Enzyme-less discrimination of chiral amino acids with femtoampere-level precision by proton-driven anthrax nanopore

Enzyme-less discrimination of chiral amino acids with femtoampere-level precision by proton-driven anthrax nanopore | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Enzyme-less discrimination of chiral amino acids with femtoampere-level precision by proton-driven anthrax nanopore Liang Wang, Yan Wang, Yunjiao Wang, Lebing Wang, Jing Li, Shilong Liu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6077470/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The precise detection of amino acids and the identification of their chirality are of paramount importance in protein sequencing, the design of druggable molecules, and the diagnosis of diseases based on protein damage. However, this remains an exceptionally challenging task. Herein, we developed a novel protein nanopore system based on anthrax protective antigen, a proton-driven transmembrane channel, for the discrimination of 20 proteinogenic amino acids and their chiral enantiomers. By employing a pH-asymmetric ionic liquids system instead of traditional salt conditions, we effectively resolved the intrinsic limitations (i.e., current fluctuation, low signal-to-noise ratio, gating phenomenon) of the wild-type anthrax nanopore in sensing activity. The optimized anthrax nanopore demonstrated exceptional sensitivity in differentiating amino acids as well as levorotary and dextrorotary enantiomers at femtoampere precision (< 100 fA). The discrimination mechanism of various amino acids through nanopore current signals can be attributed to the inhomogeneous intermolecular interactions—such as electrostatic forces, π-πinteractions, and hydrogen bonding—between the amino acids and the inner surface of the nanopore. These interactions, in conjunction with either electrophoretic forces or electroosmotic flow, collectively enable the differentiation of distinct amino acid types. Notably, the developed anthrax nanopore-based method eliminates the need for enzymes, chemical reactions, or machine learning algorithms. Instead, it relies solely on an optimized electrolyte system and the direct interpretation of nanopore current signatures to achieve chiral amino acid discrimination. This study provides an idea nanopore architecture that offers ultrahigh sensing resolution, a wide dynamic range of enantioselectivity, and specificity, thereby having implications in protein sequencing and making available a refined analytical tool for revealing properties of chiral molecules in diverse biological contexts. Biological sciences/Biotechnology/Nanobiotechnology/Nanopores Physical sciences/Chemistry/Analytical chemistry/Sensors Anthrax nanopore Proton-driven mechanism Protein sequencing Molecular chirality Femtoampere precision Figures Figure 1 Figure 2 Figure 3 Figure 6 Introduction Since the advancement of ultra-long read technologies for nucleic acids using nanopore sequencing, the field of protein sequencing has become increasingly pressing, and substantial research progress has been made based on nanopore protein analytics 1 – 5 . However, the main challenges in protein sequencing lie in how to capture and transport unfolded proteins (or long polypeptides) and ensure accurate identification of individual amino acids in the sequence during protein translocation. As demonstrated in prior studies, it has been established that monitoring of protein translocation is achievable by means of nanopore methods, which include enzymatic and enzyme-less processes. For instance, motor proteins combined with electrophoresis-driven force can ratchet protein translocation residue-by-residue in a nanopore 6 – 8 . Additionally, employing an electroosmotic flow can facilitate the translocation and recognition of unstructured native polypeptides, relying on the immobilization of charged groups (~ 1 nm apart) in the nanopore lumen 9 . Although these approaches show promise, implementing the direct and accurate identification of individual amino acids during protein unfolding and translocation remains more challenging due to the diversity of molecular structures. For example, protein linearization is hindered by the heterogeneous distribution of charges in protein sequences caused by the diversity of 20 amino acids. In addition, the presence of residue modifications, as well as chiral levorotatory and dextrorotatory enantiomers, poses additional challenges that must be overcome to achieve efficient identification 10 – 13 . It was demonstrated that some forms of nanopore fingerprinting will precede de novo sequencing because of the difficulty of fully decoding protein nanopore signals with single amino acid resolution 14 . Currently, the nanopore research community is making progress toward achieving high-resolution differentiation of the 20 amino acids and modifications. As notable examples, metal-ion-modified nanopores (Ni or Cu) were constructed to ensure the binding and recognition of amino acids. Subsequently, enzymes for polypeptide digestion were used to determine the presence of detached amino acids, while the translation of the raw complex current signals was achieved by machine learning algorithms 15 , 16 . Another prominent method for identifying amino acids involved artificially tailored peptide sequences with certain individual amino acids arranged consecutively. This strategy also involved enzymatic cleavage and machine learning to produce and analyze distinct current signals via host-guest interactions in a nanopore, corresponding to the 20 integrated amino acids 17 . Despite many benefits, it should be noted that these emerging methods all involve chemical reactions and require machine learning to improve detection resolution and the translation of complex current events. The chemical reactions (e.g., proteolysis or chelation) can provide precise recognition of specific amino acids (either through peptide bond cleavage or ion-residue coordination), but the efficiency largely depends on the reaction activity and the reaction time, and each enzyme or ion usually recognizes a few different amino acids in the reactions. Consequently, machine learning algorithms are employed to precisely decode the current signals for amino acid discrimination. Likewise, chemical reactions may also be limited in achieving the efficient detection and discrimination of chiral enantiomers. Hence, the search for new methods to circumvent algorithm-assisted nanopore amino acid decoding and to avoid chemical reactions in the detection process is attracting particular attention in nanopore-based amino acid discrimination and protein sequencing. Direct detection of single amino acids using an optimized electrolyte system is an ideal alternative solution to avoid the challenges of nanopore engineering and the limitations of chemical reaction efficiency due to time constraints. This strategy may incorporate electrophoretic force (EPF) and electroosmotic flow (EOF) as driving forces to facilitate the transport of all amino acids in an ideal biological nanopore with appropriate nanopore dimensions. Furthermore, this sensing strategy is adaptable to create highly specific and sensitive amino acid-recognition events with a high signal-to-noise ratio at sub-pA resolution levels, as well as a wide dynamic range of enantioselectivity. This should make it possible to accomplish rapid and direct signal readout in response to various amino acid molecules without the requirement of artificial intelligence-assisted data analysis 18 . The protective antigen of anthrax toxin, which assembles into a heptameric transmembrane pore (previously known as the PA 63 channel) under acidic conditions, is thus an ideal biological nanopore 19 . In anthrax toxin, it allows the intracellular transport of toxic enzyme components (i.e., lethal factor and edema factor), triggering the death of mammalian cells 20 – 23 . In the past decade, research progress has been made in revealing the mechanisms of this toxic pore, as well as proposing the use of anthrax protective antigen to construct nanopores for single-molecule sensing. However, the anthrax nanopore struggles to form a stable single channel for satisfactory sensing applications with conventional K + or Na + electrolytes due to its intrinsic obstacles, such as a smaller open-pore current (~ 5 pA), signal-to-noise interference, the frequent occurrence of gradually declining current trajectories, and pore occlusion phenomena dominated by phenylalanine molecular clamps 24 – 26 . Considering its membrane-embedded structure and pore-forming features, we herein aim to construct a stable anthrax nanopore in a substituted electrolyte system using the anthrax protective antigen. As an alternative to traditional salts, ionic liquids contain organic macromolecular cations that provide superior electrochemical properties and chemical stability as an optimized electrolyte sensing element 27 , 28 . Meanwhile, we also apply an asymmetric pH condition to construct the functional anthrax nanopore because it has been demonstrated to be a proton-driven active channel 25 . The properties of the optimized electrolyte maintain the anthrax nanopore in an open state (~ 5 pA) and eliminate channel occlusion phenomena (commonly referred to “gating”), thereby enabling the occurrence of noticeable current signals during the passage of ion/molecule flows. This approach not only constructs a stable anthrax nanopore at a single-channel level but also motivates the widespread application of the anthrax nanopore in single-molecule sensing. Here, we demonstrate that by simply changing the electrolyte, a novel molecular clamping-containing anthrax nanopore can be functionalized for detecting and discriminating all natural amino acids, including levorotatory and dextrorotatory enantiomers. The observed current signals corresponding to the identification of chiral amino acids showed significant differences in terms of current amplitudes and residence times. In addition, amino acids of different properties ( i.e. , charged, polar and non-polar residues) exhibited diverse intermolecular forces ( i.e. , electrostatic force, π-π interactions and hydrogen bond interaction) within the anthrax nanopore, which were further combined with either electrophoretic force (EPF) or electroosmotic flow (EOF) to facilitate amino acids transport in the anthrax nanopore. Notably, all the observed differences in the current signals corresponding to the identified chiral amino acids were determined at the single-molecule level with femtosecond (fA) precision. This study provides an ideal nanopore architecture with ultrahigh sensing resolution, a wide dynamic range of enantioselectivity, and specificity. It may have the potential for protein sequencing via direct, residue-by-residue readout of amino acids. Result and discussion Construction and electrical characterization of a stable anthrax nanopore The configuration of a typical anthrax nanopore sensing system is illustrated in Fig. 1a. Anthrax protective antigen should be an ideal nanopore candidate that can offer high detection resolution due to its primary funnel shape structure. In particular, the channel mouth ( cis, ~30 Å in opening diameters and inner varying down to ~20 Å), Φ-clamp (~6 Å), throat (~18 Å), and β-barrel stem ( trans , ~105 Å in length & ~12~18 Å in diameter) provide sensitive interface with numerous recognition sites for ion flow dynamics and molecular effects determination 29 . However, earlier studies have found that the functional phenylalanine clamps (Φ-clamp) within the anthrax channel usually trigger phenomena like disruption of the equilibrium of ion flow and alteration of the channel activity between “occlusion” (refers to O 1 , channel current decrement,) and “non-occlusion” states (refers to O 2, active state for electrical detection), in conventional electrolyte systems (K + or Na + ). These resulting non-unique and unstable currents trajectories consequently lead to obstacles to produce satisfied electrical fingerprints for analyte sensing and analysis (Fig. 1a) 30 . The molecular mechanism reveals that the proton-driven clamp allostery is critical to regulate anthrax toxic proteins translocation though anthrax protective antigen channel 25 . We hypothesize that constructing a pH asymmetric system between the two ends of the channel (i.e., cis: 5.6 & trans: 7.6) to form a proton gradient could help establish a more stable and functional anthrax nanopore. Hence, monovalent cations ( i.e., Na + , K + , Li + , [BMIM] + ) and Halogen anion ( i.e., Cl -1 ) at either symmetric or asymmetric ion strengths were used to construct an optimized anthrax protective antigen nanopore. As a usual fashion of electrolyte (K + , Na + or Li + ,) in nanopore electrical detection, we established four experimental systems with different ion concentrations but elected different pH strengths, applying -100 mV potential bias across the nanopore (System i: cis/ trans: 0.5 M / 0.5 M, pH 7.6 / 7.6; System ii: cis / trans: 1 M / 0.5 M, pH 7.6 / 7.6; System iii: cis/ trans : 1M / 0.5M, pH 5.6 / 7.6; System iv: cis/trans: 0.5 M / 0.5 M, pH 5.6 / 7.6). For quantitative detection (Fig. S1), we defined several key parameters, such as opening pore current ( I o ), event current blockage ( I b ), noise levels ( S.D. , standard deviation of event noise levels), event interval time ( t on ), average interval time of events ( τ on ), and average dwell time ( τ off ). We then tested whether these electrolyte systems could maintain nanopore stability under a typical single-channel condition. Meanwhile, we determined the electrical performance of anthrax nanopore by observing the pore stability (current trajectories), the open-pore current discrete constant (σ), the opening current strength of Io 2 (active nanopore state), electrical conductivity (Ω), as well as I-V curves. Among the parameters, the discrete constant (σ) is used to determine the discretization degree of nanopore electrical performance with different salts, particularly useful for characterizing the nanopore stability. A large σ indicates the larger degree of dispersion of nanopore current, meaning unstable and great current fluctuation in the nanopore electrical detection. In contrary, a small discrete constant (σ) means a stable nanopore electrical performance 31 . Fig S2 shows the ionic current properties of anthrax nanopore with KCl electrolyte. The pH asymmetric KCl electrolytes produce clean nanopore channel without fluctuating current trajectories and any background signals (Fig. S2a-b). Despite no significant difference between the opening current strengths (Io 2 , Fig. S2c), the σ values of pH asymmetric systems were smaller than those of pH symmetric systems (Fig. S2d), whereas linear properties of I-V curves obtained (Fig. S2e). These experiments demonstrated that the pH asymmetric systems provided the proton-driven effect is easier to establish a clean nanopore channel. Similar phenomena were observed for anthrax nanopore with Na + and Li electrolytes (Fig. S3 & S4). In addition, the electrical conductivity of the nanopore was determined to be increased with the elevated ion strength, but does not change with the alteration of pH condition (Fig. S5a-c & Table S1). However, one limit is there, the open-pore current gradually decreased with recording time flies, this kind of unsatisfied nanopore current trajectories would greatly hinder subsequent detection work. Compared to traditional salts, ionic liquids show better electrochemical properties in nanopore measurement 27, 28 . Therefore, we next used [BMIM]Cl to construct the anthrax nanopore system with either symmetric or asymmetric ion/pH strength (Fig. 1b-c, i-iv). Surprisingly, the electrical detection shows satisfied signal-to-noise ratios (no noticeable background signals) and stable nanopore current trajectories with both pH asymmetric systems. As the determined electrical properties shown (Fig. 1d), the electrolyte in ion symmetric and pH asymmetric produced smallest discrete constant (σ of system i-iv: 20.9 % vs. 21.68 % vs. 22.31 % vs. 13.76 %) and larger opening current strength of Io 2 , meanwhile resulted in eliminating the occurrence of pore “occlusion” (O 1 , clamping frequency of i-iv: 3 min -1 vs. 6.67 min -1 vs. 0 min -1 vs. 0 min -1 ), displaying a very satisfied channel stability. In addition, the current of anthrax nanopore in this optimized electrolyte system is symmetric and linear with respect to the sign of the applied transmembrane potentials, displaying a stable electrical conductance (Fig. 1e & Fig. S5d). Furthermore, no current trajectory decrement was observed even in long time recording. Thus, these data indicated that pH asymmetric, [BMIM]Cl strength symmetric electrolyte can contribute to a stable anthrax nanopore. Different kinds of amino acids determined by EPF/EOF cooperated intermolecular interactions In some cases, nanopore protein sequencing relying on amino acids identification was not efficiently enough to fully reveal the residues ordering, hence, the primary sequence was usually designed by artificially arranged in consecutive tailored sequence to segment into individual amino acid nodes, meaning a purpose-built method. Ideally, the complete amino acid sequence for a protein architecture should be identified during a head-to-tail translocation through the nanopore, where some amino acid nodes may be structure or polar similarity and some not at all. To help directly identify the single amino acid, we determine whether the optimized electrolyte assisted anthrax nanopore could be used for precise measurement of such small molecules (added to cis ). In our cases, the determination of single amino acids requires integration of pH-asymmetric condition. Due to the intrinsic isoelectric points of amino acids, those molecules exhibit different polarity in a pH5.6 ( cis ) environment. Therefore, where possible, the different kinds of single amino acids require to be identified in the same electric field. Four amino acids as notable examples of different types were selected for the nanopore determination (Fig. 2a-i & Table S2), which arginine has the highest isoelectric point (short as R, positively charged, pI: 10.76), aspartic acid has the lowest isoelectric point (D, negatively charged, pI: 2.77), and tyrosine (Y, aromatic residue, pI: 5.68), glutamine (Q, polar residue, pI: 5.65), have pI approximate to the environment proton strength. Electrokinetic phenomenon occurs when a fluid flow through a porous medium under an applied potential bias which know as electroosmotic flow (EOF). Here, EOF was generated in the direction of the ion flow ( cis to trans ) in anthrax nanopore 32-34 . Meanwhile, there was an electrophoretic force (EPF) during amino acids translocation in the nanopore. The strength and direction of EPF either increases or decreases depending on the difference between the molecular pI and the environment pH (5.6 as the boundary) 35 . The positive amino acids (pI > 5.6) pass through the nanopore by EPF in the direction of cis to trans , while the translocation of negative amino acids (pI < 5.6) is inhibited by a reverse EPF ( trans to cis ), but may still translocate through the nanopore under EOF. EPF has minor effect on amino acids whose pI are approximate to 5.6. Therefore, EOF and EPF work differently on amino acids translocation in the nanopore and consequently produce current events containing distinctive features. The applied bias was optimized (-100 mV) considering the opening pore current (Fig. S6 & Table S3), quality and quantity of the current events (Fig. S7-S9). In the resulting graph (Fig. 2a-ii & Fig. 2b), EPF and EOF driven arginine translocation produced current events containing distinctive features (ΔI/I o = 73.51 %, τ off = 3.23 ms). The detected amino acids showed single-gaussian and single-exponential distributions in the form of a single-peak for current blockages and dwell time. Tyrosine and glutamine translocation produced current events dominantly by EOF (Y: ΔI/I o = 82.07 %, τ off = 7.51 ms; Q: ΔI/I o = 77.18 %, τ off = 0.17 ms) (Fig. 2a-ii & Fig. 2c-d); Aspartic acid translocation was governed by both EOF and reverse EPF ( trans to cis ), whereas EPF was dominant, resulting in no current events produced (Fig. 2a-ii & Fig. 2e). Results demonstrated the current spectral reliability of anthrax nanopore is improved with prominent discrimination of amino acids in different kinds. Interestingly, we found that the EOF driven current events frequencies regarding tyrosine and glutamine varied significantly (Y: 5.47 min -1 vs. Q: 2.57 min -1 ). This variance should due to different intermolecular interactions between the detected amino acids and residues of inner interface of the anthrax nanopore 36 . In the nanopore, the most abundant interaction for tyrosine recognition means the π-π interaction by Tyr-Phe (Fig. 2c-i) 37, 38 , but for glutamine is the hydrogen bond interaction by NH 2 - OH groups (Fig. 2d-i). Besides, the interactions include the electrostatic force between arginine and the nanopore (Fig. 2b-i) 39, 40 , and the hydrogen bond interaction provided by aspartic acid (Fig. 2e-i) 41, 42 . Based on these experimental results, we can then conclude that the capture preference for different amino acids in anthrax nanopore is arginine > tyrosine > glutamine (9.30 min -1 vs. 5.47 min -1 vs. 2.57 min -1 ). In addition, it should be noted the kinetics of amino acids-anthrax nanopore interactions undergo association and dissociation rates, which were also detected under different applied bias (Fig. S10). K on demonstrated that the intermolecular strengths between detected amino acids and the anthrax nanopore were in the order of electrostatic force > π-π interaction > hydrogen bond interaction (Fig. 2f, R: 2.16 µM -1 min -1 vs. Y: 1.28 µM -1 min -1 vs. Q: 0.91 µM -1 min -1 ). Discriminate between different levorotary amino acids Next, we pursued the detailed statistical analysis based on the detection of 20 levorotary amino acids (Fig. 3). Amino acids translocated through the anthrax nanopore and produced distinct current events (Fig. 3a), of single-gaussian and single-exponential distributions for current blockages ΔI/I o and dwell time τ off , in response to charged (Fig. S11), polar (Fig. S12), and non-polar amino acids (Fig. S13). The differences in ΔI/I o between different categories of amino acids were visually represented using violin plots (Fig. 3b). In addition, we performed statistical comparisons in terms of ΔI/I o vs . molecular volume (Fig. 3c) and ΔI/I o vs . τ off (Fig. 3d) Results indicated that the discrimination of the amino acid molecules remained notable differences. Moreover, K on suggested that different categories of amino acid molecules indeed induce noteworthy deviations in the intermolecular interaction strength in the nanopore detection (Fig. 3e, p polar residues > non-polar residues, which enabled better differentiation of levorotary amino acids in anthrax nanopore. To quantitatively describe the differences among levorotary amino acids, pairwise analyses were conducted and a cross-validation map was constructed (Fig. 3f). Each square represents mean t-test of the current blockages of two corresponding amino acids. Smaller p-values indicate greater differences between the detected amino acids. From all the resulting graphs, the differences in ΔI/I o existed among different levorotary amino acids, and our optimized anthrax nanopore could distinguish all detectable levorotary amino acids, including those ones showing subtle differences of ΔI/I o (< 2 %). Considering the opening pore current of the anthrax nanopore is in range of 3-5 pA. Hence, our nanopore enables to provide the efficient discrepancy of levorotary amino acids detection at the fA precision (< 100 fA). Discriminate between different dextrorotary amino acids Amino acids (except glycine) have a central carbon atom (α-carbon), which is connected to an amino group (-NH₂), a carboxyl group (-COOH), a hydrogen atom (-H), and a side chain (R). This central carbon atom is chiral, resulting in two distinct stereoisomers of amino acids: levorotary type and dextrorotary type. Chirality amino acids paly significant roles in terms of biological activity, protein structure and function, and pharmaceutics etc 43, 44 . Therefore, the detection and then differentiation of dextrorotary ( d- ) amino acids is particularly important. We employed the same anthrax nanopore approach and experimental conditions to detect dextrorotary amino acids enantiomers. EOF and EPF-driven enantiomers translocation produced current events containing characteristic features (Fig. 4a & Fig. S14-16). Similarly, the quantitative analysis of ΔI/I o of the three groups of dextrorotary amino acids were visually represented using violin plots, revealing those significant differences between each other (Fig. 4b). Additionally, statistical comparisons in terms of ΔI/I o vs . molecular volume (Fig. 4c) and ΔI/I o vs . τ off (Fig. 4d) were conducted, the same discrimination reliability for dextrorotary amino acids was observed, where better visual differentiation is shown in a cross-validation map (Fig. 4f). Likewise, the kinetics of dextrorotary amino acids-anthrax nanopore interactions were also determined. However, the K on of the three types of dextrorotary amino acids exhibit a different stepwise distribution from that of levorotary amino acids, in the order of charged residues > non-polar residues > polar residues (Fig. 4e, p < 0.01 %). Nevertheless, the anthrax nanopore can also distinguish all detected dextrorotary amino acids at the fA precision. It is likely that no significant differences at Δ I/Io levels occured (Fig. 3f and Fig. 4f, P > 5%) in some instances--for example, levorotary type: H vs. M, V vs. W and dextrorotary type (term as “ d-” in figures): d- R vs. d- T, d- C vs. d- K. Thus, the discrimination was dependent on τ off levels. τ off of the current events reflects the mean time that molecules stay in the nanopore which is may resulted distinguishing criterion of false positives. To give unbiased discrimination of these amino acids’ samples, sensitive single-molecule amino acids identification demands discrimination throughput to be in the large numbers of observed events of mixed samples. We determined τ off threshold to identify these amino acids based on simultaneous detection of mixed samples (Fig. S17a-b). As results indicated, τ off > 2.68 ms likely corresponds to M while τ off 4.26 ms corresponds to V while 7.89 ms is likely d -C while τ off < 7.89 ms most possibly represents d -K (Fig. S17c). However, there is no doubt to d -R and d -T judgement because of significant differences of τ off (Fig. S17d). Therefore, the four amino acid groups may not present false positives using anthrax nanopore based precise differentiation. Furthermore, the plots of ΔI/I o vs. relative molecular mass were also constructed to precisely distinguish levorotary and dextrorotary amino acids, respectively (Fig. S18). Consequently, the success makes us confident that anthrax nanopore benefits discriminating chiral amino acids at single-molecule level but no necessities of enzymes or nanopore engineering. Discriminate between chiral enantiomers of amino acids We have respectively differentiated levorotary amino acids and dextrorotary amino acids (term as “ d-” in following figures). It is not clear whether molecular chirality is abided or participate chemical reactions during the linearization and sequencing. Hence, there is an increasing necessity to make highly specific and sensitive differences between chiral enantiomers of same individual amino acids. We used the mean ΔI/I o of the levorotary amino acids and dextrorotary amino acids as t-test means to determine the difference between tested chiral amino acids. Taking valine (V) for example, V and d- V were respectively used as control ( Ctl. ). It is reasonable that the t-test (P = 99.68 %) indicated no significant difference between V ( Ctl. ) and V ( Test ); In contrast, the t-test approaches to “0” (P < 0.01 %) indicates significant difference between current signals of V ( Ctl. ) and d- V ( Test ). Similarly, it is reasonable that the t-test (P = 99.99 %) indicated no significant difference between d- V( Ctl. ) and d- V ( Test ); while the t-test approaches to “0” (P < 0.01%) indicates significant difference between current signals of d- V ( Ctl. ) and V ( Test ). Finally, the efficient discrimination of chiral enantiomers of amino acids was statistical supported by t-test analysis of variance (P < 0.01 %) for each comparison via applying the current signals produced by each amino acid (Fig. 5). These kinds of results would ultimately increase the accessibility of chiral amino acids enantiomers identification. Chiral enantiomers of amino acids generated distinct current signals when passing through anthrax nanopores, these differences are likely attributed to the following reasons: Spatial structural differences due to different chirality most likely to originate difference of nanopore current signals which agrees with previous studies on molecular dynamics simulation 45 . In addition, it caused differences in non-covalent interactions ( i.e., electrostatic force, π-π interaction, hydrogen bond interaction) during the molecular translocation across the nanopore. For example, it was evidenced that the chirality of amino acids causes slight variations in charge distribution and polarity of amino acids. The spatial configuration differences between levorotary and dextrorotary amino acids may influence molecular binding stability and energy, thereby altering electrostatic interactions with nanopore surface 46 ; Meanwhile, the chirality affects π-π interactions between the detected aromatic amino acids and phenylalanine clamps in the anthrax nanopore because the chirality of different amino acids exhibits varying orientations of aromatic groups, thus altering interaction strength 47 ; Besides, the chirality directly influences the spatial positioning of their hydrogen bond donor or acceptor groups. For instance, the orientation variations of the amino and carboxyl groups in chiral isomers can lead to differences in the hydrogen bond network formed with functional groups in the nanopore. These differences affect not only the number of hydrogen bonds but also the molecular binding stability 48 . Differences in current signals between amino acid enantiomers arise from varying interactions with anthrax nanopores, we further determined their respective capture frequencies (r and r’) in the nanopore. Differences in capture frequencies may indicate the interactions variances between nanopores and detected amino acids; higher capture frequencies suggest stronger interactions, and vice versa. It was observed that the chirality indeed affects capture rates of each amino acids induced by interactions between enantiomers and nanopores (Fig. 6a-c). To further investigate the effect of chiral transformation on amino acids with different properties, we calculated the difference of capture rates between chiral amino acids enantiomers (D=r-r ', Fig. 6d). The comparison was also classified according to amino acids categories using the value differences of average capture rates between chiral enantiomers which were defined as AvgD=(r-r')/n (Fig. 6e). Meanwhile, the absolute differences of average capture rates were defined as Avg | D |=| r-r '|/n (Fig. 6f), where n is the number of amino acids of each category. It was observed that the capture rates of levorotary amino acids in charged and non-polar categories were lower than the dextrorotary enantiomers, while levorotary polar amino acids showed higher capture rates than those of dextrorotary enantiomers (Fig. 6d), it is more intuitively seen from AvgD statistics (Fig. 6e). Moreover, Avg | D | represents the degree of chirality influence on capture efficiency of different types of amino acids. The larger Avg | D |, the greater the differences in capture efficiency between chiral of these amino acids’ enantiomers, indicating the greater differences on interactions with anthrax nanopores, and vice versa. It was evident that the interactions of charged amino acids were most strongly affected by chirality, followed by non-polar amino acids, and polar amino acids are least affected. Conclusion In summary, we constructed a stable wild-type anthrax nanopore in a pH-asymmetric electrolyte system based on the proton-driven mechanism and the electrochemical stability of ionic liquids. By means of the anthrax nanopore, our research highlighted the ultrahigh sensing resolution (at fA precision) in the precise differentiation of natural amino acids as well as levorotatory and dextrorotatory enantiomers with subtle conformational changes. It is noted that the proposed anthrax nanopore amino acid discrimination doesn’t need enzymes (nor other chemical reactions) nor machine learning algorithms, but relies simply on the optimization of the electrolyte system and the use of statistical parameters such as the strength ΔI/I o and, in some instances, the lifetime of resistive pulses (τ off ) of the nanopore current signals. Meanwhile, we demonstrated that the detection of amino acids was either dominated by the electric field force or electroosmotic flow, depending on the isoelectric points of the amino acid analyte, in response to the difference in proton concentration ( i.e., cis/trans : pH5.6/7.6). The mechanism of discrimination by nanopore current signals was also explained by the action of heterogeneous intermolecular interactions ( i.e. , electrostatic force, π-π interaction, hydrogen bond interaction) mediated by the contacting residues, between the different kinds of amino acids and the nanopore interface. Statistical analyses of the translocation signal intensities and the molecular binding constants K on revealed the fact that the strength of intermolecular forces was in the order of electrostatic force > π-π interactions > hydrogen bonding. In terms of capture frequency in anthrax nanopores, charged and non-polar levorotatory amino acids were significantly lower than dextrorotatory isomers, while polar levorotatory amino acids were more frequently captured than their corresponding dextrorotatory isomers. Additionally, the capture frequency of charged amino acids was most affected by chirality, followed by non-polar amino acids, while polar amino acids were the least affected. It is likely that some form of nanopore amino acids discrimination will precede de novo sequencing because of the difficulty of fully decoding single protein translocation signals. Must admit that, in some cases, the nanopore protein sequencing relying on amino acids identification were not efficiently enough to fully reveal these residues ordering. To enable comprehensive profiling and de novo protein sequencing using anthrax nanopore, future work should concentrate on protein engineering to optimize the conformational breakdown and linearization for native proteins or peptides in the nanopore and to translate the sequence-dependent raw currents features 14 . Ideally, the complete protein architecture should be identified by amino acid nodes (or carry modifications) during a head-to-tail translocation through the nanopore, where some proteins may be structurally very similar and others not at all. Nevertheless, this enzyme-less sensing strategy has overcome one of the major obstacles in amino acid discrimination by creating highly specific and sensitive amino acid-recognition events with a high signal-to-noise ratio at sub-pA resolution levels, as well as a wide dynamic range of enantioselectivity. Declarations Author contributions Y.W.: methodology, investigation, software, data curation, original draft preparation. Y.W.: funding acquisition, data curation, formal analysis. L.W., J.L., S.L., and Z.Z.: software, data curation, formal analysis. L.W.: conceptualization, methodology, supervision, project administration, funding acquisition, reviewing and editing of manuscript. Author information Corresponding Author Dr. Liang Wang-Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences & Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. orcid.org/0000-0002-7404-4319, Email: [email protected] Authors Yan Wang- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences & Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. Dr. Yunjiao Wang-Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences & Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. orcid.org/0000-0002-7002-0889 Lebing Wang- School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences & Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. Jing Li-School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences & Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. Shilong Liu- School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences & Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. Zhirui Zhang-Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences & Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. Acknowledgments This work was supported by the National Key Research and Development Program of China (2022YFB3205600), Natural Science Foundation of Chongqing (CSTB2023NSCQ-MSX0071), and the Youth Innovation Promotion Association (2022388) of Chinese Academy of Sciences. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Correspondence and requests for materials should be addressed to Liang Wang. References Kasianowicz, J. J.; Brandin, E.; Branton, D. Characterization of individual polynucleotide molecules using a membranechannel. Proceedings of the National Academy of Sciences of the United States of America 1996 , 93 (24), 13770-13773. Ensslen, T.; Sarthak, K.; Aksimentiev, A.; Behrends, J. C. Resolving Isomeric Posttranslational Modifications Using a Biological Nanopore as a Sensor of Molecular Shape. Journal of the American Chemical Society 2022 , 144 (35), 16060-16068. DOI: 10.1021/jacs.2c06211. Martin-Baniandres, P.; Lan, W.-H.; Board, S.; Romero-Ruiz, M.; Garcia-Manyes, S.; Qing, Y.; Bayley, H. Enzyme-less nanopore detection of post-translational modifications within long polypeptides. Nature Nanotechnology 2023 , 18 (11), 1335-1340. DOI: 10.1038/s41565-023-01462-8. Jiang, J.; Li, M.-Y.; Wu, X.-Y.; Ying, Y.-L.; Han, H.-X.; Long, Y.-T. Protein nanopore reveals the renin–angiotensin system crosstalk with single-amino-acid resolution. Nature Chemistry 2023 , 15 (4), 578-586. DOI: 10.1038/s41557-023-01139-8. 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. Nature Chemical Biology 2024 . DOI: 10.1038/s41589-024-01734-x. Brinkerhoff, H.; Kang, A. S. W.; Liu, J.; Aksimentiev, A.; Dekker, C. Multiple rereads of single proteins at single–amino acid resolution using nanopores. Science 2021 , 374 (6574), 1509-1513. DOI: 10.1126/science.abl4381 (acccessed 2025/01/13). Yan, S.; Zhang, J.; Wang, Y.; Guo, W.; Zhang, S.; Liu, Y.; Cao, J.; Wang, Y.; Wang, L.; Ma, F.; Zhang, P.; Chen, H.-Y.; Huang, S. Single Molecule Ratcheting Motion of Peptides in a Mycobacterium smegmatis Porin A (MspA) Nanopore. Nano Letters 2021 , 21 (15), 6703-6710. DOI: 10.1021/acs.nanolett.1c02371. Chen, Z.; Wang, Z.; Xu, Y.; Zhang, X.; Tian, B.; Bai, J. Controlled movement of ssDNA conjugated peptide through Mycobacterium smegmatis porin A (MspA) nanopore by a helicase motor for peptide sequencing application. Chemical Science 2021 , 12 (47), 15750-15756, 10.1039/D1SC04342K. DOI: 10.1039/D1SC04342K. Sauciuc, A.; Morozzo della Rocca, B.; Tadema, M. J.; Chinappi, M.; Maglia, G. Translocation of linearized full-length proteins through an engineered nanopore under opposing electrophoretic force. Nature Biotechnology 2024 , 42 (8), 1275-1281. DOI: 10.1038/s41587-023-01954-x. Jeong, Y.; Kim, H. W.; Ku, J.; Seo, J. Breakdown of chiral recognition of amino acids in reduced dimensions. Scientific Reports 2020 , 10 (1), 16166. DOI: 10.1038/s41598-020-73300-z. Chen, X.; Zhu, R.; Zhang, B.; Zhang, X.; Cheng, A.; Liu, H.; Gao, R.; Zhang, X.; Chen, B.; Ye, S.; Jiang, J.; Zhang, G. Rapid room-temperature phosphorescence chiral recognition of natural amino acids. Nature Communications 2024 , 15 (1), 3314. DOI: 10.1038/s41467-024-47648-z. Woiwode, U.; Reischl, R. J.; Buckenmaier, S.; Lindner, W.; Lämmerhofer, M. Imaging Peptide and Protein Chirality via Amino Acid Analysis by Chiral × Chiral Two-Dimensional Correlation Liquid Chromatography. Analytical Chemistry 2018 , 90 (13), 7963-7971. DOI: 10.1021/acs.analchem.8b00676. Magalí, L.; Tomba, G.; Costantini, G.; Lucio, C. C.; Alessandro, D. V.; Kern, K. Cover Picture: Tracking the Chiral Recognition of Adsorbed Dipeptides at the Single-Molecule Level (Angew. Chem. Int. Ed. 24/2007). Angewandte Chemie International Edition 2007 . Motone, K.; Nivala, J. Not if but when nanopore protein sequencing meets single-cell proteomics. Nature Methods 2023 , 20 (3), 336-338. DOI: 10.1038/s41592-023-01800-7. Wang, K.; Zhang, S.; Zhou, X.; Yang, X.; Li, X.; Wang, Y.; Fan, P.; Xiao, Y.; Sun, W.; Zhang, P.; Li, W.; Huang, S. Unambiguous discrimination of all 20 proteinogenic amino acids and their modifications by nanopore. Nature Methods 2024 , 21 (1), 92-101. DOI: 10.1038/s41592-023-02021-8. Zhang, M.; Tang, C.; Wang, Z.; Chen, S.; Zhang, D.; Li, K.; Sun, K.; Zhao, C.; Wang, Y.; Xu, M.; Dai, L.; Lu, G.; Shi, H.; Ren, H.; Chen, L.; Geng, J. Real-time detection of 20 amino acids and discrimination of pathologically relevant peptides with functionalized nanopore. Nature Methods 2024 , 21 (4), 609-618. DOI: 10.1038/s41592-024-02208-7. Zhang, Y.; Yi, Y.; Li, Z.; Zhou, K.; Liu, L.; Wu, H.-C. Peptide sequencing based on host–guest interaction-assisted nanopore sensing. Nature Methods 2024 , 21 (1), 102-109. DOI: 10.1038/s41592-023-02095-4. Taylor, C. J.; Pomberger, A.; Felton, K. C.; Grainger, R.; Barecka, M.; Chamberlain, T. W.; Bourne, R. A.; Johnson, C. N.; Lapkin, A. A. A Brief Introduction to Chemical Reaction Optimization. Chemical Reviews 2023 , 123 (6), 3089-3126. DOI: 10.1021/acs.chemrev.2c00798. Kalu, N.; Alcaraz, A.; Yamini, G.; Abolfath, S. M.; Lucas, L.; Kenney, C.; Aguilella, V. M.; Nestorovich, E. M. Effect of endosomal acidification on small ion transport through the anthrax toxin PA63 channel. Febs Letters 2017 , 591 (21). Nassi, S.; Collier, R. J.; Finkelstein, A. PA63 Channel of Anthrax Toxin: An Extended β-Barrel. Biochemistry 2002 , 41 (5), 1445-1450. DOI: 10.1021/bi0119518. Nablo, B. J.; Halverson, K. M.; Robertson, J. W. F.; Nguyen, T. L.; Panchal, R. G.; Gussio, R.; Bavari, S.; Krasilnikov, O. V.; Kasianowicz, J. J. Sizing the Bacillus anthracis PA63 Channel with Nonelectrolyte Poly(Ethylene Glycols). Biophysical Journal 2008 , 95 (3), 1157-1164. DOI: 10.1529/biophysj.107.121715 (acccessed 2025/01/18). Kasianowicz, J. J.; Nguyen, T. L.; Stanford, V. M. Enhancing molecular flux through nanopores by means of attractive interactions. Proceedings of the National Academy of Sciences 2006 , 103 (31), 11431-11432. DOI: 10.1073/pnas.0603951103 (acccessed 2025/01/13). Krantz, B. A.; Trivedi, A. D.; Cunningham, K.; Christensen, K. A.; Collier, R. J. Acid-induced Unfolding of the Amino-terminal Domains of the Lethal and Edema Factors of Anthrax Toxin. Journal of Molecular Biology 2004 , 344 (3), 739-756. DOI: https://doi.org/10.1016/j.jmb.2004.09.067. Halverson, K. M.; Panchal, R. G.; Nguyen, T. L.; Gussio, R.; Little, S. F.; Misakian, M.; Bavari, S.; Kasianowicz, J. J. Anthrax Biosensor, Protective Antigen Ion Channel Asymmetric Blockade *. Journal of Biological Chemistry 2005 , 280 (40), 34056-34062. DOI: 10.1074/jbc.M507928200 (acccessed 2025/01/18). Das, D.; Krantz, B. A. Peptide- and proton-driven allosteric clamps catalyze anthrax toxin translocation across membranes. Proceedings of the National Academy of Sciences 2016 , 113 (34), 9611-9616. DOI: 10.1073/pnas.1600624113 (acccessed 2025/01/18). Panchal, R. G.; Halverson, K. M.; Ribot, W.; Lane, D.; Kenny, T.; Abshire, T. G.; Ezzell, J. W.; Hoover, T. A.; Powell, B.; Little, S.; Kasianowicz, J. J.; Bavari, S. Purified Bacillus anthracis Lethal Toxin Complex Formed in Vitro and during Infection Exhibits Functional and Biological Activity *. Journal of Biological Chemistry 2005 , 280 (11), 10834-10839. DOI: 10.1074/jbc.M412210200 (acccessed 2025/01/18). de Zoysa, R. S. S.; Jayawardhana, D. A.; Zhao, Q.; Wang, D.; Armstrong, D. W.; Guan, X. Slowing DNA Translocation through Nanopores Using a Solution Containing Organic Salts. The Journal of Physical Chemistry B 2009 , 113 (40), 13332-13336. DOI: 10.1021/jp9040293. Mahendran, K. R.; Raj Singh, P.; Modi, N.; Schulz, R.; Kleinekathöfer, U.; Winterhalter, M. Probing the Transport of Ionic Liquids in Aqueous Solution through Nanopores. Biophysical Journal 2012 , 102 (3), 205a. DOI: 10.1016/j.bpj.2011.11.1118 (acccessed 2025/01/18). Jiang, J.; Pentelute, B. L.; Collier, R. J.; Zhou, Z. H. Atomic structure of anthrax protective antigen pore elucidates toxin translocation. Nature 2015 , 521 (7553), 545-549. DOI: 10.1038/nature14247. Melnyk, R. A.; Collier, R. J. A loop network within the anthrax toxin pore positions the phenylalanine clamp in an active conformation. Proceedings of the National Academy of Sciences 2006 , 103 (26), 9802-9807. DOI: 10.1073/pnas.0604000103 (acccessed 2025/01/13). Roy; Dilip. The Discrete Normal Distribution. Communications in Statistics Theory & Methods 2003 , 32 (10), 1871-1883. Rezaei, M.; Azimian, A. R.; Semiromi, D. T. The surface charge density effect on the electro-osmotic flow in a nanochannel: a molecular dynamics study. Heat and Mass Transfer 2015 , 51 (5), 661-670. DOI: 10.1007/s00231-014-1441-y. Moschopoulos, P.; Dimakopoulos, Y.; Tsamopoulos, J. Electro-osmotic flow of electrolyte solutions of PEO in microfluidic channels. Journal of Colloid and Interface Science 2020 , 563 , 381-393. DOI: https://doi.org/10.1016/j.jcis.2019.12.052. Liu, Y.; Wang, K.; Wang, Y.; Wang, L.; Yan, S.; Du, X.; Zhang, P.; Chen, H.-Y.; Huang, S. Machine Learning Assisted Simultaneous Structural Profiling of Differently Charged Proteins in a Mycobacterium smegmatis Porin A (MspA) Electroosmotic Trap. Journal of the American Chemical Society 2022 , 144 (2), 757-768. DOI: 10.1021/jacs.1c09259. Bandara, Y. M. N. D. Y.; Farajpour, N.; Freedman, K. J. Nanopore Current Enhancements Lack Protein Charge Dependence and Elucidate Maximum Unfolding at Protein’s Isoelectric Point. Journal of the American Chemical Society 2022 , 144 (7), 3063-3073. DOI: 10.1021/jacs.1c11540. Jia, W.; Ouyang, Y.; Zhang, S.; Du, X.; Zhang, P.; Huang, S. Nanopore Signatures of Nucleoside Drugs. Nano Letters 2023 , 23 (20), 9437-9444. DOI: 10.1021/acs.nanolett.3c02872. Hao, W.; Guo, B.; Liu, J.; Ren, Q.; Li, S.; Li, Q.; Zhou, K.; Liu, L.; Wu, H.-C. Single-Molecule Exchange inside a Nanocage Provides Insights into the Origin of π–π Interactions. Journal of the American Chemical Society 2024 , 146 (14), 10206-10216. DOI: 10.1021/jacs.4c03159. Chen, F.; Tang, J.; Wang, J. Effects of π–π Stacking on Shale Gas Adsorption and Transport in Nanopores. ACS Omega 2023 , 8 (49), 46577-46588. DOI: 10.1021/acsomega.3c05522. Asandei, A.; Chinappi, M.; Kang, H.-K.; Seo, C. H.; Mereuta, L.; Park, Y.; Luchian, T. Acidity-Mediated, Electrostatic Tuning of Asymmetrically Charged Peptides Interactions with Protein Nanopores. ACS Applied Materials & Interfaces 2015 , 7 (30), 16706-16714. DOI: 10.1021/acsami.5b04406. Luchian, T. Dipole potential-induced modulation of the interactions between reconstituted lipid membranes and certain pore-forming peptides. Revue Roumaine de Chimie 2009 , 54 (6), 455-463. Ilgen, A. G.; Senanayake, H. S.; Thompson, W. H.; Greathouse, J. A. Structure and energetics of hydrogen bonding networks in dilute HOD/H2O solutions confined in silica nanopores. Environmental Science: Nano 2023 , 10 (11), 3025-3038, 10.1039/D3EN00291H. DOI: 10.1039/D3EN00291H. Fang, D.; Liu, C.; Chen, Y.; Peng, Q.; Wu, K.; Chen, Y.; Jiang, H.; Wu, Y.; Shen, B.; Wu, Q.; Wu, D.; Sun, H. Elucidating and manipulating pressure-induced water intrusion–extrusion in tunable hydrophobic Co/Zn bimetallic ZIFs: Roles of pore size and hydrogen bond. Nano Research 2024 , 17 (1), 344-353. DOI: 10.1007/s12274-023-5967-5. Toledo, E. B.; Lucas, D. R.; Simão, T. L. B. V.; Calixto, S. D.; Lassounskaia, E.; Muzitano, M. F.; Damica, F. Z.; Gomes, V. M.; de Oliveira Carvalho, A. Design of improved synthetic antifungal peptides with targeted variations in charge, hydrophobicity and chirality based on a correlation study between biological activity and primary structure of plant defensin γ-cores. Amino Acids 2021 , 53 (2), 219-237. DOI: 10.1007/s00726-020-02929-x. Dai, X.; Zhou, E.; Yang, W.; Zhang, X.; Zhang, W.; Rao, Y. D-Serine made by serine racemase in Drosophila intestine plays a physiological role in sleep. Nature Communications 2019 , 10 (1), 1986. DOI: 10.1038/s41467-019-09544-9. Abraham Versloot, R. C.; Arias-Orozco, P.; Tadema, M. J.; Rudolfus Lucas, F. L.; 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. Journal of the American Chemical Society 2023 , 145 (33), 18355-18365. DOI: 10.1021/jacs.3c04076. Wang, J.; Prajapati, J. D.; Gao, F.; Ying, Y.-L.; Kleinekathöfer, U.; Winterhalter, M.; Long, Y.-T. Identification of Single Amino Acid Chiral and Positional Isomers Using an Electrostatically Asymmetric Nanopore. Journal of the American Chemical Society 2022 , 144 (33), 15072-15078. DOI: 10.1021/jacs.2c03923. Huang, H.; Bian, G.; Zong, H.; Wang, Y.; Yang, S.; Yue, H.; Song, L.; Fan, H. Chiral Sensor for Enantiodiscrimination of Varied Acids. Organic Letters 2016 , 18 (11), 2524-2527. DOI: 10.1021/acs.orglett.6b00088. Peluso, P.; Chankvetadze, B. Recognition in the Domain of Molecular Chirality: From Noncovalent Interactions to Separation of Enantiomers. Chemical Reviews 2022 , 122 (16), 13235-13400. DOI: 10.1021/acs.chemrev.1c00846. Additional Declarations There is NO Competing Interest. Supplementary Files FinalSupplementalmaterials20250222.docx Enzyme-less discrimination of chiral amino acids with femtoampere-level precision by proton-driven anthrax nanopore Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6077470","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":421771834,"identity":"bc0d7bb3-2ef8-40d8-9233-30a9867ba718","order_by":0,"name":"Liang Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYLCCBwZAgr394AMGAwYe4rQkgLTwnEk2AGkhTk8CiJBIMJMA0QS1GBw/e/hFQoFdnrzPgbSKHwW1MvYMzA8/MNTcwa3lTF6aRYJBcrHh8cZjN3sMjgMdxmYswXDsGU4tZgdyzAwSDJgTN/YcSLvNYHAM5BczBsaGw7i1nH8D0lKfuHFGglkxRAv7N/xabuQYP0gwOJw4H+h9ZgaDGqAWHvy22N94YwYM5OOJG4CBLNljcICH5zBPsUTCMdxaJPtzjD98+FOdOL+9/eCHH3/q7Nnb2zd++FCDWwsQsIGjw+AAmANUycwAjSncgPkDiJRvAHPq8KsdBaNgFIyCEQkAOWRWN0HY/eQAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-7404-4319","institution":"Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences","correspondingAuthor":true,"prefix":"","firstName":"Liang","middleName":"","lastName":"Wang","suffix":""},{"id":421771835,"identity":"f6cb9fd3-be4e-4e66-9dfc-2114da6a7cf1","order_by":1,"name":"Yan Wang","email":"","orcid":"","institution":"Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Wang","suffix":""},{"id":421771836,"identity":"89ea819d-4753-40c5-b56f-60d183e275cd","order_by":2,"name":"Yunjiao Wang","email":"","orcid":"","institution":"Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yunjiao","middleName":"","lastName":"Wang","suffix":""},{"id":421771837,"identity":"b447ab4b-8420-4007-966a-8f208ff2d3e5","order_by":3,"name":"Lebing Wang","email":"","orcid":"","institution":"Chongqing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Lebing","middleName":"","lastName":"Wang","suffix":""},{"id":421771838,"identity":"5ed9643f-ebf8-4ffa-b6bc-6c8d60963fb5","order_by":4,"name":"Jing Li","email":"","orcid":"","institution":"Chongqing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Li","suffix":""},{"id":421771839,"identity":"dc515d24-7312-4848-8536-e340ce2290c1","order_by":5,"name":"Shilong Liu","email":"","orcid":"","institution":"Chongqing University of Posts and Telecommunications","correspondingAuthor":false,"prefix":"","firstName":"Shilong","middleName":"","lastName":"Liu","suffix":""},{"id":421771840,"identity":"d592d490-2624-4437-90f4-a26fa8a2e8ee","order_by":6,"name":"Zhirui Zhang","email":"","orcid":"","institution":"Chinese Academy of Sciences Chongqing Institute of Green and Intelligent Technology","correspondingAuthor":false,"prefix":"","firstName":"Zhirui","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-02-21 08:17:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6077470/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6077470/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78723701,"identity":"bb4a8cc3-a893-40b3-ab5e-75dffcd01254","added_by":"auto","created_at":"2025-03-18 05:42:21","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":425254,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConstruction of a stable anthrax nanopore with [BMIM]Cl electrolyte.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) Cartoon showing anthrax nanopore detecting system, whereas O\u003csub\u003e1\u003c/sub\u003e and O\u003csub\u003e2\u003c/sub\u003e represent open states of an anthrax nanopore; (i) Structure of anthrax nanopore; and (ii) Pore dimensions and phenylalanine clamps; (b) Cartoon showing four different [BMIM]Cl electrolyte systems. (i) \u003cem\u003ecis/ trans: \u003c/em\u003e0.5 M / 0.5 M, pH 7.6 / 7.6; (ii) \u003cem\u003ecis\u003c/em\u003e/\u003cem\u003etrans:\u003c/em\u003e1 M \u003cem\u003e/ \u003c/em\u003e0.5 M, pH 7.6 / 7.6; (iii) \u003cem\u003ecis/ trans\u003c/em\u003e: 1M / 0.5M, pH 5.6 / 7.6; (iv) \u003cem\u003ecis/trans: \u003c/em\u003e0.5 M / 0.5 M, pH 5.6 / 7.6. (c) Single-channel planar lipid bilayer records (black line) at four different buffer systems under -100mV, filtered to 100 Hz. The first two systems involve clamp induced pore occlusion, resulting in two types of current levels I\u003csub\u003eo1 \u003c/sub\u003eand I\u003csub\u003eo2\u003c/sub\u003e (i, ii), while the last two systems show no pore occlusion, resulting in one current level I\u003csub\u003eo2\u003c/sub\u003e (iii, iv). (d) Radar network diagram showing the electrical performance of the anthrax nanopore under different systems. (e) I-V curves from -100 mV to 100 mV at 10 mV step changes, and the conductivity of the system iv under -100mV. The statistical data were obtained by at least three independent experiments.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6077470/v1/c3457e29a807d846d0cbfd0a.jpeg"},{"id":78722298,"identity":"02903a29-a980-451e-8a3a-b92997b6def8","added_by":"auto","created_at":"2025-03-18 05:10:21","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":410851,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferent kinds of amino acids determined by EPF/EOF cooperated intermolecular interactions. \u003c/strong\u003e(a-i) Four types of amino acids (positive charged: R, aromatic residue: Y, polar residue: Q, negative charged: D) detected by anthrax nanopores under the action of electrophoretic force and electroosmotic flow. (a-ii) Comparison of isoelectric point, electrophoretic force, and electroosmotic flow of different amino acids in pH 5.6 (\u003cem\u003ecis\u003c/em\u003e) environment. (b) Arginine, providing the electrostatic interactions; (c) Tyrosine, providing the π-π interactions; (d) Glutamine, providing the Hydrogen bond interactions; (e) Aspartic acid, providing the Hydrogen bond interactions. (i) Schematic representation of the intermolecular interactions between amino acids and the anthrax nanopore inner interface; (ii) Statistical analysis of ΔI/I\u003csub\u003eo\u003c/sub\u003e \u003cem\u003evs.\u003c/em\u003e \u003cem\u003eτ\u003c/em\u003e\u003csub\u003e\u003cem\u003eoff\u003c/em\u003e\u003c/sub\u003e, as well as current trajectory. glutamine. (f) Statistical analysis of association constant rates (\u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003eon\u003c/em\u003e\u003c/sub\u003e) for three amino acids passing through the nanopore. Red represents arginine, purple represents tyrosine, and pink represents glutamine. Conditions: (\u003cem\u003ecis\u003c/em\u003e) 0.5 M [BMIM]Cl and 10 mM tris at pH 5.6, (\u003cem\u003etrans\u003c/em\u003e) 0.5 M [BMIM]Cl and 10 mM tris at pH 7.6, -100 mV. The statistical data were obtained by at least three independent experiments.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6077470/v1/ca310af86c8de65ead85aac9.jpeg"},{"id":78723080,"identity":"9abe7caf-b860-46a0-aa54-d05dc18a3a0b","added_by":"auto","created_at":"2025-03-18 05:34:21","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":244714,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiscriminate between different levorotary amino acids.\u003c/strong\u003e (a) Single-channel current records (black line) for detected amino acids (three categories: charged, polar, and non-polar). (b) Violin plots of ΔI/I\u003csub\u003eo\u003c/sub\u003e. Charged, polar, and non-polar amino acids are represented in green, pink and purple, respectively. (c) Plots of ΔI/I\u003csub\u003eo\u003c/sub\u003e \u003cem\u003evs.\u003c/em\u003e molecular volume. (d) Plots of ΔI/I\u003csub\u003eo\u003c/sub\u003e \u003cem\u003evs.\u003c/em\u003e dwell time (\u003cem\u003eτ\u003c/em\u003e\u003csub\u003e\u003cem\u003eoff\u003c/em\u003e\u003c/sub\u003e). (e) Determined association constant rates (\u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003eon\u003c/em\u003e\u003c/sub\u003e) for the three types of amino acids. Each point represents data by three independent experiments. **** indicates p \u0026lt; 0.01 %. (f) Cross-validation map of differences between levorotary amino acids. The lighter color indicated the smaller P-value, and the greater difference between detected amino acids. Conditions: (cis) 0.5 M [BMIM]Cl and 10 mM tris at pH 5.6; (trans) 0.5 M [BMIM]Cl and 10 mM tris at pH 7.6. -100 mV was applied for the nanopore detection. The statistical data were obtained by at least three independent experiments.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6077470/v1/f5b0d8b423f0a5bebe933b91.jpeg"},{"id":78723082,"identity":"93a7d05e-f5b3-447b-a1e2-8a530badab8f","added_by":"auto","created_at":"2025-03-18 05:34:22","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":193575,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDetermination of amino acid chiral enantiomers based on nanopore capture rates. \u003c/strong\u003eCapture rates of chiral enantiomers, of (a) Non-polar amino acids; (b) Charged amino acids; (c) Polar amino acids. r represents the capture frequency of levorotary amino acids, r` represents the capture frequency of dextrorotary (\u003cem\u003ed-\u003c/em\u003e) amino acids. (d) D-value analysis of capture rates (D=r-r‘) of different chiral amino acids. (e) Comparison of the average capture rate differences (AvgD=(r-r`)\\n. (f) The absolute differences of average capture rates defined as Avg | D |=| r-r '|/n. n is the number of amino acids of each category. The statistical data were obtained by at least three independent experiments.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6077470/v1/23c3cb2b74526793387d22b0.jpeg"},{"id":78723703,"identity":"b6c5d02a-0054-4bc3-a342-a2ff045f6d20","added_by":"auto","created_at":"2025-03-18 05:42:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11291401,"visible":true,"origin":"","legend":"Enzyme-less discrimination of chiral amino acids with femtoampere-level precision by proton-driven anthrax nanopore","description":"","filename":"FinalSupplementalmaterials20250222.docx","url":"https://assets-eu.researchsquare.com/files/rs-6077470/v1/3363083790d00917e38ef091.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Enzyme-less discrimination of chiral amino acids with femtoampere-level precision by proton-driven anthrax nanopore","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince the advancement of ultra-long read technologies for nucleic acids using nanopore sequencing, the field of protein sequencing has become increasingly pressing, and substantial research progress has been made based on nanopore protein analytics \u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, the main challenges in protein sequencing lie in how to capture and transport unfolded proteins (or long polypeptides) and ensure accurate identification of individual amino acids in the sequence during protein translocation. As demonstrated in prior studies, it has been established that monitoring of protein translocation is achievable by means of nanopore methods, which include enzymatic and enzyme-less processes. For instance, motor proteins combined with electrophoresis-driven force can ratchet protein translocation residue-by-residue in a nanopore \u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Additionally, employing an electroosmotic flow can facilitate the translocation and recognition of unstructured native polypeptides, relying on the immobilization of charged groups (~\u0026thinsp;1 nm apart) in the nanopore lumen \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Although these approaches show promise, implementing the direct and accurate identification of individual amino acids during protein unfolding and translocation remains more challenging due to the diversity of molecular structures. For example, protein linearization is hindered by the heterogeneous distribution of charges in protein sequences caused by the diversity of 20 amino acids. In addition, the presence of residue modifications, as well as chiral levorotatory and dextrorotatory enantiomers, poses additional challenges that must be overcome to achieve efficient identification \u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. It was demonstrated that some forms of nanopore fingerprinting will precede de novo sequencing because of the difficulty of fully decoding protein nanopore signals with single amino acid resolution \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Currently, the nanopore research community is making progress toward achieving high-resolution differentiation of the 20 amino acids and modifications. As notable examples, metal-ion-modified nanopores (Ni or Cu) were constructed to ensure the binding and recognition of amino acids. Subsequently, enzymes for polypeptide digestion were used to determine the presence of detached amino acids, while the translation of the raw complex current signals was achieved by machine learning algorithms \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Another prominent method for identifying amino acids involved artificially tailored peptide sequences with certain individual amino acids arranged consecutively. This strategy also involved enzymatic cleavage and machine learning to produce and analyze distinct current signals via host-guest interactions in a nanopore, corresponding to the 20 integrated amino acids \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite many benefits, it should be noted that these emerging methods all involve chemical reactions and require machine learning to improve detection resolution and the translation of complex current events. The chemical reactions (e.g., proteolysis or chelation) can provide precise recognition of specific amino acids (either through peptide bond cleavage or ion-residue coordination), but the efficiency largely depends on the reaction activity and the reaction time, and each enzyme or ion usually recognizes a few different amino acids in the reactions. Consequently, machine learning algorithms are employed to precisely decode the current signals for amino acid discrimination. Likewise, chemical reactions may also be limited in achieving the efficient detection and discrimination of chiral enantiomers. Hence, the search for new methods to circumvent algorithm-assisted nanopore amino acid decoding and to avoid chemical reactions in the detection process is attracting particular attention in nanopore-based amino acid discrimination and protein sequencing.\u003c/p\u003e \u003cp\u003eDirect detection of single amino acids using an optimized electrolyte system is an ideal alternative solution to avoid the challenges of nanopore engineering and the limitations of chemical reaction efficiency due to time constraints. This strategy may incorporate electrophoretic force (EPF) and electroosmotic flow (EOF) as driving forces to facilitate the transport of all amino acids in an ideal biological nanopore with appropriate nanopore dimensions. Furthermore, this sensing strategy is adaptable to create highly specific and sensitive amino acid-recognition events with a high signal-to-noise ratio at sub-pA resolution levels, as well as a wide dynamic range of enantioselectivity. This should make it possible to accomplish rapid and direct signal readout in response to various amino acid molecules without the requirement of artificial intelligence-assisted data analysis \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe protective antigen of anthrax toxin, which assembles into a heptameric transmembrane pore (previously known as the PA\u003csub\u003e63\u003c/sub\u003e channel) under acidic conditions, is thus an ideal biological nanopore \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In anthrax toxin, it allows the intracellular transport of toxic enzyme components (i.e., lethal factor and edema factor), triggering the death of mammalian cells \u003csup\u003e\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In the past decade, research progress has been made in revealing the mechanisms of this toxic pore, as well as proposing the use of anthrax protective antigen to construct nanopores for single-molecule sensing. However, the anthrax nanopore struggles to form a stable single channel for satisfactory sensing applications with conventional K\u003csup\u003e+\u003c/sup\u003e or Na\u003csup\u003e+\u003c/sup\u003e electrolytes due to its intrinsic obstacles, such as a smaller open-pore current (~\u0026thinsp;5 pA), signal-to-noise interference, the frequent occurrence of gradually declining current trajectories, and pore occlusion phenomena dominated by phenylalanine molecular clamps \u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsidering its membrane-embedded structure and pore-forming features, we herein aim to construct a stable anthrax nanopore in a substituted electrolyte system using the anthrax protective antigen. As an alternative to traditional salts, ionic liquids contain organic macromolecular cations that provide superior electrochemical properties and chemical stability as an optimized electrolyte sensing element \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Meanwhile, we also apply an asymmetric pH condition to construct the functional anthrax nanopore because it has been demonstrated to be a proton-driven active channel \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The properties of the optimized electrolyte maintain the anthrax nanopore in an open state (~\u0026thinsp;5 pA) and eliminate channel occlusion phenomena (commonly referred to \u0026ldquo;gating\u0026rdquo;), thereby enabling the occurrence of noticeable current signals during the passage of ion/molecule flows. This approach not only constructs a stable anthrax nanopore at a single-channel level but also motivates the widespread application of the anthrax nanopore in single-molecule sensing.\u003c/p\u003e \u003cp\u003eHere, we demonstrate that by simply changing the electrolyte, a novel molecular clamping-containing anthrax nanopore can be functionalized for detecting and discriminating all natural amino acids, including levorotatory and dextrorotatory enantiomers. The observed current signals corresponding to the identification of chiral amino acids showed significant differences in terms of current amplitudes and residence times. In addition, amino acids of different properties (\u003cem\u003ei.e.\u003c/em\u003e, charged, polar and non-polar residues) exhibited diverse intermolecular forces (\u003cem\u003ei.e.\u003c/em\u003e, electrostatic force, π-π interactions and hydrogen bond interaction) within the anthrax nanopore, which were further combined with either electrophoretic force (EPF) or electroosmotic flow (EOF) to facilitate amino acids transport in the anthrax nanopore. Notably, all the observed differences in the current signals corresponding to the identified chiral amino acids were determined at the single-molecule level with femtosecond (fA) precision. This study provides an ideal nanopore architecture with ultrahigh sensing resolution, a wide dynamic range of enantioselectivity, and specificity. It may have the potential for protein sequencing via direct, residue-by-residue readout of amino acids.\u003c/p\u003e"},{"header":"Result and discussion","content":"\u003cp\u003e\u003cstrong\u003eConstruction and electrical characterization of a stable anthrax\u003csub\u003e\u0026nbsp;\u003c/sub\u003enanopore\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe configuration of a typical anthrax nanopore sensing system is illustrated in Fig. 1a. Anthrax protective antigen should be an ideal nanopore candidate that can offer high detection resolution due to its primary funnel shape structure. In particular, the channel mouth (\u003cem\u003ecis,\u003c/em\u003e ~30 \u0026Aring; in opening diameters and inner varying down to ~20 \u0026Aring;), \u0026Phi;-clamp (~6 \u0026Aring;), throat (~18 \u0026Aring;), and \u0026beta;-barrel stem (\u003cem\u003etrans\u003c/em\u003e, ~105 \u0026Aring; in length \u0026amp; ~12~18 \u0026Aring; in diameter) provide sensitive interface with numerous recognition sites for ion flow dynamics and molecular effects determination \u003csup\u003e29\u003c/sup\u003e. However, earlier studies have found that the functional phenylalanine clamps (\u0026Phi;-clamp) within the anthrax channel usually trigger phenomena like disruption of the equilibrium of ion flow and alteration of the channel activity between \u0026ldquo;occlusion\u0026rdquo; (refers to O\u003csub\u003e1\u003c/sub\u003e, channel current decrement,) and \u0026ldquo;non-occlusion\u0026rdquo; states (refers to O\u003csub\u003e2,\u003c/sub\u003e active state for electrical detection), in conventional electrolyte systems (K\u003csup\u003e+\u003c/sup\u003e or Na\u003csup\u003e+\u003c/sup\u003e). These resulting non-unique and unstable currents trajectories consequently lead to obstacles to produce satisfied electrical fingerprints for analyte sensing and analysis (Fig. 1a) \u003csup\u003e30\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe molecular mechanism reveals that the proton-driven clamp allostery is critical to regulate anthrax toxic proteins translocation though anthrax protective antigen channel \u003csup\u003e25\u003c/sup\u003e. We hypothesize that constructing a pH asymmetric system between the two ends of the channel \u003cem\u003e(i.e.,\u003c/em\u003e \u003cem\u003ecis:\u003c/em\u003e5.6 \u0026amp; \u003cem\u003etrans:\u003c/em\u003e7.6) to form a proton gradient could help establish a more stable and functional anthrax nanopore. Hence, monovalent cations (\u003cem\u003ei.e.,\u003c/em\u003e Na\u003csup\u003e+\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, Li\u003csup\u003e+\u003c/sup\u003e, [BMIM]\u003csup\u003e\u0026nbsp;+\u003c/sup\u003e) and Halogen anion (\u003cem\u003ei.e.,\u003c/em\u003e Cl\u003csup\u003e-1\u003c/sup\u003e) at either symmetric or asymmetric ion strengths were used to construct an optimized anthrax protective antigen nanopore. As a usual fashion of electrolyte (K\u003csup\u003e+\u003c/sup\u003e, Na\u003csup\u003e+\u003c/sup\u003e or Li\u003csup\u003e+\u003c/sup\u003e,) in nanopore electrical detection, we established four experimental systems with different ion concentrations but elected different pH strengths, applying -100 mV potential bias across the nanopore (System i: \u003cem\u003ecis/ trans:\u0026nbsp;\u003c/em\u003e0.5 M / 0.5 M, pH 7.6 / 7.6; System ii: \u003cem\u003ecis\u003c/em\u003e/\u003cem\u003etrans:\u003c/em\u003e1 M \u003cem\u003e/\u0026nbsp;\u003c/em\u003e0.5 M, pH 7.6 / 7.6; System iii: \u003cem\u003ecis/ trans\u003c/em\u003e: 1M / 0.5M, pH 5.6 / 7.6; System iv: \u003cem\u003ecis/trans:\u0026nbsp;\u003c/em\u003e0.5 M / 0.5 M, pH 5.6 / 7.6). For quantitative detection (Fig. S1), we defined several key parameters, such as opening pore current (\u003cem\u003eI\u003csub\u003eo\u003c/sub\u003e\u003c/em\u003e), event current blockage (\u003cem\u003eI\u003csub\u003eb\u003c/sub\u003e\u003c/em\u003e), noise levels (\u003cem\u003eS.D.\u003c/em\u003e, standard deviation of event noise levels), event interval time (\u003cem\u003et\u003csub\u003eon\u003c/sub\u003e\u003c/em\u003e), average interval time of events (\u003cem\u003e\u0026tau;\u003csub\u003eon\u003c/sub\u003e\u003c/em\u003e), and average dwell time (\u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e). We then tested whether these electrolyte systems could maintain nanopore stability under a typical single-channel condition. Meanwhile, we determined the\u0026nbsp;electrical performance\u0026nbsp;of anthrax nanopore by observing the pore stability (current trajectories), the open-pore current\u0026nbsp;discrete\u0026nbsp;constant (\u0026sigma;), the opening current strength of Io\u003csub\u003e2\u0026nbsp;\u003c/sub\u003e(active nanopore state), electrical conductivity (\u0026Omega;), as well as I-V curves. Among the parameters, the discrete constant (\u0026sigma;) is used to determine the discretization degree of nanopore electrical performance with different salts, particularly useful for characterizing the nanopore stability. A large \u0026sigma; indicates the larger degree of dispersion of nanopore current, meaning unstable and great current fluctuation in the nanopore electrical detection. In contrary, a small discrete constant (\u0026sigma;) means a stable nanopore electrical performance \u003csup\u003e31\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFig S2\u0026nbsp;shows the ionic current properties of anthrax nanopore with KCl electrolyte. The pH asymmetric KCl electrolytes produce clean nanopore channel without fluctuating current trajectories and any background signals (Fig. S2a-b). Despite no significant difference between the opening current strengths (Io\u003csub\u003e2\u003c/sub\u003e, Fig. S2c), the \u0026sigma; values of pH asymmetric systems were smaller than those of pH symmetric systems (Fig. S2d), whereas linear properties of I-V curves obtained (Fig. S2e). These experiments demonstrated that the pH asymmetric systems provided the proton-driven effect is easier to establish a clean nanopore channel. Similar phenomena were observed for anthrax nanopore with Na\u003csup\u003e+\u003c/sup\u003e and Li\u003csup\u003e\u0026nbsp;\u003c/sup\u003eelectrolytes (Fig. S3 \u0026amp; S4). In addition, the electrical conductivity of the nanopore was determined to be increased with the elevated ion strength, but does not change with the alteration of pH condition (Fig. S5a-c \u0026amp; Table S1). However, one limit is there, the open-pore current gradually decreased with recording time flies, this kind of unsatisfied nanopore current trajectories would greatly hinder subsequent detection work.\u003c/p\u003e\n\u003cp\u003eCompared to traditional salts, ionic liquids show better electrochemical properties in nanopore measurement \u003csup\u003e27, 28\u003c/sup\u003e. Therefore, we next used [BMIM]Cl to construct the anthrax nanopore system with either symmetric or asymmetric ion/pH strength (Fig. 1b-c, i-iv). Surprisingly, the electrical detection shows satisfied signal-to-noise ratios (no noticeable background signals) and stable nanopore current trajectories with both pH asymmetric systems. As the determined electrical properties shown (Fig. 1d), the electrolyte in ion symmetric and pH asymmetric produced smallest discrete constant (\u0026sigma; of system i-iv: 20.9 % \u003cem\u003evs.\u003c/em\u003e 21.68 % \u003cem\u003evs.\u003c/em\u003e 22.31 % \u003cem\u003evs.\u003c/em\u003e13.76 %) and larger opening current strength of Io\u003csub\u003e2\u003c/sub\u003e, meanwhile resulted in eliminating the occurrence of pore \u0026ldquo;occlusion\u0026rdquo; (O\u003csub\u003e1\u003c/sub\u003e, clamping frequency of i-iv: 3 min\u003csup\u003e-1\u003c/sup\u003e \u003cem\u003evs.\u0026nbsp;\u003c/em\u003e6.67 min\u003csup\u003e-1\u003c/sup\u003e \u003cem\u003evs.\u003c/em\u003e0 min\u003csup\u003e-1\u003c/sup\u003e\u003cem\u003evs.\u003c/em\u003e0 min\u003csup\u003e-1\u003c/sup\u003e), displaying a very satisfied channel stability. In addition, the current of anthrax nanopore in this optimized electrolyte system is symmetric and linear with respect to the sign of the applied transmembrane potentials, displaying a stable electrical conductance (Fig. 1e \u0026amp; Fig. S5d). Furthermore, no current trajectory decrement was observed even in long time recording. Thus, these data indicated that pH asymmetric, [BMIM]Cl strength symmetric electrolyte can contribute to a stable anthrax nanopore.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDifferent kinds of amino acids determined by EPF/EOF cooperated intermolecular interactions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn some cases, nanopore protein sequencing relying on amino acids identification was not efficiently enough to fully reveal the residues ordering, hence, the primary sequence was usually designed by artificially arranged in consecutive tailored sequence to segment into individual amino acid nodes, meaning a purpose-built method. Ideally, the complete amino acid sequence for a protein architecture should be identified during a head-to-tail translocation through the nanopore, where some amino acid nodes may be structure or polar similarity and some not at all. To help directly identify the single amino acid, we determine whether the optimized electrolyte assisted anthrax nanopore could be used for precise measurement of such small molecules (added to \u003cem\u003ecis\u003c/em\u003e). In our cases, the determination of single amino acids requires integration of\u0026nbsp;pH-asymmetric\u0026nbsp;condition. Due to the intrinsic isoelectric points of amino acids, those molecules exhibit different polarity in a pH5.6 (\u003cem\u003ecis\u003c/em\u003e) environment. Therefore, where possible, the different kinds of single amino acids require to be identified in the same electric field. Four amino acids as notable examples of different types were selected for the nanopore determination (Fig. 2a-i \u0026amp; Table S2), which arginine has the highest isoelectric point (short as R, positively charged, pI: 10.76), aspartic acid has the lowest isoelectric point (D, negatively charged, pI: 2.77), and tyrosine (Y, aromatic residue, pI: 5.68), glutamine (Q, polar residue, pI: 5.65), have pI approximate to the environment proton strength.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eElectrokinetic phenomenon occurs when a fluid flow through a porous medium under an applied potential bias which know as electroosmotic flow (EOF). Here, EOF was generated in the direction of the ion flow (\u003cem\u003ecis\u0026nbsp;\u003c/em\u003eto \u003cem\u003etrans\u003c/em\u003e) in anthrax nanopore \u003csup\u003e32-34\u003c/sup\u003e. Meanwhile, there was an electrophoretic force (EPF) during amino acids translocation in the nanopore. The strength and direction of EPF either increases or decreases depending on the difference between the molecular pI and the environment pH (5.6 as the boundary) \u003csup\u003e35\u003c/sup\u003e. The positive amino acids (pI \u0026gt; 5.6) pass through the nanopore by EPF in the direction of \u003cem\u003ecis\u0026nbsp;\u003c/em\u003eto \u003cem\u003etrans\u003c/em\u003e, while the translocation of negative amino acids (pI \u0026lt; 5.6) is inhibited by a reverse EPF (\u003cem\u003etrans\u003c/em\u003e to \u003cem\u003ecis\u003c/em\u003e), but may still translocate through the nanopore under EOF. EPF has minor effect on amino acids whose pI are approximate to 5.6. Therefore, EOF and EPF work differently on amino acids translocation in the nanopore and consequently produce current events containing distinctive features.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe applied bias was optimized (-100 mV) considering the opening pore current (Fig. S6 \u0026amp; Table S3), quality and quantity of the current events (Fig. S7-S9). In the resulting graph (Fig. 2a-ii \u0026amp; Fig. 2b), EPF and EOF driven arginine translocation produced current events containing distinctive features (\u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e = 73.51 %, \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u0026nbsp;\u003c/em\u003e= 3.23 ms). The detected amino acids showed single-gaussian and single-exponential distributions in the form of a single-peak for current blockages and dwell time. Tyrosine and glutamine translocation produced current events dominantly by EOF (Y: \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e = 82.07 %, \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e = 7.51 ms; Q: \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e = 77.18 %, \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e = 0.17 ms) (Fig. 2a-ii \u0026amp; Fig. 2c-d); Aspartic acid translocation was governed by both EOF and reverse EPF (\u003cem\u003etrans\u003c/em\u003e to \u003cem\u003ecis\u003c/em\u003e), whereas EPF was dominant, resulting in no current events produced (Fig. 2a-ii \u0026amp; Fig. 2e). Results demonstrated the current spectral reliability of anthrax nanopore is improved with prominent discrimination of amino acids in different kinds.\u003c/p\u003e\n\u003cp\u003eInterestingly, we found that the EOF driven current events frequencies regarding tyrosine and glutamine varied significantly (Y: 5.47 min\u003csup\u003e-1\u003c/sup\u003e \u003cem\u003evs.\u003c/em\u003e Q: 2.57 min\u003csup\u003e-1\u003c/sup\u003e). This variance should due to different intermolecular interactions between the detected amino acids and residues of inner interface of the anthrax nanopore \u003csup\u003e36\u003c/sup\u003e. In the nanopore, the most abundant interaction for tyrosine recognition means the \u0026pi;-\u0026pi; interaction by Tyr-Phe (Fig. 2c-i) \u003csup\u003e37, 38\u003c/sup\u003e, but for glutamine is the hydrogen bond interaction by NH\u003csub\u003e2\u003c/sub\u003e - OH groups (Fig. 2d-i). Besides, the interactions include the electrostatic force between arginine and the nanopore (Fig. 2b-i) \u003csup\u003e39, 40\u003c/sup\u003e, and the hydrogen bond interaction provided by aspartic acid (Fig. 2e-i) \u003csup\u003e41, 42\u003c/sup\u003e. Based on these experimental results, we can then conclude that the capture preference for different amino acids in anthrax nanopore is arginine \u0026gt; tyrosine \u0026gt; glutamine (9.30 min\u003csup\u003e-1\u003c/sup\u003e \u003cem\u003evs.\u0026nbsp;\u003c/em\u003e5.47 min\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003e\u003cem\u003evs.\u0026nbsp;\u003c/em\u003e2.57 min\u003csup\u003e-1\u003c/sup\u003e). In addition, it should be noted the kinetics of amino acids-anthrax nanopore interactions undergo association and dissociation rates, which were also detected under different applied bias (Fig. S10). \u003cem\u003eK\u003csub\u003eon\u003c/sub\u003e\u003c/em\u003e demonstrated that the intermolecular strengths between detected amino acids and the anthrax nanopore were in the order of electrostatic force \u0026gt; \u0026pi;-\u0026pi; interaction \u0026gt; hydrogen bond interaction (Fig. 2f, R: 2.16 \u0026micro;M\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003emin\u003csup\u003e-1\u003c/sup\u003e\u003cem\u003evs.\u0026nbsp;\u003c/em\u003eY: 1.28 \u0026micro;M\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003emin\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003e\u003cem\u003evs.\u003c/em\u003e Q: 0.91 \u0026micro;M\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003emin\u003csup\u003e-1\u003c/sup\u003e).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscriminate between different levorotary amino acids\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNext, we pursued the detailed statistical analysis based on the detection of 20 levorotary amino acids (Fig. 3). Amino acids translocated through the anthrax nanopore and produced distinct current events (Fig. 3a), of single-gaussian and single-exponential distributions for current blockages \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e and dwell time \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e, in response to charged (Fig. S11), polar (Fig. S12), and non-polar amino acids (Fig. S13). The differences in \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e between different categories of amino acids were visually represented using violin plots (Fig. 3b). In addition, we performed statistical comparisons in terms of \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e \u003cem\u003evs\u003c/em\u003e. molecular volume (Fig. 3c) and \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e \u003cem\u003evs\u003c/em\u003e. \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e (Fig. 3d) Results indicated that the discrimination of the amino acid molecules remained notable differences. Moreover, \u003cem\u003eK\u003csub\u003eon\u003c/sub\u003e\u003c/em\u003e suggested that different categories of amino acid molecules indeed induce noteworthy deviations in the intermolecular interaction strength in the nanopore detection (Fig. 3e, p \u0026lt; 0.01 %), in the order of charged residues \u0026gt; polar residues \u0026gt; non-polar residues, which enabled better differentiation of levorotary amino acids in anthrax nanopore.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo quantitatively describe the differences among levorotary amino acids, pairwise analyses were conducted and a cross-validation map was constructed (Fig. 3f). Each square represents mean t-test of the current blockages of two corresponding amino acids. Smaller p-values indicate greater differences between the detected amino acids. From all the resulting graphs, the differences in \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e existed among different levorotary amino acids, and our optimized anthrax nanopore could distinguish all detectable levorotary amino acids, including those ones showing subtle differences of \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e (\u0026lt; 2 %). Considering the opening pore current of the anthrax nanopore is in range of 3-5 pA. Hence, our nanopore enables to provide the efficient discrepancy of levorotary amino acids detection at the fA precision (\u0026lt; 100 fA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscriminate between different dextrorotary amino acids\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmino acids (except glycine) have a central carbon atom (\u0026alpha;-carbon), which is connected to an amino group (-NH₂), a carboxyl group (-COOH), a hydrogen atom (-H), and a side chain (R). This central carbon atom is chiral, resulting in two distinct stereoisomers of amino acids: levorotary type and dextrorotary type. Chirality amino acids paly significant roles in terms of biological activity, protein structure and function, and pharmaceutics etc \u003csup\u003e43, 44\u003c/sup\u003e. Therefore, the detection and then differentiation of dextrorotary (\u003cem\u003ed-\u003c/em\u003e) amino acids is particularly important.\u0026nbsp;We employed the same anthrax nanopore approach and experimental conditions to detect dextrorotary amino acids enantiomers. EOF and EPF-driven enantiomers translocation produced current events containing characteristic features (Fig. 4a \u0026amp; Fig. S14-16). Similarly, the quantitative analysis of \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e of the three groups of dextrorotary amino acids were visually represented using violin plots, revealing those significant differences between each other (Fig. 4b). Additionally, statistical comparisons in terms of \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e \u003cem\u003evs\u003c/em\u003e. molecular volume (Fig. 4c) and \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e \u003cem\u003evs\u003c/em\u003e. \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e (Fig. 4d) were conducted, the same discrimination reliability for dextrorotary amino acids was observed, where better visual differentiation is shown in a cross-validation map (Fig. 4f). Likewise, the kinetics of dextrorotary amino acids-anthrax nanopore interactions were also determined. However, the \u003cem\u003eK\u003csub\u003eon\u003c/sub\u003e\u003c/em\u003e of the three types of dextrorotary amino acids exhibit a different stepwise distribution from that of levorotary amino acids, in the order of charged residues \u0026gt; non-polar residues \u0026gt; polar residues (Fig. 4e, p \u0026lt; 0.01 %). Nevertheless, the anthrax nanopore can also distinguish all detected dextrorotary amino acids at the fA precision.\u003c/p\u003e\n\u003cp\u003eIt is likely that no significant differences at \u0026Delta; I/Io levels occured (Fig. 3f and Fig. 4f, P \u0026gt; 5%) in some instances--for example, levorotary type: H \u003cem\u003evs.\u003c/em\u003e M, V \u003cem\u003evs.\u003c/em\u003e W and dextrorotary type (term as \u0026ldquo;\u003cem\u003ed-\u0026rdquo;\u0026nbsp;\u003c/em\u003ein figures): \u003cem\u003ed-\u003c/em\u003eR \u003cem\u003evs.\u003c/em\u003e\u003cem\u003ed-\u003c/em\u003eT, \u003cem\u003ed-\u003c/em\u003eC \u003cem\u003evs.\u003c/em\u003e\u003cem\u003ed-\u003c/em\u003eK. Thus, the discrimination was dependent on \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003elevels. \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003eof the current events reflects the mean time that molecules stay in the nanopore which is may resulted distinguishing criterion of false positives. To give unbiased discrimination of these amino acids\u0026rsquo; samples, sensitive single-molecule amino acids identification demands discrimination throughput to be in the large numbers of observed events of mixed samples. We determined \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e threshold to identify these amino acids based on simultaneous detection of mixed samples (Fig. S17a-b). As results indicated, \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e \u0026gt; 2.68 ms likely corresponds to M while \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e \u0026lt; 2.68 ms corresponds to H. \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e \u0026gt; 4.26 ms corresponds to V while \u0026lt; 4.26 ms corresponds to W. For dextrorotary amino acids, the computational curves indicated that \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e \u0026gt; 7.89 ms is likely \u003cem\u003ed\u003c/em\u003e-C while \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e \u0026lt; 7.89 ms most possibly represents \u003cem\u003ed\u003c/em\u003e-K (Fig. S17c). However, there is no doubt to\u003cem\u003e\u0026nbsp;d\u003c/em\u003e-R and \u003cem\u003ed\u003c/em\u003e-T judgement because of significant differences of \u003cem\u003e\u0026tau;\u003csub\u003eoff\u003c/sub\u003e\u003c/em\u003e (Fig. S17d). Therefore, the four amino acid groups may not present false positives using anthrax nanopore based precise differentiation. Furthermore, the plots of \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e\u003cem\u003evs.\u0026nbsp;\u003c/em\u003erelative molecular mass were also constructed to precisely distinguish levorotary and dextrorotary amino acids, respectively (Fig. S18). Consequently, the success makes us confident that anthrax nanopore benefits discriminating chiral amino acids at single-molecule level but no necessities of enzymes or nanopore engineering.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscriminate between chiral enantiomers of amino acids\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have respectively differentiated levorotary amino acids and dextrorotary amino acids (term as \u0026ldquo;\u003cem\u003ed-\u0026rdquo;\u0026nbsp;\u003c/em\u003ein following figures). It is not clear whether molecular chirality is abided or participate chemical reactions during the linearization and sequencing. Hence, there is an increasing necessity to make highly specific and sensitive differences between chiral enantiomers of same individual amino acids. We used the mean \u0026Delta;I/I\u003csub\u003eo\u003c/sub\u003e of the levorotary amino acids and dextrorotary amino acids as t-test means to determine the difference between tested chiral amino acids. Taking valine (V) for example, V and \u003cem\u003ed-\u003c/em\u003eV were respectively used as control (\u003cem\u003eCtl.\u003c/em\u003e). It is reasonable that the t-test (P = 99.68 %) indicated no significant difference between V (\u003cem\u003eCtl.\u003c/em\u003e) and V (\u003cem\u003eTest\u003c/em\u003e); In contrast, the t-test approaches to \u0026ldquo;0\u0026rdquo; (P \u0026lt; 0.01 %) indicates significant difference between current signals of V (\u003cem\u003eCtl.\u003c/em\u003e) and \u003cem\u003ed-\u003c/em\u003eV (\u003cem\u003eTest\u003c/em\u003e). Similarly, it is reasonable that the t-test (P = 99.99 %) indicated no significant difference between \u003cem\u003ed-\u003c/em\u003eV(\u003cem\u003eCtl.\u003c/em\u003e) and \u003cem\u003ed-\u003c/em\u003eV (\u003cem\u003eTest\u003c/em\u003e); while the t-test approaches to \u0026ldquo;0\u0026rdquo; (P \u0026lt; 0.01%) indicates significant difference between current signals of \u003cem\u003ed-\u003c/em\u003eV (\u003cem\u003eCtl.\u003c/em\u003e) and V (\u003cem\u003eTest\u003c/em\u003e). Finally, the efficient discrimination of chiral enantiomers of amino acids was statistical supported by t-test analysis of variance (P\u0026thinsp;\u0026lt; 0.01 %) for each comparison \u003cem\u003evia\u003c/em\u003e applying the current signals produced by each amino acid (Fig. 5). These kinds of results would ultimately increase the accessibility of chiral amino acids enantiomers identification.\u003c/p\u003e\n\u003cp\u003eChiral enantiomers of amino acids generated distinct current signals when passing through anthrax nanopores, these differences are likely attributed to the following reasons: Spatial structural differences due to different chirality most likely to originate difference of nanopore current signals which agrees with previous studies on molecular dynamics simulation \u003csup\u003e45\u003c/sup\u003e. In addition, it caused differences in non-covalent interactions (\u003cem\u003ei.e.,\u003c/em\u003e electrostatic force, \u0026pi;-\u0026pi; interaction, hydrogen bond interaction) during the molecular translocation across the nanopore. For example, it was evidenced that the chirality of amino acids causes slight variations in charge distribution and polarity of amino acids. The spatial configuration differences between levorotary and dextrorotary amino acids may influence molecular binding stability and energy, thereby altering electrostatic interactions with nanopore surface \u003csup\u003e46\u003c/sup\u003e; Meanwhile, the chirality affects \u0026pi;-\u0026pi; interactions between the detected aromatic amino acids and phenylalanine clamps in the anthrax nanopore because the chirality of different amino acids exhibits varying orientations of aromatic groups, thus altering interaction strength \u003csup\u003e47\u003c/sup\u003e; Besides, the chirality directly influences the spatial positioning of their hydrogen bond donor or acceptor groups. For instance, the orientation variations of the amino and carboxyl groups in chiral isomers can lead to differences in the hydrogen bond network formed with functional groups in the nanopore. These differences affect not only the number of hydrogen bonds but also the molecular binding stability \u003csup\u003e48\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDifferences in current signals between amino acid enantiomers arise from varying interactions with anthrax nanopores, we further determined their respective capture frequencies (r and r\u0026rsquo;) in the nanopore. Differences in capture frequencies may indicate the interactions variances between nanopores and detected amino acids; higher capture frequencies suggest stronger interactions, and vice versa. It was observed that the chirality indeed affects capture rates of each amino acids induced by interactions between enantiomers and nanopores (Fig. 6a-c). To further investigate the effect of chiral transformation on amino acids with different properties, we calculated the difference of capture rates between chiral amino acids enantiomers (D=r-r \u0026apos;, Fig. 6d). The comparison was also classified according to amino acids categories using the value differences of average capture rates between chiral enantiomers which were defined as AvgD=(r-r\u0026apos;)/n (Fig. 6e). Meanwhile, the absolute differences of average capture rates were defined as Avg | D |=| r-r \u0026apos;|/n (Fig. 6f), where n is the number of amino acids of each category. It was observed that the capture rates of levorotary amino acids in charged and non-polar categories were lower than the dextrorotary enantiomers, while levorotary polar amino acids showed higher capture rates than those of dextrorotary enantiomers (Fig. 6d), it is more intuitively seen from AvgD statistics (Fig. 6e). Moreover, Avg | D | represents the degree of chirality influence on capture efficiency of different types of amino acids. The larger Avg | D |, the greater the differences in capture efficiency between chiral of these amino acids\u0026rsquo; enantiomers, indicating the greater differences on interactions with anthrax nanopores, and vice versa. It was evident that the interactions of charged amino acids were most strongly affected by chirality, followed by non-polar amino acids, and polar amino acids are least affected.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, we constructed a stable wild-type anthrax nanopore in a pH-asymmetric electrolyte system based on the proton-driven mechanism and the electrochemical stability of ionic liquids. By means of the anthrax nanopore, our research highlighted the ultrahigh sensing resolution (at fA precision) in the precise differentiation of natural amino acids as well as levorotatory and dextrorotatory enantiomers with subtle conformational changes. It is noted that the proposed anthrax nanopore amino acid discrimination doesn\u0026rsquo;t need enzymes (nor other chemical reactions) nor machine learning algorithms, but relies simply on the optimization of the electrolyte system and the use of statistical parameters such as the strength ΔI/I\u003csub\u003eo\u003c/sub\u003e and, in some instances, the lifetime of resistive pulses (τ\u003csub\u003eoff\u003c/sub\u003e) of the nanopore current signals.\u003c/p\u003e \u003cp\u003eMeanwhile, we demonstrated that the detection of amino acids was either dominated by the electric field force or electroosmotic flow, depending on the isoelectric points of the amino acid analyte, in response to the difference in proton concentration (\u003cem\u003ei.e., cis/trans\u003c/em\u003e: pH5.6/7.6). The mechanism of discrimination by nanopore current signals was also explained by the action of heterogeneous intermolecular interactions (\u003cem\u003ei.e.\u003c/em\u003e, electrostatic force, π-π interaction, hydrogen bond interaction) mediated by the contacting residues, between the different kinds of amino acids and the nanopore interface. Statistical analyses of the translocation signal intensities and the molecular binding constants \u003cem\u003eK\u003c/em\u003e\u003csub\u003e\u003cem\u003eon\u003c/em\u003e\u003c/sub\u003e revealed the fact that the strength of intermolecular forces was in the order of electrostatic force\u0026thinsp;\u0026gt;\u0026thinsp;π-π interactions\u0026thinsp;\u0026gt;\u0026thinsp;hydrogen bonding. In terms of capture frequency in anthrax nanopores, charged and non-polar levorotatory amino acids were significantly lower than dextrorotatory isomers, while polar levorotatory amino acids were more frequently captured than their corresponding dextrorotatory isomers. Additionally, the capture frequency of charged amino acids was most affected by chirality, followed by non-polar amino acids, while polar amino acids were the least affected.\u003c/p\u003e \u003cp\u003eIt is likely that some form of nanopore amino acids discrimination will precede de novo sequencing because of the difficulty of fully decoding single protein translocation signals. Must admit that, in some cases, the nanopore protein sequencing relying on amino acids identification were not efficiently enough to fully reveal these residues ordering. To enable comprehensive profiling and de novo protein sequencing using anthrax nanopore, future work should concentrate on protein engineering to optimize the conformational breakdown and linearization for native proteins or peptides in the nanopore and to translate the sequence-dependent raw currents features \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Ideally, the complete protein architecture should be identified by amino acid nodes (or carry modifications) during a head-to-tail translocation through the nanopore, where some proteins may be structurally very similar and others not at all. Nevertheless, this enzyme-less sensing strategy has overcome one of the major obstacles in amino acid discrimination by creating highly specific and sensitive amino acid-recognition events with a high signal-to-noise ratio at sub-pA resolution levels, as well as a wide dynamic range of enantioselectivity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.W.: methodology, investigation, software, data curation, original draft preparation. Y.W.: funding acquisition, data curation, formal analysis. L.W., J.L., S.L., and Z.Z.: software, data curation, formal analysis. L.W.: conceptualization, methodology, supervision, project administration, funding acquisition, reviewing and editing of manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorresponding Author\u003c/p\u003e\n\u003cp\u003eDr. Liang Wang-Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences \u0026amp; Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. orcid.org/0000-0002-7404-4319, Email: [email protected]\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYan Wang- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences \u0026amp; Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. Yunjiao Wang-Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences \u0026amp; Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. orcid.org/0000-0002-7002-0889\u003c/p\u003e\n\u003cp\u003eLebing Wang- School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences \u0026amp; Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China.\u003c/p\u003e\n\u003cp\u003eJing Li-School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences \u0026amp; Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China.\u003c/p\u003e\n\u003cp\u003eShilong Liu- School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences \u0026amp; Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China.\u003c/p\u003e\n\u003cp\u003eZhirui Zhang-Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences \u0026amp; Chongqing School, The University of Chinese Academy of Sciences, Chongqing 400714, China. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Key Research and Development Program of China (2022YFB3205600), Natural Science Foundation of Chongqing (CSTB2023NSCQ-MSX0071), and the Youth Innovation Promotion Association (2022388) of Chinese Academy of Sciences.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence and requests for materials\u003c/strong\u003e should be addressed to Liang Wang.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKasianowicz, J. J.; Brandin, E.; Branton, D. Characterization of individual polynucleotide molecules using a membranechannel. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America \u003c/em\u003e\u003cstrong\u003e1996\u003c/strong\u003e, \u003cem\u003e93\u003c/em\u003e (24), 13770-13773.\u003c/li\u003e\n\u003cli\u003eEnsslen, T.; Sarthak, K.; Aksimentiev, A.; Behrends, J. C. Resolving Isomeric Posttranslational Modifications Using a Biological Nanopore as a Sensor of Molecular Shape. \u003cem\u003eJournal of the American Chemical Society \u003c/em\u003e\u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e144\u003c/em\u003e (35), 16060-16068. DOI: 10.1021/jacs.2c06211.\u003c/li\u003e\n\u003cli\u003eMartin-Baniandres, P.; Lan, W.-H.; Board, S.; Romero-Ruiz, M.; Garcia-Manyes, S.; Qing, Y.; Bayley, H. Enzyme-less nanopore detection of post-translational modifications within long polypeptides. \u003cem\u003eNature Nanotechnology \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e18\u003c/em\u003e (11), 1335-1340. DOI: 10.1038/s41565-023-01462-8.\u003c/li\u003e\n\u003cli\u003eJiang, J.; Li, M.-Y.; Wu, X.-Y.; Ying, Y.-L.; Han, H.-X.; Long, Y.-T. Protein nanopore reveals the renin\u0026ndash;angiotensin system crosstalk with single-amino-acid resolution. \u003cem\u003eNature Chemistry \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e15\u003c/em\u003e (4), 578-586. DOI: 10.1038/s41557-023-01139-8.\u003c/li\u003e\n\u003cli\u003eNiu, 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. \u003cem\u003eNature Chemical Biology \u003c/em\u003e\u003cstrong\u003e2024\u003c/strong\u003e. DOI: 10.1038/s41589-024-01734-x.\u003c/li\u003e\n\u003cli\u003eBrinkerhoff, H.; Kang, A. S. W.; Liu, J.; Aksimentiev, A.; Dekker, C. Multiple rereads of single proteins at single\u0026ndash;amino acid resolution using nanopores. \u003cem\u003eScience \u003c/em\u003e\u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e374\u003c/em\u003e (6574), 1509-1513. DOI: 10.1126/science.abl4381 (acccessed 2025/01/13).\u003c/li\u003e\n\u003cli\u003eYan, S.; Zhang, J.; Wang, Y.; Guo, W.; Zhang, S.; Liu, Y.; Cao, J.; Wang, Y.; Wang, L.; Ma, F.; Zhang, P.; Chen, H.-Y.; Huang, S. Single Molecule Ratcheting Motion of Peptides in a Mycobacterium smegmatis Porin A (MspA) Nanopore. \u003cem\u003eNano Letters \u003c/em\u003e\u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e21\u003c/em\u003e (15), 6703-6710. DOI: 10.1021/acs.nanolett.1c02371.\u003c/li\u003e\n\u003cli\u003eChen, Z.; Wang, Z.; Xu, Y.; Zhang, X.; Tian, B.; Bai, J. Controlled movement of ssDNA conjugated peptide through Mycobacterium smegmatis porin A (MspA) nanopore by a helicase motor for peptide sequencing application. \u003cem\u003eChemical Science \u003c/em\u003e\u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e12\u003c/em\u003e (47), 15750-15756, 10.1039/D1SC04342K. DOI: 10.1039/D1SC04342K.\u003c/li\u003e\n\u003cli\u003eSauciuc, A.; Morozzo della Rocca, B.; Tadema, M. J.; Chinappi, M.; Maglia, G. Translocation of linearized full-length proteins through an engineered nanopore under opposing electrophoretic force. \u003cem\u003eNature Biotechnology \u003c/em\u003e\u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e42\u003c/em\u003e (8), 1275-1281. DOI: 10.1038/s41587-023-01954-x.\u003c/li\u003e\n\u003cli\u003eJeong, Y.; Kim, H. W.; Ku, J.; Seo, J. Breakdown of chiral recognition of amino acids in reduced dimensions. \u003cem\u003eScientific Reports \u003c/em\u003e\u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e10\u003c/em\u003e (1), 16166. DOI: 10.1038/s41598-020-73300-z.\u003c/li\u003e\n\u003cli\u003eChen, X.; Zhu, R.; Zhang, B.; Zhang, X.; Cheng, A.; Liu, H.; Gao, R.; Zhang, X.; Chen, B.; Ye, S.; Jiang, J.; Zhang, G. Rapid room-temperature phosphorescence chiral recognition of natural amino acids. \u003cem\u003eNature Communications \u003c/em\u003e\u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e15\u003c/em\u003e (1), 3314. DOI: 10.1038/s41467-024-47648-z.\u003c/li\u003e\n\u003cli\u003eWoiwode, U.; Reischl, R. J.; Buckenmaier, S.; Lindner, W.; L\u0026auml;mmerhofer, M. Imaging Peptide and Protein Chirality via Amino Acid Analysis by Chiral \u0026times; Chiral Two-Dimensional Correlation Liquid Chromatography. \u003cem\u003eAnalytical Chemistry \u003c/em\u003e\u003cstrong\u003e2018\u003c/strong\u003e, \u003cem\u003e90\u003c/em\u003e (13), 7963-7971. DOI: 10.1021/acs.analchem.8b00676.\u003c/li\u003e\n\u003cli\u003eMagal\u0026iacute;, L.; Tomba, G.; Costantini, G.; Lucio, C. C.; Alessandro, D. V.; Kern, K. Cover Picture: Tracking the Chiral Recognition of Adsorbed Dipeptides at the Single-Molecule Level (Angew. Chem. Int. Ed. 24/2007). \u003cem\u003eAngewandte Chemie International Edition \u003c/em\u003e\u003cstrong\u003e2007\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eMotone, K.; Nivala, J. Not if but when nanopore protein sequencing meets single-cell proteomics. \u003cem\u003eNature Methods \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e20\u003c/em\u003e (3), 336-338. DOI: 10.1038/s41592-023-01800-7.\u003c/li\u003e\n\u003cli\u003eWang, K.; Zhang, S.; Zhou, X.; Yang, X.; Li, X.; Wang, Y.; Fan, P.; Xiao, Y.; Sun, W.; Zhang, P.; Li, W.; Huang, S. Unambiguous discrimination of all 20 proteinogenic amino acids and their modifications by nanopore. \u003cem\u003eNature Methods \u003c/em\u003e\u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e21\u003c/em\u003e (1), 92-101. DOI: 10.1038/s41592-023-02021-8.\u003c/li\u003e\n\u003cli\u003eZhang, M.; Tang, C.; Wang, Z.; Chen, S.; Zhang, D.; Li, K.; Sun, K.; Zhao, C.; Wang, Y.; Xu, M.; Dai, L.; Lu, G.; Shi, H.; Ren, H.; Chen, L.; Geng, J. Real-time detection of 20 amino acids and discrimination of pathologically relevant peptides with functionalized nanopore. \u003cem\u003eNature Methods \u003c/em\u003e\u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e21\u003c/em\u003e (4), 609-618. DOI: 10.1038/s41592-024-02208-7.\u003c/li\u003e\n\u003cli\u003eZhang, Y.; Yi, Y.; Li, Z.; Zhou, K.; Liu, L.; Wu, H.-C. Peptide sequencing based on host\u0026ndash;guest interaction-assisted nanopore sensing. \u003cem\u003eNature Methods \u003c/em\u003e\u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e21\u003c/em\u003e (1), 102-109. DOI: 10.1038/s41592-023-02095-4.\u003c/li\u003e\n\u003cli\u003eTaylor, C. J.; Pomberger, A.; Felton, K. C.; Grainger, R.; Barecka, M.; Chamberlain, T. W.; Bourne, R. A.; Johnson, C. N.; Lapkin, A. A. A Brief Introduction to Chemical Reaction Optimization. \u003cem\u003eChemical Reviews \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e123\u003c/em\u003e (6), 3089-3126. DOI: 10.1021/acs.chemrev.2c00798.\u003c/li\u003e\n\u003cli\u003eKalu, N.; Alcaraz, A.; Yamini, G.; Abolfath, S. M.; Lucas, L.; Kenney, C.; Aguilella, V. M.; Nestorovich, E. M. Effect of endosomal acidification on small ion transport through the anthrax toxin PA63 channel. \u003cem\u003eFebs Letters \u003c/em\u003e\u003cstrong\u003e2017\u003c/strong\u003e, \u003cem\u003e591\u003c/em\u003e (21).\u003c/li\u003e\n\u003cli\u003eNassi, S.; Collier, R. J.; Finkelstein, A. PA63 Channel of Anthrax Toxin:\u0026thinsp; An Extended \u0026beta;-Barrel. \u003cem\u003eBiochemistry \u003c/em\u003e\u003cstrong\u003e2002\u003c/strong\u003e, \u003cem\u003e41\u003c/em\u003e (5), 1445-1450. DOI: 10.1021/bi0119518.\u003c/li\u003e\n\u003cli\u003eNablo, B. J.; Halverson, K. M.; Robertson, J. W. F.; Nguyen, T. L.; Panchal, R. G.; Gussio, R.; Bavari, S.; Krasilnikov, O. V.; Kasianowicz, J. J. Sizing the \u0026lt;em\u0026gt;Bacillus anthracis\u0026lt;/em\u0026gt; PA\u0026lt;sub\u0026gt;63\u0026lt;/sub\u0026gt; Channel with Nonelectrolyte Poly(Ethylene Glycols). \u003cem\u003eBiophysical Journal \u003c/em\u003e\u003cstrong\u003e2008\u003c/strong\u003e, \u003cem\u003e95\u003c/em\u003e (3), 1157-1164. DOI: 10.1529/biophysj.107.121715 (acccessed 2025/01/18).\u003c/li\u003e\n\u003cli\u003eKasianowicz, J. J.; Nguyen, T. L.; Stanford, V. M. Enhancing molecular flux through nanopores by means of attractive interactions. \u003cem\u003eProceedings of the National Academy of Sciences \u003c/em\u003e\u003cstrong\u003e2006\u003c/strong\u003e, \u003cem\u003e103\u003c/em\u003e (31), 11431-11432. DOI: 10.1073/pnas.0603951103 (acccessed 2025/01/13).\u003c/li\u003e\n\u003cli\u003eKrantz, B. A.; Trivedi, A. D.; Cunningham, K.; Christensen, K. A.; Collier, R. J. Acid-induced Unfolding of the Amino-terminal Domains of the Lethal and Edema Factors of Anthrax Toxin. \u003cem\u003eJournal of Molecular Biology \u003c/em\u003e\u003cstrong\u003e2004\u003c/strong\u003e, \u003cem\u003e344\u003c/em\u003e (3), 739-756. DOI: https://doi.org/10.1016/j.jmb.2004.09.067.\u003c/li\u003e\n\u003cli\u003eHalverson, K. M.; Panchal, R. G.; Nguyen, T. L.; Gussio, R.; Little, S. F.; Misakian, M.; Bavari, S.; Kasianowicz, J. J. Anthrax Biosensor, Protective Antigen Ion Channel Asymmetric Blockade *. \u003cem\u003eJournal of Biological Chemistry \u003c/em\u003e\u003cstrong\u003e2005\u003c/strong\u003e, \u003cem\u003e280\u003c/em\u003e (40), 34056-34062. DOI: 10.1074/jbc.M507928200 (acccessed 2025/01/18).\u003c/li\u003e\n\u003cli\u003eDas, D.; Krantz, B. A. Peptide- and proton-driven allosteric clamps catalyze anthrax toxin translocation across membranes. \u003cem\u003eProceedings of the National Academy of Sciences \u003c/em\u003e\u003cstrong\u003e2016\u003c/strong\u003e, \u003cem\u003e113\u003c/em\u003e (34), 9611-9616. DOI: 10.1073/pnas.1600624113 (acccessed 2025/01/18).\u003c/li\u003e\n\u003cli\u003ePanchal, R. G.; Halverson, K. M.; Ribot, W.; Lane, D.; Kenny, T.; Abshire, T. G.; Ezzell, J. W.; Hoover, T. A.; Powell, B.; Little, S.; Kasianowicz, J. J.; Bavari, S. Purified \u0026lt;em\u0026gt;Bacillus anthracis\u0026lt;/em\u0026gt; Lethal Toxin Complex Formed \u0026lt;em\u0026gt;in Vitro\u0026lt;/em\u0026gt; and during Infection Exhibits Functional and Biological Activity *. \u003cem\u003eJournal of Biological Chemistry \u003c/em\u003e\u003cstrong\u003e2005\u003c/strong\u003e, \u003cem\u003e280\u003c/em\u003e (11), 10834-10839. DOI: 10.1074/jbc.M412210200 (acccessed 2025/01/18).\u003c/li\u003e\n\u003cli\u003ede Zoysa, R. S. S.; Jayawardhana, D. A.; Zhao, Q.; Wang, D.; Armstrong, D. W.; Guan, X. Slowing DNA Translocation through Nanopores Using a Solution Containing Organic Salts. \u003cem\u003eThe Journal of Physical Chemistry B \u003c/em\u003e\u003cstrong\u003e2009\u003c/strong\u003e, \u003cem\u003e113\u003c/em\u003e (40), 13332-13336. DOI: 10.1021/jp9040293.\u003c/li\u003e\n\u003cli\u003eMahendran, K. R.; Raj Singh, P.; Modi, N.; Schulz, R.; Kleinekath\u0026ouml;fer, U.; Winterhalter, M. Probing the Transport of Ionic Liquids in Aqueous Solution through Nanopores. \u003cem\u003eBiophysical Journal \u003c/em\u003e\u003cstrong\u003e2012\u003c/strong\u003e, \u003cem\u003e102\u003c/em\u003e (3), 205a. DOI: 10.1016/j.bpj.2011.11.1118 (acccessed 2025/01/18).\u003c/li\u003e\n\u003cli\u003eJiang, J.; Pentelute, B. L.; Collier, R. J.; Zhou, Z. H. Atomic structure of anthrax protective antigen pore elucidates toxin translocation. \u003cem\u003eNature \u003c/em\u003e\u003cstrong\u003e2015\u003c/strong\u003e, \u003cem\u003e521\u003c/em\u003e (7553), 545-549. DOI: 10.1038/nature14247.\u003c/li\u003e\n\u003cli\u003eMelnyk, R. A.; Collier, R. J. A loop network within the anthrax toxin pore positions the phenylalanine clamp in an active conformation. \u003cem\u003eProceedings of the National Academy of Sciences \u003c/em\u003e\u003cstrong\u003e2006\u003c/strong\u003e, \u003cem\u003e103\u003c/em\u003e (26), 9802-9807. DOI: 10.1073/pnas.0604000103 (acccessed 2025/01/13).\u003c/li\u003e\n\u003cli\u003eRoy; Dilip. The Discrete Normal Distribution. \u003cem\u003eCommunications in Statistics Theory \u0026amp; Methods \u003c/em\u003e\u003cstrong\u003e2003\u003c/strong\u003e, \u003cem\u003e32\u003c/em\u003e (10), 1871-1883.\u003c/li\u003e\n\u003cli\u003eRezaei, M.; Azimian, A. R.; Semiromi, D. T. The surface charge density effect on the electro-osmotic flow in a nanochannel: a molecular dynamics study. \u003cem\u003eHeat and Mass Transfer \u003c/em\u003e\u003cstrong\u003e2015\u003c/strong\u003e, \u003cem\u003e51\u003c/em\u003e (5), 661-670. DOI: 10.1007/s00231-014-1441-y.\u003c/li\u003e\n\u003cli\u003eMoschopoulos, P.; Dimakopoulos, Y.; Tsamopoulos, J. Electro-osmotic flow of electrolyte solutions of PEO in microfluidic channels. \u003cem\u003eJournal of Colloid and Interface Science \u003c/em\u003e\u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e563\u003c/em\u003e, 381-393. DOI: https://doi.org/10.1016/j.jcis.2019.12.052.\u003c/li\u003e\n\u003cli\u003eLiu, Y.; Wang, K.; Wang, Y.; Wang, L.; Yan, S.; Du, X.; Zhang, P.; Chen, H.-Y.; Huang, S. Machine Learning Assisted Simultaneous Structural Profiling of Differently Charged Proteins in a Mycobacterium smegmatis Porin A (MspA) Electroosmotic Trap. \u003cem\u003eJournal of the American Chemical Society \u003c/em\u003e\u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e144\u003c/em\u003e (2), 757-768. DOI: 10.1021/jacs.1c09259.\u003c/li\u003e\n\u003cli\u003eBandara, Y. M. N. D. Y.; Farajpour, N.; Freedman, K. J. Nanopore Current Enhancements Lack Protein Charge Dependence and Elucidate Maximum Unfolding at Protein\u0026rsquo;s Isoelectric Point. \u003cem\u003eJournal of the American Chemical Society \u003c/em\u003e\u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e144\u003c/em\u003e (7), 3063-3073. DOI: 10.1021/jacs.1c11540.\u003c/li\u003e\n\u003cli\u003eJia, W.; Ouyang, Y.; Zhang, S.; Du, X.; Zhang, P.; Huang, S. Nanopore Signatures of Nucleoside Drugs. \u003cem\u003eNano Letters \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e23\u003c/em\u003e (20), 9437-9444. DOI: 10.1021/acs.nanolett.3c02872.\u003c/li\u003e\n\u003cli\u003eHao, W.; Guo, B.; Liu, J.; Ren, Q.; Li, S.; Li, Q.; Zhou, K.; Liu, L.; Wu, H.-C. Single-Molecule Exchange inside a Nanocage Provides Insights into the Origin of \u0026pi;\u0026ndash;\u0026pi; Interactions. \u003cem\u003eJournal of the American Chemical Society \u003c/em\u003e\u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e146\u003c/em\u003e (14), 10206-10216. DOI: 10.1021/jacs.4c03159.\u003c/li\u003e\n\u003cli\u003eChen, F.; Tang, J.; Wang, J. Effects of \u0026pi;\u0026ndash;\u0026pi; Stacking on Shale Gas Adsorption and Transport in Nanopores. \u003cem\u003eACS Omega \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e8\u003c/em\u003e (49), 46577-46588. DOI: 10.1021/acsomega.3c05522.\u003c/li\u003e\n\u003cli\u003eAsandei, A.; Chinappi, M.; Kang, H.-K.; Seo, C. H.; Mereuta, L.; Park, Y.; Luchian, T. Acidity-Mediated, Electrostatic Tuning of Asymmetrically Charged Peptides Interactions with Protein Nanopores. \u003cem\u003eACS Applied Materials \u0026amp; Interfaces \u003c/em\u003e\u003cstrong\u003e2015\u003c/strong\u003e, \u003cem\u003e7\u003c/em\u003e (30), 16706-16714. DOI: 10.1021/acsami.5b04406.\u003c/li\u003e\n\u003cli\u003eLuchian, T. Dipole potential-induced modulation of the interactions between reconstituted lipid membranes and certain pore-forming peptides. \u003cem\u003eRevue Roumaine de Chimie \u003c/em\u003e\u003cstrong\u003e2009\u003c/strong\u003e, \u003cem\u003e54\u003c/em\u003e (6), 455-463.\u003c/li\u003e\n\u003cli\u003eIlgen, A. G.; Senanayake, H. S.; Thompson, W. H.; Greathouse, J. A. Structure and energetics of hydrogen bonding networks in dilute HOD/H2O solutions confined in silica nanopores. \u003cem\u003eEnvironmental Science: Nano \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e10\u003c/em\u003e (11), 3025-3038, 10.1039/D3EN00291H. DOI: 10.1039/D3EN00291H.\u003c/li\u003e\n\u003cli\u003eFang, D.; Liu, C.; Chen, Y.; Peng, Q.; Wu, K.; Chen, Y.; Jiang, H.; Wu, Y.; Shen, B.; Wu, Q.; Wu, D.; Sun, H. Elucidating and manipulating pressure-induced water intrusion\u0026ndash;extrusion in tunable hydrophobic Co/Zn bimetallic ZIFs: Roles of pore size and hydrogen bond. \u003cem\u003eNano Research \u003c/em\u003e\u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e17\u003c/em\u003e (1), 344-353. DOI: 10.1007/s12274-023-5967-5.\u003c/li\u003e\n\u003cli\u003eToledo, E. B.; Lucas, D. R.; Sim\u0026atilde;o, T. L. B. V.; Calixto, S. D.; Lassounskaia, E.; Muzitano, M. F.; Damica, F. Z.; Gomes, V. M.; de Oliveira Carvalho, A. Design of improved synthetic antifungal peptides with targeted variations in charge, hydrophobicity and chirality based on a correlation study between biological activity and primary structure of plant defensin \u0026gamma;-cores. \u003cem\u003eAmino Acids \u003c/em\u003e\u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e53\u003c/em\u003e (2), 219-237. DOI: 10.1007/s00726-020-02929-x.\u003c/li\u003e\n\u003cli\u003eDai, X.; Zhou, E.; Yang, W.; Zhang, X.; Zhang, W.; Rao, Y. D-Serine made by serine racemase in Drosophila intestine plays a physiological role in sleep. \u003cem\u003eNature Communications \u003c/em\u003e\u003cstrong\u003e2019\u003c/strong\u003e, \u003cem\u003e10\u003c/em\u003e (1), 1986. DOI: 10.1038/s41467-019-09544-9.\u003c/li\u003e\n\u003cli\u003eAbraham Versloot, R. C.; Arias-Orozco, P.; Tadema, M. J.; Rudolfus Lucas, F. L.; 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. \u003cem\u003eJournal of the American Chemical Society \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e145\u003c/em\u003e (33), 18355-18365. DOI: 10.1021/jacs.3c04076.\u003c/li\u003e\n\u003cli\u003eWang, J.; Prajapati, J. D.; Gao, F.; Ying, Y.-L.; Kleinekath\u0026ouml;fer, U.; Winterhalter, M.; Long, Y.-T. Identification of Single Amino Acid Chiral and Positional Isomers Using an Electrostatically Asymmetric Nanopore. \u003cem\u003eJournal of the American Chemical Society \u003c/em\u003e\u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e144\u003c/em\u003e (33), 15072-15078. DOI: 10.1021/jacs.2c03923.\u003c/li\u003e\n\u003cli\u003eHuang, H.; Bian, G.; Zong, H.; Wang, Y.; Yang, S.; Yue, H.; Song, L.; Fan, H. Chiral Sensor for Enantiodiscrimination of Varied Acids. \u003cem\u003eOrganic Letters \u003c/em\u003e\u003cstrong\u003e2016\u003c/strong\u003e, \u003cem\u003e18\u003c/em\u003e (11), 2524-2527. DOI: 10.1021/acs.orglett.6b00088.\u003c/li\u003e\n\u003cli\u003ePeluso, P.; Chankvetadze, B. Recognition in the Domain of Molecular Chirality: From Noncovalent Interactions to Separation of Enantiomers. \u003cem\u003eChemical Reviews \u003c/em\u003e\u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e122\u003c/em\u003e (16), 13235-13400. DOI: 10.1021/acs.chemrev.1c00846.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":false,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":false,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Anthrax nanopore, Proton-driven mechanism, Protein sequencing, Molecular chirality, Femtoampere precision","lastPublishedDoi":"10.21203/rs.3.rs-6077470/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6077470/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe precise detection of amino acids and the identification of their chirality are of paramount importance in protein sequencing, the design of druggable molecules, and the diagnosis of diseases based on protein damage. However, this remains an exceptionally challenging task. Herein, we developed a novel protein nanopore system based on anthrax protective antigen, a proton-driven transmembrane channel, for the discrimination of 20 proteinogenic amino acids and their chiral enantiomers. By employing a pH-asymmetric ionic liquids system instead of traditional salt conditions, we effectively resolved the intrinsic limitations (i.e., current fluctuation, low signal-to-noise ratio, gating phenomenon) of the wild-type anthrax nanopore in sensing activity. The optimized anthrax nanopore demonstrated exceptional sensitivity in differentiating amino acids as well as levorotary and dextrorotary enantiomers at femtoampere precision (\u0026lt; 100 fA). The discrimination mechanism of various amino acids through nanopore current signals can be attributed to the inhomogeneous intermolecular interactions—such as electrostatic forces, π-πinteractions, and hydrogen bonding—between the amino acids and the inner surface of the nanopore. These interactions, in conjunction with either electrophoretic forces or electroosmotic flow, collectively enable the differentiation of distinct amino acid types. Notably, the developed anthrax nanopore-based method eliminates the need for enzymes, chemical reactions, or machine learning algorithms. Instead, it relies solely on an optimized electrolyte system and the direct interpretation of nanopore current signatures to achieve chiral amino acid discrimination. This study provides an idea nanopore architecture that offers ultrahigh sensing resolution, a wide dynamic range of enantioselectivity, and specificity, thereby having implications in protein sequencing and making available a refined analytical tool for revealing properties of chiral molecules in diverse biological contexts.\u003c/p\u003e","manuscriptTitle":"Enzyme-less discrimination of chiral amino acids with femtoampere-level precision by proton-driven anthrax nanopore","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-18 05:10:17","doi":"10.21203/rs.3.rs-6077470/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-chemical-biology","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"nchembio","sideBox":"Learn more about [Nature Chemical Biology](http://www.nature.com/nchembio/)","snPcode":"","submissionUrl":"","title":"Nature Chemical Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e81d5d31-09ab-449f-9e97-a33c76997698","owner":[],"postedDate":"March 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44956923,"name":"Biological sciences/Biotechnology/Nanobiotechnology/Nanopores"},{"id":44956924,"name":"Physical sciences/Chemistry/Analytical chemistry/Sensors"}],"tags":[],"updatedAt":"2025-06-19T13:41:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-18 05:10:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6077470","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6077470","identity":"rs-6077470","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}