Elucidating the complex membrane binding of a protein with multiple anchoring domains using extHMMM.

Membrane binding is a crucial mechanism for many proteins, but understanding the specific interactions between proteins and membranes remains a challenging endeavor. Coagulation factor Va (FVa) is a large protein whose membrane interactions are complicated due to the presence of multiple anchoring domains that individually can bind to lipid membranes. Using molecular dynamics simulations, we investigate the membrane binding of FVa and identify the key mechanisms that govern its interaction with membranes. Our results reveal that FVa can either adopt an upright or a tilted molecular orientation upon membrane binding. We further find that the domain organization of FVa deviates (sometimes significantly) from its crystallographic reference structure, and that the molecular orientation of the protein matches with domain reorganization to align the C2 domain toward its favored membrane-normal orientation. We identify specific amino acid residues that exhibit contact preference with phosphatidylserine lipids over phosphatidylcholine lipids, and we observe that mostly electrostatic effects contribute to this preference. The observed lipid-binding process and characteristics, specific to FVa or common among other membrane proteins, in concert with domain reorganization and molecular tilt, elucidate the complex membrane binding dynamics of FVa and provide important insights into the molecular mechanisms of protein-membrane interactions. An updated version of the HMMM model, termed extHMMM, is successfully employed for efficiently observing membrane bindings of systems containing the whole FVa molecule.

Deciphering specificity and cross-reactivity in tachykinin NK1 and NK2 receptors.

The tachykinin receptors neurokinin 1 (NK1R) and neurokinin 2 (NK2R) are G protein-coupled receptors that bind preferentially to the natural peptide ligands substance P and neurokinin A, respectively, and have been targets for drug development. Despite sharing a common C-terminal sequence of Phe-X-Gly-Leu-Met-NH2 that helps direct biological function, the peptide ligands exhibit some degree of cross-reactivity toward each other's non-natural receptor. Here, we investigate the detailed structure-activity relationships of the ligand-bound receptor complexes that underlie both potent activation by the natural ligand and cross-reactivity. We find that the specificity and cross-reactivity of the peptide ligands can be explained by the interactions between the amino acids preceding the FxGLM consensus motif of the bound peptide ligand and two regions of the receptor: the ß-hairpin of the extracellular loop 2 (ECL2) and a N-terminal segment leading into transmembrane helix 1. Positively charged sidechains of the ECL2 (R177 of NK1R and K180 of NK2R) are seen to play a vital role in the interaction. The N-terminal positions 1 to 3 of the peptide ligand are entirely dispensable. Mutated and chimeric receptor and ligand constructs neatly swap around ligand specificity as expected, validating the structure-activity hypotheses presented. These findings will help in developing improved agonists or antagonists for NK1R and NK2R.

Cholesterol and M2 Rendezvous in Budding and Scission of Influenza A Virus.

The cholesterol of the host cell plasma membrane and viral M2 protein plays a crucial role in multiple stages of infection and replication of the influenza A virus. Cholesterol is required for the formation of heterogeneous membrane microdomains (or rafts) in the budozone of the host cell that serves as assembly sites for the viral components. The raft microstructures act as scaffolds for several proteins. Cholesterol may further contribute to the mechanical forces necessary for membrane scission in the last stage of budding and help to maintain the stability of the virus envelope. The M2 protein has been shown to cause membrane scission in model systems by promoting the formation of curved lipid bilayer structures that, in turn, can lead to membrane vesicles budding off or scission intermediates. Membrane remodeling by M2 is intimately linked with cholesterol as it affects local lipid composition, fluidity, and stability of the membrane. Thus, both cholesterol and M2 protein contribute to the efficient and proper release of newly formed influenza viruses from the virus-infected cells.

A 19F-qNMR-Guided Mathematical Model for G Protein-Coupled Receptor Signaling.

G protein-coupled receptors (GPCRs) exhibit a wide range of pharmacological efficacies, yet the molecular mechanisms responsible for the differential efficacies in response to various ligands remain poorly understood. This lack of understanding has hindered the development of a solid foundation for establishing a mathematical model for signaling efficacy. However, recent progress has been made in delineating and quantifying receptor conformational states and associating function with these conformations. This progress has allowed us to construct a mathematical model for GPCR signaling efficacy that goes beyond the traditional ON/OFF binary switch model. In this study, we present a quantitative conformation-based mathematical model for GPCR signaling efficacy using the adenosine A2A receptor (A2AR) as a model system, under the guide of 19F quantitative nuclear magnetic resonance experiments. This model encompasses two signaling states, a fully activated state and a partially activated state, defined as being able to regulate the cognate Gα s nucleotide exchange with respective G protein recognition capacity. By quantifying the population distribution of each state, we can now in turn examine GPCR signaling efficacy. This advance provides a foundation for assessing GPCR signaling efficacy using a conformation-based mathematical model in response to ligand binding. SIGNIFICANCE STATEMENT: Mathematical models to describe signaling efficacy of GPCRs mostly suffer from considering only two states (ON/OFF). However, research indicates that a GPCR possesses multiple active-(like) states that can interact with Gαßγ independently, regulating varied nucleotide exchanges. With the guide of 19F-qNMR, the transitions among these states are quantified as a function of ligand and Gαßγ, serving as a foundation for a novel conformation-based mathematical signaling model.

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.

Trifluorinated Keto-Enol Tautomeric Switch in Probing Domain Rotation of a G Protein-Coupled Receptor.

Conformational dynamics and transitions of biologically active molecules are pivotal for understanding the physiological responses they elicit. In the case of receptor activation, there are major implications elucidating disease mechanisms and drug discovery innovation. Yet, incorporation of these factors into drug screening systems remains challenging in part due to the lack of suitable approaches to include them. Here, we present a novel strategy to probe the GPCR domain rotation by utilizing the 19fluorine signal variability of a trifluorinated keto-enol (TFKE) chemical equilibrium. The method takes advantage of the high sensitivity of the TFKE tautomerism toward microenvironmental changes resulting from receptor conformational transitions upon ligand binding. We validated the method using the adenosine A2AR receptor as a model system in which the TFKE was attached to two sites exhibiting opposing motions upon ligand binding, namely, V229C6.31 on transmembrane domain VI (TM6) and A289C7.54 on TM7. Our results demonstrated that the TFKE switch was an excellent reporter for the domain rotation and could be used to study the conformational transition and dynamics of relative domain motions. Although further studies are needed in order to establish a quantitative relationship between the rotational angle and the population distribution of different components in a particular system, the research presented here provides a foundation for its application in studying receptor domain rotation and dynamics, which could be useful in drug screening efforts.

Entropic forces drive clustering and spatial localization of influenza A M2 during viral budding.

The influenza A matrix 2 (M2) transmembrane protein facilitates virion release from the infected host cell. In particular, M2 plays a role in the induction of membrane curvature and/or in the scission process whereby the envelope is cut upon virion release. Here we show using coarse-grained computer simulations that various M2 assembly geometries emerge due to an entropic driving force, resulting in compact clusters or linearly extended aggregates as a direct consequence of the lateral membrane stresses. Conditions under which these protein assemblies will cause the lipid membrane to curve are explored, and we predict that a critical cluster size is required for this to happen. We go on to demonstrate that under the stress conditions taking place in the cellular membrane as it undergoes large-scale membrane remodeling, the M2 protein will, in principle, be able to both contribute to curvature induction and sense curvature to line up in manifolds where local membrane line tension is high. M2 is found to exhibit linactant behavior in liquid-disordered-liquid-ordered phase-separated lipid mixtures and to be excluded from the liquid-ordered phase, in near-quantitative agreement with experimental observations. Our findings support a role for M2 in membrane remodeling during influenza viral budding both as an inducer and a sensor of membrane curvature, and they suggest a mechanism by which localization of M2 can occur as the virion assembles and releases from the host cell, independent of how the membrane curvature is produced.

Allostery in Coagulation Factor VIIa Revealed by Ensemble Refinement of Crystallographic Structures.

A critical step in injury-induced initiation of blood coagulation is the formation of the complex between the trypsin-like protease coagulation factor VIIa (FVIIa) and its cofactor tissue factor (TF), which converts FVIIa from an intrinsically poor enzyme to an active protease capable of activating zymogens of downstream coagulation proteases. Unlike its constitutively active ancestor trypsin, FVIIa is allosterically activated (by TF). Here, ensemble refinement of crystallographic structures, which uses multiple copies of the entire structure as a means of representing structural flexibility, is applied to explore the impacts of inhibitor binding to trypsin and FVIIa, as well as cofactor binding to FVIIa. To assess the conformational flexibility and its role in allosteric pathways in these proteases, main-chain hydrogen bond networks are analyzed by calculating the hydrogen-bond propensity. Mapping pairwise propensity differences between relevant structures shows that binding of the inhibitor benzamidine to trypsin has a minor influence on the protease flexibility. For FVIIa, in contrast, the protease domain is "locked" into the catalytically competent trypsin-like configuration upon benzamidine binding as indicated by the stabilization of key structural features: the nonprime binding cleft and the oxyanion hole are stabilized, and the effect propagates from the active site region to the calcium-binding site and to the vicinity of the disulphide bridge connecting with the light chain. TF binding to FVIIa furthermore results in stabilization of the 170 loop, which in turn propagates an allosteric signal from the TF-binding region to the active site. Analyses of disulphide bridge energy and flexibility reflect the striking stability difference between the unregulated enzyme and the allosterically activated form after inhibitor or cofactor binding. The ensemble refinement analyses show directly, for the first time to our knowledge, whole-domain structural footprints of TF-induced allosteric networks present in x-ray crystallographic structures of FVIIa, which previously only have been hypothesized or indirectly inferred.

Acid activation mechanism of the influenza A M2 proton channel.

The homotetrameric influenza A M2 channel (AM2) is an acid-activated proton channel responsible for the acidification of the influenza virus interior, an important step in the viral lifecycle. Four histidine residues (His37) in the center of the channel act as a pH sensor and proton selectivity filter. Despite intense study, the pH-dependent activation mechanism of the AM2 channel has to date not been completely understood at a molecular level. Herein we have used multiscale computer simulations to characterize (with explicit proton transport free energy profiles and their associated calculated conductances) the activation mechanism of AM2. All proton transfer steps involved in proton diffusion through the channel, including the protonation/deprotonation of His37, are explicitly considered using classical, quantum, and reactive molecular dynamics methods. The asymmetry of the proton transport free energy profile under high-pH conditions qualitatively explains the rectification behavior of AM2 (i.e., why the inward proton flux is allowed when the pH is low in viral exterior and high in viral interior, but outward proton flux is prohibited when the pH gradient is reversed). Also, in agreement with electrophysiological results, our simulations indicate that the C-terminal amphipathic helix does not significantly change the proton conduction mechanism in the AM2 transmembrane domain; the four transmembrane helices flanking the channel lumen alone seem to determine the proton conduction mechanism.

Molecular Basis of Enhanced Activity in Factor VIIa-Trypsin Variants Conveys Insights into Tissue Factor-mediated Allosteric Regulation of Factor VIIa Activity.

The complex of coagulation factor VIIa (FVIIa), a trypsin-like serine protease, and membrane-bound tissue factor (TF) initiates blood coagulation upon vascular injury. Binding of TF to FVIIa promotes allosteric conformational changes in the FVIIa protease domain and improves its catalytic properties. Extensive studies have revealed two putative pathways for this allosteric communication. Here we provide further details of this allosteric communication by investigating FVIIa loop swap variants containing the 170 loop of trypsin that display TF-independent enhanced activity. Using x-ray crystallography, we show that the introduced 170 loop from trypsin directly interacts with the FVIIa active site, stabilizing segment 215-217 and activation loop 3, leading to enhanced activity. Molecular dynamics simulations and novel fluorescence quenching studies support that segment 215-217 conformation is pivotal to the enhanced activity of the FVIIa variants. We speculate that the allosteric regulation of FVIIa activity by TF binding follows a similar path in conjunction with protease domain N terminus insertion, suggesting a more complete molecular basis of TF-mediated allosteric enhancement of FVIIa activity.

Small-Angle X-ray Scattering Data in Combination with RosettaDock Improves the Docking Energy Landscape.

We have performed a benchmark to evaluate the relative success of using small-angle X-ray scattering (SAXS) data as constraints (hereafter termed SAXSconstrain) in the RosettaDock protocol (hereafter termed RosettaDockSAXS). For this purpose, we have chosen 38 protein complex structures, calculated the theoretical SAXS data for the protein complexes using the program CRYSOL, and then used the SAXS data as constraints. We further considered a few examples where crystal structures and experimental SAXS data are available. SAXSconstrain were added to the protocol in the initial, low-resolution docking step, allowing fast rejection of complexes that violate the shape restraints imposed by the SAXS data. Our results indicate that the implementation of SAXSconstrain in general reduces the sampling space of possible protein-protein complexes significantly and can indeed increase the probability of finding near-native protein complexes. The methodology used is based on rigid-body docking and works for cases where no or minor conformational changes occur upon binding of the docking partner. In a wider perspective, the strength of RosettaDockSAXS lies in the combination of low-resolution structural information on protein complexes in solution from SAXS experiments with protein-protein interaction energies obtained from RosettaDock, which will allow the prediction of unknown three-dimensional atomic structures of protein-protein complexes.

Factor VIII Interacts with the Endocytic Receptor Low-density Lipoprotein Receptor-related Protein 1 via an Extended Surface Comprising "Hot-Spot" Lysine Residues.

Lysine residues are implicated in driving the ligand binding to the LDL receptor family. However, it has remained unclear how specificity is regulated. Using coagulation factor VIII as a model ligand, we now study the contribution of individual lysine residues in the interaction with the largest member of the LDL receptor family, low-density lipoprotein receptor-related protein (LRP1). Using hydrogen-deuterium exchange mass spectrometry (HDX-MS) and SPR interaction analysis on a library of lysine replacement variants as two independent approaches, we demonstrate that the interaction between factor VIII (FVIII) and LRP1 occurs over an extended surface containing multiple lysine residues. None of the individual lysine residues account completely for LRP1 binding, suggesting an additive binding model. Together with structural docking studies, our data suggest that FVIII interacts with LRP1 via an extended surface of multiple lysine residues that starts at the bottom of the C1 domain and winds around the FVIII molecule.

Membrane Interaction of the Factor VIIIa Discoidin Domains in Atomistic Detail.

A recently developed membrane-mimetic model was applied to study membrane interaction and binding of the two anchoring C2-like discoidin domains of human coagulation factor VIIIa (FVIIIa), the C1 and C2 domains. Both individual domains, FVIII C1 and FVIII C2, were observed to bind the phospholipid membrane by partial or full insertion of their extruding loops (the spikes). However, the two domains adopted different molecular orientations in their membrane-bound states; FVIII C2 roughly was positioned normal to the membrane plane, while FVIII C1 displayed a multitude of tilted orientations. The results indicate that FVIII C1 may be important in modulating the orientation of the FVIIIa molecule to optimize the interaction with FIXa, which is anchored to the membrane via its γ-carboxyglutamic acid-rich (Gla) domain. Additionally, a structural change was observed in FVIII C1 in the coiled main chain leading the first spike. A tight interaction with one lipid per domain, similar to what has been suggested for the homologous FVa C2, is characterized. Finally, we rationalize known FVIII antibody epitopes and the scarcity of documented hemophilic missense mutations related to improper membrane binding of FVIIIa, based on the prevalent nonspecificity of ionic interactions in the simulated membrane-bound states of FVIII C1 and FVIII C2.

Dynamic Nature of Staphylococcus aureus Type I Signal Peptidases.

Molecular dynamics simulations are used to interrogate the dynamic nature of Staphylococcus aureus Type I signal peptidases, SpsA and SpsB, including the impact of the P29S mutation of SpsB. Fluctuations and plasticity- rigidity characteristics vary among the proteins, particularly in the extracellular domain. Intriguingly, the P29S mutation, which influences susceptibility to arylomycin antibiotics, affect the mechanically coupled motions in SpsB. The integrity of the active site is crucial for catalytic competency, and variations in sampled structural conformations among the proteins are consistent with diverse peptidase capabilities. We also explored the intricate interactions between the proteins and the model S. aureus membrane. It was observed that certain membrane-inserted residues in the loop around residue 50 (50s) and C-terminal loops, beyond the transmembrane domain, give rise to direct interactions with lipids in the bilayer membrane. Our findings are discussed in the context of functional knowledge about these signal peptidases, offering additional understanding of dynamic aspects relevant to some cellular processes with potential implications for drug targeting strategies.

Optimizing Coarse-Grained Models for Large-Scale Membrane Protein Simulation.

Coarse-grained (CG) models have been developed for studying membrane proteins at physiologically relevant scales. Such methods, including popular CG lipid models, exhibit stability and efficiency at moderate scales, but they can become impractical or even unusable beyond a critical size due to various technical issues. Here, we report that these scale-dependent issues can arise from progressively slower relaxation dynamics and become confounded by unforeseen instabilities observed only at larger scales. To address these issues, we systemically optimized a 4-site solvent-free CG lipid model that is suitable for conducting micron-scale molecular dynamics simulations of membrane proteins under various membrane properties. We applied this lipid model to explore the long-range membrane deformation induced by a large mechanosensitive ion channel, PIEZO. We show that the optimized CG models are powerful in elucidating the structural and dynamic interplay between PIEZO and the membrane. Furthermore, we anticipate that our methodological insights can prove useful for resolving issues stemming from scale-dependent limitations of similar CG methodologies.

Membrane binding and lipid-protein interaction of the C2 domain from coagulation factor V.

Anchoring of coagulation factors to anionic regions of the membrane involves the C2 domain as a key player. The rate of enzymatic reactions of the coagulation factors is increased by several orders of magnitude upon membrane binding. However, the precise mechanisms behind the rate acceleration remain unclear, primarily because of a lack of understanding of the conformational dynamics of the C2-containing factors and corresponding complexes. We elucidate the membrane-bound form of the C2 domain from human coagulation factor V (FV-C2) by characterizing its membrane binding the specific lipid-protein interactions. Employing all-atom molecular dynamics simulations and leveraging the highly mobile membrane-mimetic (HMMM) model, we observed spontaneous binding of FV-C2 to a phosphatidylserine (PS)-containing membrane within 2-25 ns across twelve independent simulations. FV-C2 interacted with the membrane through three loops (spikes 1-3), achieving a converged, stable orientation. Multiple HMMM trajectories of the spontaneous membrane binding provided extensive sampling and ample data to examine the membrane-induced effects on the conformational dynamics of C2 as well as specific lipid-protein interactions. Despite existing crystal structures representing presumed "open" and "closed" states of FV-C2, our results revealed a continuous distribution of structures between these states, with the most populated structures differing from both "open" and "closed" states observed in crystal environments. Lastly, we characterized a putative PS-specific binding site formed by K23, Q48, and S78 located in the groove enclosed by spikes 1-3 (PS-specificity pocket), suggesting a different orientation of a bound headgroup moiety compared to previous proposals based upon analysis of static crystal structures.

Evaluating Polarizable Biomembrane Simulations against Experiments.

Owing to the increase of available computational capabilities and the potential for providing a more accurate description, polarizable molecular dynamics force fields are gaining popularity in modeling biomolecular systems. It is, however, crucial to evaluate how much precision is truly gained with increasing cost and complexity of the simulation. Here, we leverage the NMRlipids open collaboration and Databank to assess the performance of available polarizable lipid models─the CHARMM-Drude and the AMOEBA-based parameters─against high-fidelity experimental data and compare them to the top-performing nonpolarizable models. While some improvement in the description of ion binding to membranes is observed in the most recent CHARMM-Drude parameters, and the conformational dynamics of AMOEBA-based parameters are excellent, the best nonpolarizable models tend to outperform their polarizable counterparts for each property we explored. The identified shortcomings range from inaccuracies in describing the conformational space of lipids to excessively slow conformational dynamics. Our results provide valuable insights for the further refinement of polarizable lipid force fields and for selecting the best simulation parameters for specific applications.

Distal Protein-Protein Interactions Contribute to SARS-CoV-2 Main Protease Substrate Binding and Nirmatrelvir Resistance.

SARS-CoV-2 main protease, M pro , is responsible for the processing of the viral polyproteins into individual proteins, including the protease itself. M pro is a key target of anti-COVID-19 therapeutics such as nirmatrelvir (the active component of Paxlovid). Resistance mutants identified clinically and in viral passage assays contain a combination of active site mutations (e.g. E166V, E166A, L167F), which reduce inhibitor binding and enzymatic activity, and non-active site mutations (e.g. P252L, T21I, L50F), which restore the fitness of viral replication. Although the mechanism of resistance for the active site mutations is apparent, the role of the non-active site mutations in fitness rescue remains elusive. In this study, we use the model system of a M pro triple mutant (L50F/E166A/L167F) that confers not only nirmatrelvir drug resistance but also a similar fitness of replication compared to the wild-type both in vitro and in vivo. By comparing peptide and full-length M pro protein as substrates, we demonstrate that the binding of M pro substrate involves more than residues in the active site. In particular, L50F and other non-active site mutations can enhance the M pro dimer-dimer interactions and help place the nsp5-6 substrate at the enzyme catalytic center. The structural and enzymatic activity data of M pro L50F, L50F/E166A/L167F, and others underscore the importance of considering the whole substrate protein in studying M pro and substrate interactions, and offers important insights into M pro function, resistance development, and inhibitor design.

Staphylococcus aureus FtsZ and PBP4 bind to the conformationally dynamic N-terminal domain of GpsB.

In the Firmicutes phylum, GpsB is a membrane associated protein that coordinates peptidoglycan synthesis with cell growth and division. Although GpsB has been studied in several bacteria, the structure, function, and interactome of Staphylococcus aureus GpsB is largely uncharacterized. To address this knowledge gap, we solved the crystal structure of the N-terminal domain of S. aureus GpsB, which adopts an atypical, asymmetric dimer, and demonstrates major conformational flexibility that can be mapped to a hinge region formed by a three-residue insertion exclusive to Staphylococci. When this three-residue insertion is excised, its thermal stability increases, and the mutant no longer produces a previously reported lethal phenotype when overexpressed in Bacillus subtilis. In S. aureus, we show that these hinge mutants are less functional and speculate that the conformational flexibility imparted by the hinge region may serve as a dynamic switch to fine-tune the function of the GpsB complex and/or to promote interaction with its various partners. Furthermore, we provide the first biochemical, biophysical, and crystallographic evidence that the N-terminal domain of GpsB binds not only PBP4, but also FtsZ, through a conserved recognition motif located on their C-termini, thus coupling peptidoglycan synthesis to cell division. Taken together, the unique structure of S. aureus GpsB and its direct interaction with FtsZ/PBP4 provide deeper insight into the central role of GpsB in S. aureus cell division.

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.