4.6

CiteScore

2.2

Impact Factor
  • ISSN 1674-8301
  • CN 32-1810/R
Usman Sumo Friend Tambunan, Rizky Archintya Rachmania, Arli Aditya Parikesit. In silico modification of oseltamivir as neuraminidase inhibitor of influenza A virus subtype H1N1[J]. The Journal of Biomedical Research, 2015, 29(2): 150-159. DOI: 10.7555/JBR.29.20130024
Citation: Usman Sumo Friend Tambunan, Rizky Archintya Rachmania, Arli Aditya Parikesit. In silico modification of oseltamivir as neuraminidase inhibitor of influenza A virus subtype H1N1[J]. The Journal of Biomedical Research, 2015, 29(2): 150-159. DOI: 10.7555/JBR.29.20130024

In silico modification of oseltamivir as neuraminidase inhibitor of influenza A virus subtype H1N1

More Information
  • Received Date: April 30, 2013
  • Revised Date: June 25, 2013
  • This research focused on the modification of the functional groups of oseltamivir as neuraminidase inhibitor against influenza A virus subtype H1N1. Interactions of three of the best ligands were evaluated in the hydrated state using molecular dynamics simulation at two different temperatures. The docking result showed that AD3BF2D ligand (N-[(1S,6R)-5-amino-5-{[(2R,3S,4S)-3,4-dihydroxy-4-(hydroxymethyl) tetrahydrofuran-2- yl]oxy}-4-formylcyclohex-3-en-1-yl]acetamide-3-(1-ethylpropoxy)-1-cyclohexene-1-carboxylate) had better binding energy values than standard oseltamivir. AD3BF2D had several interactions, including hydrogen bonds, with the residues in the catalytic site of neuraminidase as identified by molecular dynamics simulation. The results showed that AD3BF2D ligand can be used as a good candidate for neuraminidase inhibitor to cope with influenza A virus subtype H1N1.
  • Related Articles

    [1]Izzatullo Ziyoyiddin o`g`li Abdullaev, Ulugbek Gapparjanovich Gayibov, Sirojiddin Zoirovich Omonturdiev, Sobirova Fotima Azamjonovna, Sabina Narimanovna Gayibova, Takhir Fatikhovich Aripov. Molecular pathways in cardiovascular disease under hypoxia: Mechanisms, biomarkers, and therapeutic targets[J]. The Journal of Biomedical Research. DOI: 10.7555/JBR.38.20240387
    [2]Hamed Amini Amirkolaee, Hamid Amini Amirkolaee. Medical image translation using an edge-guided generative adversarial network with global-to-local feature fusion[J]. The Journal of Biomedical Research, 2022, 36(6): 409-422. DOI: 10.7555/JBR.36.20220037
    [3]Qian Sun, Yusi Hu, Saiyue Deng, Yanyu Xiong, Zhili Huang. A visualization pipeline for in vivo two-photon volumetric astrocytic calcium imaging[J]. The Journal of Biomedical Research, 2022, 36(5): 358-367. DOI: 10.7555/JBR.36.20220099
    [4]Li Tiannv, Sun Jin, Hu Yao, Yang Min, Shi Haibin, Tang Lijun. Near-infrared fluorescent labeled CGRRAGGSC peptides for optical imaging of IL-11Rα in athymic mice bearing tumor xenografts[J]. The Journal of Biomedical Research, 2019, 33(6): 391-397. DOI: 10.7555/JBR.33.20180136
    [5]Xiaoquan Xu, Feiyun Wu, Yunxiang Chen, Hao Hu, Meiling Bao. CT and multimodal imaging findings of primary orbital Ewing's sarcoma involving the middle cranial fossa: a case report[J]. The Journal of Biomedical Research, 2017, 31(2): 170-174. DOI: 10.7555/JBR.30.20140132
    [6]Timothy McAlindon, Eckart Bartnik, Janina S. Ried, Lenore Teichert, Matthias Herrmann, Klaus Flechsenhar. Determination of serum biomarkers in osteoarthritis patients: a previous interventional imaging study revisited[J]. The Journal of Biomedical Research, 2017, 31(1): 25-30. DOI: 10.7555/JBR.31.20150167
    [7]Hongming Zhuang, Ion Codreanu. Growing applications of FDG PET-CT imaging in non-oncologic conditions[J]. The Journal of Biomedical Research, 2015, 29(3): 189-202. DOI: 10.7555/JBR.29.20140081
    [8]Marina Piccinelli, Ernest Garcia. Multimodality image fusion for diagnosing coronary artery disease[J]. The Journal of Biomedical Research, 2013, 27(6): 439-451. DOI: 10.7555/JBR.27.20130138
    [9]Yumin Zhang, Gerard B. Fox. PET imaging for receptor occupancy: meditations on calculation and simplification[J]. The Journal of Biomedical Research, 2012, 26(2): 69-76. DOI: 10.1016/S1674-8301(12)60014-1
    [10]Lihua Liu, Ming Zhang, Yuan Wang, Min Li. The relationship between the expression of tumor matrix-metalloproteinase and the characteristics of magnetic resonance imaging of human gliomas[J]. The Journal of Biomedical Research, 2010, 24(2): 124-131.
  • Cited by

    Periodical cited type(1)

    1. Tian M, Li Y, Chen H. 18F-FDG PET/CT Image Deep Learning Predicts Colon Cancer Survival. Contrast Media Mol Imaging, 2023, 2023: 2986379. DOI:10.1155/2023/2986379

    Other cited types(0)

Catalog

    Article Metrics

    Article views (4212) PDF downloads (549) Cited by(1)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return