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Unraveling the allosteric inhibition mechanism of TLR2 by CU-CPT22: A combined DFT and enhanced sampling MD study
Peng Jiao1, Chengliang Ni2, Haonian Jin1
1College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, PR China.
Abstract:
Aberrant activation of Toll-like receptors 1/2 (TLR1/2) is critically implicated in the pathogenesis of numerous inflammatory and immune-mediated disorders, positioning this receptor complex as a high-value therapeutic target. CU-CPT22, a well-established small-molecule TLR1/2 inhibitor, exhibits potent and selective inhibition of TLR1/2 signaling. However, the atomistic details governing its molecular recognition and allosteric modulation remain elusive. Herein, we present an integrated computational framework that synergistically combines enhanced-sampling molecular dynamics (MD) simulations, rigorous binding free energy calculations, and quantum chemical analyses to decipher the mechanistic basis of CU-CPT22 action. Our MD simulations, complemented by principal component analysis (PCA) and free energy landscape (FEL) mapping, reveal that ligand binding induces an initial conformational selection and subsequently restricts the intrinsic large-scale collective motions of the protein, effectively stabilizing the complex in a distinct, low-entropy conformational state. Per-residue energy decomposition within the MM/PBSA framework identifies a non-polar driving force that overcomes a substantial polar desolvation penalty, with hotspot residues Ile319, Phe322, Tyr323, and Phe349 contributing decisively to the binding affinity. Complementary density functional theory (DFT) calculations and interaction region indicator (IRI) analyses elucidate the frontier molecular orbital profile (ΔE = 5.419 eV) and map the electrophilic and nucleophilic regions on the polycyclic core that orchestrate specific noncovalent contacts. Collectively, these findings provide a comprehensive, multi-scale portrait of the CU-CPT22 binding mechanism and establish a robust conceptual and computational framework for the rational design of next-generation, high-affinity TLR1/2 antagonists.
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