N. Arul Murugan

This study identifies small molecule inhibitors of ILT3 using AS-MS, showing they improve cognition and reduce amyloid in Alzheimer's disease models.

The paper constructs a machine learning atlas of kinase inhibitor complexes to classify binding modes and demonstrates phylogenetic druggability transfer across the human kinome.

The paper identifies endogenous sterols as intracellular allosteric modulators of the GPCR-Gα interface using a deep learning toolkit and experimental validation.

The paper introduces CDI, a framework that unifies multiple molecular representations into a single embedding, achieving better predictive performance than individual methods.

This study investigates how CX3CR1 mediates Tau internalization by microglia and how AZD8797 modulates this interaction through molecular docking and dynamics simulations.

The paper describes the development of MPDSCOVID-19, a disease-specific web portal for computational drug discovery, with updated modules and tools for COVID-19 research.

This study identifies TGR63, a naphthalene monoimide derivative, as a promising therapeutic for Alzheimer's disease by reducing amyloid burden and cognitive decline in a mouse model.