Mapping the Ligand Binding Landscape of Nurr1 (NR4A2): Computational Characterization of Small-Molecule Interactions in Alzheimer’s Disease Pathway

For a long time, Alzheimer’s disease has been among the most commonplace and fearsome neurodegenerative disorders worldwide. It is characterized by progressive cognitive decline caused by a combination of each-interacting molecular pathological processes. Despite decades of effort, therapeutic strategies targeting single mechanisms such as β-amyloid or tau pathologies have failed to achieve durable disease modification. This leads to recently increasingly relevant focus on multi-axis regulatory approaches. Nuclear receptor related 1 protein(Nurr1/NR4A2) has been under the microscope as a promising, key transcriptional regulator of neuroinflammation, neuronal survival, and even mitochondrial function. Stacking evidence shows Nurr1 inactivity to Alzheimer’s disease progression, providing grounds and necessity for this project to target it as a potential therapeutic. In this project, a comprehensive, fully computational framework was developed to map out the ligand-binding features of Nurr1. To start off, Geometric, energetic, and machine-learning-based methods were deployed to identify, through different means, binding pockets. Then, Pharmacophore modeling and mass virtual screenings were subsequently applied to predict various candidate small molecules from trusted public chemical libraries. Next, molecular docking simulations were performed using SwissDock to eventually reveal multiple ligands with the most favorable binding energies and stable clusterings within the previously spotted cavity. Administration of the potential drug is then tested using virtual ADME and toxicity profiling, filtering down to refined candidates of drugs with optimal affinity and no significant safety concerns. At the end, this project establishes a reproducible computational process for ligand and drug discovery, identifying multiple candidates for Nurr1, which, in the near future, can be put into practical testing grounds for validation and eventually clinical drug design.