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.

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.

Simple ApproximaTion for Aggregation Number Determination by Isothermal Titration Calorimetry: STAND-ITC.

A new proposal to obtain aggregation numbers from isothermal titration calorimetry dilution experiments is described and tested using dodecyl trimethyl ammonium bromide, dodecyl methylimidazolium chloride, dodecyl methylimidazolium sulfonate, and didecyl methylimidazolium chloride aqueous solutions at different temperatures. The results were compared to those obtained from fluorescence measurements and also with data from the literature. In addition to the aggregation number, the molar free energy to transfer a solute molecule from the aggregate to the bulk solution, the enthalpy corresponding to the formation of the self-assembled suprastructures, the molar heat corresponding to the dilution of monomers and aggregates, and an offset parameter to account for unpredictable external contributions are simultaneously obtained using the same method. The new equations are compared to those obtained from previous proposals, and they are also analyzed in detail to assess the impact of each fitting parameter in the profile of the calorimetric isotherm. This new approach has been implemented in a computational code that automatically determines the fitting parameters as well as the corresponding statistical uncertainties for the large variety of calorimetric profiles that have been tested. Given the high sensitivity of the dilution experiments to the aggregation number for relatively small assemblies, our approach is proposed also to quantify the oligomerization state of biomolecules such as proteins and peptides.

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.

AFFINImeter: A software to analyze molecular recognition processes from experimental data.

The comprehension of molecular recognition phenomena demands the understanding of the energetic and kinetic processes involved. General equations valid for the thermodynamic analysis of any observable that is assessed as a function of the concentration of the involved compounds are described, together with their implementation in the AFFINImeter software. Here, a maximum of three different molecular species that can interact with each other to form an enormous variety of supramolecular complexes are considered. The corrections currently employed to take into account the effects of dilution, volume displacement, concentration errors and those due to external factors, especially in the case of ITC measurements, are included. The methods used to fit the model parameters to the experimental data, and to generate the uncertainties are described in detail. A simulation tool and the so called kinITC analysis to get kinetic information from calorimetric experiments are also presented. An example of how to take advantage of the AFFINImeter software for the global multi-temperature analysis of a system exhibiting cooperative 1:2 interactions is presented and the results are compared with data previously published. Some useful recommendations for the analysis of experiments aimed at studying molecular interactions are provided.

A strategy based on thermal flexibility to design triosephosphate isomerase proteins with increased or decreased kinetic stability.

Kinetic stability of proteins determines their susceptibility to irreversibly unfold in a time-dependent process, and therefore its half-life. A residue displacement analysis of temperature-induced unfolding molecular dynamics simulations was recently employed to define the thermal flexibility of proteins. This property was found to be correlated with the activation energy barrier (Eact) separating the native from the transition state in the denaturation process. The Eact was determined from the application of a two-state irreversible model to temperature unfolding experiments using differential scanning calorimetry (DSC). The contribution of each residue to the thermal flexibility of proteins is used here to propose multiple mutations in triosephosphate isomerase (TIM) from Trypanosoma brucei (TbTIM) and Trypanosoma cruzi (TcTIM), two parasites closely related by evolution. These two enzymes, taken as model systems, have practically identical structure but large differences in their kinetic stability. We constructed two functional TIM variants with more than twice and less than half the activation energy of their respective wild-type reference structures. The results show that the proposed strategy is able to identify the crucial residues for the kinetic stability in these enzymes. As it occurs with other protein properties reflecting their complex behavior, kinetic stability appears to be the consequence of an extensive network of inter-residue interactions, acting in a concerted manner. The proposed strategy to design variants can be used with other proteins, to increase or decrease their functional half-life.

Cyclo-lib: a database of computational molecular dynamics simulations of cyclodextrins.

MOTIVATION: Cyclodextrins (CDs) are amongst the most versatile/multi-functional molecules used in molecular research and chemical applications. They are natural cyclic oligosaccharides typically employed to encapsulate hydrophobic groups in their central cavity. This allows solubilizing, protecting or reducing the toxicity of a large variety of different molecules including drugs, dyes and surfactant agents. In spite of their great potential, atomic level information of these molecules, which is key for their function, is really scarce. Computational Molecular Dynamics (MD) simulations have the potential to efficiently fill this gap, providing structural-dynamic information at atomic level in time scales ranging from ps to µs. RESULTS: Cyclo-lib is a database with a publicly accessible web-interface containing structural and dynamic analysis obtained from computational MD simulation trajectories (250 ns long) of native and modified CDs in explicit water molecules. Cyclo-lib currently includes 70 CDs typically employed for fundamental and industrial research. Tools for comparative analysis between different CDs, as well as to restrict the analysis to specific time-segments within the trajectories are also available. Cyclo-lib provides atomic resolution information aimed to complement experimental results performed with the same molecules. AVAILABILITY AND IMPLEMENTATION: The database is freely available under http://cyclo-lib.mduse.com/ CONTACT: Angel.Pineiro@usc.es.

Complex Behavior of Aqueous α-Cyclodextrin Solutions. Interfacial Morphologies Resulting from Bulk Aggregation.

The spontaneous aggregation of α-cyclodextrin (α-CD) molecules in the bulk aqueous solution and the interactions of the resulting aggregates at the liquid/air interface have been studied at 283 K using a battery of techniques: transmission electron microscopy, dynamic light scattering, dynamic surface tensiometry, Brewster angle microscopy, neutron reflectometry, and ellipsometry. We show that α-CD molecules spontaneously form aggregates in the bulk that grow in size with time. These aggregates adsorb to the liquid/air interface with their size in the bulk determining the adsorption rate. The material that reaches the interface coalesces laterally to form two-dimensional domains on the micrometer scale with a layer thickness on the nanometer scale. These processes are affected by the ages of both the bulk and the interface. The interfacial layer formed is not in fast dynamic equilibrium with the subphase as the resulting morphology is locked in a kinetically trapped state. These results reveal a surprising complexity of the parallel physical processes taking place in the bulk and at the interface of what might have seemed initially like a simple system.

STAND: Surface Tension for Aggregation Number Determination.

Taking advantage of the extremely high dependence of surface tension on the concentration of amphiphilic molecules in aqueous solution, a new model based on the double equilibrium between free and aggregated molecules in the liquid phase and between free molecules in the liquid phase and those adsorbed at the air/liquid interface is presented and validated using literature data and fluorescence measurements. A key point of the model is the use of both the Langmuir isotherm and the Gibbs adsorption equation in terms of free molecules instead of the nominal concentration of the solute. The application of the model should be limited to non ionic compounds since it does not consider the presence of counterions. It requires several coupled nonlinear fittings for which we developed a software that is publicly available in our server as a web application. Using this tool, it is straightforward to get the average aggregation number of an amphiphile, the micellization free energy, the adsorption constant, the maximum surface excess (and so the minimum area per molecule), the distribution of solute in the liquid phase between free and aggregate species, and the surface coverage in only a couple of seconds, just by uploading a text file with surface tension vs concentration data and the corresponding uncertainties.

Effect of ionization on the behavior of n-eicosanephosphonic acid monolayers at the air/water interface. Experimental determinations and molecular dynamics simulations.

Monolayers of n-eicosanephosphonic acid, EPA, were studied using a Langmuir balance and a Brewster angle microscope at different subphase pH values to change the charge of the polar headgroups (Zav) from 0 to -2. Molecular dynamics simulations (MDS) results for |Zav| = 0, 1, and 2 were compared with the experimental ones. EPA monolayers behave as mixtures of mutually miscible species (C20H41-PO3H2, C20H41-PO3H(-), and C20H41-PO3(2-), depending on the subphase pH). The order and compactness of the monolayers decrease when increasing |Zav|, while go from strongly interconnected by phosphonic-phosphonic hydrogen bonds (|Zav| = 0-0.03) through an equilibrium between the total cohesive energy and the electrostatic repulsion between the charged polar groups (0.03 < |Zav| < 1.6) to an entirely ionic monolayer (|Zav| ≈ 2). MDS reveal for |Zav| = 0 that the chains form spiralled nearly rounded structures induced by the hydrogen-bonded network. When |Zav| ≈ 1 fingering domains were identified. When Z ≈ 2, the headgroups are more disordered and distanced, not only in the xy plane but also in the z direction, forming a rough layer and responding to compression with a large plateau in the isotherm. The monolayers collapse behavior is consistent with the structures and domains founds in the different ionization states and their consequent in-plane rigidity: there is a transition from a solid-like response at low pH subphases to a fluid-like response at high pH subphases. The film area in the close-packed state increases relatively slow when the polar headgroups are able to form hydrogen bonds but increases to near twice that this value when |Zav| ≈ 2. Other nanoscopic properties of monolayers were also determined by MDS. The computational results confirm the experimental findings and offer a nanoscopic perspective on the structure and interactions in the phosphonate monolayers.

Key structural arrangements at the C-terminus domain of CETP suggest a potential mechanism for lipid-transfer activity.

The cholesteryl-ester transfer protein (CETP) promotes cholesteryl-ester and triglyceride transfer between lipoproteins. We evaluated the secondary structure stability of a series of small peptides derived from the C-terminus of CETP in a wide range of pH's and lipid mixtures, and studied their capability to carry out disorder-to-order secondary structure transitions dependent of lipids. We report that while a mixture of phosphatidylcholine/cholesteryl-esters forms large aggregated particles, the inclusion of a series of CETP carboxy-terminal peptides in a stable α-helix conformation, allows the formation of small homogeneous micelle-like structures. This phenomenon of lipid ordering was directly connected to secondary structural transitions at the C-terminus domain when lysophosphatidic acid and lysophosphatidylcholine lipids were employed. Circular dichroism, cosedimentation experiments, electron microscopy, as well as molecular dynamics simulations confirm this phenomenon. When purified CETP is studied, the same type of phenomenon occurs by promoting the reorganization of lipid from large to smaller particles. Our findings extend the emerging view for a novel mechanism of lipid transfer carried out by CETP, assigning its C-terminus domain the property to accomplish lipid ordering through secondary structure disorder-to-order transitions.

Unlocking the specificity of antimicrobial peptide interactions for membrane-targeted therapies.

Antimicrobial peptides (AMPs) are increasingly recognized as potent therapeutic agents, with their selective affinity for pathological membranes, low toxicity profile, and minimal resistance development making them particularly attractive in the pharmaceutical landscape. This study offers a comprehensive analysis of the interaction between specific AMPs, including magainin-2, pleurocidin, CM15, LL37, and clavanin, with lipid bilayer models of very different compositions that have been ordinarily used as biological membrane models of healthy mammal, cancerous, and bacterial cells. Employing unbiased molecular dynamics simulations and metadynamics techniques, we have deciphered the intricate mechanisms by which these peptides recognize pathogenic and pathologic lipid patterns and integrate into lipid assemblies. Our findings reveal that the transverse component of the peptide's hydrophobic dipole moment is critical for membrane interaction, decisively influencing the molecule's orientation and expected therapeutic efficacy. Our approach also provides insight on the kinetic and dynamic dependence on the peptide orientation in the axial and azimuthal angles when coming close to the membrane. The aim is to establish a robust framework for the rational design of peptide-based, membrane-targeted therapies, as well as effective quantitative descriptors that can facilitate the automated design of novel AMPs for these therapies using machine learning methods.

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.

CYCLOPEp Builder: Facilitating cyclic peptide and nanotube research through a user-friendly web platform.

The study of cyclic peptides (CPs) and self-assembling cyclic peptide nanotubes (SCPNs) is pivotal in advancing applications in diverse fields such as biomedicine, nanoelectronics, and catalysis. Recognizing the limitations in the experimental study of these molecules, this article introduces CYCLOPEp Builder, a comprehensive web-based application designed to facilitate the design, simulation, and visualization of CPs and SCPNs. The tool is engineered to generate molecular topologies, essential for conducting Molecular Dynamics simulations that span All-Atom to Coarse-Grain resolutions. CYCLOPEp Builder's user-friendly interface simplifies the complex process of molecular modeling, providing researchers with the ability to readily construct CPs and SCPNs. The platform is versatile, equipped with various force fields, and capable of producing structures ranging from individual CPs to complex SCPNs with different sequences, offering parallel and antiparallel orientations among them. By enhancing the capacity for detailed visualization of molecular assemblies, CYCLOPEp Builder improves the understanding of CP and SCPN molecular interactions. This tool is a step forward in democratizing access to sophisticated simulations, offering an invaluable resource to the scientific community engaged in the exploration of supramolecular structures. CYCLOPEp is accessible at http://cyclopep.com/.

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.

The "true" affinities of metal cations to p-sulfonatocalix[4]arene: a thermodynamic study at neutral pH reveals a pitfall due to salt effects in microcalorimetry.

A microcalorimetric study on the inclusion of monovalent and divalent metal cations by p-sulfonatocalix[4]arene was performed. The thermodynamic parameters for the complexation of alkali metal cations and Ag(+) were obtained for the first time at neutral pH. The Na(+) cation is routinely present as counterion of the calixarene in neutral aqueous solution, and this must be taken into account in the determination of the thermodynamic parameters for the complexation of Na(+) and the other cations by considering a sequential or a competitive binding scheme. The ΔH° and ΔS° values show that the inclusion process is entropically driven, although an influence of the temperature on the complexation reaction indicates that the enthalpic term is also an important contributor. The results also reveal that enthalpy/entropy compensation balances the gain in one contribution against a corresponding loss in the other. The obtained thermodynamic data are in contrast to the results from previous microcalorimetric studies, which showed binding constants that were orders of magnitude smaller and complexations, which were in part enthalpically driven but which neglected the influence of the alkali metal counterions.

Cooperative assembly of discrete stacked aggregates driven by supramolecular host-guest complexation.

p-Sulfonatocalix[4]arene (SC4) interacts with the aromatic dye crystal violet (CV) to form complexes with stoichiometries ranging from SC4:CV = 1:1 up to 1:5 both in solution and in the gas phase. While the 1:1 complex is of the inclusion type, as frequently observed for other guests, in the higher-order complexes the CV molecules interact with SC4 in a peripheral manner. The formation of such complexes is driven by ionic interactions established between the dye and the calixarene and by CV-CV stacking interactions. The application of an advanced fitting procedure made possible a quantitative analysis of the UV-vis data and allowed the determination of the stepwise binding constants. This unprecedented approach provides evidence that the formation of the highest-order complexes occurs through a cooperative mechanism. Moreover, the development of a quantitative analytical model enables the possibility of using this type of system for water-soluble sensing assays, as is also exemplified in the present work.

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.