Transcriptomic, mutational and structural bioinformatics approaches to explore the therapeutic role of FAP in predominant cancer types

Gayathri Ashok, Abdullah F. AlAsmari, Fawaz AlAsmari, Paul Livingstone, Anand Anbarasu, Sudha Ramaiah*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Fibroblast activating protein (FAP) is a cell surface marker of cancer-associated fibroblasts with a distinct pro-tumorigenic role. The present study analyzed the pan-cancer expression; and clinical and mutational profiles of the FAP coding gene. Molecular dynamics simulation (MDS) deciphered the backbone dynamics and energetics of FAP. Virtual screening and subsequent pharmacokinetic-profiling (PK) filtered lead molecules, which were subjected to molecular docking. MDS projected a stable trajectory for the protein, as dynamics evidenced by low residue-level fluctuations, stable backbone dynamics, and energetics. Around five stabilization and deleterious mutations in the catalytic domain were identified. The low binding energy (BE) profiles from molecular docking studies screened the top five lead molecules for site-specific intermolecular interaction studies. Lead-16 (ZINC000245289699) exhibited a significant BE and inhibition constant of −6.87 kcal/mol and 12.27 μM, respectively, across FAP and its mutants. Interestingly, the docked complexes of Lead-16 interacted with the catalytic triad residues (S624, D702, and H734). The docked complexes of Lead-16 with FAP showed lower average root-mean-square fluctuations compared to the unbound protein, suggesting a stable ligand–protein complex. The tumor-specific expression and its critical overall survival suggest the inhibitors of FAP for potential cancer therapeutic intervention and hindering tumor microenvironment-driven cancer progression.
Original languageEnglish
Article number699
Pages (from-to)699
Number of pages1
JournalDiscover Oncology
Volume15
Issue number1
Early online date23 Nov 2024
DOIs
Publication statusPublished - 23 Nov 2024

Keywords

  • Mutations
  • Overall survival
  • Tumor microenvironment
  • Molecular docking
  • Cancer-associated fibroblasts
  • Molecular dynamics simulations

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