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Murugan, N.

Publications and source records attributed to Murugan, N..

2 recordsLinked to original sources

Discovery of ILT3 (LILRB4) Small Molecule Inhibitors by Affinity Se-lection-Mass Spectrometry Reveals Druggability of a Neuroimmune Checkpoint in Alzheimers Disease

Leukocyte immunoglobulin-like receptor B4 (LILRB4/ILT3) is an emerging neuroimmune checkpoint that restricts microglial activation and amyloid clearance in Alzheimers disease (AD) through ApoE-dependent signaling. Here, we establish ILT3 as a tractable small molecule target using affinity selection-mass spectrometry (AS-MS) to identify direct binders. Biophysical validation confirmed high-affinity engagement, with LT12 exhibiting nanomolar binding by MST and SPR. Computational modeling and mutagenesis defined a discrete ILT3 binding pocket, revealing a distributed interaction network critical for ligand engagement. Targeting ILT3 disrupted the ILT3-ApoE interaction, with LT12 showing potent inhibition in orthogonal biochemical assays. In human iPSC-derived microglia, ILT3 modulation attenuated SHP1/2 signaling, suppressed NF-{kappa}B activation, reduced IL-1{beta} secretion, and restored A{beta} uptake. In vivo, pharmacological targeting of ILT3 improved cognition, reduced amyloid burden, and attenuated neuroinflammation in 5xFAD mice. Together, these findings validate ILT3 as a druggable neuroimmune checkpoint and support its therapeutic targeting in AD.

pharmacology and toxicology↗

Mechanosensation Mediates Long-Range Spatial Decision-Making in an Aneural Organism

The unicellular protist Physarum polycephalum is an important emerging model for understanding how aneural organisms process information toward adaptive behavior. Here, we reveal that Physarum can use mechanosensation to reliably make decisions about distant objects its environment, preferentially growing in the direction of heavier, substrate-deforming but chemically-inert masses. This long-range mass-sensing is abolished by gentle rhythmic mechanical disruption, changing substrate stiffness, or addition of a mechanosensitive transient receptor potential channel inhibitor. Computational modeling revealed that Physarum may perform this calculation by sensing the fraction of its growth perimeter that is distorted above a threshold strain - a fundamentally novel method of mechanosensation. Together, these data identify a surprising behavioral preference relying on biomechanical features and not nutritional content, and characterize a new example of an aneural organism that exploits physics to make decisions about growth and form. HighlightsO_LIThe aneural Physarum makes behavioral decisions by control of its morphology C_LIO_LIIt has a preference for larger masses, which it can detect at long range C_LIO_LIThis effect is mediated by mechanosensing, not requiring chemical attractants C_LIO_LIMachine learning reveals that it surveys environment and makes decision in < 4 hours C_LIO_LIA biophysical model reveals how its pulsations enable long-distance mapping of environmental features C_LI

animal behavior and cognition↗