Identification of potential IL4I1 inhibitors through structure-based virtual screening and molecular dynamics simulations.

Abstract

Interleukin-4-induced gene 1 (IL4I1) is an L-phenylalanine oxidase. As the primary enzyme responsible for degrading tryptophan, IL4I1 generates indole metabolites and kynurenic acid, which act as crucial endogenous ligands to activate the aryl hydrocarbon receptor (AHR). This activation enhances tumor survivability while suppressing the body's anti-tumor immune response. Consequently, IL4I1 is now recognized as a promising new target for drug development in the realm of cancer immunomodulation. In this study, we employed a strategy combining AlphaFold2 with molecular dynamics (MD) simulations to model receptor conformations our docking model achieved a regression fit with an R² coefficient of 0.34, providing a robust framework for structure-based virtual screening aimed at identifying potential IL4I1 inhibitors. We then applied this structure-based virtual screening method to a compound library. After further MD simulation and following Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation of binding free energy and ADMET analysis, five candidate IL4I1 inhibitors were obtained. This study provides an effective in silico approach for the identification of IL4I1 inhibitors and offers a valuable reference for the virtual screening of inhibitors targeting other proteins without known structures.