bioRxivNeurosciencePreprint
Structure-Based Discovery of GTP-Enhanced Rab10 Modulators and Their Effects on Alzheimer Disease-Relevant Cellular Phenotypes
Satyaveni MalasalaiD, Nathan Cox, Grady Sellman, Yan-Hua Chen, Qun Lu
Abstract
Rab10-mediated membrane trafficking has been implicated in Alzheimer disease (AD), but pharmacological tools for investigating its function remain limited. Here, we screened more than 80 million compounds using structure-based virtual screening and prioritized five candidate Rab10 modulators (R1-R5). These compounds exhibited favorable docking scores, stable modeled protein-ligand complexes in molecular dynamics (MD) simulations and predicted acceptable ADME/toxicity profiles. Comparative docking against Rab5, Rab8, and Rab11 predicted preferential interactions with GTP-associated Rab10. R1 and R2 yielded the most favorable Rab10 scores, whereas R3 showed the largest differences between GTP-associated, GDP-containing, and nucleotide-free Rab10 models. Surface plasmon resonance (SPR) revealed micromolar apparent affinities of R1-R4 without added GTP and nanomolar apparent affinities under GTP-containing conditions, generally favoring GTP-bound Rab10 over Rab5. In a cell-based GTP quantification assay, R1, R2, R3, and R5 reduced GTP-bound Rab10, whereas R4 increased it. R3 produced dose- and time-dependent reductions in GTP-bound Rab10 and was selected for functional studies. R3 altered endosomal organization and reduced EEA1 and LAMP1 expressions. In amyloid precursor protein (APP)/presenilin-1-expressing CHO cells, R3 redistributed intracellular APP, reduced APP carboxyl-terminal fragments (APP-CTFs), and decreased enlarged endosome-like structures. In neuronal differentiated PC12 cells, R1-R3 attenuated NGF withdrawal-induced cytoskeletal disruption and cell death, accompanied by reduced APP-CTF accumulation and tau phosphorylation. These studies highlight novel Rab10 modulators and support their further validation as candidate pharmacological probes for investigating Rab10-associated trafficking and AD-relevant cellular phenotypes.
- organism: human
- assay: proteomics
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
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