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Targeting the NF-κB/IκBα complex via fragment-based E-Pharmacophore virtual screening and binary QSAR models.
J Mol Graph Model. 2019 01; 86:264-277.JM

Abstract

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 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 85 known NF-κB inhibitors were additionally 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) showed stronger binding and therefore are hypothesized to be more potent. The identification of 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.

Authors+Show Affiliations

School of Medicine, Bahcesehir University, Istanbul, Turkey; Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey.School of Medicine, Bahcesehir University, Istanbul, Turkey; Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey.Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey; Department of Chemistry, Gebze Technical University, Kocaeli, Turkey.Molecular Simulations and Design Group, Max Planck Institute for Dynamics and Complex Technical Systems, Magdeburg, Germany.Molecular Simulations and Design Group, Max Planck Institute for Dynamics and Complex Technical Systems, Magdeburg, Germany. Electronic address: matthias.stein@mpi-magdeburg.mpg.de.Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey; Neuroscience Program, Institute of Health Sciences, Bahcesehir University, Istanbul, Turkey. Electronic address: serdar.durdagi@med.bau.edu.tr.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

30415122

Citation

Kanan, Tarek, et al. "Targeting the NF-κB/IκBα Complex Via Fragment-based E-Pharmacophore Virtual Screening and Binary QSAR Models." Journal of Molecular Graphics & Modelling, vol. 86, 2019, pp. 264-277.
Kanan T, Kanan D, Erol I, et al. Targeting the NF-κB/IκBα complex via fragment-based E-Pharmacophore virtual screening and binary QSAR models. J Mol Graph Model. 2019;86:264-277.
Kanan, T., Kanan, D., Erol, I., Yazdi, S., Stein, M., & Durdagi, S. (2019). Targeting the NF-κB/IκBα complex via fragment-based E-Pharmacophore virtual screening and binary QSAR models. Journal of Molecular Graphics & Modelling, 86, 264-277. https://doi.org/10.1016/j.jmgm.2018.09.014
Kanan T, et al. Targeting the NF-κB/IκBα Complex Via Fragment-based E-Pharmacophore Virtual Screening and Binary QSAR Models. J Mol Graph Model. 2019;86:264-277. PubMed PMID: 30415122.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Targeting the NF-κB/IκBα complex via fragment-based E-Pharmacophore virtual screening and binary QSAR models. AU - Kanan,Tarek, AU - Kanan,Duaa, AU - Erol,Ismail, AU - Yazdi,Samira, AU - Stein,Matthias, AU - Durdagi,Serdar, Y1 - 2018/10/05/ PY - 2018/08/20/received PY - 2018/09/27/revised PY - 2018/09/30/accepted PY - 2018/11/12/pubmed PY - 2020/2/20/medline PY - 2018/11/12/entrez KW - Docking studies KW - E-pharmacophore KW - Fragment-based drug discovery KW - MetaCore/MetaDrug analysis KW - Molecular dynamics (MD) KW - NF-κB SP - 264 EP - 277 JF - Journal of molecular graphics & modelling JO - J Mol Graph Model VL - 86 N2 - 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 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 85 known NF-κB inhibitors were additionally 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) showed stronger binding and therefore are hypothesized to be more potent. The identification of 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. SN - 1873-4243 UR - https://www.unboundmedicine.com/medline/citation/30415122/Targeting_the_NF_κB/IκBα_complex_via_fragment_based_E_Pharmacophore_virtual_screening_and_binary_QSAR_models_ DB - PRIME DP - Unbound Medicine ER -