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At least 397 records · Page 22

EF-Hand Battle Royale: Hetero-ion Complexation in Lanmodulin

The lanmodulin (LanM) protein has emerged as an effective means for rare earth element (REE) extraction and separation from complex feedstocks without the use of organic solvents. Whereas the binding of LanM to individual REEs has been well characterized, little is known about the thermodynamics of mixed metal binding complexes (i.e., heterogeneous ion complexes), which limits the ability to accurately predict separation performance for a given metal ion mixture. In this paper, we employ the law of mass action to establish a theory of perfect cooperativity for LanM-REE complexation at the two highest-affinity binding sites. The theory is then used to derive an equation that explains the nonintuitive REE binding behavior of LanM, where separation factors for binary pairs of ions vary widely based on the ratio of ions in the aqueous phase, a phenomenon that is distinct from single-ion-binding chemical chelators. We then experimentally validate this theory and perform the first quantitative characterization of LanM complexation with heterogeneous ion pairs using resin-immobilized LanM. Importantly, the resulting homogeneous and heterogeneous constants enable accurate prediction of the equilibrium state of LanM in the presence of mixtures of up to 10 REEs, confirming that the perfect cooperativity model is an accurate mechanistic description of REE complexation by LanM. We further employ the model to simulate separation performance over a range of homogeneous and heterogeneous binding constants, revealing important insights into how mixed binding differentially impacts REE separations based on the relative positioning of the ion pairs within the lanthanide series. In addition to informing REE separation process optimization, these results provide mathematical and experimental insight into competition dynamics in other ubiquitous and medically relevant, cooperative binding proteins, such as calmodulin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms-a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tensor Network Path Integral Study of Dynamics in B850 LH2 Ring with Atomistically Derived Vibrations

The recently introduced multisite tensor network path integral (MS-TNPI) allows simulation of extended quantum systems coupled to dissipative media. We use MS-TNPI to simulate the exciton transport and the absorption spectrum of a B850 bacteriochlorophyll (BChl) ring. The MS-TNPI network is extended to account for the ring topology of the B850 system. Accurate molecular-dynamics-based description of the molecular vibrations and the protein scaffold is incorporated through the framework of Feynman–Vernon influence functional. To relate the present work with the excitonic picture, an exploration of the absorption spectrum is done by simulating it using approximate and topologically consistent transition dipole moment vectors. Comparison of these numerically exact MS-TNPI absorption spectra are shown with second-order cumulant approximations. Finally, the effect of temperature on both the exact and the approximate spectra is also explored.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Plasticity of the Arabidopsis leaf lipidome and proteome in response to pathogen infection and heat stress

Abstract Plants must cope with a variety of stressors during their life cycle, and the adaptive responses to these environmental cues involve all cellular organelles. Among them, comparatively little is known about the contribution of cytosolic lipid droplets (LDs) and their core set of neutral lipids and associated surface proteins to the rewiring of cellular processes in response to stress. Here, we analyzed the changes that occur in the lipidome and proteome of Arabidopsis (Arabidopsis thaliana) leaves after pathogen infection with Botrytis cinerea or Pseudomonas syringae, or after heat stress. Analyses were carried out in wild-type plants and the oil-rich double mutant trigalactosyldiacylglycerol1-1 sugar dependent 1-4 (tgd1-1 sdp1-4) that allowed for an allied study of the LD proteome in stressed leaves. Using liquid chromatography-tandem mass spectrometry-based methods, we showed that a hyperaccumulation of the primary LD core lipid TAG is a general response to stress and that acyl chain and sterol composition are remodeled during cellular adaptation. Likewise, comparative analysis of the LD protein composition in stress-treated leaves highlighted the plasticity of the LD proteome as part of the general stress response. We further identified at least two additional LD-associated proteins, whose localization to LDs in leaves was confirmed by confocal microscopy of fluorescent protein fusions. Taken together, these results highlight LDs as dynamic contributors to the cellular adaptation processes that underlie how plants respond to environmental stress.

Plant Sciences↗

Neuromorphic ionic computing in droplet interface synapses

Ionic devices with memory capabilities can emulate neural functionality, enabling neuromorphic computing and biomedical applications. In this study, we report an ionic spiking synapse based on aqueous droplet interface bilayer assembly. Under stepwise triangular voltages, the device displays coupled memcapacitive-memristive behavior, showing noncrossing pinched hysteretic I-V loops. This hysteretic ion dynamics can be regulated by modifying bilayer components, reconstituting protein channels, or adjusting droplet assembly configuration. Droplet interface synapses (DIS) exhibit fundamental neuromorphic behaviors such as paired-pulse facilitation/depression, spike rate–dependent plasticity, Hebbian learning, and short-term associative learning under classical conditioning. We also used reservoir computing with DIS to implement two learning algorithms: a classification algorithm that recognizes handwritten digits and a reinforcement learning algorithm that learns to play a board game of tic-tac-toe.

Li, Zhongwu [Lawrence Livermore National Laborator↗

Markers of mitochondrial function and oxidative metabolism in skeletal muscle do not display intrinsic circadian regulation in female mice

Mitochondria are key regulators of metabolism and ATP supply in skeletal muscle, while circadian rhythms influence many physiological processes. However, whether mitochondrial function is intrinsically regulated in a circadian manner in mouse skeletal muscle is inadequately understood. Accordingly, we measured postabsorptive transcript abundance of markers of mitochondrial autophagy, dynamics, and metabolism [extensor digitorum longus (EDL), soleus, gastrocnemius], protein abundance of electron transport chain complexes (EDL and soleus), enzymatic activity of succinate dehydrogenase (tibialis anterior and plantaris), and maximal mitochondrial respiration (tibialis anterior) in different skeletal muscles from female C57BL/6NJ mice at four zeitgeber times: 1, 7, 13, and 19. Our findings demonstrate that markers of mitochondrial function and oxidative metabolism do not display intrinsic time-of-day regulation at the gene, protein, enzymatic, or functional level. The core-clock genes Bmal1 and Dbp exhibited intrinsic circadian rhythmicity in skeletal muscle (i.e., EDL, soleus, gastrocnemius) and circadian amplitude varied by muscle type. These findings demonstrate that female mouse skeletal muscle does not display circadian regulation of markers of mitochondrial function or oxidative metabolism over 24 h.

Circadian Biology↗

Binding Free Energy Analysis of Colicin D, E3 and E8 to Their Respective Cognate Immunity Proteins Using Computational Simulations

Colicins are antimicrobial proteins produced by bacteria for the purpose of destroying neighboring bacteria. Colicin activity is neutralized by a specific cognate immunity protein in order to protect the host. This study investigates the structural and binding mechanisms underlying the interaction of colicin-D, -E3 and -E8 to their respective immunity proteins (ImD, Im3 and Im8) using structure prediction, molecular dynamics (MD) simulations and MM-PBSA approach of free energy calculations. High-confidence colicin-immunity (Col-Im) complex structures predicted using AlphaFold2 were subjected to MD simulations of 150 ns with GROMACS and were analyzed for the binding free energy calculation using gmx_MMPBSA. Results showed that the complex of Col_E3-Im3 exhibited the most favorable binding free energy, driven by strong van der Waals and electrostatic interactions. Col_D-ImD and Col_E8-Im8 also showed the favorable binding. Electrostatics and hydrogen bonding emerged as a key factor driving binding and stability, while polar solvation acted as a destabilizing factor across all systems. These outcomes provide an understanding of the molecular mechanisms of Col-Im systems, with potential applications for developing natural antimicrobials for food safety.

Biochemistry & Molecular Biology↗

Inter-Subunit Dynamics Controls Tunnel Formation During the Oxygenation Process in Hemocyanin Hexamers

Hemocyanin from horseshoe crab in its active form is a homo-hexameric protein. It exists in open and closed conformations when transitioning between deoxygenated and oxygenated states. Here, we present a detailed dynamic atomistic investigation of the oxygenated and deoxygenated states of the hexameric hemocyanin using explicit solvent molecular dynamics simulations. We focus on the variation in solvent cavities and the formation of tunnels in the two conformational states. By employing principal component analysis and CVAE-based deep learning, we are able to differentiate between the dynamics of the deoxy- and oxygenated states of hemocyanin. Finally, our results identify the deoxygenated open conformation, which adopts a stable, closed conformation after the oxygenation process.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗

Roles for Countercharge in the Voltage Sensor Domain of Ion Channels

Voltage-gated ion channels share a common structure typified by peripheral, voltage sensor domains. Their S4 segments respond to alteration in membrane potential with translocation coupled to ion permeation through a central pore domain. The mechanisms of gating in these channels have been intensely studied using pioneering methods such as measurement of charge displacement across a membrane, sequencing of genes coding for voltage-gated ion channels, and the development of all-atom molecular dynamics simulations using structural information from prokaryotic and eukaryotic channel proteins. One aspect of this work has been the description of the role of conserved negative countercharges in S1, S2, and S3 transmembrane segments to promote sequential salt-bridge formation with positively charged residues in S4 segments. These interactions facilitate S4 translocation through the lipid bilayer. In this review, we describe functional and computational work investigating the role of these countercharges in S4 translocation, voltage sensor domain hydration, and in diseases resulting from countercharge mutations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Domain coupling in activation of a family C GPCR

Abstract The G protein-coupled metabotropic glutamate receptors form homodimers and heterodimers with highly diverse responses to glutamate and varying physiological functions. We employ molecular dynamics, single-molecule spectroscopy and hydrogen–deuterium exchange to dissect the activation pathway triggered by glutamate. We find that activation entails multiple loosely coupled steps, including formation of an agonist-bound, pre-active intermediate whose transition to active conformations forms dimerization interface contacts that set efficacy. The agonist-bound receptor populates at least two additional intermediates en route to G protein-coupling conformations. Sequential transitions into these states act as ‘gates’, which attenuate the effects of glutamate. Thus, the agonist-bound receptor is remarkably dynamic, with low occupancy of G protein-coupling conformations, providing considerable headroom for modulation by allosteric ligands. Sequence variation within the dimerization interface, as well as altered conformational coupling in receptor heterodimers, may contribute to precise decoding of glutamate signals over broad spatial and temporal scales.

Biochemistry & Molecular Biology↗

Atomistic structure of the SARS-CoV-2 pseudoknot in solution from SAXS-driven molecular dynamics

SARS-CoV-2 depends on -1 programmed ribosomal frameshifting (-1 PRF) to express proteins essential for its replication. The RNA pseudoknot stimulating -1 PRF is thus an attractive drug target. However, the structural models of this pseudoknot obtained from cryo-EM and crystallography differ in some important features, leaving the pseudoknot structure unclear. We measured the solution structure of the pseudoknot using small-angle X-ray scattering (SAXS). The measured profile did not agree with profiles computed from the previously solved structures. Beginning with each of these solved structures, we used the SAXS data to direct all atom molecular dynamics (MD) simulations to improve the agreement in profiles. In all cases, this refinement resulted in a bent conformation that more closely resembled the cryo-EM structures than the crystal structure. Applying the same approach to a point mutant abolishing -1 PRF revealed a notably more bent structure with reoriented helices. This work clarifies the dynamic structures of the SARS-CoV-2 pseudoknot in solution.

60 APPLIED LIFE SCIENCES↗

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]↗

3D pattern formation of a protein–membrane suspension

Many essential cellular processes, including cell division and the establishment of cell polarity during embryogenesis, are regulated by pattern-forming proteins. These proteins often need to bind to a substrate, such as the cell membrane, onto which they interact and form two-dimensional (2D) patterns. It is unclear how the membrane’s continuity and dimensionality impact pattern formation. Here, we address this gap using the MinDE system, a prototypical example of pattern-forming membrane proteins. We show that when the lipid substrate is fragmented into submicrometer-sized diffusive liposomes, adenosine triphosphate-driven protein–protein interactions generate three-dimensional (3D) spatially extended patterns, despite the complete loss of membrane continuity. Remarkably, these 3D patterns emerge at scales four orders of magnitude larger than the individual liposomes. By systematically varying protein concentration, liposome size, and density, we observed and characterized a variety of 3D dynamical patterns not seen on continuous 2D membranes, including traveling waves, dynamical spirals, and a coexistence phase. Simulations and linear stability analysis of a coarse-grained model revealed that the physical properties of the dispersed membrane effectively rescale both the protein–membrane binding rates and diffusion, two key parameters governing pattern formation and wavelength selection. These findings highlight the robustness of Min’s pattern-forming ability, suggesting that protein–membrane suspensions could serve as an adaptable template for studying out-of-equilibrium self-organization in 3D, beyond in vivo contexts.

36 MATERIALS SCIENCE↗

A generalized Flory-Stockmayer kinetic theory of connectivity percolation and rigidity percolation of cytoskeletal networks

Actin networks are essential for living cells to move, reproduce, and sense their environments. The dynamic and rheological behavior of actin networks is modulated by actin-binding proteins such as α-actinin, Arp2/3, and myosin. There is experimental evidence that actin-binding proteins modulate the cooperation of myosin motors by connecting the actin network. In this work, we present an analytical mean field model, using the Flory-Stockmayer theory of gelation, to understand how different actin-binding proteins change the connectivity of the actin filaments as the networks are formed. We follow the kinetics of the networks and estimate the concentrations of actin-binding proteins that are needed to reach connectivity percolation as well as to reach rigidity percolation. We find that Arp2/3 increases the actomyosin connectivity in the network in a non-monotonic way. We also describe how changing the connectivity of actomyosin networks modulates the ability of motors to exert forces, leading to three possible phases of the networks with distinctive dynamical characteristics: a sol phase, a gel phase, and an active phase. Thus, changes in the concentration and activity of actin-binding proteins in cells lead to a phase transition of the actin network, allowing the cells to perform active contraction and change their rheological properties.

59 BASIC BIOLOGICAL SCIENCES↗

Insights into the substrate specificity, structure, and dynamics of plant histidinol-phosphate aminotransferase (HISN6)

Histidinol-phosphate aminotransferase is the sixth protein (hence HISN6) in the histidine biosynthetic pathway in plants. HISN6 is a pyridoxal 5'-phosphate (PLP)-dependent enzyme that catalyzes the reversible conversion of imidazole acetol phosphate into L-histidinol phosphate (HOLP). Here, we show that plant HISN6 enzymes are closely related to the orthologs from Chloroflexota. The studied example, HISN6 from Medicago truncatula (MtHISN6), exhibits a surprisingly high affinity for HOLP, which is much higher than reported for bacterial homologs. Moreover, unlike the latter, MtHISN6 does not transaminate phenylalanine. High-resolution crystal structures of MtHISN6 in the open and closed states, as well as the complex with HOLP and the apo structure without PLP, bring new insights into the enzyme dynamics, pointing at a particular role of a string-like fragment that oscillates near the active site and participates in the HOLP binding. When MtHISN6 is compared to bacterial orthologs with known structures, significant differences arise in or near the string region. The high affinity of MtHISN6 appears linked to the particularly tight active site cavity. Finally, a virtual screening against a library of over 1.3 mln compounds revealed three sites in the MtHISN6 structure with the potential to bind small molecules. Such compounds could be developed into herbicides inhibiting plant HISN6 enzymes absent in animals, which makes them a potential target for weed control agents.

59 BASIC BIOLOGICAL SCIENCES↗

Design of facilitated dissociation enables timing of cytokine signalling

Protein design has focused on the design of ground states, ensuring that they are sufficiently low energy to be highly populated. Designing the kinetics and dynamics of a system requires, in addition, the design of excited states that are traversed in transitions from one low-lying state to another. This is a challenging task because such states must be sufficiently strained to be poorly populated, but not so strained that they are not populated at all, and because protein design methods have focused on generating near-ideal structures. Here we describe a general approach for designing systems that use an induced-fit power stroke to generate a structurally frustrated and strained excited state, allosterically driving protein complex dissociation. X-ray crystallography, double electron–electron resonance spectroscopy and kinetic binding measurements show that incorporating excited states enables the design of effector-induced increases in dissociation rates as high as 5,700-fold. We highlight the power of this approach by designing rapid biosensors, kinetically controlled circuits and cytokine mimics that can be dissociated from their receptors within seconds, enabling dissection of the temporal dynamics of interleukin-2 signalling.

deformation dynamics↗

Modeling Protein–Protein and Protein–Ligand Interactions by the ClusPro Team in CASP16

ABSTRACT In the CASP16 experiment, our team employed hybrid computational strategies to predict both protein–protein and protein–ligand complex structures. For protein–protein docking, we combined physics‐based sampling—using ClusPro FFT docking and molecular dynamics—with AlphaFold (AF)‐based sampling, followed by AF‐based refinement. Our method produced numerous high‐accuracy complex models, including cases where AF alone failed, underscoring the critical role of physics‐based sampling alongside deep learning‐based refinement. For protein–ligand docking, we integrated the ClusPro LigTBM template‐based approach with a machine learning‐based confidence model for rescoring. The method preserves conserved interaction fragments derived from homologous complexes, followed by local resampling using physics‐based sampling and a diffusion model. Our template‐based strategy achieved a mean lDDT‐PLI of 0.69 across 233 targets, which was highly competitive. These results demonstrate that combining physics‐based modeling with AI‐driven refinement can significantly enhance the accuracy of both protein–protein and protein–ligand structure predictions.

Ashizawa, Ryota [Department of Applied Mathematics↗