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Background Carbohydrates are a class of large and diverse biomolecules, ranging from a simple monosaccharide to large multi-branching glycan structures. The covalent linkage of a carbohydrate to the nitrogen atom of an asparagine, a process referred to as N- linked glycosylation, plays an important role in the physiology of many living organisms. Most software for glycan modeling on a personal desktop computer requires knowledge of molecular dynamics to interface with specialized programs such as CHARMM or AMBER. There are a number of popular web-based tools that are available for modeling glycans (e.g., GLYCAM-WEB (http:// https://dev.glycam.org/gp/ ) or Glycosciences.db ( http://www.glycosciences.de/ )). However, these web-based tools are generally limited to a few canonical glycan conformations and do not allow the user to incorporate glycan modeling into their protein structure modeling workflow. Results Here, we present Glycosylator, a Python framework for the identification, modeling and modification of glycans in protein structure that can be used directly in a Python script through its application programming interface (API) or through its graphical user interface (GUI). The GUI provides a straightforward two-dimensional (2D) rendering of a glycoprotein that allows for a quick visual inspection of the glycosylation state of all the sequons on a protein structure. Modeled glycans can be further refined by a genetic algorithm for removing clashes and sampling alternative conformations. Glycosylator can also identify specific three-dimensional (3D) glycans on a protein structure using a library of predefined templates. Conclusions Glycosylator was used to generate models of glycosylated protein without steric clashes. Since the molecular topology is based on the CHARMM force field, new complex sugar moieties can be generated without modifying the internals of the code. Glycosylator provides more functionality for analyzing and modeling glycans than any other available software or webserver at present. Glycosylator will be a valuable tool for the glycoinformatics and biomolecular modeling communities.

Bacteria rely on two-component systems to sense environmental cues and regulate gene expression for adaptation. The PhoQ/PhoP system exemplifies this crucial role, playing a key part in sensing magnesium (Mg 2+ ) levels, antimicrobial peptides, mild acidic pH, osmotic upshift, and long-chain unsaturated fatty acids, promoting virulence in certain bacterial species. However, the precise details of PhoQ activation remain elusive. To elucidate PhoQ's signaling mechanism at atomic resolution, we combined AlphaFold2 predictions with molecular modeling and carried out extensive Molecular Dynamics (MD) simulations. Our MD simulations revealed three distinct PhoQ conformations that were validated by experimental data. Notably, one conformation was characterized by Mg 2+ bridging the acidic patch in the sensor domain to the membrane, potentially representing a repressed state. Furthermore, the high hydration observed in a putative intermediate state lends support to the hypothesis of water-mediated conformational changes during PhoQ signaling. Our findings not only revealed specific conformations within the PhoQ signaling pathway, but also hold significant promise for understanding the broader histidine kinase family due to their shared structural features. Our approach paves the way for a more comprehensive understanding of histidine kinase signaling mechanisms across various bacterial species and opens the door for developing novel therapeutics that target PhoQ modulation.

In recent years computational methods for molecular modeling have become a prime focus of computational biology and cheminformatics. Many dedicated systems exist for modeling specific classes of molecules such as proteins or small drug-like ligands. These are often heavily tailored toward the automated generation of molecular structures based on some meta-input by the user and are not intended for expert-driven structure assembly. Dedicated manual or semi-automated assembly software tools exist for a variety of molecule classes but are limited in the scope of structures they can produce. In this work we present BuildAMol, a highly flexible and extendable, general-purpose fragment-based molecular assembly toolkit. Written in Python and featuring a well-documented, user-friendly API, BuildAMol empowers researchers with a framework for detailed manual or semi-automated construction of diverse molecular models. Unlike specialized software, BuildAMol caters to a broad range of applications. We demonstrate its versatility across various use cases, encompassing generating metal complexes or the modeling of dendrimers or integrated into a drug discovery pipeline. By providing a robust foundation for expert-driven model building, BuildAMol holds promise as a valuable tool for the continuous integration and advancement of powerful deep learning techniques. Scientific contribution BuildAMol introduces a cutting-edge framework for molecular modeling that seamlessly blends versatility with user-friendly accessibility. This innovative toolkit integrates modeling, modification, optimization, and visualization functions within a unified API, and facilitates collaboration with other cheminformatics libraries. BuildAMol, with its shallow learning curve, serves as a versatile tool for various molecular applications while also laying the groundwork for the development of specialized software tools, contributing to the progress of molecular research and innovation.

The green-light absorbing proteorhodopsin (GPR) is the archetype of bacterial light-driven proton pumps. Here, we present the 2.9 Å cryo-EM structure of pentameric GPR, resolving important residues of the proton translocation pathway and the oligomerization interface. Superposition with the structure of a close GPR homolog and molecular dynamics simulations reveal conformational variations, which regulate the solvent access to the intra- and extracellular half channels harbouring the primary proton donor E109 and the proposed proton release group E143. We provide a mechanism for the structural rearrangements allowing hydration of the intracellular half channel, which are triggered by changing the protonation state of E109. Functional characterization of selected mutants demonstrates the importance of the molecular organization around E109 and E143 for GPR activity. Furthermore, we present evidence that helices involved in the stabilization of the protomer interfaces serve as scaffolds for facilitating the motion of the other helices. Combined with the more constrained dynamics of the pentamer compared to the monomer, these observations illustrate the previously demonstrated functional significance of GPR oligomerization. Overall, this work provides molecular insights into the structure, dynamics and function of the proteorhodopsin family that will benefit the large scientific community employing GPR as a model protein. The cryo-EM structure of pentameric green-light absorbing proteorhodopsin together with molecular dynamics simulations and functional studies provides insights into the proton translocation pathway and oligomerization, and a protonation-dependent mechanism for intracellular half channel hydration.

Glucose is the primary source of energy for many organisms and is efficiently taken up by bacteria through a dedicated transport system that exhibits high specificity. In Escherichia coli , the glucose-specific transporter IICB Glc serves as the major glucose transporter and functions as a component of the phosphoenolpyruvate-dependent phosphotransferase system. Here, we report cryo-electron microscopy (cryo-EM) structures of the glucose-bound IICB Glc protein. The dimeric transporter embedded in lipid nanodiscs was captured in the occluded, inward- and occluded, outward-facing conformations. Together with biochemical and biophysical analyses, and molecular dynamics (MD) simulations, we provide insights into the molecular basis and dynamics for substrate recognition and binding, including the gates regulating the binding sites and their accessibility. By combination of these findings, we present a mechanism for glucose transport across the plasma membrane. Overall, this work provides molecular insights into the structure, dynamics, and mechanism of the IICB Glc transporter in a native-like lipid environment. Glucose is a key energy source for many organisms, efficiently transported in bacteria by specific systems. Here, the authors reveal cryo-EM structures of the glucose transporter IICB from E. coli, providing insights into its mechanism and dynamics.

Chemical language models (CLMs) have shown strong performance in molecular property prediction and generation tasks. However, the impact of design choices, such as molecular representation format, tokenization strategy, and model architecture, on both performance and chemical interpretability remains underexplored. In this study, we systematically evaluate how these factors influence CLM performance and chemical understanding. We evaluated models through fine-tuning on downstream tasks and probing the structure of their latent spaces using probing predictors, vector operations, and dimensionality reduction techniques. Although downstream task performance was similar across model configurations, substantial differences were observed in the structure and interpretability of internal representations, highlighting that design choices meaningfully shape how chemical information is encoded. In practice, atomwise tokenization generally improved interpretability, and a RoBERTa-based model with SMILES input remains a reliable starting point for standard prediction tasks, as no alternative consistently outperformed it. These results provide guidance for the development of more chemically grounded and interpretable CLMs. Graphical Abstract Scientific Contribution This study provides a systematic evaluation of how core design choices shape chemical language models. Although different configurations often produced similar downstream performance, they produced substantial differences in the structure and interpretability of internal representations. For standard prediction tasks, the RoBERTa-based model with atomwise-tokenized SMILES input provides a practical and reliable setup for standard prediction tasks. By elucidating the impact of molecular representation and tokenization strategy, our results offer actionable guidance for the development of more interpretable and chemically informed CLMs.

The HIV-1 fusion peptide, comprising 15 to 20 hydrophobic residues at the N terminus of the Env-gp41 subunit, is a critical component of the virus-cell entry machinery. Here, we report the identification of a neutralizing antibody, N123-VRC34.01, which targets the fusion peptide and blocks viral entry by inhibiting conformational changes in gp120 and gp41 subunits of Env required for entry. Crystal structures of N123-VRC34.01 liganded to the fusion peptide, and to the full Env trimer, revealed an epitope consisting of the N-terminal eight residues of the gp41 fusion peptide and glycan N88 of gp120, and molecular dynamics showed that the N-terminal portion of the fusion peptide can be solvent-exposed. These results reveal the fusion peptide to be a neutralizing antibody epitope and thus a target for vaccine design.

Microbial ion-pumping rhodopsins (MRs) are extensively studied retinal-binding membrane proteins. However, their biogenesis, including oligomerisation and retinal incorporation, remains poorly understood. The bacterial green-light absorbing proton pump proteorhodopsin (GPR) has emerged as a model protein for MRs and is used here to address these open questions using cryo-electron microscopy (cryo-EM) and molecular dynamics (MD) simulations. Specifically, conflicting studies regarding GPR stoichiometry reported pentamer and hexamer mixtures without providing possible assembly mechanisms. We report the pentameric and hexameric cryo-EM structures of a GPR mutant, uncovering the role of the unprocessed N-terminal signal peptide in the assembly of hexameric GPR. Furthermore, certain proteorhodopsin-expressing bacteria lack retinal biosynthesis pathways, suggesting that they scavenge the cofactor from their environment. We shed light on this hypothesis by solving the cryo-EM structure of retinal-free proteoopsin, which together with mass spectrometry and MD simulations suggests that decanoate serves as a temporary placeholder for retinal in the chromophore binding pocket. Further MD simulations elucidate possible pathways for the exchange of decanoate and retinal, offering a mechanism for retinal scavenging. Collectively, our findings provide insights into the biogenesis of MRs, including their oligomeric assembly, variations in protomer stoichiometry and retinal incorporation through a potential cofactor scavenging mechanism. Microbial rhodopsins are prevalent retinal-binding membrane proteins. Here, authors reveal the roles of the N-terminal signal peptide in oligomerization and of decanoate as a retinal placeholder, providing proteorhodopsin structures and retinal incorporation mechanisms.

Cryo-EM structure determination of relatively small and flexible membrane proteins at high resolution is challenging. Increasing the size and structural features by binding of high affinity proteins to the biomolecular target allows for better particle alignment and may result in structural models of higher resolution and quality. Anticalins are alternative binding proteins to antibodies, which are based on the lipocalin scaffold and show potential for theranostic applications. The human heterodimeric amino acid transporter 4F2hc-LAT2 is a membrane protein complex that mediates transport of certain amino acids and derivatives thereof across the plasma membrane. Here, we present and discuss the cryo-EM structure of human 4F2hc-LAT2 in complex with the anticalin D11vs at 3.2 Å resolution. Relative high local map resolution (2.8–3.0 Å) in the LAT2 substrate binding site together with molecular dynamics simulations indicated the presence of fixed water molecules potentially involved in shaping and stabilizing this region. Finally, the presented work expands the application portfolio of anticalins and widens the toolset of binding proteins to promote high-resolution structure solution by single-particle cryo-EM.

Upon cell death signals, the apoptotic protease-activating factor Apaf1 and cytochrome c interact to form the apoptosome complex. The apoptosome is crucial for mitochondrial apoptosis, as it activates caspases that dismantle the cell. However, the in vivo assembly mechanism and appearance of the apoptosome remain unclear. We show that upon onset of apoptosis, Apaf1 molecules accumulate into multiple foci per cell. Disassembly of the foci correlates with cell survival. Structurally, Apaf1 foci resemble organelle-sized, cloud-like assemblies. They form through specific interactions with cytochrome c, contain caspase-9, and depend on procaspase-9 expression for their formation. We propose that Apaf1 foci correspond to the apoptosome in cells. Transientness and ultrastructure of Apaf1 foci suggest that the dynamic spatiotemporal organisation of apoptosome components regulates progression of apoptosis. The apoptosome is known as a protein complex that initiates cell death. Here Borgeaud et al . reveal that in living cells, the apoptosome protein components assemble into dynamic meshwork-like structures that dissociate in cells surviving apoptosis.