KinD-LCE Curve Estimation And Retinex Fusion On Low-Light Image

Low-light images often suffer from noise and color distortion. Object detection, semantic segmentation, instance segmentation, and other tasks are challenging when working with low-light images because of image noise and chromatic aberration. We also found that the conventional Retinex theory loses information in adjusting the image for low-light tasks. In response to the aforementioned problem, this paper proposes an algorithm for low illumination enhancement. The proposed method, KinD-LCE, uses a light curve estimation module to enhance the illumination map in the Retinex decomposed image, improving the overall image brightness. An illumination map and reflection map fusion module were also proposed to restore the image details and reduce detail loss. Additionally, a TV(total variation) loss function was applied to eliminate noise. Our method was trained on the GladNet dataset, known for its diverse collection of low-light images, tested against the Low-Light dataset, and evaluated using the ExDark dataset for downstream tasks, demonstrating competitive performance with a PSNR of 19.7216 and SSIM of 0.8213.Comment: Accepted by Signal, Image and Video Processin

Discovery of Selective Inhibitors Against EBNA1 via High Throughput In Silico Virtual Screening

Background: Epstein-Barr Virus (EBV) latent infection is associated with several human malignancies and is a causal agent of lymphoproliferative diseases during immunosuppression. While inhibitors of herpesvirus DNA polymerases, like gancyclovir, reduce EBV lytic cycle infection, these treatments have limited efficacy for treating latent infection. EBNA1 is an EBVencoded DNA-binding protein required for viral genome maintenance during latent infection. Methodology: Here, we report the identification of a new class of small molecules that inhibit EBNA1 DNA binding activity. These compounds were identified by virtual screening of 90,000 low molecular mass compounds using computational docking programs with the solved crystal structure of EBNA1. Four structurally related compounds were found to inhibit EBNA1-DNA binding in biochemical assays with purified EBNA1 protein. Compounds had a range of 20–100 mM inhibition of EBNA1 in fluorescence polarization assays and were further validated for inhibition using electrophoresis mobility shift assays. These compounds exhibited no significant inhibition of an unrelated DNA binding protein. Three of these compounds inhibited EBNA1 transcription activation function in cell-based assays and reduced EBV genome copy number when incubated with a Burkitt lymphoma cell line. Conclusions: These experiments provide a proof-of-principle that virtual screening can be used to identify specific inhibitor

PDTD: a web-accessible protein database for drug target identification

<p>Abstract</p> <p>Background</p> <p>Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D) structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (<it>Tar</it>get <it>Fis</it>hing <it>Dock</it>ing) <url>http://www.dddc.ac.cn/tarfisdock</url>, which has been used widely by others. Recently, we have constructed a protein target database, <it>P</it>otential <it>D</it>rug <it>T</it>arget <it>D</it>atabase (PDTD), and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation.</p> <p>Description</p> <p>PDTD is a web-accessible protein database for <it>in silico </it>target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling) pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores.</p> <p>Conclusion</p> <p>PDTD serves as a comprehensive and unique repository of drug targets. Integrated with TarFisDock, PDTD is a useful resource to identify binding proteins for active compounds or existing drugs. Its potential applications include <it>in silico </it>drug target identification, virtual screening, and the discovery of the secondary effects of an old drug (i.e. new pharmacological usage) or an existing target (i.e. new pharmacological or toxic relevance), thus it may be a valuable platform for the pharmaceutical researchers. PDTD is available online at <url>http://www.dddc.ac.cn/pdtd/</url>.</p

Engineering Scheffersomyces segobiensis for palmitoleic acid‐rich lipid production

Palmitoleic acid (POA; C16:1) is an essential high- value ω- 7- conjugated fatty acid with beneficial bioactivities and potential applications in the nu-traceutical and pharmaceutical industries. Previously, the oleaginous yeast Scheffersomyces segobiensis DSM27193 has been identified as a promis-ing production host as an alternative for POA extraction from plant or animal sources. Here, the POA-producing capacity of this host was further expanded by optimizing the fermentation process and molecular strain engineering. Specifically, a dual fermentation strategy (O-S dynamic regulation strategy) focused on the substrate and dissolved oxygen concentration was designed to eliminate ethanol and pyruvate accumulation during fermentation. Key genes influencing POA production, such as jen, dgat, ole were identified on the transcriptional level and were subsequently over-expressed. Furthermore, the phosphoketolase (Xpk)/phosphotransacetylase (Pta) pathway was intro-duced to improve the yield of the precursor acetyl-CoA from glucose. The resulting cell factory SS-12 produced 7.3 g/L of POA, corresponding to an 11-fold increase compared to the wild type, presenting the highest POA titre reported using oleaginous yeast to date. An economic evaluation based on the raw materials, utilities and facility-dependent costs showed that microbial POA production using S. segobiensis can supersede the current extraction method from plant oil and marine fish. This study reports the construction of a promising cell factory and an effective microbial fermentation strategy for commercial POA production

Tuning the Magnetism in Ultrathin CrxTey Films by Lattice Dimensionality

Two-dimensional (2D) magnetic transition metal compounds with atomic thickness exhibit intriguing physics in fundamental research and great potential for device applications. Understanding the correlations between their macrosopic magnetic properties and the dimensionality of microscopic magnetic exchange interactions are valuable for the designing and applications of 2D magnetic crystals. Here, using spin-polarized scanning tunneling microscopy, magnetization and magneto-transport measurements, we identify the zigzag-antiferromagnetism in monolayer CrTe2, incipient ferromagnetism in bilayer CrTe2, and robust ferromagnetism in bilayer Cr3Te4 films. Our density functional theory calculations unravel that the magnetic ordering in ultrathin CrTe2 is sensitive to the lattice parameters, while robust ferromagnetism with large perpendicular magnetic anisotropy in Cr3Te4 is stabilized through its anisotropic 3D magnetic exchange interactions

TarFisDock: a web server for identifying drug targets with docking approach

TarFisDock is a web-based tool for automating the procedure of searching for small molecule–protein interactions over a large repertoire of protein structures. It offers PDTD (potential drug target database), a target database containing 698 protein structures covering 15 therapeutic areas and a reverse ligand–protein docking program. In contrast to conventional ligand–protein docking, reverse ligand–protein docking aims to seek potential protein targets by screening an appropriate protein database. The input file of this web server is the small molecule to be tested, in standard mol2 format; TarFisDock then searches for possible binding proteins for the given small molecule by use of a docking approach. The ligand–protein interaction energy terms of the program DOCK are adopted for ranking the proteins. To test the reliability of the TarFisDock server, we searched the PDTD for putative binding proteins for vitamin E and 4H-tamoxifen. The top 2 and 10% candidates of vitamin E binding proteins identified by TarFisDock respectively cover 30 and 50% of reported targets verified or implicated by experiments; and 30 and 50% of experimentally confirmed targets for 4H-tamoxifen appear amongst the top 2 and 5% of the TarFisDock predicted candidates, respectively. Therefore, TarFisDock may be a useful tool for target identification, mechanism study of old drugs and probes discovered from natural products. TarFisDock and PDTD are available at

Possible Pathway(s) of Metyrapone Egress from the Active Site of Cytochrome P450 3A4: A Molecular Dynamics Simulation

ABSTRACT: To identify a possible pathway(s) for metyrapone egress from the active site of P450 3A4, a 5-ns conventional molecular dynamics simulation followed by steered molecular dynamics simulations was performed on the complex with metyrapone. The steered molecular dynamics simulations showed that metyrapone egress via channel 1, threading through the B-C loop, only required a relatively small rupture force and small displacement of residues, whereas egress via the third channel, between helix I and helices F and G, required a relatively large force and perturbation of helices I, B, and C. The conventional dynamics simulation indicated that channel 2, located between the ␤1 sheet, B-B loop, and F-G region, is closed because of the movement of residues in the mouth of this channel. The findings suggest that channel 1 can be used for metyrapone egress, whereas both channel 2 and channel 3 have a low probability of serving as an exit channel for metyrapone. In addition, residues F108 and I120 appear to act as two gatekeepers to prevent the inhibitor from leaving the active site. These results are in agreement with previous site-directed mutagenesis experiments