4.6 Article

High Resolution Crystal Structure of Human β-Glucuronidase Reveals Structural Basis of Lysosome Targeting

Journal

PLOS ONE
Volume 8, Issue 11, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0079687

Keywords

-

Funding

  1. Indo-US Science and Technology Forum

Ask authors/readers for more resources

Human beta-glucuronidase (GUS) cleaves beta-D-glucuronic acid residues from the non-reducing termini of glycosaminoglycan and its deficiency leads to mucopolysaccharidosis type VII (MPSVII). Here we report a high resolution crystal structure of human GUS at 1.7 angstrom resolution and present an extensive analysis of the structural features, unifying recent findings in the field of lysosome targeting and glycosyl hydrolases. The structure revealed several new details including a new glycan chain at Asn272, in addition to that previously observed at Asn173, and coordination of the glycan chain at Asn173 with Lys197 of the lysosomal targeting motif which is essential for phosphotransferase recognition. Analysis of the high resolution structure not only provided new insights into the structural basis for lysosomal targeting but showed significant differences between human GUS, which is medically important in its own right, and E. coli GUS, which can be selectively inhibited in the human gut to prevent prodrug activation and is also widely used as a reporter gene by plant biologists. Despite these differences, both human and E. coli GUS share a high structure homology in all three domains with most of the glycosyl hydrolases, suggesting that they all evolved from a common ancestral gene.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Computer Science, Artificial Intelligence

Deep learning-based multidimensional feature fusion for classification of ECG arrhythmia

Jianfeng Cui, Lixin Wang, Xiangmin He, Victor Hugo C. De Albuquerque, Salman A. AlQahtani, Mohammad Mehedi Hassan

Summary: Feature extraction plays a crucial role in arrhythmia classification. This paper presents a feature extraction method that combines traditional approaches and 1D-CNN to improve the accuracy of arrhythmia classification. Experimental results show that the proposed method achieves an average classification accuracy of 98.35%, surpassing the latest methods.

NEURAL COMPUTING & APPLICATIONS (2023)

Article Plant Sciences

Drought Stress in Brassica napus: Effects, Tolerance Mechanisms, and Management Strategies

Maria Batool, Ali Mahmoud El-Badri, Muhammad Umair Hassan, Yang Haiyun, Wang Chunyun, Yan Zhenkun, Kuai Jie, Bo Wang, Guangsheng Zhou

Summary: Drought poses serious threats to global crop production, including oilseed crops like Brassica napus L. Various approaches have been used to increase drought tolerance, but there is room for further improvement. Future research should focus on developing genetically engineered rapeseed plants with enhanced drought tolerance.

JOURNAL OF PLANT GROWTH REGULATION (2023)

Article Biochemistry & Molecular Biology

Identifying Isoononin and Candidissiol as Rho-associated protein kinase 1 (ROCK1) inhibitors: a combined virtual screening and MD simulation approach

Bader Saud Alotaibi, Jatin Joshi, Mohammad Raghibul Hasan, Mohd Shahnawaz Khan, Salem Hussain Alharethi, Taj Mohammad, Fahad A. Alhumaydhi, Abdelbaset Mohamed Elasbali, Md Imtaiyaz Hassan

Summary: In this study, potential inhibitors of ROCK1 were identified through structure-based virtual screening of natural compounds. Isoononin and Candidissiol showed appreciable binding affinity and selectivity towards ROCK1, and molecular dynamics simulations confirmed their stability.

JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS (2023)

Article Computer Science, Information Systems

Domain generated algorithms detection applying a combination of a deep feature selection and traditional machine learning models

Mohamed Hassaoui, Mohamed Hanini, Said El Kafhali

Summary: The use of C2 servers in cyberattacks has increased significantly, with attackers using DGA technique to hide their servers. Existing techniques for binary classification of domain names have issues with real-time detection and sensitivity to data. This paper proposes the DTFS-DGA model, which combines neural networks and traditional machine learning models to detect DGA in real-time without relying on reverse engineering and being insensitive to data size.

JOURNAL OF COMPUTER SECURITY (2023)

Article Biochemistry & Molecular Biology

Pan-cancer analysis of Chromobox (CBX) genes for prognostic significance and cancer classification

Ahmad Abu Turab Naqvi, Syed Afzal Murtaza Rizvi, Md. Imtaiyaz Hassan

Summary: The expression of CBX genes was found to be significantly altered in various cancers, suggesting their potential as biomarkers for therapeutic intervention. Machine learning models showed excellent performance in cancer classification.

BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE (2023)

Article Biochemistry & Molecular Biology

Targeting inhibition of microtubule affinity regulating kinase 4 by Harmaline: Strategy to combat Alzheimer's disease

Mohd Adnan, Saleha Anwar, Debarati DasGupta, Mitesh Patel, Abdelbaset Mohamed Elasbali, Hassan H. Alhassan, Alaa Shafie, Arif Jamal Siddiqui, Fevzi Bardakci, Mejdi Snoussi, Md. Imtaiyaz Hassan

Summary: In this study, the alkaloid Harmaline (HAR) was investigated for its potential as a MARK4 inhibitor. Molecular docking and fluorescence binding studies showed a strong binding affinity between HAR and MARK4, and HAR significantly inhibited the kinase activity of MARK4. Structural investigations revealed that HAR binds to the active site pocket of MARK4 and forms multiple non-covalent interactions with biologically important residues. These findings suggest that HAR could be a potential therapeutic agent for MARK4-related diseases, including Alzheimer's disease.

INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES (2023)

Article Biochemistry & Molecular Biology

Pharmacological features, health benefits and clinical implications of honokiol

Fatima Khatoon, Sabeeha Ali, Vijay Kumar, Abdelbaset Mohamed Elasbali, Hassan H. Alhassan, Salem Hussain Alharethi, Asimul Islam, Md Imtaiyaz Hassan

Summary: Honokiol is a natural polyphenolic compound extracted from Magnolia grandiflora, with various pharmacological properties and potential therapeutic implications, including antimicrobial and anti-tumorigenic effects. Recent studies have also suggested its potential role in COVID-19 therapy.

JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS (2023)

Article Biochemistry & Molecular Biology

Unravelling hub genes as potential therapeutic targets in lung cancer using integrated transcriptomic meta-analysis and in silico approach

Aiman Mushtaq, Prithvi Singh, Gulnaz Tabassum, Taj Mohammad, Md Imtaiyaz Hassan, Mansoor Ali Syed, Ravins Dohare

Summary: This study identified key genes in lung cancer and their potential as biomarkers for disease prognosis and targeted therapy. Several potential drug candidates were also identified.

JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS (2023)

Article Chemistry, Physical

Molecular basis of structural stability of Irisin: A combined molecular dynamics simulation and in vitro studies for Urea-induced denaturation

Rashid Waseem, Neetu Singh Yadav, Tanzeel Khan, Faizan Ahmad, Syed Naqui Kazim, Md Imtaiyaz Hassan, Amresh Prakash, Asimul Islam

Summary: In this study, urea-induced denaturation was used to investigate the conformational changes of irisin. The results showed that the unfolding of irisin occurs in a biphasic manner, with an intermediate state (I) populated at 2.5 M urea concentration. Molecular dynamics (MD) simulations confirmed the presence of a molten globule state during the unfolding process of irisin.

JOURNAL OF MOLECULAR LIQUIDS (2023)

Review Polymer Science

Green Composites Based on Animal Fiber and Their Applications for a Sustainable Future

Guravtar Singh Mann, Naved Azum, Anish Khan, Malik Abdul Rub, Md Imtaiyaz Hassan, Kisa Fatima, Abdullah M. Asiri

Summary: Global climate change has already caused various environmental effects and led to a shift in focus towards sustainable materials. Green composites, which combine renewable fibers with polymers, offer a wide range of applications and superior features compared to conventional materials.

POLYMERS (2023)

Review Nutrition & Dietetics

Comprehensive Insights into Biological Roles of Rosmarinic Acid: Implications in Diabetes, Cancer and Neurodegenerative Diseases

Md. Khabeer Azhar, Saleha Anwar, Gulam Mustafa Hasan, Anas Shamsi, Asimul Islam, Suhel Parvez, Md. Imtaiyaz Hassan

Summary: Rosmarinic acid (RA) is an abundant phytochemical with anti-inflammatory and antioxidant properties, playing significant roles in cancer, neuroprotection, and diabetes.

NUTRIENTS (2023)

Review Chemistry, Multidisciplinary

Therapeutic Targeting of Regulated Signaling Pathways of Non-Small Cell Lung Carcinoma

Gulam Mustafa Hasan, Md. Imtaiyaz Hassan, Sukhwinder Singh Sohal, Anas Shamsi, Manzar Alam

Summary: Non-small cell lung carcinoma (NSCLC) is the most common cancer globally, and phytochemicals and small molecule inhibitors have been found to effectively prevent NSCLC and other types of cancers by regulating signaling pathways. This review focuses on the bioactive compounds and small-molecule inhibitors, such as EGCG, Perifosine, ABT-737, Thymoquinine, Quercetin, Venetoclax, Gefitinib, and Genistein, and discusses their potential in NSCLC therapy.

ACS OMEGA (2023)

Article Chemistry, Medicinal

Synthesis, Structural Modification, and Bioactivity Evaluation of Substituted Acridones as Potent Microtubule Affinity-Regulating Kinase 4 Inhibitors

Maria Voura, Saleha Anwar, Ioanna Sigala, Eleftheria Parasidou, Souzanna Fragoulidou, Md. Imtaiyaz Hassan, Vasiliki Sarli

Summary: In this study, derivatives of 2-methylacridone were synthesized and tested for their MARK4 kinase inhibitory activity. The derivatives with piperazine and tryptophan moieties showed high antiproliferative activity against cancer cells.

ACS PHARMACOLOGY & TRANSLATIONAL SCIENCE (2023)

Article Engineering, Civil

DLTIF: Deep Learning-Driven Cyber Threat Intelligence Modeling and Identification Framework in IoT-Enabled Maritime Transportation Systems

Prabhat Kumar, Govind P. Gupta, Rakesh Tripathi, Sahil Garg, Mohammad Mehedi Hassan

Summary: The recent growth of IoT technologies in the maritime industry has digitalized Maritime Transportation Systems (MTS), but also introduced cybersecurity threats. Cyber Threat Intelligence (CTI) is an effective security strategy, but existing solutions have low detection rates and high false alarm rates. To address these challenges, an automated framework called DLTIF has been proposed, which can accurately identify threat types.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2023)

Article Engineering, Civil

Heterogeneous Blockchain and AI-Driven Hierarchical Trust Evaluation for 5G-Enabled Intelligent Transportation Systems

Xiaoding Wang, Sahil Garg, Hui Lin, Georges Kaddoum, Jia Hu, Mohammad Mehedi Hassan

Summary: This paper proposes a hierarchical trust evaluation strategy based on heterogeneous blockchain, utilizing federated deep learning technology for Intelligent Transportation Systems (ITS) security.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2023)

No Data Available