_0$) were binned at 0.0025, and the overall blockade level for different event populations was determined using Gaussian fits. The most probable dwell time for events from a single population was determined using an exponential fit to adjust the number of events versus the event duration. To establish the frequency of event population, a semi-log distribution of interevent time (binned at 100 ms) was fit using a single exponential function. At least 1000 events were used to analyze all the data, and the average and standard deviation of individual fits were determined from three independent fits. All experiments presented in this manuscript were realized at least in duplicate, and examples of the fits for the three pores (WT, D222K, E258R) are provided in Supplementary Information Figure SI-10.

## MD Pore and membrane system set-up and equilibration

The homo heptameric Aerolysin pore⁷⁹ (PDBID: 5JZT), was aligned along the z axis of our coordinate system and inserted in a POPC bilayer membrane, parallel to the x-y plane, with a previously described procedure⁸⁰,⁸¹. Single chain mutants, D222K and E258R, were obtained using VMD⁸² mutate function on corresponding residues prior to assembly in the heptameric channel. The residue E237 was patched as protonated since it is exposed to the membrane lipids. All the other titratable side chains were put in their corresponding state for neutral pH. Depending on the appropriate system, the simulation box was filled with water and KCl at the final concentration of 1 M or 4 M. Energy minimization and system equilibration were obtained with the protocol described in⁵⁸,⁶². Briefly, after minimization, a first equilibration step (NPT, with P=1 atm and T=300 K) was run to let the lipid tails and the electrolyte relax. External forces were applied to the water molecules to avoid their penetration into the membrane,
while the backbone of the protein and the lipid heads were harmonically constrained. A
second equilibration run was performed to compact the membrane, reducing the spring
constant on the protein backbone and removing the constraints on lipid heads. The last
equilibration step is an NPT run without constraints. At the end of the equilibration procedure,
the periodic box has approximately the size given by: Lx = Ly = 174 Å, and Lz = 178 Å, for around
554,000 atoms.

Molecular Dynamics production runs and analyses.

MD runs were performed using NAMD (version 2.14<sup>83</sup> with the CHARMM36 force field<sup>84</sup> . The water model used is TIP3P<sup>85</sup>, and non-bonded fix corrections were applied for ions<sup>86</sup> . A time step of &Delta;t = 2.0 fs was used, and long-range electrostatic interactions were evaluated via the particle mesh Ewald method<sup>87</sup> with a 1 Å spaced grid. A cut-off of 12 Å with a switching distance of 14 Å was set for the short-range non-bonded interactions, and periodic boundary conditions along the three directions were imposed. All covalent bonds with hydrogen were kept rigid, using SETTLE<sup>88</sup> for water molecules and SHAKE/RATTLE<sup>89</sup> for the rest of the system. A Langevin thermostat was used for all the simulations, and a Nos&egrave;-Hoover Langevin piston pressure control was used for constant pressure simulations during the equilibration steps<sup>90</sup> . Non-equilibrium production runs were performed applying a constant electric field along the z coordinate Ez, simulating a voltage drop of &Delta;V=EzLz, with Lz the height of the box<sup>58</sup>. Harmonic constraints, with spring constant kb = 10 kcal/(mol &Aring;<sup>2</sup>), were imposed on two protein C&alpha; atoms (residues 183 and 206 residing on the extracellular domain) and all lipid phosphorus atoms. A thermostat was applied to the lipid and protein atoms. Ionic and electroosmotic currents were obtained with standard protocols reported in references<sup>58,62,80</sup>. Block averages were used to estimate uncertainties. 3D ion concentration and charge density fields were calculated via VMD Volmap<sup>82</sup>, on a cubic grid of side 1Å, averaging over the stationary state of the non-equilibrium runs. The 3D Cartesian fields were mapped to a cylindrical coordinate system (r, z, &theta;) and averaged on &theta; to get density fields in the (r, z) plane. Equilibrium (no voltage) runs were 80 ns long, while nonequilibrium ones were 200 ns long. Each system was replicated entirely independently five times.

Acknowledgments

This work was supported by ANR JCJC "QuaBioNHy" No. ANR-23-CE44-0013 granted to BC. MC and BMDR acknowledge the CINECA awards under the ISCRA initiative for the availability of high-performance computing resources and support for projects IsB29_ENATOPS2 and IsCa9_EOFMUF. MC and BMDR acknowledge the grant PRIN 2022 2022AJT27Y_001 from Ministero dell'Università e della Ricerca. BMDR acknowledges support from the RSA2024-B grant N-RAID from Tor Vergata University.

**Supporting information**
The supporting information is composed of the following figures:

**Figure SI-1:** Electrophoresis (EP) vs Electroosmosis (EOF) in analyte capture and residence.

**Figure SI-2:** Detection of OXT and OXT-FA using AeL WT in a mixture at an equimolar concentration and at a ratio of OXT 1 to 1.4 OXT-FA. **Figure SI-3:** Mutant peptides identified in an AeL WT nanopore. **Figure SI-4:** AeL WT and the mutants used (D222K and E258R). **Figure SI-5:** Current traces for OXT and OXT-FA recorded at 70 mV with a D222K and E258R AeL pores.

**Figure SI-6:** Additional MD data for AeL WT, AeL D222K, and AeL E258R in 1 M KCl. **Figure SI-7:**

MD data for simulations with 4M KCl at ΔV=250 mV. **Figure SI-8:** Scatter plot showing the blockade levels versus event durations when no peptide is present at 70 mV for a wt aerolysin pore.

**Figure SI-9:** Event frequencies as a function of OXT-FA concentration recorded at 70 mV in an AeL WT nanopore. **Figure SI-10:** Event number as a function of inter-event duration at 50, 70, and 130 mV for AeL WT, AeL D222K, and AeL E258R.

## References

(1) Argiolas, A.; Gessa, G. L. Central Functions of Oxytocin. *Neurosci. Biobehav. Rev.* **1991**, *15* (2), 217–231. https://doi.org/10.1016/s0149-7634(05)80002-8

(2) Heinrichs, M.; Dawans, B. von; Domes, G. Oxytocin, Vasopressin, and Human Social Behavior. *Front. Neuroendocr.* **2009**, *30* (4), 548–557. https://doi.org/10.1016/j.yfrne.2009.05.005

(3) McQuaid, R. J.; McInnis, O. A.; Abizaid, A.; Anisman, H. Making Room for Oxytocin in Understanding Depression. *Neurosci. Biobehav. Rev.* **2014**, *45*, 305–322. https://doi.org/10.1016/j.neubiorev.2014.07.005

(4) Scantamburlo, G.; Hansenne, M.; Fuchs, S.; Pitchot, W.; Maréchal, P.; Pequeux, C.; Ansseau, M.; Legros, J. J. Plasma Oxytocin Levels and Anxiety in Patients with Major Depression. *Psychoneuroendocrinology* **2007**, *32* (4), 407–410. https://doi.org/10.1016/j.psyneuen.2007.01.009

(5) Hernández-Díaz, Y.; González-Castro, T. B.; Tovilla-Zárate, C. A.; López-Narváez, M. L.; Genis-Mendoza, A. D.; Castillo-Avila, R. G.; Ramos-Méndez, M. Á.; Juárez-Rojop, I. E. Oxytocin Levels in Individuals with Schizophrenia Are High in Cerebrospinal Fluid but Low in Serum: A Systematic Review and Meta-Analysis: Oxytocin and Schizophrenia. *Metab. Brain Dis.* **2021**, *36* (8), 2415–2424. https://doi.org/10.1007/s11011-021-00836-y

(6) Beckmann, H.; Lang, R. E.; Gattaz, W. F. Vasopressin-Oxytocin in Cerebrospinal Fluid of Schizophrenic Patients and Normal Controls. *Psychoneuroendocrinology* **1985**, *10* (2), 187–191. https://doi.org/10.1016/0306-4530(85)90056-3

(7) Linkowski, P.; Geenen, V.; Kerkhofs, M.; Mendlewicz, J.; Legros, J. J. Cerebrospinal Fluid Neurophysins in Affective Illness and in Schizophrenia. *Eur. Arch. psychiatry Neurol. Sci.* **1984**, *234* (3), 162–165. https://doi.org/10.1007/bf00461555
(8) Hollander, E.; Novotny, S.; Hanratty, M.; Yaffe, R.; DeCaria, C. M.; Aronowitz, B. R.; Mosovich, S. Oxytocin Infusion Reduces Repetitive Behaviors in Adults with Autistic and Asperger's Disorders. *Neuropsychopharmacology* **2003**, *28* (1), 193–198.
https://doi.org/10.1038/sj.npp.1300021.

(9) Vanya, M.; Szucs, S.; Vetro, A.; Bartfai, G. The Potential Role of Oxytocin and Perinatal Factors in the Pathogenesis of Autism Spectrum Disorders – Review of the Literature. *Psychiatry Res.* **2017**, *247*, 288–290. https://doi.org/10.1016/j.psychres.2016.12.007.

(10) Menon, R.; Neumann, I. D. Detection, Processing and Reinforcement of Social Cues: Regulation by the Oxytocin System. *Nat. Rev. Neurosci.* **2023**, *24* (12), 761–777.
https://doi.org/10.1038/s41583-023-00759-w.

(11) Durisko, Z.; Mulsant, B. H.; Andrews, P. W. An Adaptationist Perspective on the Etiology of Depression. *J. Affect. Disord.* **2015**, *172*, 315–323.
https://doi.org/10.1016/j.jad.2014.09.032.

(12) Zeidan, J.; Fombonne, E.; Scorah, J.; Ibrahim, A.; Durkin, M. S.; Saxena, S.; Yusuf, A.; Shih, A.; Elsabbagh, M. Global Prevalence of Autism: A Systematic Review Update. *Autism Res.* **2022**, *15* (5), 778–790. https://doi.org/10.1002/aur.2696.

(13) Lim, G. Y.; Tam, W. W.; Lu, Y.; Ho, C. S.; Zhang, M. W.; Ho, R. C. Prevalence of Depression in the Community from 30 Countries between 1994 and 2014. *Sci. Rep.* **2018**, *8* (1), 2861. https://doi.org/10.1038/s41598-018-21243-x.

(14) Vigo, D.; Thornicroft, G.; Atun, R. Estimating the True Global Burden of Mental Illness. *Lancet Psychiatry* **2016**, *3* (2), 171–178. https://doi.org/10.1016/S2215-0366(15)00505-2.

(15) Russell, J. A. Fifty Years of Advances in Neuroendocrinology. *Brain Neurosci. Adv.* **2018**, *2*, 2398212818812014. https://doi.org/10.1177/2398212818812014.

(16) Gainer, H. Cell-Type Specific Expression of Oxytocin and Vasopressin Genes: An Experimental Odyssey. *J. Neuroendocr.* **2012**, *24* (4), 528–538. https://doi.org/10.1111/j.1365-2826.2011.02236.x.

(17) Li, M.-Y.; Miao, W.-Y.; Wu, Q.-Z.; He, S.-J.; Yan, G.; Yang, Y.; Liu, J.-J.; Taketo, M. M.; Yu, X. A Critical Role of Presynaptic Cadherin/Catenin/P140Cap Complexes in Stabilizing Spines and Functional Synapses in the Neocortex. *Neuron* **2017**, *94* (6), 1155-1172.e8.
https://doi.org/10.1016/j.neuron.2017.05.022.

(18) Talpo, F.; Spaiardi, P.; Castagno, A. N.; Maniezzi, C.; Raffin, F.; Terribile, G.; Sancini, G.; Pisani, A.; Biella, G. R. Neuromodulatory Functions Exerted by Oxytocin on Different Populations of Hippocampal Neurons in Rodents. *Front. Cell. Neurosci.* **2023**, *17*, 1082010.
https://doi.org/10.3389/fncel.2023.1082010.

(19) Arrowsmith, S.; Wray, S. Oxytocin: Its Mechanism of Action and Receptor Signalling in the Myometrium. *J. Neuroendocr.* **2014**, *26* (6), 356–369. https://doi.org/10.1111/jne.12154.

(20) Kohlhoff, J.; Cibralic, S.; Hawes, D. J.; Eapen, V. Oxytocin Receptor Gene (OXTR) Polymorphisms and Social, Emotional and Behavioral Functioning in Children and Adolescents:
A Systematic Narrative Review. *Neurosci. Biobehav. Rev.* **2022**, *135*, 104573.
https://doi.org/10.1016/j.neubiorev.2022.104573.

(21) Jurek, B.; Neumann, I. D. The Oxytocin Receptor: From Intracellular Signaling to Behavior. *Physiol. Rev.* **2018**, *98* (3), 1805–1908. https://doi.org/10.1152/physrev.00031.2017.

(22) Walter, R.; Schwartz, I. L.; Darnell, J. H.; Urry, D. W. Relation of the Conformation of Oxytocin to the Biology of Neurohypophyseal Hormones. *Proc. Natl. Acad. Sci.* **1971**, *68* (6), 1355–1359. https://doi.org/10.1073/pnas.68.6.1355.

(23) Lee, H.-J.; Macbeth, A. H.; Pagani, J. H.; Young, W. S. Oxytocin: The Great Facilitator of Life. *Prog. Neurobiol.* **2009**, *88* (2), 127–151. https://doi.org/10.1016/j.pneurobio.2009.04.001.

(24) Kotelchuck, D.; Scheraga, H. A.; Walter, R. Conformational Energy Studies of Oxytocin and Its Cyclic Moiety. *Proc. Natl. Acad. Sci.* **1972**, *69* (12), 3629–3633.
https://doi.org/10.1073/pnas.69.12.3629.

(25) Rudinger, J. Synthetic Analogues of Oxytocin: An Approach to Problems of Hormone Action. *Proc. R. Soc. Lond. Ser. B Biol. Sci.* **1968**, *170* (1018), 17–26.
https://doi.org/10.1098/rspb.1968.0020.

(26) Sawyer, W. H.; Manning, M. Synthetic Analogs of Oxytocin and the Vasopressins. *Annu. Rev. Pharmacol.* **1973**, *13* (1), 5–17. https://doi.org/10.1146/anurev.pa.13.040173.000253.

(27) Camerino, C. The Long Way of Oxytocin from the Uterus to the Heart in 70 Years from Its Discovery. *Int. J. Mol. Sci.* **2023**, *24* (3), 2556. https://doi.org/10.3390/ijms24032556.

(28) Moberg, K. U.; Handlin, L.; Kendall-Tackett, K.; Petersson, M. Oxytocin Is a Principal Hormone That Exerts Part of Its Effects by Active Fragments. *Méd. Hypotheses* **2019**, *133*, 109394. https://doi.org/10.1016/j.mehy.2019.109394.

(29) Green, L.; Fein, D.; Modahl, C.; Feinstein, C.; Waterhouse, L.; Morris, M. Oxytocin and Autistic Disorder: Alterations in Peptide Forms. *Biol. Psychiatry* **2001**, *50* (8), 609–613.
https://doi.org/10.1016/S0006-3223(01)01139-8.

(30) Yonekura, H.; Kato, I.; Yamamoto, Y.; Ikeda, T.; Higashida, H.; Okamoto, H. Biosynthesis and Function of VIP and Oxytocin: Mechanisms of C-Terminal Amidation, Oxytocin Secretion and Transport. *Endocrinology* **2023**, *164* (9). https://doi.org/10.1210/en-docr/bqad121.

(31) Glass, J. D.; Schwartz, I. L.; Walter, R. ENZYMATIC INACTIVATION OF PEPTIDE HORMONES POSSESSING A C-TERMINAL AMIDE GROUP*. *Proc. Natl. Acad. Sci.* **1969**, *63* (4), 1426–1430. https://doi.org/10.1073/pnas.63.4.1426.

(32) MacLean, E. L.; Wilson, S. R.; Martin, W. L.; Davis, J. M.; Nazarloo, H. P.; Carter, C. S. Challenges for Measuring Oxytocin: The Blind Men and the Elephant? *Psychoneuroendocrinology* **2019**, *107*, 225–231. https://doi.org/10.1016/j.psyneuen.2019.05.018.
(33) Sturgeon, C. M.; Viljoen, A. Analytical Error and Interference in Immunoassay: Minimizing Risk. *Ann. Clin. Biochem.* **2011**, *48* (5), 418–432.
https://doi.org/10.1258/acb.2011.011073.

(34) Tate, J.; Ward, G. Interferences in Immunoassay. *Clin. Biochem. Rev.* **2004**, *25* (2), 105–120.

(35) Li, M.; Josephs, R. D.; Daireaux, A.; Choteau, T.; Westwood, S.; Martos, G.; Wielgosz, R. I.; Li, H. Structurally Related Peptide Impurity Identification and Accurate Quantification for Synthetic Oxytocin by Liquid Chromatography–High-Resolution Mass Spectrometry. *Anal. Bioanal. Chem.* **2021**, *413* (7), 1861–1870. https://doi.org/10.1007/s00216-021-03154-5.

(36) Lefevre, A.; Mottolese, R.; Dirheimer, M.; Mottolese, C.; Duhamel, J.-R.; Sirigu, A. A Comparison of Methods to Measure Central and Peripheral Oxytocin Concentrations in Human and Non-Human Primates. *Sci. Rep.* **2017**, *7* (1), 17222. https://doi.org/10.1038/s41598-017-17674-7.

(37) Tabak, B. A.; Leng, G.; Szeto, A.; Parker, K. J.; Verbalis, J. G.; Ziegler, T. E.; Lee, M. R.; Neumann, I. D.; Mendez, A. J. Advances in Human Oxytocin Measurement: Challenges and Proposed Solutions. *Mol. Psychiatry* **2023**, *28* (1), 127–140.
https://doi.org/10.1038/s41380-022-01719-z.

(38) Restrepo-Pérez, L.; Huang, G.; Bohländer, P. R.; Worp, N.; Eelkema, R.; Maglia, G.; Joo, C.; Dekker, C. Resolving Chemical Modifications to a Single Amino Acid within a Peptide Using a Biological Nanopore. *ACS Nano* **2019**, *13* (12), 13668–13676.
https://doi.org/10.1021/acsnano.9b05156.

(39) Ying, Y.-L.; Yang, J.; Meng, F.-N.; Li, S.; Li, M.-Y.; Long, Y.-T. A Nanopore Phosphorylation Sensor for Single Oligonucleotides and Peptides. *Research (Wash D C)* **2019**, *2019* (8), 1050735–1050738. https://doi.org/10.34133/2019/1050735.

(40) Meng, F.-N.; Ying, Y.-L.; Yang, J.; Long, Y.-T. A Wild-Type Nanopore Sensor for Protein Kinase Activity. *Anal Chem* **2019**, *91* (15), 9910–9915. https://doi.org/10.1021/acs.anal-chem.9b01570.

(41) Ensslen, T.; Sarthak, K.; Aksimentiev, A.; Behrends, J. C. Resolving Isomeric Posttranslational Modifications Using a Biological Nanopore as a Sensor of Molecular Shape. *J Am Chem Soc* **2022**, *144* (35), 16060–16068. https://doi.org/10.1021/jacs.2c06211.

(42) Versloot, R. C. A.; Lucas, F. L. R.; Yakovlieva, L.; Tadema, M. J.; Zhang, Y.; Wood, T. M.; Martin, N. I.; Marrink, S. J.; Walvoort, M. T. C.; Maglia, G. Quantification of Protein Glycosylation Using Nanopores. *Nano Lett* **2022**, *22* (13), 5357–5364.
https://doi.org/10.1021/acs.nanolett.2c01338.

(43) Stierlen, A.; Greive, S. J.; Bacri, L.; Manivet, P.; Cressiot, B.; Pelta, J. Nanopore Discrimination of Coagulation Biomarker Derivatives and Characterization of a Post-Translational Modification. *Acs Central Sci* **2023**, *9* (2), 228–238.
https://doi.org/10.1021/acscentsci.2c01256.
(44) Chang, J.; Gao, Y.; Zou, A.; Li, M.; Long, Y.; Jiang, J. Precise Identification of Native Peptides with Posttranslational Proline Hydroxylation by Nanopore. *Angew. Chem. 2025*, *137*(9). https://doi.org/10.1002/ange.202422692.

(45) Niu, H.; Li, M.-Y.; Gao, Y.; Li, J.-G.; Jiang, J.; Ying, Y.-L.; Long, Y.-T. Direct Mapping of Tyrosine Sulfation States in Native Peptides by Nanopore. *Nat. Chem. Biol. 2025*, *21* (5), 716–726. https://doi.org/10.1038/s41589-024-01734-x.

(46) Cao, C.; Magalhães, P.; Krapp, L. F.; Juarez, J. F. B.; Mayer, S. F.; Rukes, V.; Chiki, A.; Lashuel, H. A.; Peraro, M. D. Deep Learning-Assisted Single-Molecule Detection of Protein Post-Translational Modifications with a Biological Nanopore. *ACS Nano* **2023**, *18* (2), 1504–1515. https://doi.org/10.1021/acsnano.3c08623.

(47) Li, S.; Wu, X.; Li, M.; Liu, S.; Ying, Y.; Long, Y. T232K/K238Q Aerolysin Nanopore for Mapping Adjacent Phosphorylation Sites of a Single Tau Peptide. *Small Methods* **2020**, *4* (11). https://doi.org/10.1002/smtd.202000014.

(48) Versloot, R. C. A.; Arias-Orozco, P.; Tadema, M. J.; Lucas, F. L. R.; Zhao, X.; Marrink, S. J.; Kuipers, O. P.; Maglia, G. Seeing the Invisibles: Detection of Peptide Enantiomers, Diastereomers, and Isobaric Ring Formation in Lanthipeptides Using Nanopores. *J. Am. Chem. Soc. 2023*, *145* (33), 18355–18365. https://doi.org/10.1021/jacs.3c04076.

(49) Ratinho, L.; Bacri, L.; Thiebot, B.; Cressiot, B.; Pelta, J. Identification and Detection of a Peptide Biomarker and Its Enantiomer by Nanopore. *ACS Cent. Sci. 2024*, *10* (6), 1167–1178. https://doi.org/10.1021/acscentsci.4c00020.

(50) Iesu, L.; Sai, M.; Torbeev, V.; Kieffer, B.; Pelta, J.; Cressiot, B. Single-Molecule Nanopore Sensing of Proline Cis/Trans Amide Isomers. *Chem. Sci.* **2025**. https://doi.org/10.1039/d5sc01156f.

(51) Liu, W.; Zhu, Q.; Yang, C.-N.; Fu, Y.-H.; Zhang, J.-C.; Li, M.-Y.; Yang, Z.-L.; Xin, K.-L.; Ma, J.; Winterhalter, M.; Ying, Y.-L.; Long, Y.-T. Single-Molecule Sensing inside Stereo- and Regio-Defined Hetero-Nanopores. *Nat. Nanotechnol.* **2024**, *19* (11), 1693–1701. https://doi.org/10.1038/s41565-024-01721-2.

(52) Sutherland, T. C.; Long, Y.-T.; Stefureac, R.-I.; Bediako-Amoa, I.; Kraatz, H.-B.; Lee, J. S. Structure of Peptides Investigated by Nanopore Analysis. *Nano Lett* **2004**, *4* (7), 1273–1277. https://doi.org/10.1021/nl049413e.

(53) Stefureac, R. I.; Lee, J. S. Nanopore Analysis of the Folding of Zinc Fingers. *Small* **2008**, *4* (10), 1646–1650. https://doi.org/10.1002/smll.200800585.

(54) Ratinho, L.; Meyer, N.; Greive, S.; Cressiot, B.; Pelta, J. Nanopore Sensing of Protein and Peptide Conformation for Point-of-Care Applications. *Nat. Commun.* **2025**, *16* (1), 3211. https://doi.org/10.1038/s41467-025-58509-8.

(55) Zhang, S.; Wang, Y.; Song, D.; Guan, S.; Zhou, D.; Gong, L.; Liang, L.; Guan, X.; Wang, L. Nanopore Discrimination and Sensitive Plasma Detection of Multiple Natriuretic Peptides: The Representative Biomarker of Human Heart Failure. *Biosens. Bioelectron.* **2023**, *231*, 115299. https://doi.org/10.1016/j.bios.2023.115299.
(56) Cressiot, B.; Bacri, L.; Pelta, J. The Promise of Nanopore Technology: Advances in the Discrimination of Protein Sequences and Chemical Modifications. *Small Methods* **2020**, *4* (11), 2000090. https://doi.org/10.1002/smtd.202000090.

(57) Meyer, N.; Abrao-Nemeir, I.; Janot, J.-M.; Torrent, J.; Lepoitevin, M.; Balme, S. Solid-State and Polymer Nanopores for Protein Sensing: A Review. *Adv. Colloid Interface Sci.* **2021**, *298*, 102561. https://doi.org/10.1016/j.cis.2021.102561.

(58) Sauciuc, A.; Rocca, B. M. della; Tadema, M. J.; Chinappi, M.; Maglia, G. Translocation of Linearized Full-Length Proteins through an Engineered Nanopore under Opposing Electro-phoretic Force. *Nat. Biotechnol.* **2024**, *42* (8), 1275-1281. https://doi.org/10.1038/s41587-023-01954-x.

(59) Wen, C.; Schmid, S.; Dekker, C. Understanding Electrophoresis and Electroosmosis in Nanopore Sensing with the Help of the Nanopore Electro-Osmotic Trap. *ACS Nano* **2024**, *18* (31), 20449-20458. https://doi.org/10.1021/acsnano.4c04788.

(60) Gubbiotti, A.; Baldelli, M.; Muccio, G. D.; Malgaretti, P.; Marbach, S.; Chinappi, M. Electroosmosis in Nanopores: Computational Methods and Technological Applications. *Adv. Phys.: X* **2022**, *7* (1), 2036638. https://doi.org/10.1080/23746149.2022.2036638.

(61) Baldelli, M.; Muccio, G. D.; Sauciuc, A.; Rocca, B. M. della; Viola, F.; Balme, S.; Bonini, A.; Maglia, G.; Chinappi, M. Controlling Electroosmosis in Nanopores Without Altering the Nanopore Sensing Region. *Adv. Mater.* **2024**, *36* (33), e2401761. https://doi.org/10.1002/adma.202401761.

(62) Muccio, G. D.; Rocca, B. M. della; Chinappi, M. Geometrically Induced Selectivity and Unidirectional Electroosmosis in Uncharged Nanopores. *ACS Nano* **2022**, *16* (6), 8716-8728. https://doi.org/10.1021/acsnano.1c03017.

(63) Piguet, F.; Ouldali, H.; Pastoriza-Gallego, M.; Manivet, P.; Pelta, J.; Oukhaled, A. Identification of Single Amino Acid Differences in Uniformly Charged Homopolymeric Peptides with Aerolysin Nanopore. *Nature Communications* **2018**, *9* (1). https://doi.org/10.1038/s41467-018-03418-2.

(64) Cressiot, B.; Ouldali, H.; Pastoriza-Gallego, M.; Bacri, L.; Goot, F. G. V. der; Pelta, J. Aerolysin, a Powerful Protein Sensor for Fundamental Studies and Development of Upcom-ing Applications. *Acs Sensors* **2019**, *4* (3), 530-548. https://doi.org/10.1021/acssen-sors.8b01636.

(65) Xin, K.-L.; Hu, Z.-L.; Liu, S.-C.; Li, X.-Y.; Li, J.-G.; Niu, H.; Ying, Y.-L.; Long, Y.-T. 3D Blockage Mapping for Identifying Familial Point Mutations in Single Amyloid-β Peptides with a Nanopore. *Angewandte Chemie Int Ed* **2022**. https://doi.org/10.1002/anie.202209970.

(66) Greive, S. J.; Bacri, L.; Cressiot, B.; Pelta, J. Identification of Conformational Variants for Bradykinin Biomarker Peptides from a Biofluid Using a Nanopore and Machine Learning. *ACS Nano* **2024**, *18* (1), 539-550. https://doi.org/10.1021/acsnano.3c08433.
(67) Niu, H.; Li, M.-Y.; Ying, Y.-L.; Long, Y.-T. An Engineered Third Electrostatic Constriction of Aerolysin to Manipulate Heterogeneously Charged Peptide Transport. *Chem. Sci.* **2022**, *13* (8), 2456–2461. https://doi.org/10.1039/d1sc06459b.

(68) Huo, M.; Hu, Z.; Ying, Y.; Long, Y. Enhanced Identification of Tau Acetylation and Phosphorylation with an Engineered Aerolysin Nanopore. *Proteomics* **2022**, *22* (5–6), 2100041. https://doi.org/10.1002/pmic.202100041.

(69) Willems, K.; Ruić, D.; Biesemans, A.; Galenkamp, N. S.; Dorpe, P. V.; Maglia, G. Engineering and Modeling the Electrophoretic Trapping of a Single Protein Inside a Nanopore. *ACS Nano* **2019**, *13* (9), 9980–9992. https://doi.org/10.1021/acsnano.8b09137.

(70) Versloot, R. C. A.; Straathof, S. A. P.; Stouwie, G.; Tadema, M. J.; Maglia, G. B-Barrel Nanopores with an Acidic–Aromatic Sensing Region Identify Proteinogenic Peptides at Low PH. *Acs Nano* **2022**, *16* (5), 7258–7268. https://doi.org/10.1021/acsnano.1c11455.

(71) Stefureac, R.; Long, Y.-T.; Kraatz, H.-B.; Howard, P.; Lee, J. S. Transport of Alpha-Helical Peptides through Alpha-Hemolysin and Aerolysin Pores. *Biochemistry* **2006**, *45* (30), 9172–9179. https://doi.org/10.1021/bi0604835.

(72) Christensen, C.; Baran, C.; Krasniqi, B.; Stefureac, R. I.; Nokhrin, S.; Lee, J. S. Effect of Charge, Topology and Orientation of the Electric Field on the Interaction of Peptides with the α-Hemolysin Pore. *J Pept Sci* **2011**, n-a. https://doi.org/10.1002/psc.1393.

(73) Asandei, A.; Schiopu, I.; Chinappi, M.; Seo, C. H.; Park, Y.; Luchian, T. Electroosmotic Trap Against the Electrophoretic Force Near a Protein Nanopore Reveals Peptide Dynamics During Capture and Translocation. *Acs Appl Mater Inter* **2016**, *8* (20), 13166–13179. https://doi.org/10.1021/acsami.6b03697.

(74) Lu, W.; Zhao, X.; Li, M.; Li, Y.; Zhang, C.; Xiong, Y.; Li, J.; Zhou, H.; Ye, X.; Li, X.; Wang, J.; Liang, X.; Qing, G. Precise Structural Analysis of Neutral Glycans Using Aerolysin Mutant T240R Nanopore. *ACS Nano* **2024**, *18* (19), 12412–12426. https://doi.org/10.1021/acsnano.4c01571.

(75) Ouldali, H.; Sarthak, K.; Ensslen, T.; Piguet, F.; Manivet, P.; Pelta, J.; Behrends, J. C.; Aksimentiev, A.; Oukhaled, A. Electrical Recognition of the Twenty Proteinogenic Amino Acids Using an Aerolysin Nanopore. *Nature Biotechnology* **2019**, *31*, 247–6. https://doi.org/10.1038/s41587-019-0345-2.

(76) Comer, J.; Aksimentiev, A. Predicting the DNA Sequence Dependence of Nanopore Ion Current Using Atomic-Resolution Brownian Dynamics. *J. Phys. Chem. C* **2012**, *116* (5), 3376–3393. https://doi.org/10.1021/jp210641j.

(77) Chinappi, M.; Yamaji, M.; Kawano, R.; Cecconi, F. Analytical Model for Particle Capture in Nanopores Elucidates Competition among Electrophoresis, Electroosmosis, and Dielectrophoresis. *ACS Nano* **2020**, *14* (11), 15816–15828. https://doi.org/10.1021/acsnano.0c06981.
(78) Chinappi, M.; Luchian, T.; Cecconi, F. Nanopore Tweezers: Voltage-Controlled Trapping and Releasing of Analytes. *Phys. Rev. E* **2015**, *92* (3), 032714.
https://doi.org/10.1103/physreve.92.032714.

(79) Iacovache, I.; Carlo, S. D.; Cirauqui, N.; Peraro, M. D.; Goot, F. G. van der Zuber, B. Cryo-EM Structure of Aerolysin Variants Reveals a Novel Protein Fold and the Pore-Formation Process. *Nat Commun* **2016**, *7* (1), 12062. https://doi.org/10.1038/ncomms12062.

(80) Aksimentiev, A. A.; Schulten, K. K. Imaging Alpha-Hemolysin with Molecular Dynamics: Ionic Conductance, Osmotic Permeability, and the Electrostatic Potential Map. *Biophysical Journal* **2005**, *88* (6), 3745–3761. https://doi.org/10.1529/biophysj.104.058727.

(81) Bonome, E. L.; Cecconi, F.; Chinappi, M. Electroosmotic Flow through an α-Hemolysin Nanopore. *Microfluid. Nanofluidics* **2017**, *21* (5), 96. https://doi.org/10.1007/s10404-017-1928-1.

(82) Humphrey, W.; Dalke, A.; Schulten, K. VMD: Visual Molecular Dynamics. *J Mol Graph* **1996**, *14* (1), 33-8-27-28.

(83) Phillips, J. C.; Braun, R.; Wang, W.; Gumbart, J.; Tajkhorshid, E.; Villa, E.; Chipot, C.; Skeel, R. D.; Kalé, L.; Schulten, K. Scalable Molecular Dynamics with NAMD. *J Comput Chem* **2005**, *26* (16), 1781–1802. https://doi.org/10.1002/jcc.20289.

(84) Brooks, B. R.; Brooks, C. L.; Mackerell, A. D.; Nilsson, L.; Petrella, R. J.; Roux, B.; Won, Y.; Archontis, G.; Bartels, C.; Boresch, S.; Caflisch, A.; Caves, L.; Cui, Q.; Dinner, A. R.; Feig, M.; Fischer, S.; Gao, J.; Hodoscek, M.; Im, W.; Kuczera, K.; Lazaridis, T.; Ma, J.; Ovchinnikov, V.; Paci, E.; Pastor, R. W.; Post, C. B.; Pu, J. Z.; Schaefer, M.; Tidor, B.; Venable, R. M.; Woodcock, H. L.; Wu, X.; Yang, W.; York, D. M.; Karplus, M. CHARMM: The Biomolecular Simulation Program. *J. Comput. Chem.* **2009**, *30* (10), 1545–1614.
https://doi.org/10.1002/jcc.21287.

(85) Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. Comparison of Simple Potential Functions for Simulating Liquid Water. *J. Chem. Phys.* **1983**, *79* (2), 926–935. https://doi.org/10.1063/1.445869.

(86) Yoo, J.; Aksimentiev, A. Improved Parametrization of Li+, Na+, K+, and Mg2+ Ions for All-Atom Molecular Dynamics Simulations of Nucleic Acid Systems. *The Journal of Physical Chemistry Letters* **2012**, *3* (1), 45–50. https://doi.org/10.1021/jz201501a.

(87) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A Smooth Particle Mesh Ewald Method. *J. Chem. Phys.* **1995**, *103* (19), 8577–8593.
https://doi.org/10.1063/1.470117.

(88) Miyamoto, S.; Kollman, P. A. Settle: An Analytical Version of the SHAKE and RAT-TLE Algorithm for Rigid Water Models. *J. Comput. Chem.* **1992**, *13* (8), 952–962.
https://doi.org/10.1002/jcc.540130805.

(89) Andersen, H. C. Rattle: A “Velocity” Version of the Shake Algorithm for Molecular Dynamics Calculations. *J. Comput. Phys.* **1983**, *52* (1), 24–34. https://doi.org/10.1016/0021-9991(83)90014-1.
(90) Martyna, G. J.; Tobias, D. J.; Klein, M. L. Constant Pressure Molecular Dynamics Algorithms. *J. Chem. Phys.* **1994**, *101* (5), 4177–4189. https://doi.org/10.1063/1.467468.

<figure><img src="image_8.png" /><figcaption>Discrimination of oxytocin and its structural variants by nanopore</figcaption></figure>

For Table of Contents Only