A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ

Bolcato, Giovanni; Cescon, Eleonora; Pavan, Matteo; Bissaro, Maicol; Bassani, Davide; Federico, Stephanie; Spalluto, Giampiero; Sturlese, Mattia; Moro, Stefano

doi:10.3390/ijms22189741

Open AccessArticle

A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ

by

Giovanni Bolcato

¹,

Eleonora Cescon

²,

Matteo Pavan

¹

,

Maicol Bissaro

¹

,

Davide Bassani

¹

,

Stephanie Federico

²

,

Giampiero Spalluto

²,

Mattia Sturlese

¹

and

Stefano Moro

^1,*

¹

Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Via Marzolo 5, 35131 Padova, Italy

²

Department of Chemical and Pharmaceutical Sciences, University of Trieste, Via Licio Giorgeri 1, 34127 Trieste, Italy

^*

Author to whom correspondence should be addressed.

Int. J. Mol. Sci. 2021, 22(18), 9741; https://doi.org/10.3390/ijms22189741

Submission received: 29 July 2021 / Revised: 1 September 2021 / Accepted: 3 September 2021 / Published: 9 September 2021

(This article belongs to the Special Issue Protein Kinases and Their Inhibitors in CNS Diseases)

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Abstract

Fragment-Based Drug Discovery (FBDD) has become, in recent years, a consolidated approach in the drug discovery process, leading to several drug candidates under investigation in clinical trials and some approved drugs. Among these successful applications of the FBDD approach, kinases represent a class of targets where this strategy has demonstrated its real potential with the approved kinase inhibitor Vemurafenib. In the Kinase family, protein kinase CK1 isoform δ (CK1δ) has become a promising target in the treatment of different neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. In the present work, we set up and applied a computational workflow for the identification of putative fragment binders in large virtual databases. To validate the method, the selected compounds were tested in vitro to assess the CK1δ inhibition.

Keywords: fragment-based drug discovery; molecular docking; molecular dynamics; supervised molecular dynamics; protein kinase CK1δ

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MDPI and ACS Style

Bolcato, G.; Cescon, E.; Pavan, M.; Bissaro, M.; Bassani, D.; Federico, S.; Spalluto, G.; Sturlese, M.; Moro, S. A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ. Int. J. Mol. Sci. 2021, 22, 9741. https://doi.org/10.3390/ijms22189741

AMA Style

Bolcato G, Cescon E, Pavan M, Bissaro M, Bassani D, Federico S, Spalluto G, Sturlese M, Moro S. A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ. International Journal of Molecular Sciences. 2021; 22(18):9741. https://doi.org/10.3390/ijms22189741

Chicago/Turabian Style

Bolcato, Giovanni, Eleonora Cescon, Matteo Pavan, Maicol Bissaro, Davide Bassani, Stephanie Federico, Giampiero Spalluto, Mattia Sturlese, and Stefano Moro. 2021. "A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ" International Journal of Molecular Sciences 22, no. 18: 9741. https://doi.org/10.3390/ijms22189741

APA Style

Bolcato, G., Cescon, E., Pavan, M., Bissaro, M., Bassani, D., Federico, S., Spalluto, G., Sturlese, M., & Moro, S. (2021). A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ. International Journal of Molecular Sciences, 22(18), 9741. https://doi.org/10.3390/ijms22189741

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A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ

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