9QEK image
Deposition Date 2025-03-10
Release Date 2025-04-30
Last Version Date 2025-07-16
Entry Detail
PDB ID:
9QEK
Keywords:
Title:
Structure of Human ROS1 Kinase Domain Harboring the G2032R Solvent-front Mutation in Complex with Zidesamtinib (NVL-520)
Biological Source:
Source Organism:
Homo sapiens (Taxon ID: 9606)
Host Organism:
Method Details:
Experimental Method:
Resolution:
2.21 Å
R-Value Free:
0.27
R-Value Work:
0.20
Space Group:
P 64
Macromolecular Entities
Polymer Type:polypeptide(L)
Molecule:Proto-oncogene tyrosine-protein kinase ROS
Gene (Uniprot):ROS1
Mutations:G2032R
Chain IDs:A
Chain Length:301
Number of Molecules:1
Biological Source:Homo sapiens
Primary Citation
Zidesamtinib Selective Targeting of Diverse ROS1 Drug-Resistant Mutations.
Mol.Cancer Ther. 24 1005 1019 (2025)
PMID: 40299789 DOI: 10.1158/1535-7163.MCT-25-0025

Abstact

Zidesamtinib (NVL-520) is a ROS1-selective macrocyclic tyrosine kinase inhibitor designed with the aim to address clinical challenges for patients with non-small cell lung or other cancers that are ROS1 fusion-positive. These challenges include emergent ROS1 resistance mutations and brain metastases that can lead to disease progression, and central nervous system adverse events attributed to off-target TRK inhibition that can be treatment limiting. We evaluated zidesamtinib in accelerated mutagenesis screens and a brain tumor model, comparing it to other approved or investigational ROS1 inhibitors. At clinically relevant concentrations, zidesamtinib robustly inhibited >1,500 pooled ROS1 mutants with virtually no resistance emerging (≤1%), outperforming comparators crizotinib, entrectinib, and repotrectinib. Zidesamtinib also induced more durable responses than repotrectinib and taletrectinib in an aggressive intracranial ROS1 G2032R xenograft model. A 2.2 Å co-crystal structure with ROS1 G2032R, the most frequently identified ROS1 resistance mutation, reveals that zidesamtinib uniquely accommodates the mutated residue while potentially clashing with TRK, consistent with its selective ROS1-targeting design and supported by computational modeling. Taken together, these data support zidesamtinib's potential as a novel best-in-class ROS1 inhibitor.

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