Vesicle docking and fusion pore modulation by the neuronal calcium sensor Synaptotagmin-1

Synaptotagmin-1 (Syt1) is a major calcium sensor for rapid neurotransmitter release in neurons and hormone release in many neuroendocrine cells. It possesses two tandem cytosolic C2 domains that bind calcium, negatively charged phospholipids, and the neuronal SNARE complex. Calcium binding to Syt1 triggers exocytosis, but how this occurs is not well understood. Syt1 has additional roles in docking dense core vesicles (DCV) and synaptic vesicles (SV) to the plasma membrane (PM) and in regulating fusion pore dynamics. Thus, Syt1 perturbations could affect release through vesicle docking, fusion triggering, fusion pore regulation, or a combination of these. Here, using a human neuroendocrine cell line, we show that neutralization of highly conserved polybasic patches in either C2 domain of Syt1 impairs both DCV docking and efficient release of serotonin from DCVs. Interestingly, the same mutations resulted in larger fusion pores and faster release of serotonin during individual fusion events. Thus, Syt1's roles in vesicle docking, fusion triggering, and fusion pore control may be functionally related.

Synthesis of colicin Ia neoglycoproteins: tools towards glyco-engineering of bacterial cell surfaces

Colicins are antimicrobial proteins produced by certain strains of Escherichia coli that function as offensive weapons against closely-related competitor strains. Their bactericidal properties and narrow bacterial targeting range has made them of therapeutic interest. Furthermore, the applications of engineered non-bactericidal colicins are of interest as a cell surface-directed protein anchor for decorating E. coli with biomolecules. We previously demonstrated that an engineered non-bacteriocidal colicin E9 could be used to label bacterial cells with multiple biomolecules including glycans. Herein we extend our approach to colicin Ia, constructing mannose-presenting colicin la neoglycoproteins, through N-terminal organocatalyst-mediated protein aldol ligation (OPAL), or maleimide ligation targeting an internal cysteine. This work further highlights the potential utility of engineered colicins for non-genetic glyco-engineering of the E. coli cell surface.

Water-Induced Dissociative Mechanism of Carboxylate and Divalent Calcium Ions Revealed by IR Laser Spectroscopy

The dissociation of carboxylate and divalent calcium ions is investigated at the molecular level in microsolvation experiments by gradually increasing the number of water molecules around the ions. IR photodissociation (IRPD) laser spectroscopy of H2-tagged (Ca2+, AcO-)(H2O)n=8-21 clusters in the ν(CO2-) spectral range combined with RI-B97-D3-BJ-abc/TZVPPD frequency calculations is used to identify the type of ion pairs involved in this process. These results reveal that the ion dissociation follows a multistep mechanism involving in particular pseudobridged monodentate contact ion pairs (CIPs), which are found to be the first intermediate species formed from bidentate CIPs along the ion dissociation path. Altogether, structural assignments suggest a sequence of simple reactions in the first coordination shell of the carboxylate group, leading us to propose two possible dissociation paths. The appearance threshold of monodentate structures is measured at n = 10, with that of solvent-shared ion pairs (SIPs) being potentially at n = 18. By showing in detail how solvation progressively takes over from the ionic interaction in shaping these supramolecular structures, this study can serve as a reference for solving ion-pairing/dissociation problems.

Unveiling the therapeutic potential and mechanisms of stanniocalcin-1 in retinal degeneration

Retinal degeneration (RD) is a group of ocular diseases characterized by progressive photoreceptor apoptosis and visual impairment. Mitochondrial malfunction, excessive oxidative stress, and chronic activation of neuroglia collectively contribute to the development of RD. Currently, there is a lack of efficacious therapeutic interventions for RD. Stanniocalcin-1 (STC-1) is a promising candidate molecule to decelerate photoreceptor cell death. STC-1 is a secreted calcium/phosphorus regulatory protein that exerts diverse protective effects. Accumulating evidence suggests that STC-1 protects retinal cells from ischemic injury, oxidative stress, and excessive apoptosis through enhancing the expression of uncoupling protein-2 (UCP-2). Furthermore, STC-1 exerts its antiinflammatory effects by inhibiting the activation of microglia and macrophages, as well as the synthesis and secretion of proinflammatory cytokines, such as TNF-α, IL-1, and IL-6. By employing these mechanisms, STC-1 effectively shields the retinal photoreceptors and optic nerve, thereby slowing down the progression of RD. We summarize the STC-1-mediated therapeutic effects on the degenerating retina, with a particular focus on its underlying mechanisms. These findings highlight that STC-1 may act as a versatile molecule to treat degenerative retinopathy. Further research on STC-1 is imperative to establish optimal protocols for its clinical use.

Bimolecular Sandwich Aggregates of Porphyrin Nanorings

Extended π-systems often form supramolecular aggregates, drastically changing their optical and electronic properties. However, aggregation processes can be difficult to characterize or predict. Here, we show that butadiyne-linked 8- and 12-porphyrin nanorings form stable and well-defined bimolecular aggregates with remarkably sharp NMR spectra, despite their dynamic structures and high molecular weights (12.7 to 26.0 kDa). Pyridine breaks up the aggregates into their constituent rings, which are in slow exchange with the aggregates on the NMR time scale. All the aggregates have the same general two-layer sandwich structure, as deduced from NMR spectroscopy experiments, including 1H DOSY, 1H-1H COSY, TOCSY, NOESY, and 1H-13C HSQC. This structure was confirmed by analysis of residual dipolar couplings from 13C-coupled 1H-13C HSQC experiments on one of the 12-ring aggregates. Variable-temperature NMR spectroscopy revealed an internal ring-on-ring rotation process by which two π-π stacked conformers interconvert via a staggered conformation. A slower dynamic process, involving rotation of individual porphyrin units, was also detected by exchange spectroscopy in the 8-ring aggregates, implying partial disaggregation and reassociation. Molecular dynamics simulations indicate that the 8-ring aggregates are bowl-shaped and highly fluxional, compared to the 12-ring aggregates, which are cylindrical. This work demonstrates that large π-systems can form surprisingly well-defined aggregates and may inspire the design of other noncovalent assemblies.

Toward Reliable Conformational Energies of Amino Acids and Dipeptides─The DipCONFS Benchmark and DipCONL Datasets

Simulating peptides and proteins is becoming increasingly important, leading to a growing need for efficient computational methods. These are typically semiempirical quantum mechanical (SQM) methods, force fields (FFs), or machine-learned interatomic potentials (MLIPs), all of which require a large amount of accurate data for robust training and evaluation. To assess potential reference methods and complement the available data, we introduce two sets, DipCONFL and DipCONFS, which cover large parts of the conformational space of 17 amino acids and their 289 possible dipeptides in aqueous solution. The conformers were selected from the exhaustive PeptideCS dataset by Andris et al. [ J. Phys. Chem. B 2022, 126, 5949-5958]. The structures, originally generated with GFN2-xTB, were reoptimized using the accurate r2SCAN-3c density functional theory (DFT) composite method including the implicit CPCM water solvation model. The DipCONFS benchmark set contains 918 conformers and is one of the largest sets with highly accurate coupled cluster conformational energies so far. It is employed to evaluate various DFT and wave function theory (WFT) methods, especially regarding whether they are accurate enough to be used as reliable reference methods for larger datasets intended for training and testing more approximated SQM, FF, and MLIP methods. The results reveal that the originally provided BP86-D3(BJ)/DGauss-DZVP conformational energies are not sufficiently accurate. Among the DFT methods tested as an alternative reference level, the revDSD-PBEP86-D4 double hybrid performs best with a mean absolute error (MAD) of 0.2 kcal mol-1 compared with the PNO-LCCSD(T)-F12b reference. The very efficient r2SCAN-3c composite method also shows excellent results, with an MAD of 0.3 kcal mol-1, similar to the best-tested hybrid ωB97M-D4. With these findings, we compiled the large DipCONFL set, which includes over 29,000 realistic conformers in solution with reasonably accurate r2SCAN-3c reference conformational energies, gradients, and further properties potentially relevant for training MLIP methods. This set, also in comparison to DipCONFS, is used to assess the performance of various SQM, FF, and MLIP methods robustly and can complement training sets for those.

Energy gap of conformational transition related with temperature for the NACore of α-synuclein

Pathological aggregation of α-synuclein (α-syn) into amyloid fibrils is a major feature of Parkinson's disease (PD). The self-assembly of α-syn is mainly governed by a non-amyloid-β component core (NACore). However, the effects of concentrations and temperatures on their conformational transition remain unclear. To answer this question, we investigated the aggregation kinetics of NACore oligomers in silico by performing several independent all-atom molecular dynamics simulations. The simulation results show that tetramers are more prone to form β-sheets at 300 K than dimers and octamers. We also found that the NACore oligomers had higher β-sheet and β-barrel contents at 310 K. The inter-chain hydrophobic interactions, the backbone hydrogen bonding, the residue-residue interactions between V70-V77 as well as V77-V77 play important roles in the aggregation tendency of NACore octamers at 310 K. Interestingly, the energy gap analysis revealed that the conformational transition of NACore oligomers from intermediate states (β-barrel conformation) to stable structures (β-sheet layers) was dependent on the temperatures. In short, our study provides insight into the kinetic and thermodynamic mechanisms of the conformational transition of NACore at different concentrations and temperatures, contributing to a better understanding of the aggregation process of α-syn in Parkinson's disease.

Impact of Cellular Crowding on Protein Structural Dynamics Investigated by EPR Spectroscopy

The study of how the intracellular medium influences protein structural dynamics and protein-protein interactions is a captivating area of research for scientists aiming to comprehend biomolecules in their native environment. As the cellular environment can hardly be reproduced in vitro, direct investigation of biomolecules within cells has attracted growing interest in the past two decades. Among magnetic resonances, site-directed spin labeling coupled to electron paramagnetic resonance spectroscopy (SDSL-EPR) has emerged as a powerful tool for studying the structural properties of biomolecules directly in cells. Since the first in-cell EPR experiment was reported in 2010, substantial progress has been made, and this Review provides a detailed overview of the developments and applications of this spectroscopic technique. The strategies available for preparing a cellular sample and the EPR methods that can be applied to cells will be discussed. The array of spin labels available, along with their strengths and weaknesses in cellular contexts, will also be described. Several examples will illustrate how in-cell EPR can be applied to different biological systems and how the cellular environment affects the structural and dynamic properties of different proteins. Lastly, the Review will focus on the future developments expected to expand the capabilities of this promising technique.

Copper metabolism in osteoarthritis and its relation to oxidative stress and ferroptosis in chondrocytes

Ferroptosis, an iron-ion-dependent process of lipid peroxidation, damages the plasma membrane, leading to non-programmed cell death. Osteoarthritis (OA), a prevalent chronic degenerative joint disease among middle-aged and older adults, is characterized by chondrocyte damage or loss. Emerging evidence indicates that chondrocyte ferroptosis plays a role in OA development. However, most research has concentrated on ferroptosis regulation involving typical iron ions, potentially neglecting the significance of elevated copper ions in both serum and joint fluid of patients with OA. This review aims to fill this gap by systematically examining the interplay between copper metabolism, oxidative stress, ferroptosis, and copper-associated cell death in OA. It will provide a comprehensive overview of copper ions' role in regulating ferroptosis and their dual role in OA. This approach seeks to offer new insights for further research, prevention, and treatment of OA.

DNase II Can Efficiently Digest RNA and Needs to Be Redefined as a Nuclease

DNase II, identified in 1947 and named in 1953, is an acidic DNA endonuclease prevalent across organisms and crucial for normal growth. Despite its expression in nearly all human tissues, as well as its biological significance, DNase II's detailed functions and corresponding mechanisms remain unclear. Although many groups are trying to figure this out, progress is very limited. It is very hard to connect its indispensability with its DNA cleavage activity. In this study, we find that DNase II secreted to saliva can digest RNA in mildly acidic conditions, prompting us to hypothesize that salivary DNase II might digest RNA in the stomach. This finding is consistent with the interesting discovery reported in 1964 that RNA could inhibit DNase II's activity, which has been largely overlooked. This RNA digestion activity is further confirmed by using purified DNase II, showing activity to digest both DNA and RNA effectively. Here, we suggest redesignating DNase II as DNase II (RNase). The biological functions of DNase II are suggested to recycle intracellular RNA or digest external nucleic acids (both RNA and DNA) as nutrients. This discovery may untangle the mystery of DNase II and its significant biofunctions.

Renal Cell Carcinoma Discrimination through Attenuated Total Reflection Fourier Transform Infrared Spectroscopy of Dried Human Urine and Machine Learning Techniques

Renal cell carcinoma (RCC) is the sixth most common cancer in men and is often asymptomatic, leading to incidental detection in advanced disease stages that are associated with aggressive histology and poorer outcomes. Various cancer biomarkers are found in urine samples from patients with RCC. In this study, we propose to investigate the use of Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR) on dried urine samples for distinguishing RCC. We analyzed dried urine samples from 49 patients with RCC, confirmed by histopathology, and 39 healthy donors using ATR-FTIR spectroscopy. The vibrational bands of the dried urine were identified by comparing them with spectra from dried artificial urine, individual urine components, and dried artificial urine spiked with urine components. Urea dominated all spectra, but smaller intensity peaks, corresponding to creatinine, phosphate, and uric acid, were also identified. Statistically significant differences between the FTIR spectra of the two groups were obtained only for creatinine, with lower intensities for RCC cases. The discrimination of RCC was performed through Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) and Support Vector Machine (SVM). Using PCA-LDA, we achieved a higher discrimination accuracy (82%) (using only six Principal Components to avoid overfitting), as compared to SVM (76%). Our results demonstrate the potential of urine ATR-FTIR combined with machine learning techniques for RCC discrimination. However, further studies, especially of other urological diseases, must validate this approach.

Proton-coupled electron transfer at a mis-metalated zinc site detected with protein charge ladders

Distinguishing proton-coupled electron transfer (PCET) from uncoupled electron transfer (ET) in proteins can be challenging. A recent investigation [J. C. Koone, M. Simmang, D. L. Saenger, M. L. Hunsicker-Wang and B. F. Shaw, J. Am. Chem. Soc., 145, 16488-16497] reported that protein charge ladders and capillary electrophoresis can distinguish between single ET, PCET, and two-proton coupled ET (2PCET) by directly measuring the change in protein net charge upon reduction/oxidation (ΔZET). The current study used similar methods to assess PCET in zinc-free, "double copper" superoxide dismutase-1 (4Cu-SOD1), where one copper is bound at the copper site of each monomer and one copper is bound at the bridging zinc site, resulting in a quasi-type III Cu center. At pH 7.4, the net charge (Z) of the 4Cu-SOD1 dimer was unaffected by reduction of all four Cu2+ ions, i.e., ΔZ4ET = -0.09 ± 0.05 per dimer (-0.02 ± 0.01 per copper atom). These values suggest that PCET is taking place at all four Cu atoms of the homodimer. Molecular dynamics and Poisson-Boltzmann calculations suggest that a metal-coordinating histidine at the zinc site (His71) is the proton acceptor. These data show how ligands of a naturally occurring zinc site can help facilitate PCET when the right redox metal is bound.

Discovery of Benzopyrone-Based Candidates as Potential Antimicrobial and Photochemotherapeutic Agents through Inhibition of DNA Gyrase Enzyme B: Design, Synthesis, In Vitro and In Silico Evaluation

Bacterial DNA gyrase is considered one of the validated targets for antibacterial drug discovery. Benzopyrones have been reported as promising derivatives that inhibit bacterial DNA gyrase B through competitive binding into the ATP binding site of the B subunit. In this study, we designed and synthesized twenty-two benzopyrone-based derivatives with different chemical features to assess their antimicrobial and photosensitizing activities. The antimicrobial activity was evaluated against B. subtilis, S. aureus, E. coli, and C. albicans. Compounds 6a and 6b (rigid tetracyclic-based derivatives), 7a-7f (flexible-linker containing benzopyrones), and 8a-8f (rigid tricyclic-based compounds) exhibited promising results against B. subtilis, S. aureus, and E. coli strains. Additionally, these compounds demonstrated photosensitizing activities against the B. subtilis strain. Both in silico molecular docking and in vitro DNA gyrase supercoiling inhibitory assays were performed to study their potential mechanisms of action. Compounds 8a-8f exhibited the most favorable binding interactions, engaging with key regions within the ATP binding site of the DNA gyrase B domain. Moreover, compound 8d displayed the most potent IC50 value (0.76 μM) compared to reference compounds (novobiocin = 0.41 μM and ciprofloxacin = 2.72 μM). These results establish a foundation for structure-based optimization targeting DNA gyrase inhibition with antibacterial activity.

Modern Technologies Provide New Opportunities for Somatic Hybridization in the Breeding of Woody Plants

Advances in cell fusion technology have propelled breeding into the realm of somatic hybridization, enabling the transfer of genetic material independent of sexual reproduction. This has facilitated genome recombination both within and between species. Despite its use in plant breeding for over fifty years, somatic hybridization has been limited by cumbersome procedures, such as protoplast isolation, hybridized-cell selection and cultivation, and regeneration, particularly in woody perennial species that are difficult to regenerate. This review summarizes the development of somatic hybridization, explores the challenges and solutions associated with cell fusion technology in woody perennials, and outlines the process of protoplast regeneration. Recent advancements in genome editing and plant cell regeneration present new opportunities for applying somatic hybridization in breeding. We offer a perspective on integrating these emerging technologies to enhance somatic hybridization in woody perennial plants.

The changing scenario of drug discovery using AI to deep learning: Recent advancement, success stories, collaborations, and challenges

Due to the transformation of artificial intelligence (AI) tools and technologies, AI-driven drug discovery has come to the forefront. It reduces the time and expenditure. Due to these advantages, pharmaceutical industries are concentrating on AI-driven drug discovery. Several drug molecules have been discovered using AI-based techniques and tools, and several newly AI-discovered drug molecules have already entered clinical trials. In this review, we first present the data and their resources in the pharmaceutical sector for AI-driven drug discovery and illustrated some significant algorithms or techniques used for AI and ML which are used in this field. We gave an overview of the deep neural network (NN) models and compared them with artificial NNs. Then, we illustrate the recent advancement of the landscape of drug discovery using AI to deep learning, such as the identification of drug targets, prediction of their structure, estimation of drug-target interaction, estimation of drug-target binding affinity, design of de novo drug, prediction of drug toxicity, estimation of absorption, distribution, metabolism, excretion, toxicity; and estimation of drug-drug interaction. Moreover, we highlighted the success stories of AI-driven drug discovery and discussed several collaboration and the challenges in this area. The discussions in the article will enrich the pharmaceutical industry.

PharmaBench: Enhancing ADMET benchmarks with large language models

Accurately predicting ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties early in drug development is essential for selecting compounds with optimal pharmacokinetics and minimal toxicity. Existing ADMET-related benchmark sets are limited in utility due to their small dataset sizes and the lack of representation of compounds used in drug discovery projects. These shortcomings hinder their application in model building for drug discovery. To address this issue, we propose a multi-agent data mining system based on Large Language Models that effectively identifies experimental conditions within 14,401 bioassays. This approach facilitates merging entries from different sources, culminating in the creation of PharmaBench. Additionally, we have developed a data processing workflow to integrate data from various sources, resulting in 156,618 raw entries. Through this workflow, we constructed PharmaBench, a comprehensive benchmark set for ADMET properties, which comprises eleven ADMET datasets and 52,482 entries. This benchmark set is designed to serve as an open-source dataset for the development of AI models relevant to drug discovery projects.

Cavity-Mediated Enhancement of the Energy Transfer in the Reduced Fenna-Matthews-Olson Complex

Strong light-matter interaction leads to the formation of hybrid polariton states and can alter the light-harvesting properties of natural photosynthetic systems without modifying their chemical structure. In the present study, we computationally investigate the effect of the resonant cavity on the efficiency and the rate of the population transfer in a quantum system coupled to the cavity and the dissipative environment. The parameters of the model system were chosen to represent the Fenna-Matthews-Olson natural light-harvesting complex reduced to the three essential sites. The dynamics of the total system was propagated using the hierarchical equations of motion. Our results show that the strong light-matter interaction can accelerate the population transfer process compared to the cavity-free case but at the cost of lowering the transfer efficiency. The transition to the strong coupling regime was found to coincide with the degeneracy of polariton eigenvalues. Our findings indicate the potential and the limit of tuning the energy transfer in already efficient natural light-harvesting systems.

Thermodynamic Factors Controlling Electron Transfer among the Terminal Electron Acceptors of Photosystem I: Insights from Kinetic Modelling

Photosystem I is a key component of primary energy conversion in oxygenic photosynthesis. Electron transfer reactions in Photosystem I take place across two parallel electron transfer chains that converge after a few electron transfer steps, sharing both the terminal electron acceptors, which are a series of three iron-sulphur (Fe-S) clusters known as FX, FA, and FB, and the terminal donor, P700. The two electron transfer chains show kinetic differences which are, due to their close geometrical symmetry, mainly attributable to the tuning of the physicochemical reactivity of the bound cofactors, exerted by the protein surroundings. The factors controlling the rate of electron transfer between the terminal Fe-S clusters are still not fully understood due to the difficulties of monitoring these events directly. Here we present a discussion concerning the driving forces associated with electron transfer between FX and FA as well as between FA and FB, employing a tunnelling-based description of the reaction rates coupled with the kinetic modelling of forward and recombination reactions. It is concluded that the reorganisation energy for FX- oxidation shall be lower than 1 eV. Moreover, it is suggested that the analysis of mutants with altered FA redox properties can also provide useful information concerning the upstream phylloquinone cofactor energetics.

From straight to curved: A historical perspective of DNA shape

DNA is the macromolecule responsible for storing the genetic information of a cell and it has intrinsic properties such as deformability, stability and curvature. DNA Curvature plays an important role in gene transcription and, consequently, in the subsequent production of proteins, a fundamental process of cells. With recent advances in bioinformatics and theoretical biology, it became possible to analyze and understand the involvement of DNA Curvature as a discriminatory characteristic of gene-promoting regions. These regions act as sites where RNAp (ribonucleic acid-polymerase) binds to initiate transcription. This review aims to describe the formation of Curvature, as well as highlight its importance in predicting promoters. Furthermore, this article provides the potential of DNA Curvature as a distinguishing feature for promoter prediction tools, as well as outlining the calculation procedures that have been described by other researchers. This work may support further studies directed towards the enhancement of promoter prediction software.

ELUCIDATING THE DIFFERENTIAL IMPACTS OF EQUIVALENT GATING-CHARGE MUTATIONS IN VOLTAGE-GATED SODIUM CHANNELS

Voltage-gated sodium (Nav) channels are pivotal for cellular signaling and mutations in Nav channels can lead to excitability disorders in cardiac, muscular, and neural tissues. A major cluster of pathological mutations localizes in the voltage-sensing domains (VSDs), resulting in either gain-of-function (GoF), loss-of-function (LoF) effects, or both. However, the mechanism behind this functional divergence of mutations at equivalent positions remains elusive. Through hotspot analysis, we identified three gating charges (R1, R2, and R3) as major mutational hotspots in VSDs. The same amino-acid substitutions at equivalent gating-charge positions in VSDI and VSDII of the cardiac sodium channel Nav1.5 show differential gating-property impacts in electrophysiology measurements. We conducted 120 μs molecular dynamics (MD) simulations on wild-type and six mutants to elucidate the structural basis of their differential impacts. Our μs-scale MD simulations with applied external electric fields captured VSD state transitions and revealed the differential structural dynamics between equivalent R-to-Q mutants. Notably, we observed transient leaky conformations in some mutants during structural transitions, offering a detailed structural explanation for gating-pore currents. Our salt-bridge network analysis uncovered VSD-specific and state-dependent interactions among gating charges, countercharges, and lipids. This detailed analysis elucidated how mutations disrupt critical electrostatic interactions, thereby altering VSD permeability and modulating gating properties. By demonstrating the crucial importance of considering the specific structural context of each mutation, our study represents a significant leap forward in understanding structure-function relationships in Nav channels. Our work establishes a robust framework for future investigations into the molecular basis of ion channel-related disorders.

Angle-Resolved Linear Dichroism to Probe the Organization of Highly Ordered Collagen Biomaterials

Controlling the assembly of high-order structures is central to soft-matter and biomaterial engineering. Angle-resolved linear dichroism can probe the ordering of chiral collagen molecules in the dense state. Collagen triple helices were aligned by solvent evaporation. Their ordering gives a strong linear dichroism (LD) that changes sign and intensity with varying sample orientations with respect to the beam linear polarization. Being complementary to circular dichroism, which probes the structure of chiral (bio)molecules, LD can shift from the molecular to the supramolecular scale and from the investigation of the conformation to interactions. Supported by multiphoton microscopy and X-ray scattering, we show that LD provides a straightforward route to probe collagen alignment, determine the packing density, and monitor denaturation. This approach could be adapted to any assembly of chiral (bio)macromolecules, with key advantages in detecting large-scale assemblies with high specificity to aligned and chiral molecules and improved sensitivity compared to conventional techniques.

Protist biochemistry: Functional SUF system facilitated mitochondrial loss

The replacement of the mitochondrial iron-sulfur cluster machinery by a cytosolic system may have triggered complete mitochondrial loss in the anaerobic protist Monocercomonoides exilis. A new study strongly supports this scenario by confirming the functionality of this system.

All-Atom Membrane Builder via Multiscale Simulation

I present an automated and flexible tool designed for constructing bilayer membranes at all-atom (AA) resolution. The builder initiates the construction and equilibration of bilayer membranes at Martini coarse-grained (CG) resolution, followed by resolution enhancement to the atomic level using the accompanying backmapping tool. Notably, this tool enables users to create bilayer membranes with user-defined lipid compositions and protein structures, while also offering the flexibility to accommodate new lipid types. To assess the simplicity and robustness of the tool, I demonstrate the construction of several membranes incorporating protein structures. The tool is freely available at github.com/ksy141/mstool.

Structural insights into the assembly of type IIA topoisomerase DNA cleavage-religation center

The ability to catalyze reversible DNA cleavage and religation is central to topoisomerases' role in regulating DNA topology. In type IIA topoisomerases (Top2), the formation of its DNA cleavage-religation center is driven by DNA-binding-induced structural rearrangements. These changes optimally position key catalytic modules, such as the active site tyrosine of the WHD domain and metal ion(s) chelated by the TOPRIM domain, around the scissile phosphodiester bond to perform reversible transesterification. To understand this assembly process in detail, we report the catalytic core structures of human Top2α and Top2β in an on-pathway conformational state. This state features an in trans formation of an interface between the Tower and opposing TOPRIM domain, revealing a groove for accommodating incoming G-segment DNA. Structural superimposition further unveils how subsequent DNA-binding-induced disengagement of the TOPRIM and Tower domains allows a firm grasp of the bound DNA for cleavage/religation. Notably, we identified a previously undocumented protein-DNA interaction, formed between an arginine-capped C-terminus of an α-helix in the TOPRIM domain and the DNA backbone, significantly contributing to Top2 function. This work uncovers a previously unrecognized role of the Tower domain, highlighting its involvement in anchoring and releasing the TOPRIM domain, thus priming Top2 for DNA binding and cleavage.

Two RNA Folds from One Sequence: A Ribozyme with Versatile Substrate Processing Abilities

We report the design of a single RNA sequence capable of adopting one of two ribozyme folds and catalyzing the cleavage and/or ligation of the respective substrates. The RNA is able to change its conformation in response to its environment, hence it is called chameleon ribozyme (CHR). Efficient RNA cleavage of two different substrates as well as RNA ligation by CHR is demonstrated in separate experiments and in a one pot reaction. Our study shows that sequence variants of the hairpin ribozyme intersect with the hammerhead ribozyme and that rather short RNA molecules can have comprehensive conformational flexibility, which is an important feature for the emergence of new functional folds in early evolution.

Low or oscillatory shear stress and endothelial permeability in atherosclerosis

Endothelial shear stress is a tangential stress derived from the friction of the flowing blood on the endothelial surface of the arterial wall and is expressed in units of force/unit area (dyne/cm2). Branches and bends of arteries are exposed to complex blood flow patterns that generate low or oscillatory endothelial shear stress, which impairs glycocalyx integrity, cytoskeleton arrangement and endothelial junctions (adherens junctions, tight junctions, gap junctions), thus increasing endothelial permeability. The lipoproteins and inflammatory cells penetrating intima due to the increased endothelial permeability characterizes the pathological changes in early stage of atherosclerosis. Endothelial cells are critical sensors of shear stress, however, the mechanisms by which the complex shear stress regulate endothelial permeability in atherosclerosis remain unclear. In this review, we focus on the molecular mechanisms of the endothelial permeability induced by low or oscillatory shear stress, which will shed a novel sight in early stage of atherosclerosis.

Engineered transcription activator-like effector dimer proteins confer DNA loop-dependent gene repression comparable to Lac repressor

Natural prokaryotic gene repression systems often exploit DNA looping to increase the local concentration of gene repressor proteins at a regulated promoter via contributions from repressor proteins bound at distant sites. Using principles from the Escherichia coli lac operon we design analogous repression systems based on target sequence-programmable Transcription Activator-Like Effector dimer (TALED) proteins. Such engineered switches may be valuable for synthetic biology and therapeutic applications. Previous TALEDs with inducible non-covalent dimerization showed detectable, but limited, DNA loop-based repression due to the repressor protein dimerization equilibrium. Here, we show robust DNA loop-dependent bacterial promoter repression by covalent TALEDs and verify that DNA looping dramatically enhances promoter repression in E. coli. We characterize repression using a thermodynamic model that quantitates this favorable contribution of DNA looping. This analysis unequivocally and quantitatively demonstrates that optimized TALED proteins can drive loop-dependent promoter repression in E. coli comparable to the natural LacI repressor system. This work elucidates key design principles that set the stage for wide application of TALED-dependent DNA loop-based repression of target genes.

Quantification of enantiomers and blind identification of erythro-sphingosine non-racemates by cold ion spectroscopy

Enantiomers of a lipid erythro-sphingosine have been quantified with ≈4% accuracy by UV cold ion spectroscopy of their non-covalent complexes with a chiral aromatic molecule. The diastereomeric configuration of such complexes enables the quantification using just a single enantiomeric lipid standard and the identification of non-racemic solutions with no standards at all.

A Live-Cell Epigenome Manipulation by Photo-Stimuli-Responsive Histone Methyltransferase Inhibitor

Post-translational modifications on the histone H3 tail regulate chromatin structure, impact epigenetics, and hence the gene expressions. Current chemical modulation tools, such as unnatural amino acid incorporation, protein splicing, and sortase-based editing, have allowed for the modification of histones with various PTMs in cellular contexts, but are not applicable for editing native chromatin. The use of small organic molecules to manipulate histone-modifying enzymes alters endogenous histone PTMs but lacks precise temporal and spatial control. To date, there has been no achievement in modulating histone methylation in living cells with spatiotemporal resolution. In this study, a new method is presented for temporally manipulating histone dimethylation H3K9me2 using a photo-responsive inhibitor that specifically targets the methyltransferase G9a on demand. The photo-caged molecule is stable under physiological conditions and cellular environments, but rapidly activated upon exposure to light, releasing the bioactive component that can immediately inhibit the catalytic ability of the G9a in vitro. Besides, this masked compound could also efficiently reactivate the inhibition of methyltransferase activity in living cells, subsequently suppress H3K9me2, a mark that regulates various chromatin functions. Therefore, the chemical system will be a valuable tool for manipulating the epigenome for therapeutic purposes and furthering the understanding of epigenetic mechanisms.

The impact of sequence periodicity on DNA mechanics: investigating the origin of A-tract's curvature

Periodic sequences in phase with DNA helical shape are prevalent in genomes due to their capacity to modulate DNA elasticity on a global scale. However, how this occurs is not well understood. We use all-atom molecular dynamics simulations on 40 bp DNA fragments to assess the effect of periodicity on bending, twisting, and stretch elasticity. We observe that DNA static curvature is the mechanical parameter most influenced by periodicity, with A-tract sequences having the greatest effect. A-tracts generate global curvature by bending in distinct directions (minor groove and backbones) that complement the bending of the rest of DNA, which predominantly is towards the major groove. Even if A-tracts are rigid at the local scale, these small bends integrate with the greater bends from the sequences between, producing an amplifying effect. As a result, our findings support a 'delocalized bend' model in which the A-tract operates as an 'adaptable mechanical part'. By understanding how global curvature emerges from local fluctuations, we reconcile previous contradictory theories and open an avenue for manipulating DNA mechanics through sequence design.

Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

Charge regulation of nanoparticles in the presence of multivalent electrolytes

We explore the charge regulation (CR) of spherical nanoparticles immersed in an asymmetric electrolyte of a specified pH. Using a recently developed reactive canonical Monte Carlo (MC) simulation method, titration isotherms are obtained for suspensions containing monovalent, divalent, and trivalent coions. A theory based on the modified Poisson-Boltzmann approximation, which incorporates the electrostatic ion solvation free energy and discrete surface charge effects, is used to compare with the simulation results. A remarkably good agreement is found without any fitting parameters, both for the ion distributions and titration curves, suggesting that ionic correlations between coions and hydronium ions at the nanoparticle surface play only a minor role in determining the association equilibrium between hydroniums and the functional sites on the nanoparticle surface. On the other hand, if suspension contains multivalent counterions, we observe a large deviation between theory and simulations, showing that the electrostatic correlations between counterions and hydronium ions at the nanoparticle surface are very significant and must be properly taken into account to correctly describe CR for such solutions.

Molecular Dynamics Simulations of the miR-155 Duplex: Impact of Ionic Strength on Structure and Na+ and Cl- Ion Distribution

MiR-155 is a multifunctional microRNA involved in many biological processes. Since miR-155 is overexpressed in several pathologies, its detection deserves high interest in clinical diagnostics. Biosensing approaches often exploit the hybridization of miR-155 with its complementary strand. Molecular Dynamics (MD) simulations were applied to investigate the complex formed by miR-155 and its complementary strand in aqueous solution with Na+ and Cl- ions at ionic strengths in the 100-400 mM range, conditions commonly used in biosensing experiments. We found that the main structural properties of the duplex are preserved at all the investigated ionic strengths. The radial distribution functions of both Na+ and Cl- ions around the duplex show deviation from those of bulk with peaks whose relative intensity depends on the ionic strength. The number of ions monitored as a function of the distance from the duplex reveals a behavior reminiscent of the counterion condensation near the duplex surface. The occurrence of such a phenomenon could affect the Debye length with possible effects on the sensitivity in biosensing experiments.

Atomic resolution scanning transmission electron microscopy at liquid helium temperatures for quantum materials

Fundamental quantum phenomena in condensed matter, ranging from correlated electron systems to quantum information processors, manifest their emergent characteristics and behaviors predominantly at low temperatures. This necessitates the use of liquid helium (LHe) cooling for experimental observation. Atomic resolution scanning transmission electron microscopy combined with LHe cooling (cryo-STEM) provides a powerful characterization technique to probe local atomic structural modulations and their coupling with charge, spin and orbital degrees-of-freedom in quantum materials. However, achieving atomic resolution in cryo-STEM is exceptionally challenging, primarily due to sample drifts arising from temperature changes and noises associated with LHe bubbling, turbulent gas flow, etc. In this work, we demonstrate atomic resolution cryo-STEM imaging at LHe temperatures using a commercial side-entry LHe cooling holder. Firstly, we examine STEM imaging performance as a function of He gas flow rate, identifying two primary noise sources: He-gas pulsing and He-gas bubbling. Secondly, we propose two strategies to achieve low noise conditions for atomic resolution STEM imaging: either by temporarily suppressing He gas flow rate using the needle valve or by acquiring images during the natural warming process. Lastly, we show the applications of image acquisition methods and image processing techniques in investigating structural phase transitions in Cr2Ge2Te6, CuIr2S4, and CrCl3. Our findings represent an advance in the field of atomic resolution electron microscopy imaging for quantum materials and devices at LHe temperatures, which can be applied to other commercial side-entry LHe cooling TEM holders.

The influence of amphiphilic quaternary ammonium palmitoyl glycol chitosan (GCPQ) polymer composition on oil-loaded nanocapsule architecture

HYPOTHESIS

Predicting the exact nature of the self-assembly of amphiphilic molecules into supramolecular structures is of utmost importance for a variety of applications, but this is a challenge for nanotechnology. The amphiphilic drug delivery polymer-N-palmitoyl-N-monomethyl-N,N-dimethyl-N,N,N-trimethyl-6-O-glycolchitosan (GCPQ) self-assembles in aqueous media to form nanoparticles.

EXPERIMENT

This work aimed to develop a systematic predictive mathematical model on the eventual nature of oil-loaded GCPQ-nanoparticles and to determine the main independent variables that affect their nanoarchitecture following self-assembly. GCPQ polymers were produced with varying degree of palmitoylation (DP, 5.7-23.8 mol%), degree of quaternization (DQ, 7.2-22.7 mol%), and molecular weight (MW, 11.2-44.2 kDa) and their critical hydrophilic-lipophilic balance (cHLB) optimized to produce oil-loaded nanocapsules.

FINDINGS

Non-linear mathematical models (Particle size (nm) = 466.05 - 5.64DP - 6.52DQ + 0.13DQ2 - 0.03 MW2 - 14.48cHLB + 0.48cHLB2) were derived to predict the nanoparticle sizes (R2 = 0.998, R2adj = 0.995). Smaller nanoparticle sizes (148-157 nm) were obtained at high DP, DQ, and cHLB values, in which DP was the main independent variable responsible for nanoparticle size. Single or multiple-oil cores with small particles stabilizing polymer shells could be observed depending on the oil volume. Nanoparticle architectures, especially the nature of the oil-core(s), were driven by the DP, DQ, cHLB, and oil concentration. Here, we have developed a predictive model that may be applied to understand the nanoarchitecture of oil-loaded GCPQ-nanoparticles.

Phosphorylation of cytosolic hPGK1 affects protein stability and ligand binding: implications for its subcellular targeting in cancer

Human phosphoglycerate kinase 1(hPGK1) is a key glycolytic enzyme that regulates the balance between ADP and ATP concentrations inside the cell. Phosphorylation of hPGK1 at S203 and S256 has been associated with enzyme import from the cytosol to the mitochondria and the nucleus respectively. These changes in subcellular locations drive tumorigenesis and are likely associated with site-specific changes in protein stability. In this work, we investigate the effects of site-specific phosphorylation on thermal and kinetic stability and protein structural dynamics by hydrogen-deuterium exchange (HDX) and molecular dynamics (MD) simulations. We also investigate the binding of 3-phosphoglycerate and Mg-ADP using these approaches. We show that the phosphomimetic mutation S256D reduces hPGK1 kinetic stability by 50-fold, with no effect of the mutation S203D. Calorimetric studies of ligand binding show a large decrease in affinity for Mg-ADP in the S256D variant, whereas Mg-ADP binding to the WT and S203D can be accurately investigated using protein kinetic stability and binding thermodynamic models. HDX and MD simulations confirmed the destabilization caused by the mutation S256D (with some long-range effects on stability) and its reduced affinity for Mg-ADP due to the strong destabilization of its binding site (particularly in the apo-state). Our research provides evidence suggesting that modifications in protein stability could potentially enhance the translocation of hPGK1 to the nucleus in cancer. While the structural and energetic basis of its mitochondrial import remain unknown.

Enzymatic approaches for diversifying bioproducts from cellulosic biomass

Cellulosic biomass is the most abundantly available natural carbon-based renewable resource on Earth. Its widespread availability, combined with rising awareness, evolving policies, and changing regulations supporting sustainable practices, has propelled its role as a crucial renewable feedstock to meet the escalating demand for eco-friendly and renewable materials, chemicals, and fuels. Initially, biorefinery models using cellulosic biomass had focused on single-product platform, primarily monomeric sugars for biofuel. However, since the launch of the first pioneering cellulosic plants in 2014, these models have undergone significant revisions to adapt their biomass upgrading strategy. These changes aim to diversify the bioproduct portfolio and improve the revenue streams of cellulosic biomass biorefineries. Within this area of research and development, enzyme-based technologies can play a significant role by contributing to eco-design in producing and creating innovative bioproducts. This Feature Article highlights our strategies and recent progress in utilizing the biological diversity and inherent selectivity of enzymes to develop and continuously optimize sustainable enzyme-based technologies with distinct application approaches. We have advanced technologies for standalone platforms, which produce various forms of cellulose nanomaterials engineered with customized and enhanced properties and high yields. Additionally, we have tailored technologies for integration within a biorefinery concept. This biorefinery approach prioritizes designing tailored processes to establish bionanomaterials, such as cellulose and lignin nanoparticles, and bioactive molecules as part of a new multi-bioproduct platform for cellulosic biomass biorefineries. These innovations expand the range of bioproducts that can be produced from cellulosic biomass, transcending the conventional focus on monomeric sugars for biofuel production to include biomaterials biorefinery. This shift thereby contributes to strengthening the Bioeconomy strategy and supporting the achievement of several Sustainable Development Goals (SDGs) of the 2030 Agenda for Sustainable Development.

Extracellular filaments revealed by affinity capture cryo-electron tomography

Cryogenic-electron tomography (cryo-ET) has provided an unprecedented glimpse into the nanoscale architecture of cells by combining cryogenic preservation of biological structures with electron tomography. Micropatterning of extracellular matrix proteins is increasingly used as a method to prepare adherent cell types for cryo-ET as it promotes optimal positioning of cells and subcellular regions of interest for vitrification, cryo-focused ion beam (cryo-FIB) milling, and data acquisition. Here we demonstrate a micropatterning workflow for capturing minimally adherent cell types, human T-cells and Jurkat cells, for cryo-FIB and cryo-ET. Our affinity capture system facilitated the nanoscale imaging of Jurkat cells, revealing extracellular filamentous structures. It improved workflow efficiency by consistently producing grids with a sufficient number of well positioned cells for an entire cryo-FIB session. Affinity capture can be extended to facilitate high resolution imaging of other adherent and non-adherent cell types with cryo-ET.

Stapled Peptides: An Innovative and Ultimate Future Drug Offering a Highly Powerful and Potent Therapeutic Alternative

Peptide-based therapeutics have traditionally faced challenges, including instability in the bloodstream and limited cell membrane permeability. However, recent advancements in α-helix stapled peptide modification techniques have rekindled interest in their efficacy. Notably, these developments ensure a highly effective method for improving peptide stability and enhancing cell membrane penetration. Particularly in the realm of antimicrobial peptides (AMPs), the application of stapled peptide techniques has significantly increased peptide stability and has been successfully applied to many peptides. Furthermore, constraining the secondary structure of peptides has also been proven to enhance their biological activity. In this review, the entire process through which hydrocarbon-stapled antimicrobial peptides attain improved drug-like properties is examined. First, the essential secondary structural elements required for their activity as drugs are validated, specific residues are identified using alanine scanning, and stapling techniques are strategically incorporated at precise locations. Additionally, the mechanisms by which these structure-based stapled peptides function as AMPs are explored, providing a comprehensive and engaging discussion.

3D Variability Analysis Reveals a Hidden Conformational Change Controlling Ammonia Transport in Human Asparagine Synthetase

How motions in enzymes might be linked to catalytic function is of considerable general interest. Advances in X-ray crystallography and cryogenic electron microscopy (cryo-EM) offer the promise of elucidating functionally relevant conformational changes that are not easily studied by other biophysical methods. Here we use 3D variability analysis (3DVA) of the cryo-EM map for wild-type (WT) human asparagine synthetase (ASNS) to identify a functional role for the Arg-142 side chain as a gate that mediates ammonia access to a catalytically relevant intramolecular tunnel. Our 3DVA-derived hypothesis is assessed experimentally, using the R142I variant in which Arg-142 is replaced by isoleucine, and by molecular dynamics (MD) simulations on independent, computational models of the WT human ASNS monomer and its catalytically relevant, ternary complex with β-aspartyl-AMP and MgPPi. Residue fluctuations in the MD trajectories for the human ASNS monomer are consistent with those determined for 3DVA-derived structures. These MD simulations also indicate that the gating function of Arg-142 is separate from the molecular events that form a continuous tunnel linking the two active sites. Experimental support for Arg-142 playing a role in intramolecular ammonia translocation is provided by the glutamine-dependent synthetase activity of the R142 variant relative to WT ASNS. MD simulations of computational models for the R142I variant and the R142I/β-aspartyl-AMP/MgPPi ternary complex provide a possible molecular basis for this observation. Overall, the combination of 3DVA with MD simulations is a generally applicable approach to generate testable hypotheses of how conformational changes in buried side chains might regulate function in enzymes.

Quantitative localisation of titanium in the framework of titanium silicalite-1 using anomalous X-ray powder diffraction

One of the biggest obstacles to developing better zeolite-based catalysts is the lack of methods for quantitatively locating light heteroatoms on the T-sites in zeolites. Titanium silicalite-1 (TS-1) is a Ti-bearing zeolite-type catalyst commonly used in partial oxidation reactions with H2O2, such as aromatic hydroxylation and olefin epoxidation. The reaction mechanism is controlled by the configuration of titanium sites replacing silicon in the zeolite framework, but these sites remain unknown, hindering a fundamental understanding of the reaction. This study quantitatively determines heteroatoms within the zeolite-type framework using anomalous X-ray powder diffraction (AXRD) and the changes in the titanium X-ray scattering factor near the Ti K-edge (4.96 keV). Two TS-1 samples, each with approximately 2 Ti atoms per unit cell, were examined. Half of the titanium atoms are primarily split between sites T3 and T9, with the remainder dispersed among various T-sites within both MFI-type frameworks. One structure showed significant non-framework titanium in the micropores of a more distorted lattice. In both samples, isolated titanium atoms were more prevalent than dinuclear species, which could only potentially arise at site T9, but with a significant energy penalty and were not detected.

Transcriptional activation domains interact with ATPase subunits of yeast chromatin remodelling complexes SWI/SNF, RSC and INO80

Chromatin remodelling complexes (CRC) are ATP-dependent molecular machines important for the dynamic organization of nucleosomes along eukaryotic DNA. CRCs SWI/SNF, RSC and INO80 can move positioned nucleosomes in promoter DNA, leading to nucleosome-depleted regions which facilitate access of general transcription factors. This function is strongly supported by transcriptional activators being able to interact with subunits of various CRCs. In this work we show that SWI/SNF subunits Swi1, Swi2, Snf5 and Snf6 can bind to activation domains of Ino2 required for expression of phospholipid biosynthetic genes in yeast. We identify an activator binding domain (ABD) of ATPase Swi2 and show that this ABD is functionally dispensable, presumably because ABDs of other SWI/SNF subunits can compensate for the loss. In contrast, mutational characterization of the ABD of the Swi2-related ATPase Sth1 revealed that some conserved basic and hydrophobic amino acids within this domain are essential for the function of Sth1. While ABDs of Swi2 and Sth1 define separate functional protein domains, mapping of an ABD within ATPase Ino80 showed co-localization with its HSA domain also required for binding actin-related proteins. Comparative interaction studies finally demonstrated that several unrelated activators each exhibit a specific binding pattern with ABDs of Swi2, Sth1 and Ino80.

Bacterial siderophores: diversity, uptake pathways and applications

Iron is an essential nutrient for the growth, survival and virulence of almost all bacteria. To access iron, many bacteria produce siderophores, molecules with a high affinity for iron. Research has highlighted substantial diversity in the chemical structure of siderophores produced by bacteria, as well as remarkable variety in the molecular mechanisms involved in strategies for acquiring iron through these molecules. The metal-chelating properties of siderophores, characterized by their high affinity for iron and ability to chelate numerous other metals (albeit with lower affinity compared with iron), have also generated interest in diverse fields. Siderophores find applications in the environment, such as in bioremediation and agriculture, in which emerging and innovative strategies are being developed to address pollution and enhance nutrient availability for plants. Moreover, in medicine, siderophores could be used as a tool for novel antimicrobial therapies and medical imaging, as well as in haemochromatosis, thalassemia or cancer treatments. This Review offers insights into the diversity of siderophores, highlighting their potential applications in environmental and medical contexts.

Supramolecular chemical biology: designed receptors and dynamic chemical systems

Supramolecular chemistry focuses on the study of species joined by non-covalent interactions, and therefore on dynamic and relatively ill-defined structures. Despite being a well-developed field, it has to face important challenges when dealing with the selective recognition of biomolecules in highly competitive biomimetic media. However, supramolecular interactions reside at the core of chemical biology systems, since many processes in nature are governed by weak, non-covalent, strongly dynamic contacts. Therefore, there is a natural connection between these two research fields, which are not frequently related or share interests. In this feature article, I will highlight our most recent results in the molecular recognition of biologically relevant species, following different conceptual approaches from the most conventional design of elaborated receptors to the less popular dynamic combinatorial chemistry methodology. Selected illustrative examples from other groups will be also included. The discussion has been focused mainly on systems with potential biomedical applications.

Asymmetric Dynamics Drive Catalytic Activation of the Hsp90 Chaperone

The Hsp90 chaperone is an ATPase enzyme composed of two copies of a three-domain subunit. Hsp90 stabilizes and activates a diverse array of regulatory proteins. Substrates are bound and released by the middle domain through a clamping cycle involving conformational transitions between a dynamic open state and a compact conformationally restricted closed state. Intriguingly, the overall ATPase activity of dimeric Hsp90 can be asymmetrically enhanced through a single subunit when Hsp90 is bound to a cochaperone or when Hsp90 is composed of one active and one catalytically defunct subunit as a heterodimer. To explore the mechanism of asymmetric Hsp90 activation, we designed a subunit bearing N-terminal ATPase mutations that demonstrate increased intra- and interdomain dynamics. Using intact Hsp90 and various N-terminal and middle domain constructs, we blended 19F NMR spectroscopy, molecular dynamics (MD) simulations, and ATPase assays to show that within the context of heterodimeric Hsp90, the conformationally dynamic subunit stimulates the ATPase activity of the normal subunit. The contrasting dynamic properties of the subunits within heterodimeric Hsp90 provide a mechanistic framework to understand the molecular basis for asymmetric Hsp90 activation and its importance for the biological function of Hsp90.

An escape from ESKAPE pathogens: A comprehensive review on current and emerging therapeutics against antibiotic resistance

The rise of antimicrobial resistance has positioned ESKAPE pathogens as a serious global health threat, primarily due to the limitations and frequent failures of current treatment options. This growing risk has spurred the scientific community to seek innovative antibiotic therapies and improved oversight strategies. This review aims to provide a comprehensive overview of the origins and resistance mechanisms of ESKAPE pathogens, while also exploring next-generation treatment strategies for these infections. In addition, it will address both traditional and novel approaches to combating antibiotic resistance, offering insights into potential new therapeutic avenues. Emerging research underscores the urgency of developing new antimicrobial agents and strategies to overcome resistance, highlighting the need for novel drug classes and combination therapies. Advances in genomic technologies and a deeper understanding of microbial pathogenesis are crucial in identifying effective treatments. Integrating precision medicine and personalized approaches could enhance therapeutic efficacy. The review also emphasizes the importance of global collaboration in surveillance and stewardship, as well as policy reforms, enhanced diagnostic tools, and public awareness initiatives, to address resistance on a worldwide scale.

Predicting Small Molecule Binding Nucleotides in RNA Structures Using RNA Surface Topography

RNA small molecule interactions play a crucial role in drug discovery and inhibitor design. Identifying RNA small molecule binding nucleotides is essential and requires methods that exhibit a high predictive ability to facilitate drug discovery and inhibitor design. Existing methods can predict the binding nucleotides of simple RNA structures, but it is hard to predict binding nucleotides in complex RNA structures with junctions. To address this limitation, we developed a new deep learning model based on spatial correlation, ZHmolReSTasite, which can accurately predict binding nucleotides of small and large RNA with junctions. We utilize RNA surface topography to consider the spatial correlation, characterizing nucleotides from sequence and tertiary structures to learn a high-level representation. Our method outperforms existing methods for benchmark test sets composed of simple RNA structures, achieving precision values of 72.9% on TE18 and 76.7% on RB9 test sets. For a challenging test set composed of RNA structures with junctions, our method outperforms the second best method by 11.6% in precision. Moreover, ZHmolReSTasite demonstrates robustness regarding the predicted RNA structures. In summary, ZHmolReSTasite successfully incorporates spatial correlation, outperforms previous methods on small and large RNA structures using RNA surface topography, and can provide valuable insights into RNA small molecule prediction and accelerate RNA inhibitor design.

Insights into the Role of Side-Chain Team Work in nDsbDOx/Red Proteins: Mechanism of Substrate Binding

N-terminal disulfide bond oxidoreductase (nDsbDOx/Red) proteins display divergent substrate binding mechanisms depending on the conformational changes to the Phe70 cap, which is also dependent on the disulfide redox state. In nDsbDOx, the cap dynamics is complex (shows both open/closed Phe70 cap conformations), resulting in an active site that is highly flexible. So the system's active site is conformationally selective (the active site adapts before substrate binding) toward its substrate. In nDsbDRed, the cap is generally closed, resulting in induced fit-type binding (adapts after substrate approach). Recent studies predict Tyr40 and Tyr42 residues to act as internal nucleophiles (Tyr40/42O-) for disulfide association/dissociation in nDsbDOx/Red, supplementing the electron transfer channel. From this perspective, we investigate the cap dynamics and the subsequent substrate binding modes in these proteins. Our molecular dynamics simulations show that the cap opening eliminates Tyr42O- electrostatic interactions irrespective of the disulfide redox state. The active site becomes highly flexible, and the conformational selection mechanism governs. However, Tyr40O- formation does not alter the chemical environment; the cap remains mostly closed and plausibly follows the induced fit mechanism. Thus, it is apparent that mostly Tyr42O- facilitates the internal nucleophile-mediated self-preparation of nDsbDOx/Red proteins for binding.

Sensing the structural and conformational properties of single-stranded nucleic acids using electrometry and molecular simulations

Inferring the 3D structure and conformation of disordered biomolecules, e.g., single stranded nucleic acids (ssNAs), remains challenging due to their conformational heterogeneity in solution. Here, we use escape-time electrometry (ETe) to measure with sub elementary-charge precision the effective electrical charge in solution of short to medium chain length ssNAs in the range of 5-60 bases. We compare measurements of molecular effective charge with theoretically calculated values for simulated molecular conformations obtained from Molecular Dynamics simulations using a variety of forcefield descriptions. We demonstrate that the measured effective charge captures subtle differences in molecular structure in various nucleic acid homopolymers of identical length, and also that the experimental measurements can find agreement with computed values derived from coarse-grained molecular structure descriptions such as oxDNA, as well next generation ssNA force fields. We further show that comparing the measured effective charge with calculations for a rigid, charged rod-the simplest model of a nucleic acid-yields estimates of molecular structural dimensions such as linear charge spacings that capture molecular structural trends observed using high resolution structural analysis methods such as X-ray scattering. By sensitively probing the effective charge of a molecule, electrometry provides a powerful dimension supporting inferences of molecular structural and conformational properties, as well as the validation of biomolecular structural models. The overall approach holds promise for a high throughput, microscopy-based biomolecular analytical approach offering rapid screening and inference of molecular 3D conformation, and operating at the single molecule level in solution.