The Journal of Physical Chemistry B

Molecular dynamics simulations of nucleic acids are performed using a solvent-buffer distance of 10 [A] between the solute surface and the simulation box boundary. Although this cell size has been extensively explored in protein simulations, its implications for nucleic acid dynamics are not well understood. Nucleic acids are elongated, highly charged, and flexible structures with hydration and dynamical properties distinct from those of proteins and therefore, they may require different solvent-layer considerations in simulations. In this study, we investigated the effect of simulation cell size on nucleic acid dynamics by simulating a 30-base-pair double-helical nucleic acid structure and its two single-stranded forms using solvent-buffer distances of 3, 5, 10, 15, and 20 [A]. Smaller cells may impose restricted hydration, molecular crowding, and periodic image interactions. However, larger cells provide solvent space for conformational relaxation. A total of 45 s of molecular dynamics simulations were performed (3 structures x 5 cell sizes x 3 replicates x 1 s). Our results show that while the commonly used 10 [A] buffer may be sufficient to maintain the stability of the double-stranded nucleic acid, larger cells are required to capture the conformational dynamics of single-stranded structures. In both, increasing the cell size to 15 or 20 [A] enables broader conformational sampling. The first hydration shell exhibits reduced crowding in the 20 [A] cell, consistent with more relaxed conformations. At larger cell sizes, single-stranded nucleic acids adopt compact, self-associated conformations for stability. Together, this study presents physical insight into how simulation cell size and solvent environment influence nucleic acid dynamics.

Plexin-B1 is a transmembrane receptor that integrates signals from Rho-family and Ras-family (Rap1b) GTPases to regulate cellular processes. While ligand simulated activation of the receptor is largely understood, the role of membrane composition and GTPase allosteric effects on plexin structure, internal protein dynamics, and function is still to be elucidated. Here, we performed multi-replica, 1 s all-atom simulations of Plexin-B1-GTPase complexes on PIP2- and PIP3-containing membranes to investigate the effects of these two signaling lipids, as well as on the GTPases. We found that both Rap1b and Rnd1 stably associate with the membrane, with PIP2 promoting broader lipid engagement and stronger Rap1b-Plexin-B1 interactions, whereas PIP3 enhances Rnd1-Plexin contacts and induces a membrane proximal orientation of Plexins juxtamembrane helix and makes contacts with a previously discovered activation switch loop. Contact map and network analyses revealed lipid-dependent shifts in allosteric communication, with PIP2 favoring Rap1b-centric hotspots and PIP3 favoring Rnd1-centric pathways. These predictions allow us to suggest a model for plexin intracellular region activation where both the identity of phosphoinositides and GTPase context synergistically stabilize Plexin-B1 membrane engagement, alter structural dynamics, and allosteric networks. Thus, we propose that the membrane is an active modulator of plexin receptor signaling.

The SMN2 exon 7 5' splice-site/U1 snRNA duplex contains an A$_{-1}$ bulge that weakens splice-site recognition and represents a therapeutically relevant RNA connectivity defect, yet its conformational landscape and coupling to solvation remain poorly understood. Here, we performed enhanced-sampling Hamiltonian replica-exchange molecular dynamics simulations of the SMN2 splice-site duplex using four explicit-solvent models (OPC, TIP4P-Ew, TIP3P, and SPC/E) and characterized the sampled ensemble using linear and machine-learned latent representations. Across representations, the A$_{-1}$ defect consistently populated three metastable conformational states distinguished by local duplex geometry, base stacking, hydrogen-bonding patterns, and solvent exposure. The relative populations of these states, together with first-shell hydration and Na$^+$ distributions around the defect, varied substantially across water models, demonstrating that hydration and ion organization actively shape the equilibrium between locally accommodated and solvent-exposed conformations of the SMN2 splice-site bulge. Our results shed light on the conformational components of this therapeutic RNA target and highlight the impact of solvation model as an important consideration for molecular simulations of RNA splice-site recognition and small-molecule repair.

Staphyloxanthin (STX) is a carotenoid synthesized by the human pathogen Staphylococcus aureus. The golden color of this bacterium is due to this carotenoid. STX protects Staphylococcus aureus from oxidative stress by scavenging free radical species. Furthermore, STX has been shown to mechanically strengthen the Staphylococcus aureus membrane and to form microdomains that recruit antibiotic-resistance factors. Thus, inhibition of STX is a promising strategy for intervening against multidrug-resistant strains of this pathogen. However, the molecular mechanisms by which STX regulates the membrane structure and function of Staphylococcus aureus remain unclear. More specifically, the localization of STX within phosphatidylglycerol (PG) bilayers, the primary phospholipid of this bacteriums membrane, and how this localization drives macroscopic biophysical changes remain unresolved questions. Here, we addressed this issue by integrating molecular dynamics (MD) simulations, X-ray scattering experiments, and fluorescence spectroscopy. We developed an atomistic model of STX, which was validated against X-ray scattering data and which is suitable for all-atom MD simulations. We demonstrate that STX significantly increases lipid packing and acyl chain order of STX-PG bilayer mixtures. In addition, STX self-assembles into clusters, where the long and rigid conjugated triterpenoid chain interdigitates across both leaflets, modifying locally the density of the surrounding PG molecules. These findings provide a molecular explanation to the reduced headgroup spacing and core dynamics observed in fluorescence experiments and are consistent with the formation of structurally-distinct STX-enriched microdomains. Notably, STX reduces the gel-to-liquid crystalline phase transition temperature, indicating a general stabilizing effect for the fluid phase of PG lipids of varying length. Overall, our findings provide molecular insights into how STX enhances membrane mechanical integrity. It will be highly interesting to establish how the membrane remodeling effects observed here connect with STXs dual roles, acting as an antioxidant and preventing pore formation and other mechanical perturbations induced by antimicrobial molecules.

Small molecule modifiers whence bound, allosterically, will alter the binding of a macromolecule to one- or more-cognate substrates/partners via conformational and non-conformational changes. Although allostery is inferred directly from empirical data, the mathematical basis of these models, constraints deployed and choice of parameter(s) are not clear. Here, we present and characterize a discrete-to-continuous mathematical model for ensemble distributions of a ligand-interacting macromolecular species across milieux-dependent conformational states and examine its role in the genesis and progression of cooperative binding. The premise, of our model, is a set of occupancy matrices (sparse, binary, strictly delocalized) which can be partitioned by a probability-based hyperparameter into mutually exclusive proper subsets of occupancy matrices with identical multinomial probabilities. Since each subset is canonical with a constituent occupancy matrix, it is characterized by a unique multinomial probability. The inner product of combinatorial pairs of all mutually exclusive subsets of occupancy matrices, with an expression for the summed transitional probabilities (finite differences between unique multinomial probabilities), is the differentiable matrix of strictly positive real-valued numbers for the system of ensemble distributions. Whilst the harmonic mean is presented as a generic solution for a system of ensemble distributions, the row-wise definite integral for each column is the finite union of open intervals (contiguous, strictly monotone) which in tandem with a set of interval-specific and bounded transitional probabilities constitutes a piecewise smooth curve (path-connected-, closed- and compact-set). Our discrete-to-continuous model is phenomenological and able to recapitulate the basic tenets of cooperative binding whilst offering insights into the genesis and progression of the same.

Biological membranes contain a diverse set of membrane proteins surrounded by many different lipids, and the lateral organization and function of these molecules are closely intertwined. Here, we use coarse-grained molecular dynamics (MD) simulations to explore how hydrophobic mismatch between the length of transmembrane (TM) proteins and the thickness of the surrounding lipid membrane impacts the spatial distribution of the lipids. We constructed idealized cylindrically symmetric proteins, inspired by the Mattress Model developed in the 1980s, and simulated these model proteins in different lipid compositions. We found that unsaturated lipids were attracted to short TM proteins that thinned the membrane, while fully saturated lipids were attracted to long TM proteins that induced membrane extension. A simple mechanical description of the membrane deformation energy coupled to a lipid mixing model accurately predicted the enrichment/depletion, which was up to 33% in some cases. Our simulations also highlight that lipid sorting behavior is sensitive to protein tilt and protein surface roughness. By teasing out the fundamental physical principles in these simple models, our results provide a foundational understanding of how proteins and lipids form complex and transient assemblies, which we believe will be important for interpreting lipid-protein interactions for a host of membrane proteins that regulate cellular membranes and cell function.

The inhibition of A{beta}42 ({beta}-amyloid) fibril formation is a key therapeutic strategy in Alzheimer's disease research. Paddlewheel diruthenium complexes have shown promising activity against A{beta}42 aggregation and preformed fibril disaggregation, yet their molecular mode of action remains poorly understood. In this work, we perform atomistic simulations to explore how charge modulation influences the interactions of three analogous paddlewheel diruthenium complexes, the parent neutral complex [Ru2Cl(D-p-FPhF)(O2CCH3)3], and its anionic [Ru2Cl2(D-p-FPhF)(O2CCH3)3]- and cationic [Ru2(D-p-FPhF)(O2CCH3)3]+ counterparts (D-p-FPhF- is the N,N' -bis(4-fluorophenyl)formamidinato ligand) with A{beta}42. Our results indicate that electrostatic tuning governs binding affinity and the extent of interaction across the A{beta}42 fibril surface. As the complexes' charge changes from -1 to +1, the interaction pattern shifts from localized contacts to widespread, multi-site engagement encompassing key charged, aromatic, and hydrophobic regions of A{beta}42. This enhanced binding correlates with longer-lived, thermodynamically stable interactions at the fibril interface, which effectively lower the free energy penalty for fibril disassembly. Overall, our findings propose a mechanism in which charge-dependent activation through ligand exchange enhances fibril recognition and promotes disruptive binding modes, demonstrating the potential of charge-tunable diruthenium complexes as therapeutic modulators of A{beta}42 fibril stability.

We present a comparative study of the inner membrane of three Gram-positive bacterial strains, namely S. aureus, S. epidermidis and N. lacusekhoensis. A lipidomics study is used to obtain the lipid architecture and composition for S. epidermidis found in the skin microbiome and N. lacusekhoensis, an extremophile present in halophilic and alkophilic environments. Differences between the strains arise from both the lipid architecture and the cardiolipin content varying from 5% in S. aureus to 85% in N. lacusekhoensis. We develop coarse grained (CG) Martini-3 membrane models which reproduce structural properties such as membrane area, thickness, density distributions as well as ion-correlations with all-atom models. Inter-lipid correlations reveal a homogeneous distribution of lipids in the membranes despite the wide variation in lipid types and composition. Mechanical properties such as the area stretch modulus increased with cardiolipin content, however the bending modulus has a more complex dependence on membrane charge and lipid type. Using the CG models we evaluate the insertion free energies for four widely used antimicrobial molecules. Entry barriers for thymol and methylparaben arise from the charge density modulation at the membrane headgroups due to counterion condensation. The entry mechanisms of the antimicrobial peptide cecropin-melittin-15 (CM15) and the preservative molecule ethyl-lauroyl-arginate (ELAR) are found to be similar across all three strains. We also illustrate the manner in which the extremophilic strain, N. lacusekhoensis with its high cardiolipin content, modulates the partitioning kinetics of the antimicrobial molecule thymol with pH and salt. Our study reveals that membrane properties are largely conserved across the three model membranes. The molecular models and insights emerging from the present work should aid in the development of novel antimicrobials against Gram-positive strains.

Numerous advances in quantum and computational chemistry over the last decades, well as the development of computer science, allowed utilisation of more precise and complex models, which can be now applied to much bigger systems than in the past. The authors used Gaussian, coupled with theoretical methods, to predict a new way of peptide bond formation, which could have taken place in prebiotic conditions. To better tackle this difficult task, the properties of substrates (glycine-derived radicals) were extensively analysed, using the aforementioned tool - Gaussian, paired with taking resonance and hybridisation into account, to better understand the stereochemistry and the very nature of processes taking place. The result is a series of reactions, which without any sophisticated catalysts and with relatively low energy thresholds ({inverted exclamation}20 kcal/mol) can lead to formation of dipeptides (and further, oligopeptides). The authors also hope, the other predicted properties of the investigated molecules can be of use to any researcher, who would like to utilise them in their experiments. Author summaryOur goal was to investigate a way first peptide bonds in prebiotic conditions could have been formed. This is an extremely important step in research into the beginning of life on Earth. We found a very promising series of reactions, which uses atomic hydrogen as its only catalyst and confirmed our expectations with theoretical calculations, using Gaussian. There are two radicals derived from glycine, which perform major roles in the process, so we investigated their properties with Gaussian and verified that the results are in agreement with our own theoretical considerations. This involved checking for possible geometric isomers and conformers and creating models which could explain their properties. We are well aware that such calculations have limitations and there is no model, which is 100% accurate, so our results should be further confirmed by empirical data in the future. However, we still to be as thorough as possible in how we approached the subject.

Lipid droplets (LDs) are cellular organelles responsible for lipid storage and metabolism. The mechanism of biogenesis of LDs involves phase separation of neutral lipids from the surrounding phospholipids, which generates oil lenses embedded in lipid bilayers, also known as nascent LDs. As nascent LDs grow, at some point they bud out of the bilayer, forming nearly spherical droplets. Nascent LDs have different propensity to bud, and it has been proposed that their shape provides information on such propensity; however, LD shape is difficult to determine experimentally. Here we studied the shape of lipid droplets using MD simulations at the coarse-grained level, and compared it to the predictions by an established theory. Our general system setup features an oil lens embedded into a flat, periodic bilayer. We found that the shape of simulated nascent LDs resembles a spherical cap (i.e., it has constant curvature over most of the surface), in excellent agreement with the theory, already for very small droplet sizes. The aspect ratio (height/radius) of nascent LDs increases with increasing LD volume, increasing membrane softness, and increasing surface tension between oil and water, also in agreement with theoretical predictions; however, it remains lower than 1 (i.e., the ratio for a sphere) for LDs of up to 40 nm in diameter. Fitting the simulated LD shapes with a theoretical shape equation suggests that a non-zero surface tension is present in both the monolayer and in the bilayer region. The existence of a relatively high surface tension in the bilayer region is confirmed by local stress calculations, and indicates that the periodic system setup does not reproduce the properties of nascent LDs in the endoplasmic reticulum, where the bilayer tension is two orders of magnitude lower. However, the simulations provide a microscopic view into the properties of droplet embedded vesicles.

DnaK, a prokaryotic Hsp70 chaperone, plays a central role in proteostasis by restoring native structures to heat-denatured proteins in an ATP-hydrolysis-dependent manner. While structures of DnaK in complex with nucleotides, co-chaperones, and short peptides have been resolved, structures with larger, stably folded substrates--such as firefly luciferase (Fluc, 61 kDa)--are lacking, limiting mechanistic understanding of how DnaK refolds such proteins. Here, we generated models of the DnaK-Fluc complex using AlphaFold3 and evaluated their mechanistic relevance. In one of three major model clusters, Fluc is unexpectedly immobilized beneath the DnaK -helical lid against the nucleotide-binding domain (NBD), rather than interacting primarily with the substrate-binding domain {beta} (SBD{beta}), as commonly assumed. All-atom molecular dynamics simulations indicate that, in this configuration, the lid can engage a thermally destabilized Fluc helix (residues 405-411), which we recently identified as the first--and likely the only--helix to irreversibly melt at 42 {degrees}C. Upon binding, the lid forms extensive hydrogen-bonding interactions with the melted helix. These interactions persist during lid movement toward SBD{beta} (following ATP hydrolysis), enabling the lid to actively extract the helix from the Fluc surface. In contrast, simulations with the helix in its native folded state show that the lid cannot extract it, leaving the native structure unaffected. Equilibrium simulations further indicate that, once extracted and mechanically stretched, the melted helix can refold to its native conformation. Together, these findings suggest a revised mechanism for DnaK-mediated protein refolding, in which the -helical lid selectively recognizes structurally compromised segments, forms stabilizing hydrogen bonds, and--powered by ATP hydrolysis--mechanically pulls them away from the protein surface to facilitate their refolding. SIGNIFICANCEDnaK is a model chaperone, which can reactivate thermally denatured proteins. Over the span of 40 years, significant findings have been made about DnaKs structure, dynamics and interactions with its co-chaperones, the exact molecular mechanism by which DnaK refolds misfolded proteins remains a mystery. This work exploited Alphafold3 to generate atomistic models of complexes between DnaK and Firefly luciferase. Molecular dynamics simulations directly captured how DnaK may assist thermally denatured proteins by mechanically pulling out their misfolded helices. This study provides a new insight into the DnaK mechanism.

The growing number of approved nucleic acid therapeutics illustrates the potential to treat diseases by targeting their genetic blueprints in vivo. The 10-23 DNAzyme is capable of cleaving a wide range of target RNA with high selectivity. However, its poor performance in vivo restricts its therapeutic application as gene silencing agent. Studies on ribozymes have shown that the crowded environment in cells and associated effects can impact ribozyme folding and thermostability, resulting in a change in activity. This opens up the question whether DNAzymes are also affected by molecular crowding. Here, we investigate the functional and structural influence of molecular crowding conditions on the 10-23 DNAzyme. The stability and activity of a PrP-specific 10-23 DNAzyme were examined in presence of PEG, dextran, and osmolytes. Our results indicate that osmolytes decrease DNAzyme activity in a concentration-dependent manner, while certain PEG and dextran concentrations promote activity. To rationalize our observations, we studied the cosolutes effect on physicochemical solution properties and the structure of the DNAzyme:RNA complex using FCS and SAXS. The data reveal that enhanced activity is observed under conditions where a combination of physiochemical properties matches an optimum that seems to be dependent on the metal ion cofactor. Structural influence under such conditions is indicated less. We propose that a certain degree of molecular crowding is required to favor a state, which allows for higher catalytic turnover. In addition, we show that the requirement for magnesium and manganese as a cofactor remains unchanged under the conditions applied. Our work contributes to a better understanding of how the cellular environment affects DNAzyme structure and function.

A priori assessment of target proteins' druggability remains an unsolved problem in the field of drug development. The empirical approaches widely used to solve this problem demonstrate low efficiency. In this work, we investigated the factor of hydration of a representative set of 65 evolutionarily and structurally unrelated human enzymes in a water environment. This factor depends only on the structure of the proteins, and not on the physical and chemical properties of any potential ligands. The results show that, unlike the widely used approaches based on calculations of the accessible surface area (ASA), the content of low-entropy water molecules (LEW) in the active sites of human enzymes is systematically higher than that in other areas of their surface, including inactive cavities. Optimal criteria and a step-by-step procedure for identifying protein ligand binding sites are proposed. The proposed approach, based on the calculation of the LEW content in the first hydration layer of potentially interesting target proteins, makes it possible to evaluate their medicinal suitability even before the development of any ligands. The article also presents the results of a comparative analysis of experimental Raman spectroscopy data and the results of molecular dynamics simulations of water hydrogen bonds using three widely used water models (TIP3P, OPC3, and TIP5P) and standard algorithms for calculating hydrogen bond networks.

Weak magnetic fields affect many biological processes across the tree of life, though the precise molecular sensors and pathways involved in such magnetoresponses remain mostly uncharacterized. Fluorescence is a useful tool for investigating magnetic field effects in flavoproteins, as their chromophores fluorescence intensity can be shown to depend on the spin states of electronic radical pairs. Here, we describe a four-state ordinary differential equation model to understand what parameter sets result in fluorescence contrast between spin states in photocycles with singlet and triplet radical pairs. We conclude that only certain sets of parameters result in the fluorescence intensity being a good proxy measurement for singlet yield. In particular, we observe that the illumination intensity required to obtain fluorescence contrast depends on the rate of the slow spin-independent radical termination reactions that recover ground-state oxidized fluorophores. Moreover, to observe a magnetic field effect in fluorescence intensity when an external magnetic field modulates the singlet yield, the illumination intensity must be strong enough such that photoexcitation is not the rate-limiting step. This understanding suggests that flavoproteins that do not exhibit magnetic field effects in their fluorescence emission under certain experimental setups may still be sensitive to weak magnetic fields in terms of function, as magnetosensitivity in fluorescence depends strongly on illumination conditions.

Protein folding is the process by which a polypeptide chain organizes into its three-dimensional structure through a balance of stabilizing and destabilizing interactions encoded by the sequence. A central question in protein biophysics is how thermodynamic factors guide a polypeptide toward its native folded state despite the rugged energy landscape and the competing influence of nonnative interactions. In many biomolecular processes, cooperativity provides a mechanism by which multiple weak interactions act collectively to generate a robust response. In the context of protein folding, such cooperative effects may arise when the formation of one native contact enhances the stability or likelihood of nearby native contacts, thereby promoting collective organization toward the folded state. At the same time, folding is opposed by the much larger number of non-native interactions, whose heterogeneity can introduce frustration and destabilize folding even when the average native bias favors the folded phase. The interplay of these competing effects in determining foldability remains unclear in statistical-mechanical models. Here, we address this problem using a one-dimensional spin-glass model of protein folding with explicit shared-residue cooperative interactions encoded through wedge-based motifs. We show that modest cooperative bias can stabilize folding even where the noncooperative system remains unfolded, whereas non-native energetic fluctuation suppresses folding and shifts the transition to higher cooperative strengths. We further find that partial cooperative coverage is sufficient to lower the folding threshold. Therefore, the model provides a mean-field framework for incorporating cooperative interaction strength into the native one-dimensional model of protein folding and for describing how local cooperativity reshapes the folding transition.

The ability to tune protein function through the binding of modulatory ligands enables the development of therapeutics that steer a biological system away from dysfunctional states underlying disease. Understanding the dynamic mechanisms by which allosteric ligands alter protein function remains an important open question. Dynamical network models allow us to quantify information flow between protein functional sites. However, existing network models use time-symmetric metrics for computing information from correlated residue motions extracted from molecular dynamics (MD) simulations, failing to fully capture directional information flow between sites. Here, we developed a Python library, TEntroPy, and analysis workflow using transfer entropy to generate a directional protein network from equilibrium MD trajectories. Applying this workflow to proteins with known allosteric ligands, we identified residues in both allosteric and orthosteric (primary) binding sites acting as broadcasters and receivers of information. We then computed optimal paths of directional information flow between binding sites. The presence of temporal asymmetry in residue coupling identified from simulations of the unbound (apo) state suggests that directional information flow is encoded in the intrinsic dynamics of the protein. To test this, we perturbed key binding-site residues and demonstrated that our TE-weighted network captures perturbation-induced changes in dynamics along communication routes between binding sites. Identifying residue pairs with high temporal asymmetry provides an additional tool for understanding the dynamic mechanisms of allosteric communication.

The chirality of proteins originates at the C stereocentre of each L-amino acid, and is expressed in secondary structure as the consistent twist of -helices and {beta}-sheets. How far does this handedness propagate as secondary-structure elements pack into a tertiary fold? This question is central to the development of neural networks for the design of heterochiral and mixed-chirality proteins containing mirror-image D-amino acids. Such networks are most effectively trained on the far more abundant structural data available for natural all-L proteins, yet in practice they must generate and evaluate the reflected, D-configured counterparts, which are not explicitly represented in the training set. Here, I develop a spatial tessellation-based parity-odd descriptor, the signed volume of Delaunay tetrahedra (VD), to measure how chirality is distributed in protein structure. Reflecting a structure only flips the sign of any parity-odd descriptor, so the asymmetry of the VD distribution quantifies the chirality of a given sequence-local or tertiary structural element. I find that the signed Delaunay volume distribution within individual secondary-structure elements is strongly asymmetric, but this handedness largely cancels once elements pack against one another. The resulting tertiary distribution is nearly symmetric across a broad range of structures, from monomers to protein-protein and protein-ligand complexes. Individual folds can nonetheless be strongly handed at the tertiary scale, solenoid and repeat proteins most of all, yet across a broad sample of the fold universe this handedness cancels, leaving the ensemble near-achiral. Tertiary packing is therefore only weakly chiral, with the small residual handedness greatest at binding interfaces and near-zero in the buried core. How much chirality a model perceives in a D-protein is thus largely a choice of representation, a trade-off between reflection symmetry and the richness of structural information the representation retains. Because VDreduces the parity-odd content of each structural element to a single scalar while capturing tertiary protein packing, it offers a natural representation for the design of heterochiral complexes and mixed-chirality proteins. Significance StatementThe macromolecules of life are handed, and this mirror-asymmetry is built into every protein at the scale of its amino-acid monomers. Local segments of proteins are also strongly handed. Alpha helices and beta sheets are consistently right-handed. Does this handedness build up through the layers of a proteins structure, as in some synthetic polymers, or cancel? Using a geometric test across thousands of structures, we find that it largely cancels: the 3D-packing of a folded protein, when described as a tetrahedral tessellation, is almost symmetric under reflection, though its building blocks are not. This means that the design of mirror-image D-protein binders, which are attractive as protease-resistant, low-immunogenicity drug candidates, could rely on AI models trained only on natural L-proteins, using representations developed here.

Human aquaporins (AQPs) are essential membrane channels, yet their inherent hydrophobicity complicates structural and functional studies. We present the systematic application of the QTY code to human AQPs, integrating it with AlphaFold 3 structure prediction to design and validate that four-representative human AQPs (AQP1, AQP3, AQP4, AQP7) can be converted into water-soluble analogs while maintaining their conformation. This approach features a novel platform for editing challenging membrane proteins. The QTY code was applied to the transmembrane regions of the selected four AQPs. Subsequently, the water-soluble QTY analogs of the four AQPs were predicted using AlphaFold 3. The predicted structures were superposed with CyroEM- or X-ray-determined native structures in PyMOL. Further analyses included root-mean-square deviation (RMSD) calculations, visualization of hydrophobic surface reduction, and inspection of conserved protein-ligand binding ability. After applying the QTY code, sequence changes between native AQPs and their QTY analogs was significant (42.86-48.80%). Nevertheless, their structures superposed well in analyses, with only slight deviations (RMSD < 0.6 [A]). In addition, the surface hydrophobicity of all QTY-edited AQPs was significantly reduced. Importantly, molecular contacts between the cholesterol ligand and protein were largely preserved for both native AQP1 and its QTY analog. Finally, all AlphaFold3-predicted structures for AQPs have high confidence values (pLDDT > 90; pTM ~0.83), supporting the reliability of the predicted structures. The findings demonstrate that membrane protein hydrophobicity can be edited and reduced without compromising fold integrity or functional architecture. Integration of the QTY code with AlphaFold 3 affords a high-throughput platform for designing water-soluble, structurally faithful analogs of challenging membrane proteins. Such a strategy can provide a potent platform for detergent-free biochemical studies and water-soluble analogs for therapeutic monoclonal antibody discoveries, thus advancing research of this pharmacologically important protein family.

Protein kinase activation is driven by conformational changes across multiple structural components, including the conserved Asp-Phe-Gly (DFG) motif, but whether these transitions follow a universal mechanism remains unclear. Here we combine over 8.3 milliseconds of distributed unbiased molecular dynamics simulations with Markov state models (MSMs) to compare the conformational landscapes of the ABL1, EGFR and MET kinase domains. To maximize unbiased sampling of functionally relevant conformational space, we use a transfer seeding strategy that steers AlphaFold2 models derived from homologous templates to sample MET conformational states absent from available experimental databases. We find that related DFG-motif geometries separate into distinct kinetic networks. These shared structural states are connected by kinase-specific activation pathways with different regulatory elements controlling the slowest step of activation. Our findings reveal that the shared nomenclature masks distinct transition mechanisms between kinase domains, revealing new regions critical for activity and targetable conformations for inhibitor design.

Auxetic metamaterials exhibit negative Poisson's ratio behaviors due to their architecture of periodically arranged unit cells. Although mechanical metamaterials are well established at the macroscale, programmable auxetic units remain scarce at the nanoscale. DNA origami offers a promising platform to bridge this gap, but design principles for dynamically deformable 3D auxetic nanostructures remain largely unexplored. Here, we develop design strategies for such 3D auxetic metastructures built from wireframe DNA origami. As a model system, we use a 3D re-entrant triangular unit composed of double-stranded DNA (dsDNA) bundle edges connected by single-stranded DNA (ssDNA) joints. Using coarse-grained molecular dynamics (MD) and umbrella-sampling free-energy simulations, we examine how edge design and joint-connection scheme govern auxetic responses and the energetics of the structural transformation. Our results show that auxetic performance and deformation energetics emerge from the coupled effects of DNA bundle rigidity and connector mechanics at the joints. This study provides mechanistic insights and design guidelines for programmable auxetic motion and energetics in 3D DNA origami metamaterials, advancing the development of stimuli-responsive nanomechanical devices.