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  • Simulation methods In our study the TIP P model


    Simulation methods In our study, the TIP3P model is applied for water, AMBER99sb force field [24] is used to describe three types of EGFR, including the wild type (PDB: 2ITY) [25], its mutant G719S (PDB: 2ITO) [25] and mutant T790M (PDB: 3IKA) [26]. The force field of Tubemoside molecule is parameterized with optimized geometry configuration by AmberTools [27] force field topology builder, its bonded and non-bonded parameters were taken from the AMBER-GAFF [28] force field. MD simulations are performed by the Gromacs-5.0 package [29] and carried out in the NPT ensemble with periodic boundary conditions in all three dimensions (3D). All snapshots of protein are generated by the VMD-1.9.2 software [30]. The temperature and pressure are maintained at 300 K and 1.0 atm by the V-rescale thermostat and Parrinello-Rahman, respectively. The SHAKE algorithm [31] is used to freeze the OH bond of molecules in the system. The vdW interactions are calculated with 1.2 nm cutoff. Meanwhile, the particle mesh Ewald (PME) algorithm [32] is implemented to compute the long-range electrostatic interactions. The time step is 1 fs and the trajectory data is collected every 1 ps. The structure of each ensemble was relaxed through 10,000 steps of prmt5 inhibitor minimization. Equilibration of the ensembles was conducted in two parts: the one of 1 ns constant NVT simulation, and another of 5 ns constant NPT simulation. Afterward, total 300ns MD trajectories (50ns per job) were collected and used to analysis.
    Results and discussion
    Conflict of interest
    Acknowledgements This study was financially supported by Shaanxi Administration of Traditional Chinese Medicine Projects (No. 15-ZY017), Department of Science and Technology of Shaanxi Province Projects (No. 2017SF-297) and Xi’an Science and Technology Bureau Projects (No. 2016054SF/YX10(5)).
    Introduction Hypoxia is a common condition in the core of a wide range of solid tumors, which changes the characteristics of cancer cells and contributes to therapy resistance (Bertout et al., 2008; Semenza, 2012; Wilson and Hay, 2011). As tumor mass gradually grows, the oxygen concentration decreases as the distance of tumor cells from blood vessels increases, creating mild to severe hypoxia. In response to hypoxia, tumor cells will either become resistant to cancer therapies or undergo cell death. One key factor that plays a central role in hypoxia induced resistance to tumor therapeutics such as radioresistance is the epidermal growth factor receptor (EGFR) (Sigismund et al., 2018), which is a membrane-associated receptor belonging to the ErbB/HER family of tyrosine kinases. Ligand binding, as well as various intrinsic or therapy-induced cellular stresses trigger EGFR trafficking and signaling, leading to a multitude of cellular responses including cell growth, proliferation, apoptosis, migration, and angiogenesis. Evidences have shown that hypoxic microenvironment in solid tumors not only translationally upregulates EGFR expression through HIF2α (Franovic et al., 2007), but also transactivates EGFR and triggers its internalization and non-degradative endosomal accumulation (Tan et al., 2016). In return, EGFR elicits the cellular response to hypoxia by activating its downstream signals such as ERK and AKT to promote the transcription of target genes, which are involved in EGFR-mediated cancer cell survival and therapy resistance (Guo et al., 2015; Yarden and Sliwkowski, 2001). Although the expression of EGFR was reported to be upregulated by hypoxic conditions in breast, non-small-cell lung, cervical and head and neck cancers, some recent researches demonstrated that EGFR was significantly downregulated in hypoxic areas of the head and neck cancer (Mayer et al., 2016). EGFR signaling was found to be notably attenuated under hypoxic conditions (Garvalov et al., 2014; Nijkamp et al., 2011). The reason for these contradicting findings and the mechanism underlying hypoxia-mediated EGFR downregulation is still unclear.