Identification of potential SPHK1 inhibitors based on structural optimization by molecular simulation

Sphingosine Kinase 1 (SPHK1), observed to be overexpressed in an array of human malignancies, plays a pivotal role in modulating essential cellular activities throughout the process of tumor formation. Consequently, SPHK1 represents a promising therapeutic target, offering novel approaches to tumor treatment. Here, the structure-activity relationship was researched by using CoMFA and CoMSIA models. Both CoMFA (q<sup>2</sup>=0.621; <i>n</i> = 10; r<sup>2</sup>=0.992) and CoMSIA (q<sup>2</sup>=0.585; <i>n</i> = 7; r<sup>2</sup>=0.967) demonstrated satisfactory predictive capabilities. The structure-activity relationship of the compounds was analyzed by the counter maps of various fields. Further on, the compounds were interfaced with SPHK1 using the Surfex-Dock method to elucidate their interactive characteristics. Findings reveal that the binding is predominantly reliant on van der Waals, carbon-hydrogen bonds and hydrophobic interactions. Furthermore, the potential activities and ADME/T properties of six novel compounds were predicted utilizing 3D-QSAR models and online tools. The newly designed compounds were validated to have better activities and suitable ADME/T properties. In addition, molecular dynamics (MD) simulation further revealed that key residues, such as Ala339, Ala170, Ala115, Asp81, Gly342, Phe288 Ser164, Phe188, Ile170, etc. This study offers a roadmap to the discovery and design of innovative SPHK1 inhibitors.

Publication Details

Journal
Figshare
Published
2025-03-24
DOI
https://doi.org/10.6084/m9.figshare.28652453.v1
Primary Topic
Computational Physics and Python Applications
Type
article
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Identification of potential SPHK1 inhibitors based on structural optimization by molecular simulation

Figshare
Computational Physics and Python Applications
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Identification of potential SPHK1 inhibitors based on structural optimization by molecular simulation

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Abstract

Sphingosine Kinase 1 (SPHK1), observed to be overexpressed in an array of human malignancies, plays a pivotal role in modulating essential cellular activities throughout the process of tumor formation. Consequently, SPHK1 represents a promising therapeutic target, offering novel approaches to tumor treatment. Here, the structure-activity relationship was researched by using CoMFA and CoMSIA models. Both CoMFA (q<sup>2</sup>=0.621; <i>n</i> = 10; r<sup>2</sup>=0.992) and CoMSIA (q<sup>2</sup>=0.585; <i>n</i> = 7; r<sup>2</sup>=0.967) demonstrated satisfactory predictive capabilities. The structure-activity relationship of the compounds was analyzed by the counter maps of various fields. Further on, the compounds were interfaced with SPHK1 using the Surfex-Dock method to elucidate their interactive characteristics. Findings reveal that the binding is predominantly reliant on van der Waals, carbon-hydrogen bonds and hydrophobic interactions. Furthermore, the potential activities and ADME/T properties of six novel compounds were predicted utilizing 3D-QSAR models and online tools. The newly designed compounds were validated to have better activities and suitable ADME/T properties. In addition, molecular dynamics (MD) simulation further revealed that key residues, such as Ala339, Ala170, Ala115, Asp81, Gly342, Phe288 Ser164, Phe188, Ile170, etc. This study offers a roadmap to the discovery and design of innovative SPHK1 inhibitors.

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Computational Physics and Python Applications
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