Disrupting AIP-Protein Interactions for Therapeutic Advances in Infectious and Inflammatory Diseases

Our project aims to characterize AIP’s interactions with calcineurin A isozyme c (PPP3CC/CNA3) and yeast mitochondrial escape 1-like 1 (YME1L1), and assess their druggability using computational modeling. We will utilize molecular dynamics (MD) simulations (GROMACS 2024.5 or higher, GPU version) with MM/PBSA and molecular docking calculations to identify druggable regions on AIP. A virtual screening campaign will identify small molecules capable of disrupting these interactions. Promising inhibitors will be experimentally tested at the MV lab to evaluate their potential in modulating inflammatory responses.

This project consists of three main tasks: (1) Stability Evaluation of Pre-determined Complexes: long MD simulations to evaluate AIP:PPP3CC and AIP:YME1L1 complex stability (~4 months). (2) Identification of Key Regions on AIP and Virtual Screening: screening of ~300,000 compounds from NCI and Sigma Aldrich databases (~4 months). (3) In silico validation and scoring of promising compounds: MD simulations of the interaction between AIP and selected compounds with MM/PBSA calculations (~4 months). Tasks will be parallelized to optimize resource usage, overseen by the Principal Investigator.

Simulation data (~1000GB) will be stored transiently and transferred to AccelBio local servers for analysis. A GitHub page will host simulation data and disseminate findings to the scientific community. The project team consists of three experienced HPC users proficient in MD (GROMACS), docking (AutoDock-GPU), and MM/PBSA (g_mmpbsa), ensuring efficient execution without additional training. This study pioneers the computational exploration of AIP's immune function and represents a novel strategy for selective immunomodulatory therapies, offering an alternative to broad-spectrum immunosuppressants.