Identification of potential modulators of IFITM3 by in-silico modeling and virtual screening

被引:0
|
作者
Vikas Tiwari
Shruthi Viswanath
机构
[1] Tata Institute of Fundamental Research,National Centre for Biological Sciences
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
IFITM3 is a transmembrane protein that confers innate immunity. It has been established to restrict entry of multiple viruses. Overexpression of IFITM3 has been shown to be associated with multiple cancers, implying IFITM3 to be good therapeutic target. The regulation of IFITM3 activity is mediated by multiple post-translational modifications (PTM). In this study, we have modelled the structure of IFITM3, consistent with experimental predictions on its membrane topology. MD simulation in membrane-aqueous environment revealed the stability of the model. Ligand binding sites on the IFITM3 surface were predicted and it was observed that the best site includes important residues involved in PTM and has good druggable score. Molecular docking was performed using FDA approved ligands and natural ligands from Super Natural II database. The ligands were re-ranked by calculating binding free energy. Select docking complexes were simulated again to substantiate the binding between ligand and IFITM3. We observed that known drugs like Eluxadoline and natural products like SN00224572 and Parishin A have good binding affinity against IFITM3. These ligands form persistent interactions with key lysine residues (Lys83, Lys104) and hence can potentially alter the activity of IFITM3. The results of this computational study can provide a starting point for experimental investigations on IFITM3 modulators.
引用
收藏
相关论文
共 50 条
  • [41] In-silico screening and identification of glycomimetic as potential human sodium-glucose co-transporter 2 inhibitor
    Ganwir, Prerna
    Bhadane, Rajendra
    Chaturbhuj, Ganesh U.
    COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2024, 110
  • [42] IN-SILICO MOLECULAR SCREENING OF NATURAL PLANT PRODUCTS FOR THE IDENTIFICATION OF NOVEL POTENTIAL CHEMOTHERAPEUTIC AGENTS AGAINST BREAST CANCER
    Megana, K. S. N. M.
    Suneetha, Y.
    INTERNATIONAL JOURNAL OF PHARMACEUTICAL SCIENCES AND RESEARCH, 2019, 10 (10): : 4546 - 4551
  • [43] Evaluation of Virtual Screening Strategies for the Identification of γ-Secretase Inhibitors and Modulators
    Ioppolo, Alicia
    Eccles, Melissa
    Groth, David
    Verdile, Giuseppe
    Agostino, Mark
    MOLECULES, 2022, 27 (01):
  • [44] Discovery of novel TLR modulators by Molecular Modeling and Virtual Screening
    Manuela S Murgueitio
    Sandra Santos-Sierra
    Gerhard Wolber
    Journal of Cheminformatics, 4 (Suppl 1)
  • [45] In-silico identification of potential inhibitors against FabI protein in Klebsiella pneumoniae
    Khan, Shama
    Madhi, Shabir A.
    Olwagen, Courtney
    JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 2024, 42 (03): : 1506 - 1517
  • [46] Identification of a new class of potential antimalaria agents using in-silico methodology
    Richardson, Reg
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2015, 249
  • [47] In silico identification of potential drug targets in Clostridium difficile R20291: modeling and virtual screening analysis of a candidate enzyme MurG
    Vijayalakshmi Ezhilarasan
    Om Prakash Sharma
    Archana Pan
    Medicinal Chemistry Research, 2013, 22 : 2692 - 2705
  • [48] In silico identification of potential drug targets in Clostridium difficile R20291: modeling and virtual screening analysis of a candidate enzyme MurG
    Ezhilarasan, Vijayalakshmi
    Sharma, Om Prakash
    Pan, Archana
    MEDICINAL CHEMISTRY RESEARCH, 2013, 22 (06) : 2692 - 2705
  • [49] In-silico identification of high potential SSH-2 specific inhibitors
    Mui, Matthew K.
    Levesque, Marshall J.
    Chien, Shu
    Haga, Jason H.
    FASEB JOURNAL, 2010, 24
  • [50] Identification of Potential Drug Targets of Leishmania infantum by In-silico Genome Analysis
    Suthar, Neeraj
    Goyal, Arun
    Dubey, Vikash Kumar
    LETTERS IN DRUG DESIGN & DISCOVERY, 2009, 6 (08) : 620 - 622