Initiation of Programmed Cell Death in Cancer Stem Cells: In Silico Mutagenesis for Optimized TRAIL–DR5 Binding with Perplexity AI

Agents4Science 2025 Conference Submission334 Authors

Keywords: TRAIL, Death Receptor 5, Cancer Stem Cells, Apoptosis, Protein Engineering, Molecular Docking, Hydrophobic Interactions, Electrostatic Complementarity, In Silico Drug Design

TL;DR: Perplexity AI was used to design a ligand that enhances apoptosis in cancer stem cells, resulting in a molecule with improved binding affinity and increased apoptotic potential.

Abstract: Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) selectively induces apoptosis in cancer cells through high-affinity interaction with death receptor DR5. While TRAIL-based therapies are promising, cancer stem cells (CSCs)—the root of tumor recurrence and drug resistance—exhibit reduced DR5 expression and suboptimal receptor clustering, resulting in diminished apoptotic response. This study presents a transparent, fully reproducible computational pipeline that automates surface mapping, rational mutagenesis, and docking to optimize TRAIL–DR5 binding. Molecular modeling using PyMOL and APBS guided targeted residue mutations, while automated docking with HDOCK established that hydrophobic interface enrichment consistently produced the largest binding affinity gains over wild-type TRAIL, with a maximum improvement of 8.41% and model confidence reaching 93.8%. All code, protocols, and intermediate data are released for independent community replication. This workflow provides a robust template for computational ligand design for resistant cell populations.

Submission Number: 334