Docking Stage Research Articles

Quality inspection and error correction of fork-ear type wing-fuselage docking assembly based on multi-camera stereo vision

Abstract During the automatic docking assembly of aircraft wing-fuselage, using monocular camera or dual-camera to monitor the docking stage of the fork-ear will result in an incomplete identification of the fork-ear pose-position and an inaccurate description of the deviation in the intersection holes’ position coordinates. To address this, a quality inspection and error correction method is proposed for the fork-ear docking assembly based on multi-camera stereo vision. Initially, a multi-camera stereo vision detection system is established to inspect the quality of fork-ear docking assembly. Subsequently, a spatial position solution mathematical model of the fork-ear feature points is developed, and a spatial pose determination mathematical model of fork-ear is established by utilised the elliptical cone. Finally, an enhanced artificial fish swarm particle filter algorithm is proposed to track and estimate the coordinate of the fork-ear feature points. An adaptive weighted fusion algorithm is employed to fuse the detection data from the multi-camera and the laser tracker, and a wing pose-position fine-tuning error correction model is constructed. Experimental results demonstrate that the method enhances the effect of the assembly quality inspection and effectively improves the wing-fuselage docking assembly accuracy of the fork-ear type aircraft.

Dynamic Docking Anti‐Disturbance Control of Overactuated AUV: System, Method, and Lake Trails

ABSTRACTDynamic docking control technology is crucial for autonomous underwater vehicles (AUV) to perform tasks underwater. To enhance the docking success rate of AUVs during dynamic docking, this paper presents a robust anti‐disturbance control algorithm specifically designed for overactuated AUV dynamic docking scenarios. During a dynamic docking mission, the AUV's depth control is adversely affected by the complex flow field generated by the underwater recovery device. To address this issue, this research proposes an AUV control scheme that combines an extended state observer (ESO) with a combined disturbance rejection method of the elevator‐vertical tunnel controller. First, an ESO is constructed to estimate and compensate for complicated disturbances such as model uncertainty and environmental disturbances. These estimations are then incorporated into the control law to mitigate the effects of the complicated flow field interference experienced during the AUV's dynamic docking process. Second, as turbulence intensifies at the end of the docking stage, the vertical thrust allocation is achieved using a hyperbolic tangent transition function. This ensures the stability of the AUV's attitude and depth, thereby enabling precise docking. Finally, the effectiveness of the proposed control algorithm is verified through lake trials and compared against the classic proportional‐integral‐differential (PID) and active disturbance rejection control (ADRC) methods. The trial results indicate that the proposed control algorithm significantly reduces the pitch and depth errors of the AUV, resulting in a remarkable 91% success rate for dynamic docking (based on 45 tests). The lake trials demonstrate that the proposed control algorithm is highly precise and robust.

Bioinformatic Test and Pharmacokinetic Profile Prediction of Gnetin-C Compound in Melinjo (Gnetum gnemon L.) Seeds Toward Colorectal Cancer

Cancer is one of the unresolved health problems in the world, including Indonesia. One of the most common types of cancer is colorectal cancer. Melinjo (Gnetum gnemon L.) is one of Indonesian local commodities which has many benefits including its potential to be developed as an anticancer agent. Through bioinformatics and molecular docking technology, the aim of this study was to investigate the functions of gnetin-C from melinjo against colorectal cancer. PkCSM database were used to search the ADMET (absorption, distribution, metabolism, elimination and toxicity) properties and stitch-string database were used to identify common genes related to colon cancer. During identification of colon cancer related genes, STAT3 protein showed the highest degree score. Furthermore, molecular docking was carried out to find out the interaction between the STAT3 protein and gnetin c compound found in melinjo seeds. From the docking stage, the pose with the best affinity energy was obtained with a docking score of 1,966 kcal/mol. this shows that the compound gnetin c has the potential to be used as a new anticancer agent from natural ingredients.Keywords: Melinjo, Gnetum gnemon, colon cancer, bioinformatics, molecular docking.

A multi-stage localization framework for accurate and precise docking of autonomous mobile robots (AMRs)

AbstractAutonomous navigation has been a long-standing research topic, and researchers have worked on many challenging problems in indoor and outdoor environments. One application area of navigation solutions is material handling in industrial environments. With Industry 4.0, the simple problem in traditional factories has evolved into the use of autonomous mobile robots within flexible production islands in a self-decision-making structure. Two main stages of such a navigation system are safe transportation of the vehicle from one point to another and reaching destinations at industrial standards. The main concern in the former is roughly determining the vehicle’s pose to follow the route, while the latter aims to reach the target with high accuracy and precision. Often, it may not be possible or require extra effort to satisfy requirements with a single localization method. Therefore, a multi-stage localization approach is proposed in this study. Particle filter-based large-scale localization approaches are utilized during the vehicle’s movement from one point to another, while scan-matching-based methods are used in the docking stage. The localization system enables the appropriate approach based on the vehicle’s status and task through a decision-making mechanism. The decision-making mechanism uses a similarity metric obtained through the correntropy criterion to decide when and how to switch from large-scale localization to precise localization. The feasibility and performance of the developed method are corroborated through field tests. These evaluations demonstrate that the proposed method accomplishes tasks with sub-centimeter and sub-degree accuracy and precision without affecting the operation of the navigation algorithms in real time.

SFSNet: An Inherent Feature Segmentation Method for Ground Testing of Spacecraft

In the final approach stage of rendezvous and docking of a spacecraft, the pose parameters of the target spacecraft need to meet docking or berthing capture conditions. Visible light visual measurement systems are increasingly employed in spacecraft ground tests to extract the geometric features of spacecraft to calculate and verify the accuracy of pose parameters. Most current feature-segmentation algorithms are unable to break through the scale transformation problem of spacecraft movement and the noise interference of multi-layer insulation materials in imaging. To overcome these challenges, we propose a novel feature segmentation algorithm based on the framework of deep convolutional neural networks. Firstly, a full convolution model of the encoding-decoding structure is constructed based on data for the ground test. A feature concatenation module is applied and combined with a network backbone to improve the segmentation performance. Then, a comprehensive loss function is presented and optimized by the pose characteristics of the spacecraft in the approach phase. Furthermore, a specific spacecraft simulation dataset to train and test our segmentation model is built through data augmentation. The experimental results verify that the proposed method achieves accurate segmentation of spacecraft of different scales, suppresses the interference caused by multilayer insulation material, and has strong robustness against motion ambiguity. The pixel accuracy of our proposed method reaches 96.5%, and the mean intersection over union is 93.0%.

Underwater Acoustically Guided Docking Method Based on Multi-Stage Planning

Autonomous underwater vehicles (AUVs) are important in areas such as underwater scientific research and underwater resource collection. However, AUVs suffer from data portability and energy portability problems due to their physical size limitation. In this work, an acoustic guidance method for underwater docking is proposed to solve the problem of persistent underwater operation. A funnel docking station and an autonomous remotely operated vehicle (ARV) are used as the platform for designing the guidance algorithms. First, the underwater docking guidance is divided into three stages: a long-range approach stage, a mid-range adjustment stage and a short-range docking stage. Second, the relevant guidance strategy is designed for each stage to improve the docking performance. Third, a correction method based on an ultra-short baseline (USBL) system is proposed for the ARV’s estimate of the depth, relative position and orientation angle of the docking station. To verify the feasibility of the docking guidance method, in this work, tests were performed on a lake and in a shallow sea. The success rate of autonomous navigation docking on the lake was 4 out of 7. The success rate of acoustic guidance docking on the lake and in the shallow sea were 11 out of 14 and 6 out of 8, respectively. The experimental results show the effectiveness of the docking guidance method in lakes and shallow seas.

Tuning the Biological Activity of PI3Kδ Inhibitor by the Introduction of a Fluorine Atom Using the Computational Workflow.

As a member of the class I PI3K family, phosphoinositide 3-kinase δ (PI3Kδ) is an important signaling biomolecule that controls immune cell differentiation, proliferation, migration, and survival. It also represents a potential and promising therapeutic approach for the management of numerous inflammatory and autoimmune diseases. We designed and assessed the biological activity of new fluorinated analogues of CPL302415, taking into account the therapeutic potential of our selective PI3K inhibitor and fluorine introduction as one of the most frequently used modifications of a lead compound to further improve its biological activity. In this paper, we compare and evaluate the accuracy of our previously described and validated in silico workflow with that of the standard (rigid) molecular docking approach. The findings demonstrated that a properly fitted catalytic (binding) pocket for our chemical cores at the induced-fit docking (IFD) and molecular dynamics (MD) stages, along with QM-derived atomic charges, can be used for activity prediction to better distinguish between active and inactive molecules. Moreover, the standard approach seems to be insufficient to score the halogenated derivatives due to the fixed atomic charges, which do not consider the response and indictive effects caused by fluorine. The proposed computational workflow provides a computational tool for the rational design of novel halogenated drugs.

Hydroxamic acid derivatives as selective HDAC3 inhibitors: computer-aided drug design strategies

Histone deacetylases (HDACs) are critical epigenetic drug targets that have gained significant attention in the scientific community for the treatment of cancer. The currently marketed HDAC inhibitors lack selectivity for the various HDAC isoenzymes. Here, we describe our protocol for the discovery of novel potential hydroxamic acid based HDAC3 inhibitors through pharmacophore modeling, virtual screening, docking, molecular dynamics (MD) simulation and toxicity studies. The ten pharmacophore hypotheses were established, and their reliability was validated by different ROC (receiving operator curve) analysis. Among them, the best model (Hypothesis 9 or RRRA) was employed for searching SCHEMBL, ZINC and MolPort database to screen out hit molecules as selective HDAC3 inhibitors, followed by different docking stages. MD simulation (50 ns) and MMGBSA study were performed to study the stability of ligand binding modes and with the help of trajectory analysis, to calculate the ligand-receptor complex RMSD (root-mean-square deviation), RMSF (root-mean-square fluctuation) and H-bond distance, etc. Finally, in-silico toxicity studies were performed on top screened molecules and compared with reference drug SAHA and established structure-activity relationship (SAR). The results indicated that compound 31, with high inhibitory potency and less toxicity (probability value 0.418), is suitable for further experimental analysis. Communicated by Ramaswamy H. Sarma

Studies of the symmetric binding mode of daclatasvir and analogs using a new homology model of HCV NS5A GT-4a

ContextEgypt has a high prevalence of the hepatitis C virus (HCV) genotype 4a (GT-4a). Unfortunately, the high resistance it exhibited still was not given the deserved attention in the scientific community. There is currently no consensus on the NS5A binding site because the crystal structure of HCV NS5A has not been resolved. The prediction of the binding modes of direct-acting antivirals (DAA) with the NS5A is a point of controversy due to the fact that several research groups presented different interaction models to elucidate the NS5A binding site. Consequently, a 3D model of HCV NS5A GT-4a was constructed and evaluated using molecular dynamics (MD) simulations. The generated model implies an intriguing new orientation of the AH relative to domain I. Additionally, the probable binding modes of marketed NS5A inhibitors were explored. MD simulations validated the stability of the predicted protein–ligand complexes. The suggested model predicts that daclatasvir and similar drugs bind symmetrically to HCV NS5A GT-4a. This will allow for the development of new NS5A-directed drugs, which may result in reduced resistance and/or a wider range of effectiveness against HCV.MethodsThe 3D model of HCV NS5A GT-4a was constructed using the comparative modeling approach of the web-based application Robetta. Its stability was tested with 200-ns MD simulations using the Desmond package of Schrodinger. The OPLS2005 force field was assigned for minimization, and the RMSD, RMSF, and rGyr were tracked throughout the MD simulations. Fpocket was used to identify druggable protein pockets (cavities) over the simulation trajectories. The binding modes of marketed NS5A inhibitors were then generated and refined with the aid of docking predictions made by FRED and AutoDock Vina. The stability of these drugs in complex with GT-4a was investigated by using energetic and structural analyses over MD simulations. The Prime MM-GBSA (molecular mechanics/generalized Born surface area) method was used as a validation tool after the docking stage and for the averaged clusters after the MD simulation stage. We utilized PyMOL and VMD to visualize the data.

Natural Compounds as DPP-4 Inhibitors: 3D-Similarity Search, ADME Toxicity, and Molecular Docking Approaches

Type 2 diabetes mellitus is one of the most common diseases of the 21st century, caused by a sedentary lifestyle, poor diet, high blood pressure, family history, and obesity. To date, there are no known complete cures for type 2 diabetes. To identify bioactive natural products (NPs) to manage type 2 diabetes, the NPs from the ZINC15 database (ZINC-NPs DB) were screened using a 3D shape similarity search, molecular docking approaches, and ADMETox approaches. Frequently, in silico studies result in asymmetric structures as “hit” molecules. Therefore, the asymmetrical FDA-approved diabetes drugs linagliptin (8-[(3R)-3-aminopiperidin-1-yl]-7-but-2-ynyl-3-methyl-1-[(4-methylquinazolin-2-yl)methyl]purine-2,6-dione), sitagliptin ((3R)-3-amino-1-[3-(trifluoromethyl)-6,8-dihydro-5H-[1,2,4]triazolo[4,3-a]pyrazin-7-yl]-4-(2,4,5-trifluorophenyl)butan-1-one), and alogliptin (2-[[6-[(3R)-3-aminopiperidin-1-yl]-3-methyl-2,4-dioxopyrimidin-1-yl]methyl]benzonitrile) were used as queries to virtually screen the ZINC-NPs DB and detect novel potential dipeptidyl peptidase-4 (DPP-4) inhibitors. The most promising NPs, characterized by the best sets of similarity and ADMETox features, were used during the molecular docking stage. The results highlight that 11 asymmetrical NPs out of 224,205 NPs are potential DPP-4 candidates from natural sources and deserve consideration for further in vitro/in vivo tests.

Bunyaviral N Proteins Localize at RNA Processing Bodies and Stress Granules: The Enigma of Cytoplasmic Sources of Capped RNA for Cap Snatching

Most cytoplasmic-replicating negative-strand RNA viruses (NSVs) initiate genome transcription by cap snatching. The source of host mRNAs from which the cytoplasmic NSVs snatch capped-RNA leader sequences has remained elusive. Earlier reports have pointed towards cytoplasmic-RNA processing bodies (P body, PB), although several questions have remained unsolved. Here, the nucleocapsid (N) protein of plant- and animal-infecting members of the order Bunyavirales, in casu Tomato spotted wilt virus (TSWV), Rice stripe virus (RSV), Sin nombre virus (SNV), Crimean-Congo hemorrhagic fever virus (CCHFV) and Schmallenberg virus (SBV) have been expressed and localized in cells of their respective plant and animal hosts. All N proteins localized to PBs as well as stress granules (SGs), but extensively to docking stages of PB and SG. TSWV and RSV N proteins also co-localized with Ran GTPase-activating protein 2 (RanGAP2), a nucleo-cytoplasmic shuttling factor, in the perinuclear region, and partly in the nucleus when co-expressed with its WPP domain containing a nuclear-localization signal. Upon silencing of PB and SG components individually or concomitantly, replication levels of a TSWV minireplicon, as measured by the expression of a GFP reporter gene, ranged from a 30% reduction to a four-fold increase. Upon the silencing of RanGAP homologs in planta, replication of the TSWV minireplicon was reduced by 75%. During in vivo cap-donor competition experiments, TSWV used transcripts destined to PB and SG, but also functional transcripts engaged in translation. Altogether, the results implicate a more complex situation in which, besides PB, additional cytoplasmic sources are used during transcription/cap snatching of cytoplasmic-replicating and segmented NSVs.

In silico analysis of the predicted protein-protein interaction of syntaxin-18, a putative receptor of Peregrinus maidis Ashmead (Hemiptera: Delphacidae) with Maize mosaic virus glycoprotein

The corn planthopper, Peregrinus maidis Ashmead (Hemiptera:Delphacidae), is a widely distributed insect pest which serves as a vector of two phytopathogenic viruses, Maize mosaic virus (MMV) and Maize stripe virus (MStV). It transmits the viruses in a persistent and propagative manner. MMV is an alphanucleorhabdovirus with a negative-sense, single-stranded RNA unsegmented genome. One identified insect vector protein that may serve as receptor to MMV is Syntaxin-18 (PmStx18) which belongs to the SNAREs (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) proteins. SNAREs play major roles in the final stage of docking and subsequent fusion of diverse vesicle-mediated transport events. In this work, in silico analysis of the interaction of MMV glycoprotein (MMV G) and PmStx18 was performed. Various freely available protein-protein docking web servers were used to predict the 3 D complex of MMV G and PmStx18. Analysis and protein-protein interaction (PPI) count showed that the complex predicted by the ZDOCK server has the highest number of interaction and highest affinity, as suggested by the calculated solvation free energy gain upon formation of the interface (ΔiG = −31 kcal/mol). Molecular dynamics simulation of the complex revealed important interactions at the interface over the course of 25 ns. This is the first in silico analysis performed for the interaction on a putative receptor of P. maidis and MMV G. The results of the PPI prediction provide novel information for studying the role of Stx18 in the transport, docking and fusion events involved in virus particle transport in the insect vector cells and its release. Communicated by Ramaswamy H. Sarma

A Novel Two-Stage Adaptive Filtering Model-Based GNSS/INS Tightly Coupled Precise Relative Navigation Algorithm for Autonomous Aerial Refueling

Autonomous aerial refueling (AAR) has generated great interest in recent years. However, much research has focused on the vision-based close docking stage; few studies have been conducted on the navigation algorithm for the rendezvous and following stages. High-precision relative navigation in following stage can provide favourable conditions for successful docking. Aiming at precise relative navigation in the complex high dynamic environment of aerial refueling rendezvous and following stages, a two-stage adaptive filtering architecture is exploited in this paper. An adaptive main Kalman filter (AKF) is realized for ambiguity eliminated GNSS/INS tightly coupled integrated system, and a robust adaptive subfilter is developed for GNSS individually. Particularly, aiming at the influence of pseudorange observation multipath outliers and state abnormal disturbances in unmanned air vehicle- (UAV-) tanker proximity, an INS-aided bifactor robust and classified factor adaptive filtering (IBRCAF) algorithm for single-frequency ambiguity resolution is proposed. Finally, the effectiveness of the algorithm is verified by the simulation experiments for UAV-tanker. The results indicate that the IBRCAF algorithm can efficiently suppress the influence of pseudorange multipath gross errors and abnormal state disturbances and greatly raise the success rate of ambiguity resolution, and the two-stage adaptive filtering algorithm of IBRCAF-AKF can significantly improve relative navigation performance and achieve centimeter-level accuracy.

The Molecular Dynamics Effects of Rutin on CDKS 2, 4 and 6: In Silico Modelling and Molecular Dynamics

Objectives: This simulated study has mechanistically evaluated the molecular dynamics effects of rutin on CDKs 2, 4, and 6 in cell cycling. Methods: Protein Data Bank (http://www.rcsb.org) was used to obtain the PDB file of CDK 2, 4, and 6. After simulation of CDKs in Gromacs software, AutoDock 4.2 was used to run 200 stages of molecular docking of CDKs in the presence of the rutin. CDK 2, 4, and 6 were simulated in the presence of rutin after docking. Results: Rutin had the highest tendency to bind the CDK-2 and CDK-6 via binding 16 and 18 residues in the binding site with hydrogen and hydrophobic bonds (respectively). Also, they had the highest amount of binding energy released. Rutin decreased total energy in CDKs and reduced the radius of gyration in CDK-2 and CDK-6 after docking. The secondary coil structure increased in CDK-2 and decreased in CDK-4 and 6. Conclusion: Conformational changes in CDK2 and 6 via rutin can inhibit the activity of these proteins and subsequently arrest the cell cycle in phases G1, S, and G2, which can lead the damaged cell to cell repair or Apoptosis. Keywords: Apoptosis, cell arresting, rutin, molecular dynamic, simulation

Identification of Novel Protein Targets for Fenugreek to Treat Diabetes: A Molecular Docking Study

Abstract: Trigonella foenum-graecum has been shown to have anti-diabetic potential through a wide variety of in-vivo assays as well as by inhibiting enzymes such as alpha-glucosidase and alpha-amylase. Studies have indicated the therapeutic potential of different phytoconstituents found in Trigonella foenum-graceum including diosgenin trigonelline, 4-hydroxyisoleucine, leucine, and L-lysine. This study aims to find novel protein targets that these specific phytoconstituents from fenugreek can bind to, thereby helping to treat diabetes mellitus. Through multiple stages of molecular docking and analyzing the binding sites in comparison to previously reported inhibitors, a suitable and novel target protein for four of the compounds was found and the relevance to diabetes was discussed, setting up these compounds as novel inhibitors for the target proteins.

A Unified Approach for Underwater Homing and Docking of over-Actuated AUV

During the implementation of time-consuming tasks such as underwater observation or detection, AUV has to face a difficult and urgent problem that its working duration is greatly shortened by the limited energy stored in the battery device. To solve the power problem, a docking station is installed underwater for AUV charging its battery. However, to realize the automatic underwater charging of AUV via a docking station, the accurate and efficient completion of underwater homing and docking is required for AUV. Underwater automatic homing and docking system is of great significance to improve work efficiency and prolong the endurance of AUV save cost. In this paper, a unified approach that involves such as task planning, guidance and control design, thrust allocation has been proposed to provide a complete solution to the problem of homing and docking of an over-actuated AUV. The task-based hybrid target point/line planning and following strategy are proposed for AUV homing and docking. At the beginning of homing, AUV is planned to follow a straight line via the line of sight (LoS) method. Afterward, AUV starts to follow multiple predefined target points until reaching the docking station. At the final stage of docking (within 10 m), a dedicated computer vision algorithm is applied to detect a newly designed LED light array fixed on the docking station to provide accurate guidance for the AUV to dock. The sliding mode control technique is used for the motion control of the AUV allowing robustness. As the AUV configured with eight thrusters is over-actuated, the problem of the thrust allocation is very important and successfully solved using the quadratic programming (QP) optimization method. Finally, the simulations of homing and docking tasks using the AUV are accomplished to verify the proposed approach.

The significance of the original characteristics of the active substance of injectable chondroitin sulfate preparations for intramuscular injections in the evidence-based medicine

Given the data from normative control resources and the research and development information system of the Ministry of Science and Education of the Russian Federation, we were unable to review the results and the quality of publications comprising method development and analytical validation of quantitative and qualitative values of injectable chondroitin sulfate preparations for intramuscular injections.
 Therefore, the results obtained in the research The development of a method for determining the intrinsic viscosity of an injectable chondroitin sodium sulfate preparation for intramuscular injections of 100 mg/ml, 2 ml remain valid, the method is considered reliable and practical.
 The materials and methods used in the research The development of a method for determining the intrinsic viscosity of an injectable chondroitin sulfate preparation have provided the possibility to determine the intrinsic viscosity for injectable chondroitin sodium sulfate preparations for intramuscular injections and the use of 0.2 M sodium chloride solution as a solvent. Also, the viscosity of the tested solutions in the concentration range of chondroitin sulfate 4.5-20 mg/ml was accurately сalculated, the value of the intrinsic viscosity determined for each of the preparations under test was in the range of 0.03-0.042 m3/kg.
 This study presents the results of a review of recent information, published in a number of academic journals, concerning modern approaches to the treatment and major clinical problems when applying chondroprotectors for arthrological diseases treatment.
 Considering the continuing interest in chondroprotectors, stability problems with formulations and modern possibilities in the application of machine learning in drug discovery, additional pharmaceutical design research (Drug design) is expected - from the docking stage to the quantum calculations stage.

A Novel Vision‐Based PRPL Multistage Image Processing Algorithm for Autonomous Aerial Refueling

Autonomous aerial refueling (AAR) technology can increase the flight endurance of unmanned air vehicles (UAVs) effectively. Drogue detection and target tracking method are significant for probe‐drogue refueling system in the docking stage. This paper proposes a novel vision‐based multistage image processing algorithm of drogue detection and target tracking for AAR. This algorithm divides the whole task into four stages: preprocessor, recognizer, predictor, and locker (PRPL). The adaptive threshold segmentation (ATS) algorithm and support vector machine (SVM) classifier are utilized in preprocessor and recognizer for drogue detection. An improved kernelized correlation filter (IKCF) tracking algorithm and scale adaptive method by window position as well as image resolution adjusted are adopted in predictor and locker for target tracking in complex dynamic environments. Finally, the proposed PRPL multistage image processing strategy is tested using an autonomous aerial refueling testbed. The results indicate that the proposed algorithm achieves high precision, good reliability, and real‐time capability compared with conventional algorithms. The average processing time is within 11 ms in various environments, which can meet the requirement for drogue detection and tracking in AAR.

Insight on Estrogen Receptor Alpha Modulator from Indonesian Herbal Database: An in-silico analysis

Estrogen receptor α (ERα) is liable for regulating transcription factors which are an important part of hormonal signaling in breast cancer. This study intends to find hit compounds that are considered capable of inhibiting ERα by utilizing structure-based pharmacophores and molecular docking. Pharmacophore of the original ERα ligand (E4D600) has one hydrogen bond acceptor and three hydrogen bond donors which are used to select compounds from the Indonesian herbal database. This pharmacophore model had an Area under Curve of the Receiver Operating Characteristics (AUC-ROC) value is 0.80 and the Goodness of Hits (GH) value is 0.81. The selection process generated 330 compounds which proceed to the molecular docking stage to analyze their binding energy and interactions to ERα. The results indicated potential hit compounds seen from their binding energies in the range -5.42 to -10.01 kcal/mol. four of the best compounds including Lig57/(-)-Bidwillon A, Lig47/Quercetin 3-(6''-galloylgalactoside), Lig197/Multifloroside and Lig83/Erythrabyssin II provide promising information for their detailed analysis as ERα inhibitors.

Plasma Membrane PI4P Regulates Vesicle Docking in Neuronal Exocytosis

Plasma membrane (PM) phosphatidylinositol 4-phosphate (PI4P) plays a crucial role in diverse cellular functions, but its role beyond being a precursor of phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) in secretory pathways including neurotransmitter release and hormone secretion remains unclear. Here, using structured illumination microscopy on the PM of PC12 cells, we show that PI4P is an inner-leaflet lipid that is clustered in microdomain and involved in clustering of t-SNARE protein syntaxin 1 essential for vesicle docking. We found that PI4P interacted with the C2 domain of synaptotagmin 1 and synaptotagmin-like protein 4 in a Ca2+-independent manner, resulting in recruiting SNARE proteins to the target membrane. Interestingly, the frequency of spontaneous excitatory postsynaptic currents (sEPSCs) was decreased by PI4P depletion in cultured hippocampal neurons, particularly it was most significantly decreased when PI(4,5)P2 depleted together. Thus, PI4P contributes to anionic PM lipid pool for SNARE-lipid interaction at vesicle docking stage of neuronal exocytosis.