Myr-Arf1 conformational flexibility at the membrane surface sheds light on the interactions with ArfGAP ASAP1

ADP-ribosylation factor 1 (Arf1) interacts with multiple cellular partners and membranes to regulate intracellular traffic, organelle structure and actin dynamics. Defining the dynamic conformational landscape of Arf1 in its active form, when bound to the membrane, is of high functional relevance and key to understanding how Arf1 can alter diverse cellular processes. Through concerted application of nuclear magnetic resonance (NMR), neutron reflectometry (NR) and molecular dynamics (MD) simulations, we show that, while Arf1 is anchored to the membrane through its N-terminal myristoylated amphipathic helix, the G domain explores a large conformational space, existing in a dynamic equilibrium between membrane-associated and membrane-distal conformations. These configurational dynamics expose different interfaces for interaction with effectors. Interaction with the Pleckstrin homology domain of ASAP1, an Arf-GTPase activating protein (ArfGAP), restricts motions of the G domain to lock it in what seems to be a conformation exposing functionally relevant regions.

Short-course Palliative Hypofractionated Radiotherapy in Patients with Poor-prognosis High-grade Glioma: Survival and Quality of Life Outcomes from a Prospective Phase II Study

AIMS

To report longitudinal quality of life (QoL) outcomes and survival in patients with poor-prognosis high-grade glioma (HGG) treated with palliative hypofractionated radiotherapy.

MATERIALS AND METHODS

Patients with poor-prognosis HGG were accrued on a prospective study of short-course palliative hypofractionated radiotherapy (35 Gy/10 fractions/2 weeks). The European Organization for Research and Treatment of Cancer QoL core questionnaire (QLQ-C30) and brain cancer module (BN20) were used in English or validated Indian vernacular languages (Hindi and Marathi) for QoL assessment at baseline (before radiotherapy), the conclusion of radiotherapy, 1 month post-radiotherapy and subsequently at 3-monthly intervals until disease progression/death. Baseline QoL scores were compared with corresponding scores from a historical HGG cohort. Summary QoL scores were compared longitudinally over time by related samples Friedman's two-way test. Progression-free survival and overall survival were calculated using the Kaplan-Meier method and reported as 1-year estimates with 95% confidence intervals.

RESULTS

Forty-nine (89%) of 55 patients completed the planned course of hypofractionated radiotherapy. Longitudinal QoL data were available in 42 (86%) of 49 patients completing radiotherapy, comprising the present cohort. The median age of included patients, comprised mainly of glioblastoma patients (81%), was 57 years, with an interquartile range (IQR) of 50-66 years and a median baseline Karnofsky score of 60 (IQR = 50-60). Baseline QoL scores were significantly worse for several domains compared with a historical institutional cohort of HGG patients treated previously with conventionally fractionated radiotherapy, indicating negative selection bias. QoL scores remained stable for most domains after palliative hypofractionated radiotherapy, with statistically significant improvements in fatigue (P = 0.032), dyspnoea (P = 0.042) and motor dysfunction (P = 0.036) over time. At a median follow-up of 8 months, Kaplan-Meier estimates of 1-year progression-free survival and overall survival were 33.3% (95% confidence interval 21.7-51.1%) and 38.1% (95% confidence interval 25.9-56%), respectively.

CONCLUSION

Short-course palliative hypofractionated radiotherapy in patients with poor-prognosis HGG is associated with stable and/or improved QoL scores in several domains, making it a viable resource-sparing regimen.

Repurposing of antiparasitic drugs against the NS2B-NS3 protease of the Zika virus

To date, no approved drugs are available to treat the Zika virus (ZIKV) infection. Therefore, it is necessary to urgently identify potential drugs against the ZIKV infection. Here, the repurposing of 30 antiparasitic drugs against the NS2B-NS3 protease of the ZIKV has been carried out by using combined docking and molecular dynamics- (MD) simulations. Based on the docking results, 5 drugs, such as Amodiaquine, Primaquine, Paromomycin, Dichlorophene, and Ivermectin were screened for further analysis by MD simulations and free energy calculations. Among these drugs, Amodiaquine and Dichlorophen are found to produce the most stable complexes and possess relative binding free energies of about -44.3 ± 3.7 kcal/mol and -41.1 ± 5.3 kcal/mol respectively. Therefore, they would act as potent small-molecule inhibitors of the ZIKV protease.However, evaluations of biological and safety activities of these drugs against the ZIKV protease are required before their clinical use.Communicated by Ramaswamy H. Sarma.

Cryo-EM structures of human ABCA7 provide insights into its phospholipid translocation mechanisms

Phospholipid extrusion by ABC subfamily A (ABCA) exporters is central to cellular physiology, although the specifics of the underlying substrate interactions and transport mechanisms remain poorly resolved at the molecular level. Here we report cryo-EM structures of lipid-embedded human ABCA7 in an open state and in a nucleotide-bound, closed state at resolutions between 3.6 and 4.0 Å. The former reveals an ordered patch of bilayer lipids traversing the transmembrane domain (TMD), while the latter reveals a lipid-free, closed TMD with a small extracellular opening. These structures offer a structural framework for both substrate entry and exit from the ABCA7 TMD and highlight conserved rigid-body motions that underlie the associated conformational transitions. Combined with functional analysis and molecular dynamics (MD) simulations, our data also shed light on lipid partitioning into the ABCA7 TMD and localized membrane perturbations that underlie ABCA7 function and have broader implications for other ABCA family transporters.

Targeting lipid-protein interaction to treat Syk-mediated acute myeloid leukemia

Membrane lipids control the cellular activity of kinases containing the Src homology 2 (SH2) domain through direct lipid-SH2 domain interactions. Here we report development of new nonlipidic small molecule inhibitors of the lipid-SH2 domain interaction that block the cellular activity of their host proteins. As a pilot study, we evaluated the efficacy of lipid-SH2 domain interaction inhibitors for spleen tyrosine kinase (Syk), which is implicated in hematopoietic malignancies, including acute myeloid leukemia (AML). An optimized inhibitor (WC36) specifically and potently suppressed oncogenic activities of Syk in AML cell lines and patient-derived AML cells. Unlike ATP-competitive Syk inhibitors, WC36 was refractory to de novo and acquired drug resistance due to its ability to block not only the Syk kinase activity, but also its noncatalytic scaffolding function that is linked to drug resistance. Collectively, our study shows that targeting lipid-protein interaction is a powerful approach to developing new small molecule drugs.

Accelerating All-Atom Simulations and Gaining Mechanistic Understanding of Biophysical Systems through State Predictive Information Bottleneck

An effective implementation of enhanced sampling algorithms for molecular dynamics simulations requires a priori knowledge of the approximate reaction coordinate describing the relevant mechanisms in the system. In this work, we focus on the recently developed artificial intelligence-based State Predictive Information Bottleneck (SPIB) approach and demonstrate how SPIB can learn such a reaction coordinate as a deep neural network even from undersampled trajectories. We exemplify its usefulness by achieving more than 40 times acceleration in simulating two model biophysical systems through well-tempered metadynamics performed by biasing along the SPIB-learned reaction coordinate. These include left- to right-handed chirality transitions in a synthetic helical peptide (Aib)₉ and permeation of a small benzoic acid molecule through a synthetic, symmetric phospholipid bilayer. In addition to significantly accelerating the dynamics and achieving back and forth movement between different metastable states, the SPIB-based reaction coordinate gives mechanistic insights into the processes driving these two important problems.

Microscopic Characterization of the Chloride Permeation Pathway in the Human Excitatory Amino Acid Transporter 1 (EAAT1)

Excitatory amino acid transporters (EAATs) are glutamate transporters that belong to the solute carrier 1A (SLC1A) family. They couple glutamate transport to the cotransport of three sodium (Na⁺) ions and one proton (H⁺) and the counter-transport of one potassium (K⁺) ion. In addition to this coupled transport, binding of cotransported species to EAATs activates a thermodynamically uncoupled chloride (Cl^-) conductance. Structures of SLC1A family members have revealed that these transporters use a twisting elevator mechanism of transport, where a mobile transport domain carries substrate and coupled ions across the membrane, while a static scaffold domain anchors the transporter in the membrane. We recently demonstrated that the uncoupled Cl^- conductance is activated by the formation of an aqueous pore at the domain interface during the transport cycle in archaeal Glt_Ph. However, a pathway for the uncoupled Cl^- conductance has not been reported for the EAATs, and it is unclear if such a pathway is conserved. Here, we employ all-atom molecular dynamics (MD) simulations combined with enhanced sampling, free-energy calculations, and experimental mutagenesis to approximate large-scale conformational changes during the transport process and identified a Cl^--conducting conformation in human EAAT1 (hEAAT1). Sampling the large-scale structural transitions in hEAAT1 allowed us to capture an intermediate conformation formed during the transport cycle with a continuous aqueous pore at the domain interface. The free-energy calculations performed for the conduction of Cl^- and Na⁺ ions through the captured conformation highlight the presence of two hydrophobic gates that control low-barrier movement of Cl^- through the aqueous pathway. Overall, our findings provide insights into the mechanism by which a human neurotransmitter transporter supports functional duality of active transport and passive Cl^- permeation and confirm the commonality of this mechanism in different members of the SLC1A family.

A Companion Guide to the String Method with Swarms of Trajectories: Characterization, Performance, and Pitfalls

The string method with swarms of trajectories (SMwST) is an algorithm that identifies a physically meaningful transition pathway─a one-dimensional curve, embedded within a high-dimensional space of selected collective variables. The SMwST algorithm leans on a series of short, unbiased molecular dynamics simulations spawned at different locations of the discretized path, from whence an average dynamic drift is determined to evolve the string toward an optimal pathway. However conceptually simple in both its theoretical formulation and practical implementation, the SMwST algorithm is computationally intensive and requires a careful choice of parameters for optimal cost-effectiveness in applications to challenging problems in chemistry and biology. In this contribution, the SMwST algorithm is presented in a self-contained manner, discussing with a critical eye its theoretical underpinnings, applicability, inherent limitations, and use in the context of path-following free-energy calculations and their possible extension to kinetics modeling. Through multiple simulations of a prototypical polypeptide, combining the search of the transition pathway and the computation of the potential of mean force along it, several practical aspects of the methodology are examined with the objective of optimizing the computational effort, yet without sacrificing accuracy. In light of the results reported here, we propose some general guidelines aimed at improving the efficiency and reliability of the computed pathways and free-energy profiles underlying the conformational transitions at hand.

Structures and dynamics of peptide and peptidomimetic inhibitors bound to the NS2B-NS3 protease of the ZIKA virus

Infections caused by the Zika virus (ZIKV) have detrimental effects on human health, in particular on infants. As no potent drug or vaccine is available to date to contain this viral disease, it is necessary to design inhibitors that can target the NS2B-NS3 protease of the ZIKV, which is mainly responsible for the proliferation of the virus inside the host cells . Here, molecular dynamics (MD) simulation and molecular mechanics energies combined with the generalized Born and surface area continuum solvation model (MM/GBSA) are used to understand the binding modes and stabilities of R, KR, KKR, WKR, WKKR, YKKR, and FKKR peptide inhibitors bound to the NS3-NS2B protease. The results are compared with the corresponding results obtained for covalent (compound 1) and non-covalent (compound 4*) peptidomimetic inhibitors . It is revealed that peptide inhibitors can bind strongly with the ZIKV protease with the ΔG_bind ranging from -12 kcal/mol to -73 kcal/mol. Among these peptides, YKKR is found to make the most stable complex with the protease and fully occupy the electrostatically active substrate binding site. Hence, it would inhibit the protease activities of ZIKV strongly. The residue-wise decomposition of ΔG_bind indicates that Asp75, Asp129, Tyr130, Ser135, Gly151, Asn152, Glys153, and Tyr161 of NS3 and Ser81, Asp83, and Phe84 of NS2B play a prominent role in the inhibitor binding. Therefore, any future design of inhibitors should be aimed to target these residues.

Ataxia-linked SLC1A3 mutations alter EAAT1 chloride channel activity and glial regulation of CNS function

Glutamate is the predominant excitatory neurotransmitter in the mammalian central nervous system (CNS). Excitatory Amino Acid Transporters (EAATs) regulate extracellular glutamate by transporting it into cells, mostly glia, to terminate neurotransmission and to avoid neurotoxicity. EAATs are also chloride (Cl-) channels, but the physiological role of Cl- conductance through EAATs is poorly understood. Mutations of human EAAT1 (hEAAT1) have been identified in patients with episodic ataxia type 6 (EA6). One mutation showed increased Cl- channel activity and decreased glutamate transport, but the relative contributions of each function of hEAAT1 to mechanisms underlying the pathology of EA6 remain unclear. Here we investigated the effects of five additional EA6-related mutations on hEAAT1 function in Xenopus laevis oocytes, and on CNS function in a Drosophila melanogaster model of locomotor behavior. Our results indicate that mutations resulting in decreased hEAAT1 Cl- channel activity but with functional glutamate transport can also contribute to the pathology of EA6, highlighting the importance of Cl- homeostasis in glial cells for proper CNS function. We also identified a novel mechanism involving an ectopic sodium (Na+) leak conductance in glial cells. Together, these results strongly support the idea that EA6 is primarily an ion channelopathy of CNS glia.

Identification of Structural transitions in bacterial fatty acid binding proteins that permit ligand entry and exit at membranes

Fatty acid (FA) transfer proteins extract FA from membranes and sequester them to facilitate their movement through the cytosol. Detailed structural information is available for these soluble protein–FA complexes, but the structure of the protein conformation responsible for FA exchange at the membrane is unknown. Staphylococcus aureus FakB1 is a prototypical bacterial FA transfer protein that binds palmitate within a narrow, buried tunnel. Here, we define the conformational change from a “closed” FakB1 state to an “open” state that associates with the membrane and provides a path for entry and egress of the FA. Using NMR spectroscopy, we identified a conformationally flexible dynamic region in FakB1, and X-ray crystallography of FakB1 mutants captured the conformation of the open state. In addition, molecular dynamics simulations show that the new amphipathic α-helix formed in the open state inserts below the phosphate plane of the bilayer to create a diffusion channel for the hydrophobic FA tail to access the hydrocarbon core and place the carboxyl group at the phosphate layer. The membrane binding and catalytic properties of site-directed mutants were consistent with the proposed membrane docked structure predicted by our molecular dynamics simulations. Finally, the structure of the bilayer-associated conformation of FakB1 has local similarities with mammalian FA binding proteins and provides a conceptual framework for how these proteins interact with the membrane to create a diffusion channel from the FA location in the bilayer to the protein interior.

Multi-Scale Input Strategies for Medulloblastoma Tumor Classification using Deep Transfer Learning

Medulloblastoma (MB) is a primary central nervous system tumor and the most common malignant brain cancer among children. Neuropathologists perform microscopic inspection of histopathological tissue slides under a microscope to assess the severity of the tumor. This is a timeconsuming task and often infused with observer variability. Recently, pre-trained convolutional neural networks (CNN) have shown promising results for MB subtype classification. Typically, high-resolution images are divided into smaller tiles for classification, while the size of the tiles has not been systematically evaluated. We study the impact of tile size and input strategy and classify the two major histopathological subtypes-Classic and Desmoplastic/Nodular. To this end, we use recently proposed EfficientNets and evaluate tiles with increasing size combined with various downsampling scales. Our results demonstrate using large input tiles pixels followed by intermediate downsampling and patch cropping significantly improves MB classification performance. Our top-performing method achieves the AUC-ROC value of 90.90% compared to 84.53% using the previous approach with smaller input tiles.

Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database

This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease-carotid artery stenosis (CAS), subclavian artery stenosis (SAS), peripheral arterial disease (PAD), and abdominal aortic aneurysms (AAA)-are considered. The ML methods are trained and tested on a physiologically realistic virtual patient database (VPD) containing 28,868 healthy subjects, adapted from the authors previous work and augmented to include disease. It is found that the tree-based methods of Random Forest and Gradient Boosting outperform other approaches. The performance of ML methods is quantified through the [Formula: see text] score and computation of sensitivities and specificities. When using six haemodynamic measurements (pressure in the common carotid, brachial, and radial arteries; and flow-rate in the common carotid, brachial, and femoral arteries), it is found that maximum [Formula: see text] scores larger than 0.9 are achieved for CAS and PAD, larger than 0.85 for SAS, and larger than 0.98 for both low- and high-severity AAAs. Corresponding sensitivities and specificities are larger than 90% for CAS and PAD, larger than 85% for SAS, and larger than 98% for both low- and high-severity AAAs. When reducing the number of measurements, performance is degraded by less than 5% when three measurements are used, and less than 10% when only two measurements are used for classification. For AAA, it is shown that [Formula: see text] scores larger than 0.85 and corresponding sensitivities and specificities larger than 85% are achievable when using only a single measurement. The results are encouraging to pursue AAA monitoring and screening through wearable devices which can reliably measure pressure or flow-rates.

Active participation of membrane lipids in inhibition of multidrug transporter P-glycoprotein

P-glycoprotein (Pgp) is a major efflux pump in humans, overexpressed in a variety of cancers and associated with the development of multi-drug resistance. Allosteric modulation by various ligands (e.g., transport substrates, inhibitors, and ATP) has been biochemically shown to directly influence structural dynamics, and thereby, the function of Pgp. However, the molecular details of such effects, particularly with respect to the role and involvement of the surrounding lipids, are not well established. Here, we employ all-atom molecular dynamics (MD) simulations to study the conformational landscape of Pgp in the presence of a high-affinity, third-generation inhibitor, tariquidar, in comparison to the nucleotide-free (APO) and the ATP-bound states, in order to characterize the mechanical effects of the inhibitor that might be of relevance to its blocking mechanism of Pgp. Simulations in a multi-component lipid bilayer show a dynamic equilibrium between open(er) and more closed inward-facing (IF) conformations in the APO state, with binding of ATP shifting the equilibrium towards conformations more prone to ATP hydrolysis and subsequent events in the transport cycle. In the presence of the inhibitor bound to the drug-binding pocket within the transmembrane domain (TMD), Pgp samples more open IF conformations, and the nucleotide binding domains (NBDs) become highly dynamic. Interestingly, and reproduced in multiple independent simulations, the inhibitor is observed to facilitate recruitment of lipid molecules into the Pgp lumen through the two proposed drug-entry portals, where the lipid head groups from the cytoplasmic leaflet penetrate into and, in some cases, translocate inside the TMD, while the lipid tails remain extended into the bulk lipid environment. These "wedge" lipids likely enhance the inhibitor-induced conformational restriction of the TMD leading to the differential modulation of coupling pathways observed with the NBDs downstream. We suggest a novel inhibitory mechanism for tariquidar, and potentially for related third-generation Pgp inhibitors, where lipids are seen to enhance the inhibitory role in the catalytic cycle of membrane transporters.

Glutamate transporters have a chloride channel with two hydrophobic gates

Glutamate is the most abundant excitatory neurotransmitter in the central nervous system, and its precise control is vital to maintain normal brain function and to prevent excitotoxicity¹. The removal of extracellular glutamate is achieved by plasma-membrane-bound transporters, which couple glutamate transport to sodium, potassium and pH gradients using an elevator mechanism^2-5. Glutamate transporters also conduct chloride ions by means of a channel-like process that is thermodynamically uncoupled from transport^6-8. However, the molecular mechanisms that enable these dual-function transporters to carry out two seemingly contradictory roles are unknown. Here we report the cryo-electron microscopy structure of a glutamate transporter homologue in an open-channel state, which reveals an aqueous cavity that is formed during the glutamate transport cycle. The functional properties of this cavity, combined with molecular dynamics simulations, reveal it to be an aqueous-accessible chloride permeation pathway that is gated by two hydrophobic regions and is conserved across mammalian and archaeal glutamate transporters. Our findings provide insight into the mechanism by which glutamate transporters support their dual function, and add information that will assist in mapping the complete transport cycle shared by the solute carrier 1A transporter family.

Evaluation and Selection of Video Stabilization Techniques for UAV-Based Active Infrared Thermography Application

Unmanned Aerial Vehicles (UAVs) that can fly around an aircraft carrying several sensors, e.g., thermal and optical cameras, to inspect the parts of interest without removing them can have significant impact in reducing inspection time and cost. One of the main challenges in the UAV based active InfraRed Thermography (IRT) inspection is the UAV’s unexpected motions. Since active thermography is mainly concerned with the analysis of thermal sequences, unexpected motions can disturb the thermal profiling and cause data misinterpretation especially for providing an automated process pipeline of such inspections. Additionally, in the scenarios where post-analysis is intended to be applied by an inspector, the UAV’s unexpected motions can increase the risk of human error, data misinterpretation, and incorrect characterization of possible defects. Therefore, post-processing is required to minimize/eliminate such undesired motions using digital video stabilization techniques. There are number of video stabilization algorithms that are readily available; however, selecting the best suited one is also challenging. Therefore, this paper evaluates video stabilization algorithms to minimize/mitigate undesired UAV motion and proposes a simple method to find the best suited stabilization algorithm as a fundamental first step towards a fully operational UAV-IRT inspection system.

Sensitivity and Specificity of Lateral Flow Antigen Test Kits for COVID-19 in Asymptomatic Population of Quarantine Centre of Province 3

Background Nearly after 6 months of the spread of Corona Virus Disease 19, along with the world Nepal is still trying to control the spread and prevent general population from acquiring it. With limited resources in manpower, technology and evidence it has been a difficult battle. But with time and more understanding of the virus new technology to detect the virus are coming up. It is a major breakthrough in the diagnostic field as this helps us in not only detecting the virus but also helps us to mobilize our human resources. This comes in a time where the cases are increasing at an alarming rate. Although numbers of Polymerase Chain Reaction testing have increased but due to the time consuming and the cost wise, we need a faster and equally reliable alternative. Antigen test approved by different countries can be used for point of care, screening and surveillance depending upon the requirements after calculating its sensitivity, specificity and accuracy. Objective To find out sensitivity and specificity of the Antigen test kit for COVID-19. Method Antigen tests were compared with Reverse Transcription Polymerase Chain Reaction as a reference standard in calculated sample size of 113 subjects in a high risk population. Both Reverse Transcription Polymerase Chain Reaction and antigen test were performed in a same subject with in maximum of 2 days' interval. Convenience sampling technique was used to select the subjects. Ethical approval was taken from Nepal Health Research Council before data collection. Study was done from August to September 2020 from Quarantine center of Province 3. Result There were total of 113 test carried out, among those 47 were positive and 66 were negative in Reverse Transcription Polymerase Chain Reaction. After preparing two by two table, Sensitivity and specificity of the tested was calculated which came out to be 85% and 100% respectively, with accuracy of 93.80%. Conclusion Even though the sensitivity and specificity came to be higher, this test should be interpreted cautiously depending upon the prevalence of Corona Virus Disease 19 in that particular community and the clinical and epidemiological context of the person who has been tested. When in doubt by clinical correlation should be confirmed with Reverse Transcription Polymerase Chain Reaction.

Confronting pitfalls of AI-augmented molecular dynamics using statistical physics

Artificial intelligence (AI)-based approaches have had indubitable impact across the sciences through the ability to extract relevant information from raw data. Recently, AI has also found use in enhancing the efficiency of molecular simulations, wherein AI derived slow modes are used to accelerate the simulation in targeted ways. However, while typical fields where AI is used are characterized by a plethora of data, molecular simulations, per construction, suffer from limited sampling and thus limited data. As such, the use of AI in molecular simulations can suffer from a dangerous situation where the AI-optimization could get stuck in spurious regimes, leading to incorrect characterization of the reaction coordinate (RC) for the problem at hand. When such an incorrect RC is then used to perform additional simulations, one could start to deviate progressively from the ground truth. To deal with this problem of spurious AI-solutions, here, we report a novel and automated algorithm using ideas from statistical mechanics. It is based on the notion that a more reliable AI-solution will be one that maximizes the timescale separation between slow and fast processes. To learn this timescale separation even from limited data, we use a maximum caliber-based framework. We show the applicability of this automatic protocol for three classic benchmark problems, namely, the conformational dynamics of a model peptide, ligand-unbinding from a protein, and folding/unfolding energy landscape of the C-terminal domain of protein G. We believe that our work will lead to increased and robust use of trustworthy AI in molecular simulations of complex systems.

An Investigation of Rotary Drone HERM Line Spectrum under Manoeuvering Conditions

Detecting and identifying drones is of great interest due to the proliferation of highly manoeuverable drones with on-board sensors of increasing sensing capabilities. In this paper, we investigate the use of radars for tackling this problem. In particular, we focus on the problem of detecting rotary drones and distinguishing between single-propeller and multi-propeller drones using a micro-Doppler analysis. Two different radars were used, an ultra wideband (UWB) continuous wave (CW) C-band radar and an automotive frequency modulated continuous wave (FMCW) W-band radar, to collect micro-Doppler signatures of the drones. By taking a closer look at HElicopter Rotor Modulation (HERM) lines, the spool and chopping lines are identified for the first time in the context of drones to determine the number of propeller blades. Furthermore, a new multi-frequency analysis method using HERM lines is developed, which allows the detection of propeller rotation rates (spool and chopping frequencies) of single and multi-propeller drones. Therefore, the presented method is a promising technique to aid in the classification of drones.

Membrane surface recognition by the ASAP1 PH domain and consequences for interactions with the small GTPase Arf1

Adenosine diphosphate-ribosylation factor (Arf) guanosine triphosphatase-activating proteins (GAPs) are enzymes that need to bind to membranes to catalyze the hydrolysis of guanosine triphosphate (GTP) bound to the small GTP-binding protein Arf. Binding of the pleckstrin homology (PH) domain of the ArfGAP With SH3 domain, ankyrin repeat and PH domain 1 (ASAP1) to membranes containing phosphatidylinositol 4,5-bisphosphate [PI(4,5)P₂] is key for maximum GTP hydrolysis but not fully understood. By combining nuclear magnetic resonance, neutron reflectometry, and molecular dynamics simulation, we show that binding of multiple PI(4,5)P₂ molecules to the ASAP1 PH domain (i) triggers a functionally relevant allosteric conformational switch and (ii) maintains the PH domain in a well-defined orientation, allowing critical contacts with an Arf1 mimic to occur. Our model provides a framework to understand how binding of the ASAP1 PH domain to PI(4,5)P₂ at the membrane may play a role in the regulation of ASAP1.