Mengxu Zhu

ORCID: 0000-0003-1277-2000
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Research Areas
  • Cancer therapeutics and mechanisms
  • Lung Cancer Treatments and Mutations
  • Computational Drug Discovery Methods
  • Remote Sensing and LiDAR Applications
  • Protein Structure and Dynamics
  • RNA and protein synthesis mechanisms
  • Machine Learning in Materials Science
  • Food Quality and Safety Studies
  • Advanced Image and Video Retrieval Techniques
  • Advanced Data Compression Techniques
  • Chemical Synthesis and Analysis
  • vaccines and immunoinformatics approaches
  • Scientific Computing and Data Management
  • Advanced Image Fusion Techniques
  • Advanced Neural Network Applications
  • Aquaculture disease management and microbiota
  • thermodynamics and calorimetric analyses
  • Water Quality Monitoring Technologies
  • Synthesis and biological activity
  • Immunotherapy and Immune Responses
  • Fermentation and Sensory Analysis
  • Vibrio bacteria research studies
  • SARS-CoV-2 and COVID-19 Research
  • Microplastics and Plastic Pollution
  • Lung Cancer Research Studies

Hainan University
2025

North China Institute of Aerospace Engineering
2021-2022

City University of Hong Kong
2019-2022

Jiangnan University
2016

Mutation-induced variation of protein-ligand binding affinity is the key to many genetic diseases and emergence drug resistance, therefore predicting such mutation impacts great importance. In this work, we aim predict on using efficient structure-based, computational methods.Relying consolidated databases experimentally determined data characterize change upon based a number local geometrical features monitor feature differences during molecular dynamics (MD) simulations. The are quantified...

10.1016/j.csbj.2020.02.007 article EN cc-by-nc-nd Computational and Structural Biotechnology Journal 2020-01-01

Accurately predicting protein-ligand binding affinities can substantially facilitate the drug discovery process, but it remains as a difficult problem. To tackle challenge, many computational methods have been proposed. Among these methods, free energy-based simulations and machine learning-based scoring functions potentially provide accurate predictions. In this paper, we review two classes of following number thermodynamic cycles for feature-representation taxonomy functions. More recent...

10.1093/bib/bbaa107 article EN Briefings in Bioinformatics 2020-05-08

Non-small cell lung cancer (NSCLC) caused by mutation of the epidermal growth factor receptor (EGFR) is a major cause death worldwide. Tyrosine kinase inhibitors (TKIs) EGFR have been developed and show promising results at initial stage therapy. However, in most cases, their efficacy becomes limited due to emergence secondary mutations causing drug resistance after about year. In this work, we investigated mechanism these mutations. We performed molecular dynamics (MD) simulations EGFR-drug...

10.1109/jbhi.2020.3027511 article EN IEEE Journal of Biomedical and Health Informatics 2020-09-29

Water surface plastic pollution turns out to be a global issue, having aroused rising attention worldwide. How monitor water waste in real time and accurately collect analyze the relevant numerical data has become hotspot environment research. (1) Background: Over past few years, unmanned aerial vehicles (UAVs) have been progressively adopted conduct studies on monitoring of waste. On whole, monitored are stored UAVS subsequently retrieved analyzed, thereby probably causing loss real-time...

10.3390/pr10010131 article EN Processes 2022-01-10

Abstract Background Epidermal growth factor receptor (EGFR) and its signaling pathways play a vital role in pathogenesis of lung cancer. By disturbing EGFR signaling, mutations may lead to progression cancer or the emergence resistance EGFR-targeted drugs. Results We investigated correlation between EGFR-receptor tyrosine kinase (RTK) crosstalk network, order uncover drug mechanism induced by mutations. For several wild type (WT) mutated proteins, we measured EGFR-RTK interactions using...

10.1186/s12860-021-00358-6 article EN cc-by BMC Molecular and Cell Biology 2021-06-10

Non-small cell lung cancer (NSCLC) with activating epidermal growth factor receptor (EGFR) is a major cause of death worldwide. Tyrosine kinase inhibitors (TKIs) have been developed to target the EGFR, stop downstream signaling and tumor growth. Despite initial good results, drug resistance after one year due secondary mutation. The L858R, T790M mutation their combination change conformational redistribution EGFR. To combat caused by mutation, AZD9291 third generation was approved food...

10.1109/bibm47256.2019.8983351 article EN 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2019-11-01

UAV remote sensing multispectral image has become more and popular because of its high temporal spatial resolution. However, the characteristics large number bands, amount data, spectral redundancy. These bring great challenges to storage transmission. According images, an end-to-end compression framework based on CNN is adopted. The whole composed self-encoder, quantization structure, entropy coding rate distortion optimization. innovation this paper propose a new multi-source data...

10.1109/icgmrs55602.2022.9849323 article EN 2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS) 2022-04-22

Epidermal growth factor receptor (EGFR) plays an important role in lung cell proliferation. Dimerization of EGFR family members and other tyrosine kinases (RTKs) act as a vital controller for life cycle signals. Mutations the kinase domain may disorder signaling networks lead to cancer. Drug resistance occurs several generations drugs due genetic mutations, there is very less understanding about mechanism EGFR-mutated drug resistance. In this work, we investigate wild type protein its...

10.1109/access.2020.3048427 article EN cc-by IEEE Access 2020-12-31

Understanding protein dynamics are essential for deciphering functional mechanisms and developing molecular therapies. However, the complex high-dimensional interatomic interactions of biological processes pose significant challenge existing computational techniques. In this paper, we approach problem first time by introducing Deep Signature, a novel computationally tractable framework that characterizes based on their evolving trajectories. Specifically, our incorporates soft spectral...

10.48550/arxiv.2410.02847 preprint EN arXiv (Cornell University) 2024-10-03

Background: COVID-19 emerged in late 2019 and became a pandemic disease with severe mortality morbidity. No specific remedy exists at present, but some drugs, such as Dexamethasone, have shown clinical benefits against the causative agent, SARS-CoV-2 virus. Objective: To analyze binding affinity between drugs an protein through geometrical methods to study theoretical effectiveness of Dexamethasone potential treatment for COVID-19. Method: The target was compared those different inhibitors....

10.2174/1574893616666210625164651 article EN Current Bioinformatics 2021-06-28

Earth and Space Science Open Archive This preprint has been submitted to is under consideration at Science. ESSOAr a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]A Deep Learning Model Automatic Plastic Waste Monitoring Using Unmanned Aerial Vehicle (UAV) DataAuthorsWenlongHaniDWeiLuoYongtaoJinMengxuZhuSee all authors Wenlong HaniDCorresponding Author•...

10.1002/essoar.10507932.1 preprint EN cc-by 2021-09-09

Covid-19 has become a world pandemic for years. With the appearance of mutations, immune escape problem, reducing effectiveness vaccines and antibodies. To reveal mechanism escape, we analyze geometrical properties receptor-binding domain in SARS-CoV-2 spike protein, which plays vital role reaction. Several important variants are taken as examples, wild type model is prepared reference. The computational method applied to simulate behaviors models, alpha shape algorithm employed extract data...

10.1109/bibm55620.2022.9995089 article EN 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2022-12-06
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