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Mutations in the kinase and juxtamembrane domains of the MET Receptor Tyrosine Kinase are responsible for oncogenesis in various cancers and can drive resistance to MET-directed treatments. Determining the most effective inhibitor for each mutational profile is a major challenge for MET-driven cancer treatment in precision medicine. Here, we used a deep mutational scan (DMS) of ~5764 MET kinase domain variants to profile the growth of each mutation against a panel of 11 inhibitors that are reported to target the MET kinase domain. We validate previously identified resistance mutations, pinpoint common resistance sites across type I, type II, and type I ½ inhibitors, unveil unique resistance and sensitizing mutations for each inhibitor, and verify non-cross-resistant sensitivities for type I and type II inhibitor pairs. We augment a protein language model with biophysical and chemical features to improve the predictive performance for inhibitor-treated datasets. Together, our study demonstrates a pooled experimental pipeline for identifying resistance mutations, provides a reference dictionary for mutations that are sensitized to specific therapies, and offers insights for future drug development.

The antibiotics chloramphenicol (CHL) and oxazolidinones, including linezolid (LZD), are known to inhibit mitochondrial translation. This can result in serious, potentially deadly, side effects when used therapeutically. Although the mechanism by which CHL and LZD inhibit bacterial ribosomes has been elucidated in detail, their mechanism of action against mitochondrial ribosomes has yet to be explored. CHL and oxazolidinones bind to the ribosomal peptidyl transfer center (PTC) of the bacterial ribosome and prevent incorporation of incoming amino acids under specific sequence contexts, causing ribosomes to stall only at certain sequences. Through mitoribosome profiling, we show that inhibition of mitochondrial ribosomes is similarly context-specific-CHL and LZD lead to mitoribosome stalling primarily when there is an alanine, serine, or threonine in the penultimate position of the nascent peptide chain. We further validate context-specific stalling through in vitro translation assays. A high-resolution cryo-electron microscopy structure of LZD bound to the PTC of the human mitoribosome shows extensive similarity to the mode of bacterial inhibition and also suggests potential avenues for altering selectivity. Our findings could help inform the rational development of future, less mitotoxic, antibiotics, which are critically needed in the current era of increasing antimicrobial resistance.

MET is a receptor tyrosine kinase (RTK) responsible for initiating signaling pathways involved in development and wound repair. MET activation relies on ligand binding to the extracellular receptor, which prompts dimerization, intracellular phosphorylation, and recruitment of associated signaling proteins. Mutations, which are predominantly observed clinically in the intracellular juxtamembrane and kinase domains, can disrupt typical MET regulatory mechanisms. Understanding how juxtamembrane variants, such as exon 14 skipping (METΔEx14), and rare kinase domain mutations can increase signaling, often leading to cancer, remains a challenge. Here, we perform a parallel deep mutational scan (DMS) of the MET intracellular kinase domain in two fusion protein backgrounds: wild-type and METΔEx14. Our comparative approach has revealed a critical hydrophobic interaction between a juxtamembrane segment and the kinase ⍺C-helix, pointing to potential differences in regulatory mechanisms between MET and other RTKs. Additionally, we have uncovered a β5 motif that acts as a structural pivot for the kinase domain in MET and other TAM family of kinases. We also describe a number of previously unknown activating mutations, aiding the effort to annotate driver, passenger, and drug resistance mutations in the MET kinase domain.

In the folded state, biomolecules exchange between multiple conformational states crucial for their function. However, most structural models derived from experiments and computational predictions only encode a single state. To represent biomolecules accurately, we must move towards modeling and predicting structural ensembles. Information about structural ensembles exists within experimental data from X-ray crystallography and cryo-electron microscopy. Although new tools are available to detect conformational and compositional heterogeneity within these ensembles, the legacy PDB data structure does not robustly encapsulate this complexity. We propose modifications to the macromolecular crystallographic information file (mmCIF) to improve the representation and interrelation of conformational and compositional heterogeneity. These modifications will enable the capture of macromolecular ensembles in a human and machine-interpretable way, potentially catalyzing breakthroughs for ensemble-function predictions, analogous to the achievements of AlphaFold with single-structure prediction.

UNLABELLED: PIK3CA (PI3Kα) is a lipid kinase commonly mutated in cancer, including ∼40% of hormone receptor-positive breast cancer. The most frequently observed mutants occur in the kinase and helical domains. Orthosteric PI3Kα inhibitors suffer from poor selectivity leading to undesirable side effects, most prominently hyperglycemia due to inhibition of wild-type (WT) PI3Kα. Here, we used molecular dynamics simulations and cryo-electron microscopy to identify an allosteric network that provides an explanation for how mutations favor PI3Kα activation. A DNA-encoded library screen leveraging electron microscopy-optimized constructs, differential enrichment, and an orthosteric-blocking compound led to the identification of RLY-2608, a first-in-class allosteric mutant-selective inhibitor of PI3Kα. RLY-2608 inhibited tumor growth in PIK3CA-mutant xenograft models with minimal impact on insulin, a marker of dysregulated glucose homeostasis. RLY-2608 elicited objective tumor responses in two patients diagnosed with advanced hormone receptor-positive breast cancer with kinase or helical domain PIK3CA mutations, with no observed WT PI3Kα-related toxicities. SIGNIFICANCE: Treatments for PIK3CA-mutant cancers are limited by toxicities associated with the inhibition of WT PI3Kα. Molecular dynamics, cryo-electron microscopy, and DNA-encoded libraries were used to develop RLY-2608, a first-in-class inhibitor that demonstrates mutant selectivity in patients. This marks the advance of clinical mutant-selective inhibition that overcomes limitations of orthosteric PI3Kα inhibitors. See related commentary by Gong and Vanhaesebroeck, p. 204 . See related article by Varkaris et al., p. 227 . This article is featured in Selected Articles from This Issue, p. 201.

Structural biology, as powerful as it is, can be misleading. We highlight four fundamental challenges: interpreting raw experimental data; accounting for motion; addressing the misleading nature of in vitro structures; and unraveling interactions between drugs and "anti-targets." Overcoming these challenges will amplify the impact of structural biology on drug discovery.

Peer review is an important part of the scientific process, but traditional peer review at journals is coming under increased scrutiny for its inefficiency and lack of transparency. As preprints become more widely used and accepted, they raise the possibility of rethinking the peer-review process. Preprints are enabling new forms of peer review that have the potential to be more thorough, inclusive, and collegial than traditional journal peer review, and to thus fundamentally shift the culture of peer review toward constructive collaboration. In this Consensus View, we make a call to action to stakeholders in the community to accelerate the growing momentum of preprint sharing and provide recommendations to empower researchers to provide open and constructive peer review for preprints.