Membrane fusion is a fundamental process involved in exocytosis, fertilization, or cell entry by enveloped viruses. Membrane fusion is facilitated by fusion proteins, which are anchored in membranes by helical transmembrane domains (TMDs). Previous studies showed that TMD variations may alter the fusion efficiency, suggesting that TMDs are not merely passive anchors, however the mechanism by which TMDs drive fusion is not well understood. We used high-throughput coarse-grained molecular dynamics simulations and free energy calculations to quantify effects of TMDs on the formation of the first fusion intermediate, that is, of a fusion stalk. We analyzed five physiologically relevant TMDs derived from viral fusion proteins and the SNARE complex embedded in various lipid environments. We find that the addition of TMDs favors stalk formation by typically 10 to 30 kJ/mol in a concentration-dependent manner. Using helices with sequences R2LnR2 (n=6,...,26), we find that negative hydrophobic mismatch between the TMD and the membrane core strongly promotes fusion. Analysis of the lipid tail order parameters of annular lipids revealed a strong correlation between stalk stabilization and induced lipid disorder. Together, our findings suggest that TMDs actively contribute to membrane fusogenicity by locally perturbing the membrane order.

Small-angle scattering (SAS) is widely used in structural biology, soft matter, and colloidal science to probe molecular structures in solution. SAS rests on a single physical principle: wave interference from a distribution of scatterers, averaged over orientations. Yet the theoretical foundations of SAS are spread across the literature, often based on differing notation, definitions, and implicit assumptions. We present the theory of SAS in solution from first principles as a continuous derivation, spanning the scattering of a single electron to the observed intensity of a molecular solution and its comparison with atomistic structural models. The derivation is explicit throughout – approximations, averaging procedures, and algebraic manipulations are stated rather than assumed – and is independent of the probe (X-ray or neutron) and applicable to both rigid and flexible molecules. The framework resolves several ambiguities in the current literature, notably the role of background subtraction as a theoretical rather than a purely experimental operation and the role of boundary cross-terms in justifying that subtraction. A central result is that analytical scattering calculations and approaches based on explicit-solvent molecular dynamics, typically treated as distinct traditions, are realizations of the common theoretical framework derived here. As the precision and reproducibility of SAS data continue to increase, this unified framework provides a basis for integrating theory, simulation, and experiment in future developments of SAS.

Photoreceptor proteins regulate fundamental biological processes such as vision, photosynthesis and circadian rhythms1. A large photoreceptor subfamily uses vitamin B12 derivatives for light sensing2, contrasting with the well-established mode of action of these organometallic derivatives in thermally activated enzymatic reactions3. The exact molecular mechanism of B12 photoreception and how this differs from the thermal pathways remains unknown. Here we provide a detailed description of photoactivation in the prototypical B12 photoreceptor CarH4,5 from nanoseconds to seconds, combining time-resolved and temperature-resolved structural and spectroscopic methods with quantum chemical calculations. Building on the crystal structures of the initial tetrameric dark and final monomeric light-activated states5, our structural snapshots of key intermediates in the truncated B12-binding domain illustrate how photocleavage of a cobalt-carbon (Co-C) bond within the B12 chromophore adenosylcobalamin triggers a series of structural changes that propagate throughout CarH. Breakage of the photolabile Co-C5 ' bond leads to the formation of a previously unknown adduct that links the C4 ' position of the adenosyl moiety to the Co ion and can subsequently be cleaved thermally over longer timescales to allow release of the adenosyl group, ultimately causing tetramer dissociation4,5. This adduct, which differentiates CarH from thermally activated B12 enzymes, steers the photoactivation pathway and acts as the molecular bridge between photochemical and photobiological timescales. The biological relevance of our study is corroborated by kinetic data on full-length CarH in the presence of DNA. Our results offer a spatiotemporal understanding of CarH photoactivation and pave the way for designing B12-dependent photoreceptors for optogenetic applications.

Predicting protein-ligand binding affinity with high accuracy is critical in structure-based drug discovery. While docking methods offer computational efficiency, they often lack the precision required for reliable affinity ranking. In contrast, molecular dynamics (MD)-based approaches such as MMGBSA provide more accurate binding free energy estimates but are computationally intensive, limiting their scalability. To address this trade-off, we introduce an active learning framework that automates molecule selection for docking and MD simulations, replacing manual expert-driven decisions with a data-efficient, model-guided strategy. Our approach integrates fixed, partly pre-trained deep learning molecular embeddings (MolFormer, ChemBERTa-2, and Morgan fingerprints) with adaptive regression models (e.g. Bayesian Ridge and Random Forest) to iteratively improve binding affinity predictions. We evaluate this approach retrospectively on a new dataset of 59 356 chemically diverse compounds from ZINC-22 targeting the MCL1 protein using both AutoDock Vina and MMGBSA binding free energy scores. Validation against a subset of experimentally measured binding affinities demonstrates that MMGBSA scores exhibit a stronger ranking correlation than the docking scores. Our results show that incorporating MMGBSA scores into the active learning loop enables highly efficient compound selection, recovering 79.9% of the top 1% MMGBSA-ranked binders while screening only a fraction of the dataset. In contrast, docking-guided selection identifies a largely distinct set of compounds, recovering only 6.7% of these top MMGBSA-ranked binders, underscoring the critical impact of scoring function choice. Furthermore, we demonstrate that a one-at-a-time acquisition active learning strategy consistently outperforms traditional batched acquisition, with the latter achieving just 78.4% recovery with MolFormer and Bayesian Ridge. These findings underscore the potential of integrating deep learning-based molecular representations with MD-level accuracy in an active learning framework, offering a scalable and efficient path to accelerate virtual screening and improve hit identification in drug discovery.

We present BindFlow, a Python-based software for automated absolute binding free energy (ABFE) calculations at the free energy perturbation (FEP) or at the molecular mechanics Poisson-Boltzmann/generalized Born surface area [MM(PB/GB)SA] level of theory. BindFlow is free, open-source, user-friendly, and easily customizable, runs on workstations or distributed computing platforms, and provides extensive documentation and tutorials. BindFlow uses GROMACS as a molecular dynamics engine and provides built-in support for the small-molecule force fields GAFF, OpenFF, and Espaloma, as well as support for user-provided custom force fields. We test BindFlow by computing affinities for 139 receptor-ligand pairs, involving eight different targets, including six soluble proteins, one membrane protein, and one nonprotein host-guest system. We find that the agreement of BindFlow predictions with experiments is overall similar to gold standards in the field. Interestingly, we find that MM(PB/GB)SA achieves correlations that, for some systems and force fields, approach those obtained with FEP while requiring only a fraction of the computational cost. This study establishes BindFlow as a validated and accessible tool for ABFE calculations.

Biological membranes display remarkable compositional diversity with functional consequences. In viral infections, lipids play active roles beyond forming a structural barrier: they modulate fusion protein binding, and tune membrane mechanics to prime them for efficient fusion, while viruses hijack host lipid metabolism to support replication. This highlights how membrane remodeling is exploited throughout the viral life cycle and points to potential avenues for antiviral intervention.

The primary function of biological membranes is to enable compartmentalization among cells and organelles. Loss of integrity by the formation of membrane pores would trigger uncontrolled depolarization or influx of toxic compounds, posing a fatal threat to living cells. How the lipid complexity of biological membranes enables mechanical stability against pore formation while, simultaneously, allowing for ongoing membrane remodeling is largely enigmatic. We performed molecular dynamics simulations of eight complex lipid membranes including the plasma membrane and membranes of the organelles endoplasmic reticulum, Golgi, lysosome, and mitochondrion. To quantify the mechanical stability of these membranes, we computed the free energy of transmembrane pore nucleation as well as the line tension of the rim of open pores. Our simulations reveal that complex biological membranes are remarkably stable, however, with the plasma membrane standing out as exceptionally stable, which aligns with its crucial role as a protective layer. We observe that sterol content is a key regulator for biomembrane stability, and that lateral sorting among lipid mixtures influences the energetics of membrane pores. A comparison of 25 model membranes with varying sterol content, tail length, tail saturation, and head group type shows that the pore nucleation free energy is mostly associated with the lipid tilt modulus, whereas the line tension along the pore rim is determined by the lipid intrinsic curvature. Together, our study provides an atomistic and energetic view on the role of lipid complexity in biomembrane stability.

The protein hydration shell is a key mediator of processes such as molecular recognition, protein folding, and proton transfer. How solvent-exposed amino acids shape the hydration shell structure is not well understood. We combine molecular dynamics simulations with explicit-solvent predictions of small-angle x-ray scattering (SAXS) curves to quantify the contributions of all 20 proteinogenic amino acids to the hydration shell of the globular GB3 domain and the intrinsically disordered protein (IDP) XAO. We focus on two quantities encoded by SAXS curves: the hydration shell effect on the radius of gyration and the electron density contrast between protein and solvent. We derive an amino acid-specific contrast score, revealing that acidic residues generate the strongest contrast with 1-1.5 excess water molecules relative to alanine, followed by cationic and polar residues. In contrast, apolar residues generate a water depletion layer. These trends are consistent across simulations with different water models. Around the XAO peptide, the hydration shell is generally far weaker compared with the globular GB3 domain, indicating unfavorable water-peptide packing at the IDP surface. The hydration shell effect on the radius of gyration of the IDP is strongly conformation-dependent. Together, the calculations show that the composition and spatial arrangement of solvent-exposed amino acids govern the hydration shell structure, with implications for a wide range of biological functions and for hydration-sensitive experimental techniques such as solution scattering.

Monkeypox virus (MPXV) is a poxvirus endemic to Central and West Africa with high epidemic potential. Poxviruses enter host cells via a conserved entry-fusion complex (EFC), which mediates viral fusion to the cell membrane. The EFC is a promising therapeutic target, but the absence of structural data has limited the development of fusion-inhibiting treatments. Here, we investigated A16/G9, a subcomplex of the EFC that controls fusion timing. Using cryo-electron microscopy, we showed how A16/G9 interacts with A56/K2, a viral fusion suppressor that prevents superinfection. Immunization with A16/G9 elicited a protective immune response in mice. Using X-ray crystallography, we characterized two neutralizing antibodies and engineered a chimeric antibody that cross-neutralizes several poxviruses more efficiently than 7D11, the most potent antibody targeting the EFC described to date. These findings highlight the potential of A16/G9 as a candidate for subunit vaccines and identify regions of the EFC as targets for antiviral development.

Mpox is a zoonotic disease endemic to Central and West Africa. Since 2022, two human-adapted monkeypox virus (MPXV) strains have caused large outbreaks outside these regions. Tecovirimat is the most widely used drug to treat mpox. It blocks viral egress by targeting the viral phospholipase F13; however, the structural details are unknown, and mutations in the F13 gene can result in resistance against tecovirimat, raising public health concerns. Here we report the structure of an F13 homodimer using X-ray crystallography, both alone (2.1 & Aring;) and in complex with tecovirimat (2.6 & Aring;). Combined with molecular dynamics simulations and dimerization assays, we show that tecovirimat acts as a molecular glue that promotes dimerization of the phospholipase. Tecovirimat resistance mutations identified in clinical MPXV isolates map to the F13 dimer interface and prevent drug-induced dimerization in solution and in cells. These findings explain how tecovirimat works, allow for better monitoring of resistant MPXV strains and pave the way for developing more potent and resilient therapeutics.

Viral infection requires stable binding of viral fusion proteins to host membranes, which contain hundreds of lipid species. The mechanisms by which fusion proteins utilize specific host lipids to drive virus–host membrane fusion remains elusive. We conducted molecular simulations of classes I, II, and III fusion proteins interacting with membranes of diverse lipid compositions. Free energy calculations reveal that class I fusion proteins generally exhibit stronger membrane binding compared to classes II and III — a trend consistent across 74 fusion proteins from 13 viral families as suggested by sequence analysis. Class II fusion proteins utilize a lipid binding pocket formed by fusion protein monomers, stabilizing the initial binding of monomers to the host membrane prior to assembling into fusogenic trimers. In contrast, class III fusion proteins form a lipid binding pocket at the monomer–monomer interface through a unique fusion loop crossover. The distinct lipid binding modes correlate with the differing maturation pathways of classes II and III proteins. Binding affinity was predominantly controlled by cholesterol and gangliosides as well as via local enrichment of polyunsaturated lipids, thereby locally enhancing membrane disorder. Our study reveals energetics and atomic details underlying lipid recognition and reorganization by different viral fusion protein classes, offering insights into their specialized membrane fusion pathways.

Microtubules are cytoskeletal filaments characterized by dynamic instability at their tips and a dynamic lattice that undergoes continuous tubulin loss and incorporation. Tau, a neuronal microtubule-associated protein, is well known for its role in stabilizing microtubule tips and promoting microtubule bundling. Here we demonstrate that tau also modulates microtubule lattice dynamics. Although tau lacks enzymatic activity, it significantly accelerates tubulin exchange within the lattice, particularly at topological defect sites. Our findings indicate that tau enhances lattice anisotropy by stabilizing longitudinal tubulin-tubulin interactions while destabilizing lateral ones, thereby enhancing the mobility and annihilation of lattice defects. These results challenge the traditional view of tau as merely a passive stabilizer, revealing its active role in dynamically remodelling the microtubule lattice structure.

The hydration shell is an integral part of proteins since it plays key roles in conformational transitions, molecular recognition, and enzymatic activity. While the dynamics of the hydration shell have been described by spectroscopic techniques, the structure of the hydration shell remains less understood due to the lack of hydration shell-sensitive structural probes with high spatial resolution. We combined temperature-ramp small-angle X-ray scattering (T-ramp SAXS) from 255 to 335 K with molecular simulations to demonstrate that the hydration shells of the IgG-binding domain of Protein G (GB3) and the villin headpiece are remarkably temperature-sensitive. For proteins in the folded state, T-ramp SAXS data and explicit-solvent SAXS predictions consistently demonstrate decays of protein contrasts and radii of gyration with increasing temperature, which are shown to reflect predominantly temperature-sensitive, depleting hydration shells. The depletion is caused not merely by enhanced disorder within the hydration shells but also by partial displacements of surface-coordinated water molecules. Together, T-ramp SAXS and explicit-solvent SAXS calculations provide a novel structural view of the protein hydration shell, which underlies temperature-dependent processes such as cold denaturation, thermophoresis, or biomolecular phase separation.

We present Moldrug, a computational tool for accelerating the hit-to-lead phase in structure-based drug design. Moldrug explores the chemical space using structural modifications suggested by the CReM library and by optimizing an adaptable fitness function with a genetic algorithm. Moldrug is complemented by Moldrug-Dashboard, a cross-platform and user-friendly graphical interface tailored for the analysis of Moldrug simulations. To illustrate Moldrug, we designed new potential inhibitors targeting the main protease (MPro) of SARS-CoV-2 by optimizing a consensus fitness function that balances binding affinity, drug-likeness, and synthetic accessibility. The designed molecules exhibited high chemical diversity. A subset of the designed molecules were ranked using MM/GBSA and alchemical binding free energy calculations, revealing predicted affinities as low as −10 kcal mol−1. Moldrug is distributed as a Python package under the Apache 2.0 license. It offers pre-configured multi-parameter fitness functions for molecular design, while being highly adaptable for integrating functionalities from external software. Documentation and tutorials are available at https://moldrug.rtfd.io.

The protein hydration shell is a key mediator of processes such as molecular recognition, protein folding, and proton transfer. How surface-exposed amino acids shape the hydration shell structure is not well understood. We combine molecular dynamics simulations with explicit-solvent predictions of small-angle X-ray scattering (SAXS) curves to quantify the contributions of all 20 proteinogenic amino acids to the hydration shell of the globular GB3 domain and the intrinsically disordered protein (IDP) XAO. We focus on two quantities encoded by SAXS curves: the hydration shell effect on the radius of gyration and the electron density contrast between protein and solvent. We derive an amino-acid-specific contrast score, revealing that acidic residues generate the strongest contrast with 1 to 1.5 excess water molecules relative to alanine, followed by cationic and polar residues. In contrast, apolar residues generate a water depletion layer. These trends are consistent across simulations with different water models. Around the XAO peptide, the hydration shell is generally far weaker compared to the globular GB3 domain, indicating unfavorable water–peptide packing at the IDP surface. The hydration shell effect on the radius of gyration of the IDP is strongly conformation-dependent. Together, the calculations show that the composition and spatial arrangement of surface-exposed amino acids govern the hydration shell structure, with implications for a wide range of biological functions and for hydration-sensitive experimental techniques such as solution scattering. Significance Hydration shells of biomolecules constitute a large fraction of the water in crowded cellular environments and play key roles in biological functions such as enzymatic reactions and conformational transitions. Small-angle X-ray scattering (SAXS) has shown that hydration shells differ in density from bulk water, yet how surface-exposed amino acids and protein surface geometry shape the hydration shell is not well understood. We combined molecular dynamics simulations with explicit-solvent SAXS predictions to quantify how surface-exposed chemical moieties and protein geometry drive variations in hydration shell density. Notably, the hydration shell of a globular protein differs markedly from that of an intrinsically disordered protein. Our study offers a comprehensive characterization of protein hydration and informs the interpretation of hydration-sensitive experimental techniques. ### Competing Interest Statement The authors have declared no competing interest. Deutsche Forschungsgemeinschaft, https://ror.org/018mejw64, HU 1971/3-2, INST 256/539-1

SHP2 is a tyrosine phosphatase that plays a regulatory role in multiple intracellular signaling cascades and is known to be oncogenic in certain contexts. In the absence of effectors, SHP2 adopts an autoinhibited conformation with its N-SH2 domain blocking the active site. Given the key role of N-SH2 in regulating SHP2, this domain has been extensively studied, often by X-ray crystallography. Using a combination of structural analyses and molecular dynamics (MD) simulations we show that the crystallographic environment can significantly influence the structure of the isolated N-SH2 domain, resulting in misleading interpretations. As an orthogonal method to X-ray crystallography, we use a combination of NMR spectroscopy and MD simulations to accurately determine the conformation of apo N-SH2 in solution. In contrast to earlier reports based on crystallographic data, our results indicate that apo N-SH2 in solution primarily adopts a conformation with a fully zipped central 0-sheet, and that partial unzipping of this 0-sheet is promoted by binding of either phosphopeptides or even phosphate/sulfate ions.

Mpox is a zoonotic disease endemic in central and west Africa. However, since 2022, human-adapted mpox virus (MPXV) strains are causing large outbreaks spreading outside these regions, leading the World Health Organization to declare public health emergency twice. Tecovirimat, the most widely used drug to treat these infections, blocks viral egress through a poorly understood mechanism. Tecovirimat-resistant strains, all with mutations in the viral phospholipase F13, pose public health concerns. Herein, we report the structure of an F13 homodimer, both alone and in complex with tecovirimat. We demonstrate that tecovirimat acts as a molecular glue, inducing the dimerization of the phospholipase. F13 escape mutations in MPXV clinical isolates are at the dimer interface and prevent drug-induced dimerization in solution and cells. These findings, which decipher tecovirimat's mode of action, will allow better monitoring of poxvirus outbreaks and pave the way for developing more potent and resilient therapeutics.