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

Area of Science:

• Medicinal Chemistry
• Computational Drug Discovery
• Oncology

Background:

• Sphingosine Kinase 1 (SPHK1) is overexpressed in many human cancers.
• SPHK1 plays a critical role in tumor formation and progression.
• Targeting SPHK1 offers a potential therapeutic strategy for cancer treatment.

Purpose of the Study:

• To investigate the structure-activity relationship (SAR) of potential SPHK1 inhibitors.
• To design and predict the properties of novel SPHK1 inhibitors.
• To provide a computational roadmap for developing new anti-cancer agents targeting SPHK1.

Main Methods:

• Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) models were employed to analyze SAR.
• Surfex-Dock was used to elucidate the binding interactions between compounds and SPHK1.
• 3D-QSAR models and online tools predicted the activity and ADME/T properties of novel compounds.
• Molecular dynamics (MD) simulations were performed to further analyze binding interactions.

Main Results:

• CoMFA and CoMSIA models demonstrated satisfactory predictive capabilities for SAR (q² values of 0.621 and 0.585, respectively).
• Binding analysis revealed predominant van der Waals, carbon-hydrogen bonds, and hydrophobic interactions.
• Six newly designed compounds exhibited enhanced activities and suitable ADME/T properties.
• MD simulations identified key residues involved in SPHK1 inhibition.

Conclusions:

• The study successfully established SAR for SPHK1 inhibitors using 3D-QSAR.
• Novel compounds with promising anti-cancer potential and favorable drug-like properties were identified.
• This research provides a foundation for the rational design of innovative SPHK1-targeted cancer therapeutics.