Revealing the graded activation mechanism of neurotensin receptor 1.

Graded activation contributes to the precise regulation of GPCR activity, presenting new opportunities for drug design. In this work, a total of 10 μs enhanced-sampling simulations are performed to provide molecular insights into the binding dynamics differences of the neurotensin receptor 1 (NTSR1) to the full agonist SRI-9829, partial agonist RTI-3a and inverse agonist SR48692. The possible graded activation mechanism of NTSR1 is revealed by an integrated analysis utilizing the reweighted potential of mean force (PMF), deep learning (DL) and transfer entropy (TE). Specifically, the orthosteric pocket is observed to undergo expansion and contraction, with the G-protein-binding site experiencing interconversions among the inactive, intermediate and active-like states. Detailed structural comparisons capture subtle conformational differences arising from ligand binding in allosteric signaling, which can well explain the graded activation. Critical microswitches that contribute to graded activation are efficiently identified with the DL model. TE calculations enable the visualization of allosteric communication networks within the receptor, elucidating the driver-responder relationships associated with signal transduction. Fortunately, the dissociation of the full agonist from the orthosteric pocket is observed. The current findings systematically reveal the mechanism of NTSR1 graded activation, and also provide implications for structure-based drug design.

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Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Chunhua Li reports financial support was provided by the National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.