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A computational approach to explore and identify potential herbal inhibitors for the p21-activated kinase 1 (PAK1).

Authors
  • Shahinozzaman, Md1, 2
  • Ishii, Takahiro2
  • Ahmed, Sinthyia3
  • Halim, Mohammad A4
  • Tawata, Shinkichi1, 2
  • 1 PAK Research Center, University of the Ryukyus, Okinawa, Japan. , (Japan)
  • 2 Department of Bioscience and Biotechnology, University of the Ryukyus, Okinawa, Japan. , (Japan)
  • 3 Division of Computer Aided Drug Design, The Red-Green Research Center, Dhaka, Bangladesh. , (Bangladesh)
  • 4 Department of Physical Sciences, University of Arkansas-Fort Smith, Fort Smith, AR, USA.
Type
Published Article
Journal
Journal of biomolecular structure & dynamics
Publication Date
Aug 01, 2020
Volume
38
Issue
12
Pages
3514–3526
Identifiers
DOI: 10.1080/07391102.2019.1659855
PMID: 31448698
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

The oncogenic kinase PAK1 (p21-activated kinase 1) is involved in developing many diseases including cancers, neurofibromatosis, Alzheimer's disease, diabetes (type 2), and hypertension. Thus, it is thought to be a prominent therapeutic target, and its selective inhibitors have a huge market potential. Recently, herbal PAK1 inhibitors have gained immense interest over synthetic ones mainly due to their non-toxic effects. Till date, many herbal compounds have been suggested to inhibit PAK1, but their information on selectivity, bioavailability, ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties, and molecular interactions with PAK1 has not been explored. Hence, this study was designed with computational approaches to explore and identify the best herbal PAK1-blockers showing good ADMET properties, druggable features and binding affinity with PAK1. Herbal inhibitors reported here were initially filtered with Lipinski's rule of five (RO5). Then, molecular docking between these inhibitors and PAK1 catalytic sites was performed using AutoDock Vina and GOLD suite to determine the binding affinity and interactions. Finally, 200 ns molecular dynamics (MD) simulations on three top-ranked inhibitors including cucurbitacin I (C-I), nymphaeol A (NA), and staurosporine (SPN) were carried out. The binding free energies and interactions revealed that NA can strongly bind with the PAK1 catalytic cleft. PASS prediction and ADMET profiling supported that NA is appeared to be a more selective and safer inhibitor than C-I and SPN. These results conform to the previous experimental evidences, and therefore, NA from Okinawa propolis could be a promising inhibitor for treating PAK1-dependent illnesses.Communicated by Ramaswamy H. Sarma.

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