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    Critical Residues in Hsp70 Nucleotide Binding Domain for Challenges in Drug Design
    (Bentham Science Publ Ltd, 2022) Ergul, Mustafa; Aktan, Fugen; Tutar, Yusuf
    Background: The association of a drug with its target protein correlates to its medicinal activity and the microenvironment plays a key role in this association. The key challenge is to iden-tify mutations which unlikely to respond to designed drugs. Objective: Hsp70 is an anti-apoptotic factor and tumor cells overexpress Hsp70 to survive against anti-cancer agents. The impact of pathogenic mutations on Hsp70 is unknown. Elucidation of these alterations is essential to understand the molecular switch mechanism. Thus, critical spots on Hsp70 Nucleotide Binding Domain (NBD) are important since mutation-driven sensitivity may be useful in designing innovative inhibitors. Methods: ATP, AMP-PNP (non-hydrolyzable analog of ATP) along with commercially available compounds VER-155008 (ATP analog and competitive inhibitor) and MKT-077 (allosteric inhibi-tor of ADP bound form) were docked to Hsp70 NBD structurein silico to identify critical amino acids of inhibition mechanism. Site-directed mutagenesis of the determined critical residues along with ATP hydrolysis and luciferase refolding was performed. Wild-type and mutant Hsp70s were compared to determine the effect on protein functions in the presence or absence of inhibitors. Results: This study identified three mutants that have a loss of function for Hsp70, which may alter the drug inhibition activity as oncogenic cells have multiple mutations. Conclusion: Two commercial inhibitors employed here that mimic ATP and ADP states, respec-tively, are not affected by these mutational perturbations and displayed effective interference for Hsp70 functions. Designing inhibitors by considering these critical residues may improve drug de-sign and increase drug efficiency.
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    Perturbation of HSP Network in MCF-7 Breast Cancer Cell Line Triggers Inducible HSP70 Expression and Leads to Tumor Suppression
    (Bentham Science Publ Ltd, 2020) Ergul, Mustafa; Aktan, Fugen; Yildiz, Mehmet T.; Tutar, Yusuf
    Background: Heat shock protein 70 (HSP70) is constitutively expressed in normal cells but aberrantly expressed in several types of tumor cells, helping their survival in extreme conditions. Thus, specific inhibition of HSP70 in tumor cells is a promising strategy in the treatment of cancer. HSP70 has a variety, of isoforms in the cellular organelles and form different functions by co-ordinating and cooperating with co chaperones. Cancer cells overexpress HSPs during cell growth and proliferation and HSP network provides resistance against apoptosis. The present study aimed to evaluate quantitative changes in HSPs- and cancer-associated gene expressions and their interactions in the presence of 2-phenylethyenesulfonamide (PES) in MCF-7 cells. Methods: AntiproliCerative activity of PES was evaluated using the wXTT assay. Inducible HSP70 (HSP70i) levels in the PES-treated cells were determined using the ELISA kit. PCR Array was performed to assess the IISPs- and cancer-pathway focused gene expression profiling. Gene network analysis was performed using the X2K, yLd (N1.3.18.1) programs, and web-based gene list enrichment analysis tool Enrichr. Results: The results demonstrated that PES exposure increased the amount of both HSP70i gene and protein expression surprisingly. However, the expression of HSP70 isoforms as well as other co-chaperones, and 17 cancer-associated genes decreased remarkably as expected. Additionally, interaction network analysis revealed a different mechanism; PES induction of HSP70i employs a cell cycle negative regulator, RBI, which is a tumor suppressor gene. Conclusion: PES treatment inhibited MCF-7 cell proliferation and changed several HSPs- and cancer-related gene expressions along with their interactions through a unique mechanism although it causes an interesting increase at HSP70i gene and protein expressions. RBI gene expression may play an important role in this effect as revealed by the interaction network analysis.