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SSRN 2024年

作者： Toopradab, Borwornlak Xie, Wanting Duan, Lian Hengphasatporn, Kowit Harada, Ryuhei Sinsulpsiri, Silpsiri Shigeta, Yasuteru Shi, Liyi Maitarad, Phornphimon Rungrotmongkol, Thanyada Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok10330 Thailand Center of Excellence in Biocatalyst and Sustainable Biotechnology Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok10330 Thailand Research Center of Nano Science and Technology Department of Chemistry College of Science Shanghai University Shanghai200444 China University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan Graduate School of Pure and Applied Sciences University of Tsukuba 1-1-1 Tennodai Ibaraki305–8571 Japan Emerging Industries Institute Shanghai University Zhejiang Jiaxing314006 China

The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (Mpro). The ligand-binding pathway sampling method based on parallel cascade selection molecular dynamics (LB-PaCS-MD) simulations was employed to elucidate plausible paths and conformations of ebselen, a synthetic organoselenium drug, within the Mpro catalytic site. Ebselen effectively engaged the active site, adopting proximity to H41 and interacting through the benzoisoselenazole ring in a π-π T-shaped arrangement, with an additional π-sulfur interaction with C145. In addition, the ligand-based drug design using the QSAR with GFA-MLR, RF, and ANN models were employed for biological activity prediction. The QSAR-ANN model showed robust statistical performance, with an R2training exceeding 0.98 and an RMSEtest of 0.21, indicating its suitability for predicting biological activities. Integration the ANN model with the LB-PaCS-MD insights enabled the rational design of novel compounds anchored in the ebselen core structure, identifying promising candidates with favorable predicted IC50 values. The designed compounds exhibited suitable drug-like characteristics and adopted an active conformation similar to ebselen, inhibiting Mpro function. These findings represent a synergistic approach merging ligand and structure-based drug design;with the potential to guide experimental synthesis and enzyme assay testing. © 2024, The Authors. All rights reserved.

关键词： Coronavirus

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Development of label-free triboelectric nanosensors as screening platforms for anti-tumor drugs

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Nano Energy 2024年 125卷

作者： Cheng, Yu-Ying Ganguly, Anindita Cheng, Yi-Yun Ortiz, Christopher Llynard D. Pal, Arnab Shah, Pramod Kaswan, Kuldeep Yang, Lee-Wei Lin, Zong-Hong Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Institute of Biomedical Engineering National Tsing Hua University Hsinchu30013 Taiwan Internet of Senses Research Center National Tsing Hua University Hsinchu30013 Taiwan Praexisio Taiwan Inc. New Taipei221425 Taiwan Institute of Bioinformatics and Structural Biology National Tsing Hua University Hsinchu300044 Taiwan Chemical Biology and Molecular Biophysics Program Taiwan International Graduate Program Institute of Biological Chemistry Academia Sinica Taipei115 Taiwan Department of Chemistry National Tsing Hua University Hsinchu300044 Taiwan International Intercollegiate PhD Program National Tsing Hua University Hsinchu300044 Taiwan Department of Power Mechanical Engineering National Tsing Hua University Hsinchu300044 Taiwan Biomedical Artificial Intelligence PhD Program National Tsing Hua University Hsinchu300044 Taiwan Physics Division National Center for Theoretical Sciences Taipei Taiwan

This study introduces a general label-free drug screening platform with potential to support high-throughput drug screening for any protein target. Its innovation lies in quantifying the affinity of molecule-molecule interactions via voltage output variation, which achieves unprecedented selectivity and sensitivity. It combines computational analysis complemented by experimental substantiation with a solid-liquid triboelectric nanosensor. Owing to its high binding affinity, FKBP-rapamycin is used as a model system to demonstrate the platform's sensitivity. Subsequently, the research is extended to study drug interactions with an oncogenic protein ATG4B. The findings unveil the binding of S130 and Tioconazole to ATG4B, a critical cysteine protease involved in autophagy, while revealing that Dexamethasone does not bind ATG4B. This binding exerts a specific inhibitory effect on autophagic flux and triggers cancer cell apoptosis. The results support the previously verified inhibitory effects of these drugs and the effectiveness of a newly developed self-powered drug screening platform, leveraging the principles of solid-liquid contact electrification. This approach adeptly confronts enduring challenges in traditional drug development methods where biochemical assays need to be designed for each individual protein target or only time-consuming and concentration-demanding molecular interaction measurements were made available. © 2024 Elsevier Ltd

关键词： Nanosensors

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Successive responses of three coral holobiont components (coral hosts, symbiotic algae, and bacteria) to daily temperature fluctuations

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Ecological Indicators 2024年 158卷

作者： Hsieh, Yunli Eric Lu, Chih-Ying Liu, Po-Yu Kao, Jia-Min Yang, Sung-Yin Wu, Chien-Yi Wong, Jing-Wen Michelle Shikina, Shinya Fan, Tung-Yung Yang, Shan-Hua Systems Biology and Mathematical Modelling group Max Planck Institute of Molecular Plant Physiology Potsdam Germany Institute of Biochemistry and Biology Bioinformatics Department University of Potsdam Potsdam Germany School of BioSciences The University of Melbourne ParkvilleVIC Australia Molecular and Biological Agricultural Sciences Program Taiwan International Graduate Program National Chung Hsing University and Academia Sinica Taipei Taiwan Graduate Institute of Biotechnology National Chung Hsing University Taichung Taiwan Biodiversity Research Center Academia Sinica Taipei Taiwan School of Medicine College of Medicine National Sun Yat-sen University Kaohsiung Taiwan Institute of Fisheries Science National Taiwan University Taipei Taiwan Department of Aquatic Bioscience National Chiayi University Chiayi Taiwan Institute of Marine Environment and Ecology National Taiwan Ocean University Keelung Taiwan National Museum of Marine Biology and Aquarium Pingtung Taiwan

Corals and their associated microbiota form a "holobiont," which includes symbiotic algae and other associated microbiota dominated by bacteria. The composition of holobiont is influenced by various environmental factors, such as increasing sea water temperatures. Previous studies of the effects of temperature changes on coral physiology and associated bacterial communities have been conducted based on stable water temperatures set by mean temperatures, or by slowly increasing/decreasing temperatures. However, the daily temperature fluctuations that corals experience in nature are not stable. The current understanding of the effects of large daily temperature fluctuations on coral and associated bacterial community dynamics is limited. Hence, we conducted a four-week tank experiment using different large daily temperature fluctuations (±5 °C and ±7 °C) accompanied by continuous warming conditions (26 °C to 29 °C) to investigate the effects on two common reef-building corals, Stylophora pistillata and Pocillopora acuta. During the experiment, the activity of coral host catalase and superoxide dismutase were measured, the photosynthetic ability of symbiotic algae was recorded, and the variation in bacterial communities was analyzed using the V6-V8 region of 16S rDNA. According to the results, different parts of the holobionts of two coral species exhibited varying response rates to the continuous warming conditions and diurnal temperature fluctuations. Additionally, it was found that diurnal temperature fluctuations may mitigate the heat stress on the host and reduce the changes in bacterial response to warming. Therefore, it is suggested that the holobionts of different coral species may adopt different adaptation and survival strategies in response to diurnal temperature fluctuations and warming. Finally, based on the response of these two coral species under the conditions of diurnal temperature fluctuations and continuous warming, Acinetobacter and Rhodobacteracea

关键词： Temperature distribution

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Comprehensive genomic profiling of the lung transcriptome in emphysema and idiopathic pulmonary fibrosis using RNA-Seq

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BMC Proc 2012年第SUPPL 6期6卷 P21-P21页

作者： Rebecca L Kusko John Brothers, II Gang Liu Lingqi Luo Brenda Juan Guardela John Tedrow Yuriy Aleksyev Ivana V Yang Mick Correll Mark Geraci John Quackenbush Frank Sciurba Marc Lenburg David A Schwartz Jennifer Beane Naftali Kaminski Avrum Spira Genetics and Genomics Graduate Program Boston University School of Medicine Boston MA USA Bioinformatics Program Boston University Boston MA USA Division of Computational Biomedicine Department of Medicine Boston University School of Medicine Boston MA USA Simmons Center for Interstitial Lung Disease and Department of Medicine University of Pittsburgh Medical Center Pittsburgh PA USA Department of Pathology and Laboratory Medicine Boston University School of Medicine Boston MA USA Center for Genes Environment and Health and Department of Medicine National Jewish Health Denver CO USA Dana-Farber Cancer Institute and Harvard School of Public Health Boston MA USA Department of Medicine University of Colorado School of Medicine Aurora CO USA

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Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks

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Nucleic acids research 2023年第13期51卷 6578-6592页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Bo-Jia Chen Yu-Te Lin Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung 402 Taiwan. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Program in Integrative & Complex Diseases Department of Nutrition Texas A&M University College Station TX 77843 USA. Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA.

In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples are available. Without using any information from real KO samples, GenKI is designed to capture shifting patterns in gene regulation caused by the KO perturbation in an unsupervised manner and provide a robust and scalable framework for gene function studies. To achieve this goal, GenKI adapts a variational graph autoencoder (VGAE) model to learn latent representations of genes and interactions between genes from the input WT scRNA-seq data and a derived single-cell gene regulatory network (scGRN). The virtual KO data is then generated by computationally removing all edges of the KO gene-the gene to be knocked out for functional study-from the scGRN. The differences between WT and virtual KO data are discerned by using their corresponding latent parameters derived from the trained VGAE model. Our simulations show that GenKI accurately approximates the perturbation profiles upon gene KO and outperforms the state-of-the-art under a series of evaluation conditions. Using publicly available scRNA-seq data sets, we demonstrate that GenKI recapitulates discoveries of real-animal KO experiments and accurately predicts cell type-specific functions of KO genes. Thus, GenKI provides an in-silico alternative to KO experiments that may partially replace the need for genetically modified animals or other genetically perturbed systems.

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Inhibition of ADAM9 promotes the selective degradation of KRAS and sensitizes pancreatic cancers to chemotherapy

Nature Cancer

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Nature Cancer 2024年第3期5卷 400-419页

作者： Huang, Yu-Kai Cheng, Wei-Chung Kuo, Ting-Ting Yang, Juan-Cheng Wu, Yang-Chang Wu, Heng-Hsiung Lo, Chia-Chien Hsieh, Chih-Ying Wong, Sze-Ching Lu, Chih-Hao Wu, Wan-Ling Liu, Shih-Jen Li, Yi-Chuan Lin, Ching-Chan Shen, Chia-Ning Hung, Mien-Chie Lin, Jaw-Town Yeh, Chun-Chieh Sher, Yuh-Pyng Graduate Institute of Biomedical Sciences China Medical University Taichung Taiwan Cancer Biology and Precision Therapeutics Center China Medical University Taichung Taiwan Ph.D. Program for Cancer Biology and Drug Discovery China Medical University and Academia Sinica Taichung Taiwan School of Chinese Medicine College of Chinese Medicine China Medical University Taichung Taiwan Graduate Institute of Integrated Medicine College of Chinese Medicine China Medical University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology College of Medical and Health Science Asia University Taichung Taiwan Center for Molecular Medicine China Medical University Hospital Taichung Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Taipei Taiwan National Institute of Infectious Diseases and Vaccinology National Health Research Institutes Miaoli Taiwan Graduate Institute of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Biological Science and Technology China Medical University Taichung Taiwan Division of Hematology and Oncology China Medical University Hospital Taichung Taiwan Genomics Research Center Academia Sinica Taipei Taiwan Division of Gastroenterology and Hepatology Department of Internal Medicine E-Da Hospital Kaohsiung Taiwan Department of Medicine School of Medicine China Medical University Taichung Taiwan Department of Surgery Organ Transplantation Center China Medical University Hospital Taichung Taiwan Institute of Biochemistry and Molecular Biology China Medical University Taichung Taiwan

Kirsten rat sarcoma virus (KRAS) signaling drives pancreatic ductal adenocarcinoma (PDAC) malignancy, which is an unmet clinical need. Here, we identify a disintegrin and metalloproteinase domain (ADAM)9 as a modulator of PDAC progression via stabilization of wild-type and mutant KRAS proteins. Mechanistically, ADAM9 loss increases the interaction of KRAS with plasminogen activator inhibitor 1 (PAI-1), which functions as a selective autophagy receptor in conjunction with light chain 3 (LC3), triggering lysosomal degradation of KRAS. Suppression of ADAM9 by a small-molecule inhibitor restricts disease progression in spontaneous models, and combination with gemcitabine elicits dramatic regression of patient-derived tumors. Our findings provide a promising strategy to target the KRAS signaling cascade and demonstrate a potential modality to enhance sensitivity to chemotherapy in PDAC. © The Author(s), under exclusive licence to Springer Nature America, Inc. 2024.

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Virtual Lung Screening Trial (VLST): An In Silico Replica of the National Lung Screening Trial for Lung Cancer Detection

arXiv

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arXiv 2024年

作者： Tushar, Fakrul Islam Vancoillie, Liesbeth McCabe, Cindy Kavuri, Amareswararao Dahal, Lavsen Harrawood, Brian Fryling, Milo Zarei, Mojtaba Sotoudeh-Paima, Saman Ho, Fong Chi Ghosh, Dhrubajyoti Harowicz, Michael R. Tailor, Tina D. Luo, Sheng Segars, W. Paul Abadi, Ehsan Lafata, Kyle J. Lo, Joseph Y. Samei, Ehsan Center for Virtual Imaging Trials Carl E. Ravin Advanced Imaging Laboratories Dept. of Radiology Duke University School of Medicine United States Dept. of Electrical & Computer Engineering Pratt School of Engineering Duke University United States Medical Physics Graduate Program Duke University United States Dept. of Biostatistics and Bioinformatics Duke University School of Medicine United States Dept. of Radiation Oncology Duke University School of Medicine United States

Importance: Clinical imaging trials are crucial for evaluation of medical innovations, but the process is inefficient, expensive, and ethically-constrained. Virtual imaging trial (VIT) approach addresses these limitations by emulating the components of a clinical trial. An in silico rendition of the National Lung Screening Trial (NCLS) via Virtual Lung Screening Trial (VLST) demonstrates the promise of VITs to expedite clinical trials, reduce risks to subjects, and facilitate the optimal use of imaging technologies in clinical settings. Objectives: To demonstrate that a virtual imaging trial platform can accurately emulate a major clinical trial, specifically the National Lung Screening Trial (NLST) that compared computed tomography (CT) and chest radiography (CXR) imaging for lung cancer screening. Design, Setting, and Participants: A virtual patient population of 294 subjects was created from human models (XCAT) emulating the NLST, with two types of simulated cancerous lung nodules. Each virtual patient in the cohort was assessed using simulated CT and CXR systems to generate images reflecting the NLST imaging technologies. Deep learning models trained for lesion detection, AI CT-Reader, and AI CXR-Reader served as virtual readers. Main Outcomes and Measures: The primary outcome was the difference in the Receiver Operating Characteristic Area Under the Curve (AUC) for CT and CXR modalities. Results: The study analyzed paired CT and CXR simulated images from 294 virtual patients. The AI CT-Reader outperformed the AI CXR-Reader across all levels of analysis. At the patient level, CT demonstrated superior diagnostic performance with an AUC of 0.92 (95% CI: 0.90-0.95), compared to CXR’s AUC of 0.72 (0.67-0.77). Subgroup analyses of lesion types revealed CT had significantly better detection of homogeneous lesions (AUC 0.97, 95% CI: 0.95-0.98) compared to heterogeneous lesions (0.89;0.86-0.93). Furthermore, when the specificity of the AI CT-Reader was adjusted to match

关键词： Lung cancer

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Characterizing the mechanical response of metallic glasses to uniaxial tension using a spring network model

arXiv

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arXiv 2023年

作者： Nawano, Aya Schroers, Jan Shattuck, Mark D. O’Hern, Corey S. Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department The City College of New York New YorkNY10031 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

Metallic glasses are frequently used as structural materials. Therefore, it is important to develop methods to predict their mechanical response as a function of the microstructure prior to loading. We develop a novel coarse-grained spring network model, which describes the mechanical response of metallic glasses using an equivalent series network of springs, which can break and re-form to mimic atomic rearrangements during deformation. To validate the spring network model, we perform numerical simulations of quasistatic, uniaxial tensile deformation of Lennard-Jones and embedded atom method (EAM) potentials for Cu50Zr50 metallic glasses in the absence of large-scale shear band formation. We consider samples prepared using a wide range of cooling rates and with different amounts of crystalline order. We show that both the Lennard-Jones and EAM models possess qualitatively similar stress σ versus strain γ curves. By specifying five parameters in the spring network model (ultimate strength, strain at ultimate strength, slopes of σ(γ) at γ = 0 and at large strain, and strain at fracture where σ = 0), we can accurately describe the form of the stress-strain curves during uniaxial tension for the computational studies of Cu50Zr50, as well as recent experimental studies of several Zr-based metallic glasses. For the computational studies of Cu50Zr50, we find that the yield strain distribution is shifted to larger strains for slowly cooled glasses compared to rapidly cooled glasses. In addition, the average number of new springs and their rate of formation decreases with decreasing cooling rate. These effects offset each other at large strains, causing the stress-strain curve to become independent of the sample preparation protocol in this regime. In future studies, we will extract the parameters that define the spring network model directly from atomic rearrangements that occur during uniaxial deformation. © 2023, CC BY-NC-ND.

关键词： Metallic glass

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Integration of Protein Structure and Population-Scale DNA Sequence Data for Disease Gene Discovery and Variant Interpretation

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Biomedical Data Science 1000年第1期5卷 141-161页

作者： Bian Li Bowen Jin John A. Capra William S. Bush 1Department of Biological Sciences and Center for Structural Biology Vanderbilt University Nashville Tennessee USA 2Graduate Program in Systems Biology and Bioinformatics Department of Nutrition School of Medicine Case Western Reserve University Cleveland Ohio USA 3Bakar Computational Health Sciences Institute and Department of Epidemiology and Biostatistics University of California San Francisco California USA email: tony@*** 4Cleveland Institute for Computational Biology Department of Population and Quantitative Health Sciences Case Western Reserve University Cleveland Ohio USA email: wsb36@case.edu

The experimental and computational techniques for capturing information about protein structures and genetic variation within the human genome have advanced dramatically in the past 20 years, generating extensive new data resources. In this review, we discuss these advances, along with new approaches for determining the impact a genetic variant has on protein function. We focus on the potential of new methods that integrate human genetic variation into protein structures to discover relationships to disease, including the discovery of mutational hotspots in cancer-related proteins, the localization of protein-altering variants within protein regions for common complex diseases, and the assessment of variants of unknown significance for Mendelian traits. We expect that approaches that integratethese data sources will play increasingly important roles in disease gene discovery and variant interpretation.

关键词： protein 3D structure population genetics variant interpretation disease gene discovery data integration

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Association of Multiple Environmental Toxicants with Markers of Early Kidney Injury in the Pregnant Women: An Exposome Approach

SSRN

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SSRN 2024年

作者： Chen, Jia-Jen Wu, Chia-Fang Li, Sih-Syuan Chen, Chu-Chih Wang, Yin-Han Hsieh, Chia-Jung Wang, Shu-Li Chen, Mei-Lien Wu, Ming-Tsang Ph.D. Program in Environmental and Occupational Medicine Kaohsiung Medical University Kaohsiung Taiwan Division of Biostatistics and Bioinformatics Institute of Population Health Sciences National Health Research Institutes Taiwan Department of Public Health Tzu Chi University Hualien Taiwan National Institute of Environmental Health Sciences National Health Research Institutes Miaoli Taiwan Institute of Environmental and Occupational Health Sciences School of Medicine National Yang Ming Chiao Tung University Taipei Taiwan Graduate Institute of Clinical Medicine Taiwan

Pregnant women are regularly exposed to a variety of environmental toxicants in daily life, posing a potential threat of their kidney injury before presence of clinical manifestations. There is a paucity of studies employing an exposome-based approach of kidney health in pregnant women. Thus, this study utilizes the above-mentioned strategy to identify the most significant environmental toxicants associated with early kidney injury in pregnant women in the cohort of TMICS (Taiwan Maternal and Infant Cohort Study). A total of 1,139 third-trimester pregnant women (week 29-40) were recruited between 2012 and 2015 and successfully collected one-spot urine sample for study. Exposure and outcome of interest in urine covered 16 biomonitoring chemicals, including melamine, 9 phthalate metabolites, nonylphenol (NP), bisphenol A (BPA), methylparaben (MP), ethylparaben (EP), propylparaben (PP), and butylparaben (BP), for exposure variables and NAG (N-acetyl-β-D-glucosaminidase) and albumin-to-creatinine ratio (ACR) for outcome variables. A two-tier strategy of statistical analyses was employed and data was randomly and evenly splitted to the training set (n = 569) and the validation set (n = 570). Using a weighted quantile sum (WQS) regression in the training set and subsequently a multivariate regression in the validation set, we found that NP is the most important chemical to link with markers of early kidney injury, both ACR and NAG. Other chemicals, including BPA and MP, are still needed to pay an attention on their potential nephrotoxicity in the pregnant women. Another cohort is necessary to reconfirm our findings. © 2024, The Authors. All rights reserved.

关键词： Regression analysis

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