4.7 Article

Molecular Insights into the Interaction of RONS and Thieno[3,2-c]pyran Analogs with SIRT6/COX-2: A Molecular Dynamics Study

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SCIENTIFIC REPORTS
卷 8, 期 -, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41598-018-22972-9

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  1. Basic Science Research Program of the National Research Foundation of Korea (NRF) - Ministry of Education, Science, and Technology at Gachon University of Medicine and Science, Incheon city, Korea [2017R1C1B2003380]
  2. Science & Engineering Research Board (SERB), New Delhi at the All India Institute of Medical Sciences, Jodhpur, India [SB/YS/LS-130/2014]
  3. DST, New Delhi [INT/RUS/RFBR/P-169]
  4. CSIR, New Delhi [02(0189)/14/EMR-II]
  5. National Institute of Supercomputing and Network/Korea Institute of Science and Technology Information [KSC-2017-C1-0013, KSC-2017-C2-0017]
  6. Research Foundation-Flanders (FWO) [12J5617N]

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SIRT6 and COX-2 are oncogenes target that promote the expression of proinflammatory and pro-survival proteins through a signaling pathway, which leads to increased survival and proliferation of tumor cells. However, COX-2 also suppresses skin tumorigenesis and their relationship with SIRT6, making it an interesting target for the discovery of drugs with anti-inflammatory and anti-cancer properties. Herein, we studied the interaction of thieno[3,2-c] pyran analogs and RONS species with SIRT6 and COX-2 through the use of molecular docking and molecular dynamic simulations. Molecular docking studies revealed the importance of hydrophobic and hydrophilic amino acid residues for the stability. The molecular dynamics study examined conformational changes in the enzymes caused by the binding of the substrates and how those changes affected the stability of the protein-drug complex. The average RMSD values of the backbone atoms in compounds 6 and 10 were calculated from 1000 ps to 10000 ps and were found to be 0.13 nm for both compounds. Similarly, the radius of gyration values for compounds 6 and 10 were found to be 1.87 +/- 0.03 nm and 1.86 +/- 0.02 nm, respectively. The work presented here, will be of great help in lead identification and optimization for early drug discovery.

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