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Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches

Background: Activated Cdc42-associated kinase (ACK1) is essential for numerous cellular functions, such as growth, proliferation, and migration. ACK1 signaling occurs through multiple receptor tyrosine kinases; therefore, its inhibition can provide effective antiproliferative effects against multipl...

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Autores principales: Kumar, Vikas, Kumar, Raj, Parate, Shraddha, Danishuddin, Lee, Gihwan, Kwon, Moonhyuk, Jeong, Seong-Hee, Ro, Hyeon-Su, Lee, Keun Woo, Kim, Seon-Won
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9953130/
https://www.ncbi.nlm.nih.gov/pubmed/36830587
http://dx.doi.org/10.3390/biom13020217
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author Kumar, Vikas
Kumar, Raj
Parate, Shraddha
Danishuddin,
Lee, Gihwan
Kwon, Moonhyuk
Jeong, Seong-Hee
Ro, Hyeon-Su
Lee, Keun Woo
Kim, Seon-Won
author_facet Kumar, Vikas
Kumar, Raj
Parate, Shraddha
Danishuddin,
Lee, Gihwan
Kwon, Moonhyuk
Jeong, Seong-Hee
Ro, Hyeon-Su
Lee, Keun Woo
Kim, Seon-Won
author_sort Kumar, Vikas
collection PubMed
description Background: Activated Cdc42-associated kinase (ACK1) is essential for numerous cellular functions, such as growth, proliferation, and migration. ACK1 signaling occurs through multiple receptor tyrosine kinases; therefore, its inhibition can provide effective antiproliferative effects against multiple human cancers. A number of ACK1-specific inhibitors were designed and discovered in the previous decade, but none have reached the clinic. Potent and selective ACK1 inhibitors are urgently needed. Methods: In the present investigation, the pharmacophore model (PM) was rationally built utilizing two distinct inhibitors coupled with ACK1 crystal structures. The generated PM was utilized to screen the drug-like database generated from the four chemical databases. The binding mode of pharmacophore-mapped compounds was predicted using a molecular docking (MD) study. The selected hit-protein complexes from MD were studied under all-atom molecular dynamics simulations (MDS) for 500 ns. The obtained trajectories were ranked using binding free energy calculations (ΔG kJ/mol) and Gibb’s free energy landscape. Results: Our results indicate that the three hit compounds displayed higher binding affinity toward ACK1 when compared with the known multi-kinase inhibitor dasatinib. The inter-molecular interactions of Hit1 and Hit3 reveal that compounds form desirable hydrogen bond interactions with gatekeeper T205, hinge region A208, and DFG motif D270. As a result, we anticipate that the proposed scaffolds might help in the design of promising selective ACK1 inhibitors.
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spelling pubmed-99531302023-02-25 Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches Kumar, Vikas Kumar, Raj Parate, Shraddha Danishuddin, Lee, Gihwan Kwon, Moonhyuk Jeong, Seong-Hee Ro, Hyeon-Su Lee, Keun Woo Kim, Seon-Won Biomolecules Article Background: Activated Cdc42-associated kinase (ACK1) is essential for numerous cellular functions, such as growth, proliferation, and migration. ACK1 signaling occurs through multiple receptor tyrosine kinases; therefore, its inhibition can provide effective antiproliferative effects against multiple human cancers. A number of ACK1-specific inhibitors were designed and discovered in the previous decade, but none have reached the clinic. Potent and selective ACK1 inhibitors are urgently needed. Methods: In the present investigation, the pharmacophore model (PM) was rationally built utilizing two distinct inhibitors coupled with ACK1 crystal structures. The generated PM was utilized to screen the drug-like database generated from the four chemical databases. The binding mode of pharmacophore-mapped compounds was predicted using a molecular docking (MD) study. The selected hit-protein complexes from MD were studied under all-atom molecular dynamics simulations (MDS) for 500 ns. The obtained trajectories were ranked using binding free energy calculations (ΔG kJ/mol) and Gibb’s free energy landscape. Results: Our results indicate that the three hit compounds displayed higher binding affinity toward ACK1 when compared with the known multi-kinase inhibitor dasatinib. The inter-molecular interactions of Hit1 and Hit3 reveal that compounds form desirable hydrogen bond interactions with gatekeeper T205, hinge region A208, and DFG motif D270. As a result, we anticipate that the proposed scaffolds might help in the design of promising selective ACK1 inhibitors. MDPI 2023-01-22 /pmc/articles/PMC9953130/ /pubmed/36830587 http://dx.doi.org/10.3390/biom13020217 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kumar, Vikas
Kumar, Raj
Parate, Shraddha
Danishuddin,
Lee, Gihwan
Kwon, Moonhyuk
Jeong, Seong-Hee
Ro, Hyeon-Su
Lee, Keun Woo
Kim, Seon-Won
Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches
title Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches
title_full Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches
title_fullStr Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches
title_full_unstemmed Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches
title_short Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches
title_sort identification of activated cdc42-associated kinase inhibitors as potential anticancer agents using pharmacoinformatic approaches
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9953130/
https://www.ncbi.nlm.nih.gov/pubmed/36830587
http://dx.doi.org/10.3390/biom13020217
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