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Malfunction of the actin cytoskeleton is linked to numerous human diseases including neurological disorders and cancer. LIMK1 (LIM domain kinase 1) and its paralogue LIMK2 are two closely related kinases that control actin cytoskeleton dynamics. Consequently, they are potential therapeutic targets for the treatment of such diseases. In the present review, we describe the LIMK conformational space and its dependence on ligand binding. Furthermore, we explain the unique catalytic mechanism of the kinase, shedding light on substrate recognition and how LIMK activity is regulated. The structural features are evaluated for implications on the drug discovery process. Finally, potential future directions for targeting LIMKs pharmacologically, also beyond just inhibiting the kinase domain, are discussed.

Mutations in the gene coding for leucine-rich repeat kinase 2 (LRRK2) are a leading cause of the inherited form of Parkinson’s disease (PD), while LRRK2 overactivation is also associated with the more common idiopathic form of PD. LRRK2 is a large multidomain protein, including a GTPase as well as a Ser/Thr protein kinase domain. Common, disease-causing mutations increase LRRK2 kinase activity, presenting LRRK2 as an attractive target for drug discovery. Currently, drug development has mainly focused on ATP-competitive kinase inhibitors. Here, we report the identification and characterization of a variety of nanobodies that bind to different LRRK2 domains and inhibit or activate LRRK2 in cells and in in vitro. Importantly, nanobodies were identified that inhibit LRRK2 kinase activity while binding to a site that is topographically distinct from the active site and thus act through an allosteric inhibitory mechanism that does not involve binding to the ATP pocket or even to the kinase domain. Moreover, while certain nanobodies completely inhibit the LRRK2 kinase activity, we also identified nanobodies that specifically inhibit the phosphorylation of Rab protein substrates. Finally, in contrast to current type I kinase inhibitors, the studied kinase-inhibitory nanobodies did not induce LRRK2 microtubule association. These comprehensively characterized nanobodies represent versatile tools to study the LRRK2 function and mechanism and can pave the way toward novel diagnostic and therapeutic strategies for PD.

Sodium metal batteries (SMBs) have gained interest due to the high natural abundance and lower cost of sodium (Na) compared to lithium (Li), making them a promising alternative to conventional Li‐based battery systems. However, a key challenge toward the commercial viability of SMBs lies in mitigating uneven electrodeposition and dendrite growth, stemming from inherent interfacial instabilities during Na plating. This work explores how electrodeposition stability in SMBs is governed by thermal conditions, which directly affect ionic transport and interfacial reaction kinetics. A range of thermal environments are explored using a phase‐field modeling (PFM) framework, with a particular emphasis on the influence of temperature gradient‐induced thermodiffusion (Soret effect) on deposition dynamics. A quantitative analysis of dendrite growth under varying thermal conditions is conducted to identify regimes that promote stable plating behavior. It is found that operational temperature serves as a strong modulator of plating instability by simultaneously influencing reaction kinetics and ion transport, and thermodiffusion under imposed temperature gradients further redistributes ionic flux and alters deposition morphology. This work provides new insights into the role of thermal landscapes in dictating interface evolution during Na metal plating and offers design guidelines for leveraging thermal conditions to enhance deposition stability in Na metal electrodes. Unstable electrodeposition in sodium metal electrodes during plating gives rise to dendritic morphologies. A comprehensive analysis of how various thermal profiles, including uniform and non‐uniform temperature distributions and thermodiffusion can affect electrodeposition instability has been performed. Mechanistic interface instability descriptors have been introduced to quantify dendritic growth.

[This corrects the article DOI: 10.1371/journal.pbio.3001427.].

The 2 major molecular switches in biology, kinases and GTPases, are both contained in the Parkinson disease–related leucine-rich repeat kinase 2 (LRRK2). Using hydrogen–deuterium exchange mass spectrometry (HDX-MS) and molecular dynamics (MD) simulations, we generated a comprehensive dynamic allosteric portrait of the C-terminal domains of LRRK2 (LRRK2 RCKW ). We identified 2 helices that shield the kinase domain and regulate LRRK2 conformation and function. One helix in COR-B (COR-B Helix) tethers the COR-B domain to the αC helix of the kinase domain and faces its activation loop, while the C-terminal helix (Ct-Helix) extends from the WD40 domain and interacts with both kinase lobes. The Ct-Helix and the N-terminus of the COR-B Helix create a “cap” that regulates the N-lobe of the kinase domain. Our analyses reveal allosteric sites for pharmacological intervention and confirm the kinase domain as the central hub for conformational control.

Dendrite growth arising from interfacial instability remains a major obstacle to the advancement and commercialization of metal anode-based batteries. Sodium metal batteries (SMBs), a promising alternative to lithium (Li)-based systems due to the broad availability and lower cost of sodium (Na), suffer from pronounced interfacial instabilities during plating. A principal modulating factor influencing the propensity for dendritic growth in metal anodes is the interfacial surface energy at the active metal-electrolyte interface. This work explores the role of surface energy-induced interfacial instability in SMBs employing liquid electrolytes. It is shown that higher interfacial energies promote a more uniform deposition front, thereby reducing the tendency for uneven electrodeposition. For low interfacial energies, the reduced energetic penalty for creating new surfaces promotes rapid tip growth and branching, leading to highly unstable deposition morphologies with pronounced dendritic features. Furthermore, a comparative analysis between Li and Na metal anodes reveals that intrinsic differences in the material properties significantly influence electrodeposition stability. Through a combination of qualitative visualization and quantitative analysis, this study provides a comprehensive understanding of the role of surface energy in dictating interface evolution in SMBs, offering insights for the rational design of stable metal anode systems.

Matched-filtering detection techniques for gravitational-wave (GW) signals in ground-based interferometers rely on having well-modeled templates of the GW emission. Such techniques have been traditionally used in searches for compact binary coalescences (CBCs), and have been employed in all known GW detections so far. However, interesting science cases aside from compact mergers do not yet have accurate enough modeling to make matched filtering possible, including core-collapse supernovae and sources where stochasticity may be involved. Therefore the development of techniques to identify sources of these types is of significant interest. In this paper, we present a method of anomaly detection based on deep recurrent autoencoders to enhance the search region to unmodeled transients. We use a semi-supervised strategy that we name ‘Gravitational Wave Anomalous Knowledge’ (GWAK). While the semi-supervised approach to this problem entails a potential reduction in accuracy compared to fully supervised methods, it offers a generalizability advantage by enhancing the reach of experimental sensitivity beyond the constraints of pre-defined signal templates. We construct a low-dimensional embedded space using the GWAK method, capturing the physical signatures of distinct signals on each axis of the space. By introducing signal priors that capture some of the salient features of GW signals, we allow for the recovery of sensitivity even when an unmodeled anomaly is encountered. We show that regions of the GWAK space can identify CBCs, detector glitches and also a variety of unmodeled astrophysical sources.

Detections of coalescing binary black holes by LIGO have opened a new window of transient astronomy. With increasing sensitivity of LIGO and participation of the Virgo detector in Cascina, Italy, we expect to soon detect coalescence of compact binary systems with one or more neutron stars. These are the prime targets for electromagnetic follow-up of gravitational wave triggers, which holds enormous promise of rich science. However, hunting for electromagnetic counterparts of gravitational wave events is a non-trivial task due to the sheer size of the error regions, which could span hundreds of square degrees. This may require deep observation with large field-of-view telescopes and/or use of galaxy catalogs. The Zwicky Transient facility (ZTF), scheduled to begin operation in 2017, is designed to cover such large sky-localization areas. In this work, we present the strategies of efficiently tiling the sky to facilitate the observation of the gravitational wave error regions using ZTF. To do this, we used simulations consisting of 475 binary neutron star coalescences detected using a mix of two- and three-detector networks. Our studies reveal that, using two overlapping sets of ZTF tiles and a (modified) ranked-tiling algorithm, we can cover the gravitational-wave sky-localization regions with half as many pointings as a simple contour-covering algorithm. We then incorporated the ranked-tiling strategy to study our ability to observe the counterparts. This requires optimization of observation depth and localization area coverage. Our results show that observation in r-band with ∼600 seconds of integration time per pointing seems to be optimum for typical assumed brightnesses of electromagnetic counterparts, if we plan to spend equal amount of time per pointing. However, our results also reveal that we can gain by as much as 50% in detection efficiency if we linearly scale our integration time per pointing based on the tile probability.

Understanding of the molecular mechanisms of protein function requires detailed insight into the conformational landscape accessible to the protein. Conformational changes can be crucial for biological processes, such as ligand binding, protein folding, and catalysis. NMR spectroscopy is exquisitely sensitive to such dynamic changes in protein conformations. In particular, Carr–Purcell–Meiboom–Gill (CPMG) relaxation dispersion experiments are a powerful tool to investigate protein dynamics on a millisecond time scale. CPMG experiments that probe the chemical shift modulation of 15N in-phase magnetization are particularly attractive, due to their high sensitivity. These experiments require high power 1H decoupling during the CPMG period to keep the 15N magnetization in-phase. Recently, an improved version of the in-phase 15N-CPMG experiment was introduced, offering greater ease of use by employing a single 1H decoupling power for all CPMG pulsing rates. In these experiments however, incomplete decoupling of off-resonance amide 1H spins introduces an artefactual dispersion of relaxation rates, the so-called slow-pulsing artifact. Here, we analyze the slow-pulsing artifact in detail and demonstrate that it can be suppressed through the use of composite pulse decoupling (CPD). We report the performances of various CPD schemes and show that CPD decoupling based on the 90x–240y–90x element results in high-quality dispersion curves free of artifacts, even for amides with high 1H offset.

Purpose This study aims to investigate the influence of wall curvature in a semicircular thermal annular system on magneto-nanofluidic flow, heat transfer and entropy generation. The analysis is conducted under constant cooling surface and fluid volume constraints. Design/methodology/approach The mathematical equations describing the thermo-fluid flow in the semicircular system are solved using the finite element technique. Four different heating wall configurations are considered, varying the undulation numbers of the heated wall. Parametric variations of bottom wall undulation (f), buoyancy force characterized by the Rayleigh number (Ra), magnetic field strength represented by the Hartmann number (Ha) and inclination of the magnetic field (γ) on the overall thermal performance are studied extensively. Findings This study reveals that the fluid circulation strength is maximum in the case of a flat bottom wall. The analysis shows that the bottom wall contour and other control parameters significantly influence fluid flow, entropy production and heat transfer. The modified heated wall with a single undulation exhibits the highest entropy production and thermal convection, leading to a heat transfer enhancement of up to 21.85% compared to a flat bottom. The magnetic field intensity and orientation have a significant effect on heat transfer and irreversibility production. Research limitations/implications Further research can explore a wider range of parameter values, alternative heating wall profiles and boundary conditions to expand the understanding of magneto-nanofluidic flow in semicircular thermal systems. Originality/value This study introduces a constraint-based analysis of magneto-nanofluidic thermal behavior in a complex semicircular thermal system, providing insights into the impact of wall curvature on heat transfer performance. The findings contribute to the design and optimization of thermal systems in various applications.