Cyclodextrins: Establishing building blocks for AI-driven drug design by determining affinity constants in silico.

Cyclodextrins (CDs) are cyclic carbohydrate polymers that hold significant promise for drug delivery and industrial applications. Their effectiveness depends on their ability to encapsulate target molecules with strong affinity and specificity, but quantifying affinities in these systems accurately is challenging for a variety of reasons. Computational methods represent an exceptional complement to in vitro assays because they can be employed for existing and hypothetical molecules, providing high resolution structures in addition to a mechanistic, dynamic, kinetic, and thermodynamic characterization. Here, we employ potential of mean force (PMF) calculations obtained from guided metadynamics simulations to characterize the 1:1 inclusion complexes between four different modified ßCDs, with different type, number, and location of substitutions, and two sterol molecules (cholesterol and 7-ketocholesterol). Our methods, validated for reproducibility through four independent repeated simulations per system and different post processing techniques, offer new insights into the formation and stability of CD-sterol inclusion complexes. A systematic distinct orientation preference where the sterol tail projects from the CD's larger face and significant impacts of CD substitutions on binding are observed. Notably, sampling only the CD cavity's wide face during simulations yielded comparable binding energies to full-cavity sampling, but in less time and with reduced statistical uncertainty, suggesting a more efficient approach. Bridging computational methods with complex molecular interactions, our research enables predictive CD designs for diverse applications. Moreover, the high reproducibility, sensitivity, and cost-effectiveness of the studied methods pave the way for extensive studies of massive CD-ligand combinations, enabling AI algorithm training and automated molecular design.

Unraveling the molecular dynamics of sugammadex-rocuronium complexation: A blueprint for cyclodextrin drug design.

Sugammadex, marketed as Bridion™, is an approved cyclodextrin (CD) based drug for the reversal of neuromuscular blockade in adults undergoing surgery. Sugammadex forms an inclusion complex with the neuromuscular blocking agent (NMBA) rocuronium, allowing rapid reversal of muscle paralysis. In silico methods have been developed for studying CD inclusion complexes, aimed at accurately predicting their structural, energetic, dynamic, and kinetic properties, as well as binding constants. Here, a computational study aimed at characterizing the sugammadex-rocuronium system from the perspective of docking calculations, free molecular dynamics (MD) simulations, and biased metadynamics simulations with potential of mean force (PMF) calculations is presented. The aim is to provide detailed information about this system, as well as to use it as a model system for validation of the methods. This method predicts results in line with experimental evidence for both the optimal structure and the quantitative value for the binding constant. Interestingly, there is a less profound preference for the orientation than might be assumed based on electrostatic interactions, suggesting that both orientations may exist in solution. These results show that this technology can efficiently analyze CD inclusion complexes and could be used to facilitate the development and optimization of novel applications for CDs.

Unraveling lipid and inflammation interplay in cancer, aging and infection for novel theranostic approaches.

The synergistic relationships between Cancer, Aging, and Infection, here referred to as the CAIn Triangle, are significant determinants in numerous health maladies and mortality rates. The CAIn-related pathologies exhibit close correlations with each other and share two common underlying factors: persistent inflammation and anomalous lipid concentration profiles in the membranes of affected cells. This study provides a comprehensive evaluation of the most pertinent interconnections within the CAIn Triangle, in addition to examining the relationship between chronic inflammation and specific lipidic compositions in cellular membranes. To tackle the CAIn-associated diseases, a suite of complementary strategies aimed at diagnosis, prevention, and treatment is proffered. Our holistic approach is expected to augment the understanding of the fundamental mechanisms underlying these diseases and highlight the potential of shared features to facilitate the development of novel theranostic strategies.

Overlay databank unlocks data-driven analyses of biomolecules for all.

Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make data scattered in various locations and formats accessible for data-driven and machine learning applications using the overlay databank format. To demonstrate the practical relevance of such approach, we present the NMRlipids Databank-a community-driven, open-for-all database featuring programmatic access to quality-evaluated atom-resolution molecular dynamics simulations of cellular membranes. Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. While MD simulations have been useful in understanding membrane systems, they require significant computational resources and often suffer from inaccuracies in model parameters. Here, we demonstrate how programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface, unlock possibilities beyond current MD simulation and experimental studies to understand cellular membranes. The proposed overlay databank concept can be further applied to other biomolecules, as well as in other fields where similar barriers hinder the AI revolution.

ß-Peptides incorporating polyhydroxylated cyclohexane ß-amino acid: synthesis and conformational study.

We describe the synthesis of trihydroxylated cyclohexane ß-amino acids from (-)-shikimic acid, in their cis and trans configuration, and the incorporation of the trans isomer into a trans-2-aminocyclohexanecarboxylic acid peptide chain. Subsequently, the hydroxyl groups were partially or totally deprotected. The structural study of the new peptides by FTIR, CD, solution NMR and DFT calculations revealed that they all fold into a 14-helix secondary structure, similarly to the homooligomer of trans-2-aminocyclohexanecarboxylic acid. This means that the high degree of substitution of the cyclohexane ring of the new residue is compatible with the adoption of a stable helical secondary structure and opens opportunities for the design of more elaborate peptidic foldamers with oriented polar substituents at selected positions of the cycloalkane residues.

Molecular insights into the effects of focused ultrasound mechanotherapy on lipid bilayers: Unlocking the keys to design effective treatments.

Administration of focused ultrasounds (US) represents an attractive complement to classical therapies for a wide range of maladies, from cancer to neurological pathologies, as they are non-invasive, easily targeted, their dosage is easy to control, and they involve low risks. Different mechanisms have been proposed for their activity but the direct effect of their interaction with cell membranes is not well understood at the molecular level. This is in part due to the difficulty of designing experiments able to probe the required spatio-temporal resolutions. Here we use Molecular Dynamics (MD) simulations at two resolution levels and machine learning (ML) classification tools to shed light on the effects that focused US mechanotherapy methods have over a range of lipid bilayers. Our results indicate that the dynamic-structural response of the membrane models to the mechanical perturbations caused by the sound waves strongly depends on the lipid composition. The analyses performed on the MD trajectories contribute to a better understanding of the behavior of lipid membranes, and to open up a path for the rational design of new therapies for the long list of diseases characterized by specific lipid profiles of pathological membrane cells.

The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies.

Artificial intelligence (AI) has the potential to revolutionize the drug discovery process, offering improved efficiency, accuracy, and speed. However, the successful application of AI is dependent on the availability of high-quality data, the addressing of ethical concerns, and the recognition of the limitations of AI-based approaches. In this article, the benefits, challenges, and drawbacks of AI in this field are reviewed, and possible strategies and approaches for overcoming the present obstacles are proposed. The use of data augmentation, explainable AI, and the integration of AI with traditional experimental methods, as well as the potential advantages of AI in pharmaceutical research, are also discussed. Overall, this review highlights the potential of AI in drug discovery and provides insights into the challenges and opportunities for realizing its potential in this field. Note from the human authors: This article was created to test the ability of ChatGPT, a chatbot based on the GPT-3.5 language model, in terms of assisting human authors in writing review articles. The text generated by the AI following our instructions (see Supporting Information) was used as a starting point, and its ability to automatically generate content was evaluated. After conducting a thorough review, the human authors practically rewrote the manuscript, striving to maintain a balance between the original proposal and the scientific criteria. The advantages and limitations of using AI for this purpose are discussed in the last section.

Uncovering the mechanisms of cyclic peptide self-assembly in membranes with the chirality-aware MA(R/S)TINI forcefield.

Cyclic peptides (CPs) formed by alternation of D- and L-amino acids (D,L-CPs) can self-assemble into nanotubes (SCPNs) by parallel or/and antiparallel stacking. Different applications have been attributed to these nanotubes, including the disruption of lipid bilayers of specific compositions and the selective transport of ions throughout membranes. Molecular dynamics (MD) simulations have significantly contributed to understand the interaction between CPs, including the structural, dynamic and transport properties of their supramolecular aggregates. The high computational cost of atomic resolution forcefields makes them impractical for simulating the self-assembly of macromolecules, so coarse-grained (CG) models might represent a more feasible solution for this purpose. However, general CG models used for the simulation of biomolecules such as the MARTINI forcefield do not explicitly consider the non-covalent interactions leading to the formation of secondary structure patterns in proteins. This becomes particularly important in the case of CPs due to the D- and L-chirality alternation in their sequence, leading to opposite orientations of the backbone polar groups on both sides of the cyclic ring plane. In order to overcome this limitation, we have extended the MARTINI forcefield to introduce chirality in each residue of the CPs. The new parametrization, which we have called MA(R/S)TINI, reproduces the expected self-assembly patterns for several CP sequences in the presence of different membrane models, explicitly considering the chirality of the CPs and with no significant extra computational cost. Our simulations provide new mechanistic information of how these systems self-assemble in presence of different lipid scenarios, showing that the CP-CP and CP-membrane interactions are sensitive to the peptide sequence chirality. This opens the door to design new bioactive CPs based on CG-MD simulations. A web-based tool for the automatic parameterization of new CP sequences using MA(R/S)TINI, among other functionalities, is under construction (see http://cyclopep.com).

Unravelling hierarchical levels of structure in lipid membranes.

In analogy with the hierarchical levels typically used to describe the structure of nucleic acids or proteins and keeping in mind that lipid bilayers are not just mere envelopers for biological material but directly responsible for many important functions of life, it is discussed here how membrane models can also be interpreted in terms of different hierarchies in their structure. Namely, lipid composition, interaction between leaflets, existence and interaction of domains arising from the coordinate behavior of lipids and their properties, plus the manifest and specific perturbation of the lipid organization around macromolecules embedded in a membrane are hereby used to define the primary, secondary, tertiary and quaternary structures, respectively. Molecular Dynamics simulations are used to illustrate this proposal. Alternative levels of organization and methods to define domains can be proposed but the final aim is to highlight the paradigm arising from this description which is expected to have significant consequences on deciphering the underlying factors governing membranes and their interactions with other molecules.

Not so rigid capsids based on cyclodextrin complexes: Keys to design.

HYPOTHESIS: Membranes based on cyclodextrin complexes can be used as functional nanocarrier envelopers by chemical modifications of the cyclodextrin hydroxyl groups or by encapsulating different ligands in their cavities. EXPERIMENTS: Molecular dynamics simulations of monolayers and bilayers based on supramolecular complexes consisting of two α or ß-cyclodextrin and one sodium dodecylsulfate or dodecane at 283 K and at 298 K were performed. FINDINGS: It is shown that the structure and main interactions stabilizing the membranes, as well as their permeability to water and ions can be tuned by changing the cyclodextrin, the ligand, the number of layers or/and the temperature. These results provide new evidences about both their dynamic nature and the interactions responsible for the stabilization of the membranes and will facilitate the design of new functional capsides and applications based on cyclodextrin complexes.

Molecular Dynamics Simulations of Transmembrane Cyclic Peptide Nanotubes Using Classical Force Fields, Hydrogen Mass Repartitioning, and Hydrogen Isotope Exchange Methods: A Critical Comparison.

Self-assembled cyclic peptide nanotubes with alternating D- and L-amino acid residues in the sequence of each subunit have attracted a great deal of attention due to their potential for new nanotechnology and biomedical applications, mainly in the field of antimicrobial peptides. Molecular dynamics simulations can be used to characterize these systems with atomic resolution at different time scales, providing information that is difficult to obtain via wet lab experiments. However, the performance of classical force fields typically employed in the simulation of biomolecules has not yet been extensively tested with this kind of highly constrained peptide. Four different classical force fields (AMBER, CHARMM, OPLS, and GROMOS), using a nanotube formed by eight D,L-α-cyclic peptides inserted into a lipid bilayer as a model system, were employed here to fill this gap. Significant differences in the pseudo-cylindrical cavities formed by the nanotubes were observed, the most important being the diameter of the nanopores, the number and location of confined water molecules, and the density distribution of the solvent molecules. Furthermore, several modifications were performed on GROMOS54a7, aiming to explore acceleration strategies of the MD simulations. The hydrogen mass repartitioning (HMR) and hydrogen isotope exchange (HIE) methods were tested to slow down the fastest degrees of freedom. These approaches allowed a significant increase in the time step employed in the equation of the motion integration algorithm, from 2 fs up to 5-7 fs, with no serious changes in the structural and dynamical properties of the nanopores. Subtle differences with respect to the simulations with the unmodified force fields were observed in the concerted movements of the cyclic peptides, as well as in the lifetime of several H-bonds. All together, these results are expected to contribute to better understanding of the behavior of self-assembled cyclic peptide nanotubes, as well as to support the methods tested to speed up general MD simulations; additionally, they do provide a number of quantitative descriptors that are expected to be used as a reference to design new experiments intended to validate and complement computational studies of antimicrobial cyclic peptides.

SuPepMem: A database of innate immune system peptides and their cell membrane interactions.

Host defense peptides (HDPs) are short cationic peptides that play a key role in the innate immune response of all living organisms. Their action mechanism does not depend on the presence of protein receptors, but on their ability to target and disrupt the membranes of a wide range of pathogenic and pathologic cells which are recognized by their specific compositions, typically with a relatively high concentration of anionic lipids. Lipid profile singularities have been found in cancer, inflammation, bacteria, viral infections, and even in senescent cells, enabling the possibility to use them as therapeutic targets and/or diagnostic biomarkers. Molecular dynamics (MD) simulations are extraordinarily well suited to explore how HDPs interact with membrane models, providing a large amount of qualitative and quantitative information that, nowadays, cannot be assessed by wet-lab methods at the same level of temporal and spatial resolution. Here, we present SuPepMem, an open-access repository containing MD simulations of different natural and artificial peptides with potential membrane lysis activity, interacting with membrane models of healthy mammal, bacteria, viruses, cancer or senescent cells. In addition to a description of the HDPs and the target systems, SuPepMem provides both the input files necessary to run the simulations and also the results of some selected analyses, including structural and MD-based quantitative descriptors. These descriptors are expected to be useful to train machine learning algorithms that could contribute to design new therapeutic peptides. Tools for comparative analysis between different HDPs and model membranes, as well as to restrict the queries to structural and time-averaged properties are also available. SuPepMem is a living project, that will continuously grow with more simulations including peptides of different sequences, MD simulations with different number of peptide units, more membrane models and also several resolution levels. The database is open to MD simulations from other users (after quality check by the SuPepMem team). SuPepMem is freely available under https://supepmem.com/.

Partition of antimicrobial D-L-α-cyclic peptides into bacterial model membranes.

Fluorescence spectroscopy is used to characterize the partition of three second-generation D,L-α-cyclic peptides to two lipid model membranes. The peptides have proven antimicrobial activity, particularly against Gram positive bacteria, and the model membranes are formed of either with 1,2-dimyristoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (DMPG) or its mixture with 1,2-dimyristoyl-sn-glycero-3-phosphoethanolamine (DMPE), at a molar ratio of (1:1). The peptide's intrinsic fluorescence was used in the Steady State and/or Time Resolved Fluorescence Spectroscopy experiments, showing that the peptides bind to the membranes, and the extent of their partition is thereof quantified. The peptide-induced membrane leakage was followed using an encapsulated fluorescent dye. Overall, the partition is mainly driven by electrostatics, but also involves hydrophobic interactions. The introduction of a hydrocarbon tail in one of the residues of the parent peptide, CPR, adjacent to the tryptophan (Trp) residue, significantly improves the partition of the modified peptides, CPRT10 and CPRT14, to both membrane systems. Further, we show that the length of the tail is the main distinguishing factor for the extension of the partition process. The parent peptide induces very limited leakage, at odds with the peptides with tail, that promote fast leakage, increasing in most cases with peptide concentration, and being almost complete for the highest peptide concentration and negatively charged membranes. Overall, the results help the unravelling of the antimicrobial action of these peptides and are well in line with their proven high antimicrobial activity.

Inverse Conformational Selection in Lipid-Protein Binding.

Interest in lipid interactions with proteins and other biomolecules is emerging not only in fundamental biochemistry but also in the field of nanobiotechnology where lipids are commonly used, for example, in carriers of mRNA vaccines. The outward-facing components of cellular membranes and lipid nanoparticles, the lipid headgroups, regulate membrane interactions with approaching substances, such as proteins, drugs, RNA, or viruses. Because lipid headgroup conformational ensembles have not been experimentally determined in physiologically relevant conditions, an essential question about their interactions with other biomolecules remains unanswered: Do headgroups exchange between a few rigid structures, or fluctuate freely across a practically continuous spectrum of conformations? Here, we combine solid-state NMR experiments and molecular dynamics simulations from the NMRlipids Project to resolve the conformational ensembles of headgroups of four key lipid types in various biologically relevant conditions. We find that lipid headgroups sample a wide range of overlapping conformations in both neutral and charged cellular membranes, and that differences in the headgroup chemistry manifest only in probability distributions of conformations. Furthermore, the analysis of 894 protein-bound lipid structures from the Protein Data Bank suggests that lipids can bind to proteins in a wide range of conformations, which are not limited by the headgroup chemistry. We propose that lipids can select a suitable headgroup conformation from the wide range available to them to fit the various binding sites in proteins. The proposed inverse conformational selection model will extend also to lipid binding to targets other than proteins, such as drugs, RNA, and viruses.

Macromolecular assembly and membrane activity of antimicrobial D,L-α-Cyclic peptides.

Antimicrobial peptides are viewed as a promising alternative to conventional antibiotics, as their activity through membrane targeting makes them less prone to resistance development. Among them, antimicrobial D,L-α-cyclic peptides (CPs) have been proposed as an alternative, specially due to their cyclic nature and to the presence of D-α-amino acids that increases their resistance to proteases. In present work, second generation D,L-α-cyclic peptides with proven antimicrobial activity are shown to form complex macromolecular assemblies in the presence of membranes. We addressed the CPs:membrane interactions through a combination of experimental techniques (DSC and ATR-FTIR) with coarse-grained molecular dynamics (CG-MD) simulations, aiming at understanding their interactions, macromolecular assemblies and eventually unveil their mechanism of action. DSC shows that the interaction depends heavily on the negatively charge content of the membrane and on lipid/peptide ratio, suggesting different mechanisms for the different peptides and lipid systems. CG-MD proved that CPs can self-assemble at the lipid surface as nanotubes or micellar aggregates, depending on the peptide, in agreement with ATR-FTIR results. Finally, our results shed light into possible mechanisms of action of the peptides with pending hydrocarbon tail, namely membrane extensive segregation and/or membrane disintegration through the formation of disk-like lipid/peptide aggregates.

Aggregation versus inclusion complexes to solubilize drugs with cyclodextrins. A case study using sulphobutylether-ß-cyclodextrins and remdesivir.

The formation of small hybrid aggregates between excipient and drug molecules is one of the mechanisms that contributes to the solubilization of active principles in pharmaceutical formulations. The characterization of the formation, governing interactions and structure of such entities is not trivial since they are highly flexible and dynamic, quickly exchanging molecules from one to another. In the case of cyclodextrins, this mechanism and the formation of inclusion complexes synergistically cooperate to favour the bioavailability of drugs. In a previous study we reported a detailed characterization of the possible formation of inclusion complexes with 1:1 stoichiometry between remdesivir, the only antiviral medication currently approved by the United States Food and Drug Administration for treating COVID-19, and sulphobutylether-ß-cyclodextrins. Here we extend our study to assess the role of the spontaneous aggregation in the solubilization of the same drug, by molecular dynamics simulations at different relative concentrations of both compounds. The number of sulphobutylether substitutions in the cyclodextrin structure and two different protonation states of the remdesivir molecule are considered. We aim to shed light in the solubilization mechanism of sulphobutylether-ß-cyclodextrins, broadly used as an excipient in many pharmaceutical formulations, in particular in the case of remdesivir as an active compound.

Short oligoalanine helical peptides for supramolecular nanopore assembly and protein cytosolic delivery.

In this work we report a rational design strategy for the identification of new peptide prototypes for the non-disruptive supramolecular permeation of membranes and the transport of different macromolecular giant cargos. The approach targets a maximal enhancement of helicity in the presence of membranes with sequences bearing the minimal number of cationic and hydrophobic moieties. The here reported folding enhancement in membranes allowed the selective non-lytic translocation of different macromolecular cargos including giant proteins. The transport of different high molecular weight polymers and functional proteins was demonstrated in vesicles and in cells with excellent efficiency and optimal viability. As a proof of concept, functional monoclonal antibodies were transported for the first time into different cell lines and cornea tissues by exploiting the helical control of a short peptide sequence. This work introduces a rational design strategy that can be employed to minimize the number of charges and hydrophobic residues of short peptide carriers to achieve non-destructive transient membrane permeation and transport of different macromolecules.

Transmembrane Self-Assembled Cyclic Peptide Nanotubes Based on α-Residues and Cyclic δ-Amino Acids: A Computational Study.

Self-assembling cyclic peptide nanotubes have been shown to function as synthetic, integral transmembrane channels. The combination of natural and nonnatural aminoacids in the sequence of cyclic peptides enables the control not only of their outer surface but also of the inner cavity behavior and properties, affecting, for instance, their permeability to different molecules including water and ions. Here, a thorough computational study on a new class of self-assembling peptide motifs, in which δ-aminocycloalkanecarboxylic acids are alternated with natural α-amino acids, is presented. The presence of synthetic δ-residues creates hydrophobic regions in these α,δ-SCPNs, which makes them especially attractive for their potential implementation in the design of new drug or diagnostic agent carrier systems. Using molecular dynamics simulations, the behavior of water molecules, different ions (Li+, Na+, K+, Cs+, and Ca2+), and their correspondent counter Cl- anions is extensively investigated in the nanoconfined environment. The structure and dynamics are mutually combined in a diving immersion inside these transmembrane channels to discover a fascinating submarine nanoworld where star-shaped water channels guide the passage of cations and anions therethrough.

Cyclodextrin dimers: A versatile approach to optimizing encapsulation and their application to therapeutic extraction of toxic oxysterols.

We have developed a novel class of specifically engineered, dimerized cyclodextrin (CD) nanostructures for the encapsulation of toxic biomolecules such as 7-ketocholesterol (7KC). 7KC accumulates over time and causes dysfunction in many cell types, linking it to several age-related diseases including atherosclerosis and age-related macular degeneration (AMD). Presently, treatments for these diseases are invasive, expensive, and show limited benefits. CDs are cyclic glucose oligomers utilized to capture small, hydrophobic molecules. Here, a combination of in silico, in vitro, and ex vivo methods is used to implement a synergistic rational drug design strategy for developing CDs to remove atherogenic 7KC from cells and tissues. Mechanisms by which CDs encapsulate sterols are discussed, and we conclude that covalently linked head-to-head dimers of ßCDs have substantially improved affinity for 7KC compared to monomers. We find that inclusion complexes can be stabilized or destabilized in ways that allow the design of CD dimers with increased 7KC selectivity while maintaining an excellent safety profile. These CD dimers are being developed as therapeutics to treat atherosclerosis and other debilitating diseases of aging.

Effect of Water Models on Transmembrane Self-Assembled Cyclic Peptide Nanotubes.

Self-assembling cyclic peptide nanotubes can form nanopores when they are inserted in lipid bilayers, acting as ion and/or water permeable channels. In order to improve the versatility of these systems, it is possible to specifically design cyclic peptides with a combination of natural and non-natural amino acids, enabling the control of the nature of the inner cavity of the channels. Here, the behavior of two types of self-assembling peptide motifs, alternating α-amino acids with γ- or δ-aminocycloalkanecarboxylic acids, is studied via molecular dynamics (MD) simulations. The behavior of water molecules in nanopores is expected to affect the properties of these channels and therefore merits detailed examination. A number of water models commonly used in MD simulations have been validated by how well they reproduce bulk water properties. However, it is less clear how these water models behave in the nanoconfined condition inside a channel. The behavior of four different water models-TIP3P, TIP4P, TIP4P/2005, and OPC-are evaluated in MD simulations of self-assembled cyclic peptide nanotubes of distinct composition and diameter. The dynamic behavior of the water molecules and ions in these designed artificial channels depends subtly on the water model used. TIP3P water molecules move faster than those of TIP4P, TIP4P/2005, and OPC. This demeanor is clearly observed in the filling of the nanotube, in water diffusion within the pore, and in the number and stability of hydrogen bonds of the peptides with water. It was also shown that the water model influences the simulated ion flux through the nanotubes, with TIP3P producing the greatest ion flux. Additionally, the two more recent models, TIP4P/2005 and OPC, which are known to reproduce the experimental self-diffusion coefficient of bulk water quite well, exhibit very similar results under the nanoconfined conditions studied here. Because none of these models have been parametrized specifically for waters confined in peptide nanotubes, this study provides a point of reference for further validation.