CRAFTing Delivery of Membrane Proteins into Protocells using Nanodiscs.

For the successful generative engineering of functional artificial cells, a convenient and controllable means of delivering membrane proteins into membrane lipid bilayers is necessary. Here we report a delivery system that achieves this by employing membrane protein-carrying nanodiscs and the calcium-dependent fusion of phosphatidylserine lipid membranes. We show that lipid nanodiscs can fuse a transported lipid bilayer with the lipid bilayers of small unilamellar vesicles (SUVs) or giant unilamellar vesicles (GUVs) while avoiding recipient vesicles aggregation. This is triggered by a simple, transient increase in calcium concentration, which results in efficient and rapid fusion in a one-pot reaction. Furthermore, nanodiscs can be loaded with membrane proteins that can be delivered into target SUV or GUV membranes in a detergent-independent fashion while retaining their functionality. Nanodiscs have a proven ability to carry a wide range of membrane proteins, control their oligomeric state, and are highly adaptable. Given this, our approach may be the basis for the development of useful tools that will allow bespoke delivery of membrane proteins to protocells, equipping them with the cell-like ability to exchange material across outer/subcellular membranes.

Watching Molecular Nanotubes Self-Assemble in Real Time.

Molecular self-assembly is a fundamental process in nature that can be used to develop novel functional materials for medical and engineering applications. However, their complex mechanisms make the short-lived stages of self-assembly processes extremely hard to reveal. In this article, we track the self-assembly process of a benchmark system, double-walled molecular nanotubes, whose structure is similar to that found in biological and synthetic systems. We selectively dissolved the outer wall of the double-walled system and used the inner wall as a template for the self-reassembly of the outer wall. The reassembly kinetics were followed in real time using a combination of microfluidics, spectroscopy, cryogenic transmission electron microscopy, molecular dynamics simulations, and exciton modeling. We found that the outer wall self-assembles through a transient disordered patchwork structure: first, several patches of different orientations are formed, and only on a longer time scale will the patches interact with each other and assume their final preferred global orientation. The understanding of patch formation and patch reorientation marks a crucial step toward steering self-assembly processes and subsequent material engineering.

Strategies for Enhancing the Dielectric Constant of Organic Materials.

High dielectric constant organic semiconductors, often obtained by the use of ethylene glycol (EG) side chains, have gained attention in recent years in the efforts of improving the device performance for various applications. Dielectric constant enhancements due to EGs have been demonstrated extensively, but various effects, such as the choice of the particular molecule and the frequency and temperature regime, that determine the extent of this enhancement require further understanding. In this work, we study these effects by means of polarizable molecular dynamics simulations on a carefully selected set of fullerene derivatives with EG side chains. The selection allows studying the dielectric response in terms of both the number and length of EG chains and also the choice of the group connecting the fullerene to the EG chain. The computed time- and frequency-dependent dielectric responses reveal that the experimentally observed rise of the dielectric constant within the kilo/megahertz regime for some molecules is likely due to the highly stretched dielectric response of the EGs: the initial sharp increase over the first few nanoseconds is followed by a smaller but persistent increase in the range of microseconds. Additionally, our computational protocol allows the separation of different factors that contribute to the overall dielectric constant, providing insights to make several molecular design guides for future organic materials in order to enhance their dielectric constant further.

Sequence-complementarity dependent co-assembly of phosphodiester-linked aromatic donor-acceptor trimers.

We have created sequenced phosphoester-linked trimers of aromatic donor/acceptors which participate in charge-transfer interactions. Each sequence displays characteristic self-assembly, and complementary sequences interact with each other to produce new nanostructures and thermochromism. This paves the way towards new functional nanomaterials which make bio-analogous use of sequence to tune structure.

Modelling structural properties of cyanine dye nanotubes at coarse-grained level.

Self-assembly is a ubiquitous process spanning from biomolecular aggregates to nanomaterials. Even though the resulting aggregates can be studied through experimental techniques, the dynamic pathways of the process and the molecular details of the final structures are not necessarily easy to resolve. Consequently, rational design of self-assembling aggregates and their properties remains extremely challenging. At the same time, modelling the self-assembly with computational methods is not trivial, because its spatio-temporal scales are usually beyond the limits of all-atom based simulations. The use of coarse-grained (CG) models can alleviate this limitation, but usually suffers from the lack of optimised parameters for the molecular constituents. In this work, we describe the procedure of parametrizing a CG Martini model for a cyanine dye (C8S3) that self-assembles into hollow double-walled nanotubes. First, we optimised the model based on quantum mechanics calculations and all-atom reference simulations, in combination with available experimental data. Then, we conducted random self-assembly simulations, and the performance of our model was tested on preformed assemblies. Our simulations provide information on the time-dependent local arrangement of this cyanine dye, when aggregates are being formed. Furthermore, we provide guidelines for designing and optimising parameters for similar self-assembling nanomaterials.

Cryogenic TEM imaging of artificial light harvesting complexes outside equilibrium.

The energy transport in natural light-harvesting complexes can be explored in laboratory conditions via self-assembled supramolecular structures. One such structure arises from the amphiphilic dye C8S3 molecules, which self-assemble in an aqueous medium to a double-wall cylindrical nanotube reminiscent of natural light-harvesting complexes found in green sulphur bacteria. In this paper, we report a way to investigate the structure of inner nanotubes (NTs) alone by dissolving the outer NTs in a microfluidic setting. The resulting thermodynamically unstable system was rapidly frozen, preventing the reassembly of the outer NT from the dissolved molecules, and imaged using cryogenic transmission electron microscopy (cryo-TEM). The experimental cryo-TEM images and the molecular structure were compared by simulating high-resolution TEM images, which were based on the molecular modelling of C8S3 NTs. We found that the inner NT with outer walls removed during the flash-dilution process had a similar size to the parent double-walled NTs. Moreover, no structural inhomogeneity was observed in the inner NT after flash-dilution. This opens up exciting possibilities for functionalisation of inner NTs before the reassembly of the outer NT occurs, which can be broadly extended to modify the intra-architecture of other self-assembled nanostructures.

Comparing Dimerization Free Energies and Binding Modes of Small Aromatic Molecules with Different Force Fields.

Dimerization free energies are fundamental quantities that describe the strength of interaction of different molecules. Obtaining accurate experimental values for small molecules and disentangling the conformations that contribute most to the binding can be extremely difficult, due to the size of the systems and the small energy differences. In many cases, one has to resort to computational methods to calculate such properties. In this work, we used molecular dynamics simulations in conjunction with metadynamics to calculate the free energy of dimerization of small aromatic rings, and compared three models from popular online servers for atomistic force fields, namely G54a7, CHARMM36 and OPLS. We show that, regardless of the force field, the profiles for the dimerization free energy of these compounds are very similar. However, significant care needs to be taken when studying larger molecules, since the deviations from the trends increase with the size of the molecules, resulting in force field dependent preferred stacking modes; for example, in the cases of pyrene and tetracene. Our results provide a useful background study for using topology builders to model systems which rely on stacking of aromatic moieties, and are relevant in areas ranging from drug design to supramolecular assembly.

Capturing Membrane Phase Separation by Dual Resolution Molecular Dynamics Simulations.

Understanding the lateral organization in plasma membranes remains an open problem and is of great interest to many researchers. Model membranes consisting of coexisting domains are commonly used as simplified models of plasma membranes. The coarse-grained (CG) Martini force field has successfully captured spontaneous separation of ternary membranes into a liquid-disordered and a liquid-ordered domain. With all-atom (AA) models, however, phase separation is much harder to achieve due to the slow underlying dynamics. To remedy this problem, here, we apply the virtual site (VS) hybrid method on a ternary membrane composed of saturated lipids, unsaturated lipids, and cholesterol to investigate the phase separation. The VS scheme couples the two membrane leaflets at CG and AA resolution. We found that the rapid phase separation reached by the CG leaflet can accelerate and guide this process in the AA leaflet.

Martini 3: a general purpose force field for coarse-grained molecular dynamics.

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Structural characterization of supramolecular hollow nanotubes with atomistic simulations and SAXS.

Self-assembled nanostructures arise when building blocks spontaneously organize into ordered aggregates that exhibit different properties compared to the disorganized monomers. Here, we study an amphiphilic cyanine dye (C8S3) that is known to self-assemble into double-walled, hollow, nanotubes with interesting optical properties. The molecular packing of the dyes inside the nanotubes, however, remains elusive. To reveal the structural features of the C8S3 nanotubes, we performed atomistic Molecular Dynamics simulations of preformed bilayers and nanotubes. We find that different packing arrangements lead to stable structures, in which the tails of the C8S3 molecules are interdigitated. Our results are verified by SAXS experiments. Together our data provide a detailed structural characterization of the C8S3 nanotubes. Furthermore, our approach was able to resolve the ambiguity inherent from cryo-TEM measurements in calculating the wall thickness of similar systems. The insights obtained are expected to be generally useful for understanding and designing other supramolecular assemblies.

Titratable Martini model for constant pH simulations.

In this work, we deliver a proof of concept for a fast method that introduces pH effects into classical coarse-grained (CG) molecular dynamics simulations. Our approach is based upon the latest version of the popular Martini CG model to which explicit proton mimicking particles are added. We verify our approach against experimental data involving several different molecules and different environmental conditions. In particular, we compute titration curves, pH dependent free energies of transfer, and lipid bilayer membrane affinities as a function of pH. Using oleic acid as an example compound, we further illustrate that our method can be used to study passive translocation in lipid bilayers via protonation. Finally, our model reproduces qualitatively the expansion of the macromolecule dendrimer poly(propylene imine) as well as the associated pKa shift of its different generations. This example demonstrates that our model is able to pick up collective interactions between titratable sites in large molecules comprising many titratable functional groups.

Coupling Coarse-Grained to Fine-Grained Models via Hamiltonian Replica Exchange.

The energy landscape of biomolecular systems contains many local minima that are separated by high energy barriers. Sampling this landscape in molecular dynamics simulations is a challenging task and often requires the use of enhanced sampling techniques. Here, we increase the sampling efficiency by coupling the fine-grained (FG) GROMOS force field to the coarse-grained (CG) Martini force field via the Hamiltonian replica exchange method (HREM). We tested the efficiency of this procedure using a lutein/octane system. In traditional simulations, cis-trans transitions of lutein are barely observed due to the high energy barrier separating these states. However, many of these transitions are sampled with our HREM scheme. The proposed method offers new possibilities for enhanced sampling of biomolecular conformations, making use of CG models without compromising the accuracy of the FG model.

Dual Resolution Membrane Simulations Using Virtual Sites.

All-atomistic (AA) and coarse-grain (CG) simulations have been successfully applied to investigate a broad range of biomolecular processes. However, the accessible time and length scales of AA simulation are limited and the specific molecular details of CG simulation are simplified. Here, we propose a virtual site (VS) based hybrid scheme that can concurrently couple AA and CG resolutions in a single membrane simulation, mitigating the shortcomings of either representation. With some adjustments to make the AA and CG force fields compatible, we demonstrate that lipid bilayer properties are well kept in our hybrid approach. Our VS hybrid method was also applied to simulate a small lipid vesicle, with the inner leaflet and interior solvent represented in AA, and the outer leaflet together with exterior solvent at the CG level. Our multiscale method opens the way to investigate biomembrane properties at increased computational efficiency, in particular applications involving large solvent filled regions.

Capturing Choline-Aromatics Cation-π Interactions in the MARTINI Force Field.

Cation-π interactions play an important role in biomolecular recognition, including interactions between membrane phosphatidylcholine lipids and aromatic amino acids of peripheral proteins. While molecular mechanics coarse grain (CG) force fields are particularly well suited to simulate membrane proteins in general, they are not parameterized to explicitly reproduce cation-π interactions. We here propose a modification of the polarizable MARTINI coarse grain (CG) model enabling it to model membrane binding events of peripheral proteins whose aromatic amino acid interactions with choline headgroups are crucial for their membrane binding. For this purpose, we first collected and curated a dataset of eight peripheral proteins from different families. We find that the MARTINI CG model expectedly underestimates aromatics-choline interactions and is unable to reproduce membrane binding of the peripheral proteins in our dataset. Adjustments of the relevant interactions in the polarizable MARTINI force field yield significant improvements in the observed binding events. The orientation of each membrane-bound protein is comparable to reference data from all-atom simulations and experimental binding data. We also use negative controls to ensure that choline-aromatics interactions are not overestimated. We finally check that membrane properties, transmembrane proteins, and membrane translocation potential of mean force (PMF) of aromatic amino acid side-chain analogues are not affected by the new parameter set. This new version "MARTINI 2.3P" is a significant improvement over its predecessors and is suitable for modeling membrane proteins including peripheral membrane binding of peptides and proteins.

Multiscale modeling of molecular structure and optical properties of complex supramolecular aggregates.

Supramolecular aggregates of synthetic dye molecules offer great perspectives to prepare biomimetic functional materials for light-harvesting and energy transport. The design is complicated by the fact that structure-property relationships are hard to establish, because the molecular packing results from a delicate balance of interactions and the excitonic properties that dictate the optics and excited state dynamics, in turn sensitively depend on this packing. Here we show how an iterative multiscale approach combining molecular dynamics and quantum mechanical exciton modeling can be used to obtain accurate insight into the packing of thousands of cyanine dye molecules in a complex double-walled tubular aggregate in close interaction with its solvent environment. Our approach allows us to answer open questions not only on the structure of these prototypical aggregates, but also about their molecular-scale structural and energetic heterogeneity, as well as on the microscopic origin of their photophysical properties. This opens the route to accurate predictions of energy transport and other functional properties.

Pitfalls of the Martini Model.

The computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.

Binding of quinazolinones to c-KIT G-quadruplex; an interplay between hydrogen bonding and π-π stacking.

Stabilization of G-quadruplex structures in the c-KIT promoter with the aid of ligands has become an area of great interest in potential cancer therapeutics. Understanding the binding process between ligands and G-quadruplex is essential for a discovery of selective ligands with high binding affinity to G-quadruplex. In the present work, binding mechanisms of 4-quinazolinones to c-KIT G-quadruplex were investigated theoretically by means of molecular dynamics (MD) simulations. To explore the binding affinity of ligands, binding free energy calculations were performed using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. We demonstrate that the key interactions in G-quadruplex-ligand complexes are π-π stacking and hydrogen bond interactions. However, neither of these two interactions alone determines the stability of the G-quadruplex-ligand complexes; rather, it is the result of an intricate interplay between the two. To further examine the nature of the binding, a free energy decomposition analysis at residue level was carried out. The results clearly demonstrate the crucial roles of two hot spot residues (DG4 and DG8) for the binding of ligands to c-KIT G-quadruplex, and highlight the importance of the planar aromatic moiety of ligands in G-quadruplex stabilization via π-π stacking interactions. Our study can assist in the design of new derivatives of 4-quinazolinone with high binding affinity for c-KIT G-quadruplex.

Direct and Regioselective Di-α-fucosylation on the Secondary Rim of ß-Cyclodextrin.

A straightforward glycosylation method is described to regio- and stereoselectively introduce two α-l-fucose moieties directly to the secondary rim of ß-cyclodextrin. Using NMR and MS fragmentation studies, the nonasaccharide structure was determined, which was also visualized using molecular dynamics simulations. The reported glycosylation method proved to be robust on gram-scale, and may be generally applied to directly glycosylate ß-cyclodextrins to make well-defined multivalent glycoclusters.

Transferable MARTINI Model of Poly(ethylene Oxide).

Motivated by the deficiencies of the previous MARTINI models of poly(ethylene oxide) (PEO), we present a new model featuring a high degree of transferability. The model is parametrized on (a) a set of 8 free energies of transfer of dimethoxyethane (PEO dimer) from water to solvents of varying polarity; (b) the radius of gyration in water at high dilution; and (c) matching angle and dihedral distributions from atomistic simulations. We demonstrate that our model behaves well in five different areas of application: (1) it produces accurate densities and phase behavior or small PEO oligomers and water mixtures; (2) it yields chain dimensions in good agreement with the experiment in three different solvents (water, diglyme, and benzene) over a broad range of molecular weights (∼1.2 kg/mol to 21 kg/mol); (3) it reproduces qualitatively the structural features of lipid bilayers containing PEGylated lipids in the brush and mushroom regime; (4) it is able to reproduce the phase behavior of several PEO-based nonionic surfactants in water; and (5) it can be combined with the existing MARTINI PS to model PS-PEO block copolymers. Overall, the new PEO model outperforms previous models and features a high degree of transferability.

Photoswitching of DNA Hybridization Using a Molecular Motor.

Reversible control over the functionality of biological systems via external triggers may be used in future medicine to reduce the need for invasive procedures. Additionally, externally regulated biomacromolecules are now considered as particularly attractive tools in nanoscience and the design of smart materials, due to their highly programmable nature and complex functionality. Incorporation of photoswitches into biomolecules, such as peptides, antibiotics, and nucleic acids, has generated exciting results in the past few years. Molecular motors offer the potential for new and more precise methods of photoregulation, due to their multistate switching cycle, unidirectionality of rotation, and helicity inversion during the rotational steps. Aided by computational studies, we designed and synthesized a photoswitchable DNA hairpin, in which a molecular motor serves as the bridgehead unit. After it was determined that motor function was not affected by the rigid arms of the linker, solid-phase synthesis was employed to incorporate the motor into an 8-base-pair self-complementary DNA strand. With the photoswitchable bridgehead in place, hairpin formation was unimpaired, while the motor part of this advanced biohybrid system retains excellent photochemical properties. Rotation of the motor generates large changes in structure, and as a consequence the duplex stability of the oligonucleotide could be regulated by UV light irradiation. Additionally, Molecular Dynamics computations were employed to rationalize the observed behavior of the motor-DNA hybrid. The results presented herein establish molecular motors as powerful multistate switches for application in biological environments.