Nuclear factor-κB (NF κB) transcription factors represent a conserved family of proteins that regulate not only immune cells, but also heart cells, glial cells and neurons, playing a fundamental role in various cellular processes. Due to its dysregulation in certain cancer types as well as in chronic inflammation and autoimmune diseases, it has recently been appreciated as an important therapeutic target. The aim of this study was to investigate the binding pocket of NF κB (p50/p65) heterodimer complex in association with NF κB inhibitor IκBα to identify potent ligands via fragment-based e-pharmacophore screening. The ZINC Clean Fragments (~2 million) and the Schrodinger's medically relevant Glide fragments library (~670) were used to create the e-pharmacophore models at the potential binding site of the target which was validated by site mapping. Glide/HTVS docking was conducted followed by re-docking of the top 20% fragments by Glide/SP and Glide/XP protocols. The top-85000 Glide XP-docked fragments were used to generate the e-pharmacophore hypotheses. The Otava small molecule library (~260000 drug-like molecules) and additional 85 known NF κB inhibitors were screened against the derived e-pharmacophore models. The top-1000 high-scored molecules, which were well aligned to the e-pharmacophore models, from the Otava small molecule library, were then docked into the binding pocket. Finally, the selected 88 hit molecules and the 85 known inhibitors were analyzed by the MetaCore/MetaDrug™ platform, which uses developed binary QSAR models for therapeutic activity prediction as well as pharmacokinetic and toxicity profile predictions of screening molecules. Ligand selection criteria led to the refinement of 3 potent hit molecules using molecular dynamics (MD) simulations to better investigate their structural and dynamical profiles. The selected hit molecules had a low toxicity and a significant therapeutic potential for heart failure, antiviral activity, asthma and depression, all conditions in which NF κB plays a critical role. These hit ligands were also structurally stable at the NF-κB/IκBα complex as per the MD simulations and MM/GBSA analysis. Two of these ligands (Otava IDs: 1426436 and 6248112) were energetically more favorable and therefore are hypothesized to be more potent. Identifying new potent NF κB/IκBα inhibitors may thus present a novel therapy for inflammation-mediated conditions as well as cancer, facilitating more efficient research, and leading the way to future drug development efforts.
NF-κB is a central regulator of immunity and inflammation. It is suggested that the inflammatory response mediated by SARS-CoV-2 is predominated by NF-κB activation. Thus, NF-κB inhibition is considered a potential therapeutic strategy for COVID-19. The aim of this study was to identify potential anti-inflammation lead molecules that target NF-κB using a quantitative structure-activity relationship (QSAR) model of currently used and investigated anti-inflammatory drugs as the basis for screening. We applied an integrated approach by starting with the inflammation- based QSAR model to screen three libraries containing more than 220,000 drug-like molecules for the purpose of finding potential drugs that target the NF-κB/ IκBα p50/p65 (RelA) complex. We also used QSAR models to rule out molecules that were predicted to be toxic. Only 382 molecules were selected as potentially nontoxic and were analyzed further by short and long molecular dynamic (MD) simulations and free energy calculations. We have discovered five hit ligands with highly predicted anti-inflammation activity and nearly no predicted toxicities which had strongly favorable protein-ligand interactions and conformational stability at the binding pocket compared to a known NF-κB inhibitor (procyanidin B2). We propose these hit molecules as potential NF-κB inhibitors which can be further investigated in pre-clinical studies against SARS-CoV-2 and may be used as a scaffold for chemical optimization and drug development efforts.
The ubiquitin‐specific protease 7 (USP7) is a highly promising well‐validated target for a variety of malignancies. USP7 is critical in regulating the tumor suppressor p53 along with numerous epigenetic modifiers and transcription factors. Previous studies showed that USP7 inhibitors led to increased levels of p53 and anti‐proliferative effects in hematological and solid tumor cell lines. Thus, this study aimed to identify potent and safe USP7 hit inhibitors as potential anti‐cancer therapeutics via an integrated computational approach that combines pharmacophore modeling, molecular docking, molecular dynamics (MD) simulations and post‐MD free energy calculations. In this study, the crystal structure of USP7 has been extensively investigated using a combination of three different chemical pharmacophore modeling approaches. We then screened ∼220.000 drug‐like small molecule library and the hit ligands predicted to be nontoxic were evaluated further. The identified hits from each pharmacophore modeling study were further examined by 1‐ns short MD simulations and MM/GBSA free energy analysis. In total, we ran 1 ns MD simulations for 1137 selected on small compounds. Based on their average MM/GBSA scores, 18 ligands were selected for 50 ns MD simulations along with one highly potent USP7 inhibitor used as a positive control. The in vitro enzymatic inhibition assay testing of our lead 18 molecules confirmed that 7 of these molecules were successful in USP7 inhibition. Screening results showed that within the used screening approaches, the most successful one was structure‐based pharmacophore modeling with the success rate of 75 %. The identification of potent and safe USP7 small molecules as potential inhibitors is a step closer to finding appropriate effective therapies for cancer. Our lead ligands can be used as a scaffold for further structural optimization and development, enabling further research in this promising field.
The deubiquitinating enzyme ubiquitin-specific protease 7 (USP7) is a novel protein target for various hematological and solid-organ malignancies [1]. Its inhibition is thus considered a highly promising strategy for the development of new antineoplastic drugs. In this study, we applied an integrated approach with a major focus on pharmacophore modeling and screening combined with molecular dynamic simulations and free energy-based calculations to identify promising drugs as USP7-small molecule inhibitors. We started this drug repurposing study with the development of structure-based complex pharmacophore model hypotheses using the crystal structure of USP7. This pharmacophore modeling strategy was found to be most successful for the identification of promising molecules in drug discovery as we have recently reported [2]. We used three pharmacophore hypotheses to screen 6654 FDA-approved and investigational drugs as derived from the NPC's NIH library. Our pharmacophore screening led to the identification of 100 drugs that have well matched several chemical features of our hypotheses based on fitness scoring. All drugs were analyzed using 10-ns MD simulations and MM/GBSA system free energy. The 100 selected molecules encompassed over 35 different classes of drugs, among which antibiotics (13 identified), antivirals (6 identified) and anti-inflammatory drugs (5 identified) were the most represented. It is important to highlight that we found 4 antineoplastic drugs, suggesting potential interactions with the USP7 enzyme. Considering the important role of USP7 in cancer development and viral infections [3], we decided to further analyze all the discovered anticancer and antiviral drugs using 100-ns MD simulations. Additionally, we included the ten most stable molecules based on their system free energy (MM/GBSA scores lower than -69.0 kcal/mol) and all discovered anti-inflammatory drugs. In total, we ran 100-ns MD simulations for 24 molecules and a known USP7 inhibitor. Depending on this analysis, certain drugs will be tested in vitro to assess their level of USP7 inhibition. Our results thus far demonstrate the potential role of selected approved/investigational drugs as promising drugs that target USP7. These findings may open the route for efficient identification and characterization of promising USP7 inhibitors that could advance to clinical studies. References [1] Z. Wang, W. Kang, Y. You, J. Pang, H. Ren, Z. Suo, H. Liu, Y. Zheng, Frontiers in Pharmacology 2019, 10. [2] D. Kanan, T. Kanan, B. Dogan, M. D. Orhan, T. Avsar, S. Durdagi, ChemMedChem 2020. https://doi.org/10.1002/cmdc.202000675 [3] S. Bhattacharya, D. Chakraborty, M. Basu, M. K. Ghosh, Signal Transduct Target Ther 2018, 3, 17. Citation Format: Duaa Kanan, Tarek Kanan, Berna Dogan, Serdar Durdagi. Discovery of promising antineoplastic drugs against the USP7 deubiquitinating enzyme: A pharmacophore-based FDA-approved and investigational drugs repurposing study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 277.
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