Processing Temporal Growth Factor Patterns by an Epidermal Growth Factor Receptor Network Dynamically Established in Space.

The proto-oncogenic epidermal growth factor (EGF) receptor (EGFR) is a tyrosine kinase whose sensitivity and response to growth factor signals that vary over time and space determine cellular behavior within a developing tissue. The molecular reorganization of the receptors on the plasma membrane and the enzyme-kinetic mechanisms of phosphorylation are key determinants that couple growth factor binding to EGFR signaling. To enable signal initiation and termination while simultaneously accounting for suppression of aberrant signaling, a coordinated coupling of EGFR kinase and protein tyrosine phosphatase activity is established through space by vesicular dynamics. The dynamical operation mode of this network enables not only time-varying growth factor sensing but also adaptation of the response depending on cellular context. By connecting spatially coupled enzymatic kinase/phosphatase processes and the corresponding dynamical systems description of the EGFR network, we elaborate on the general principles necessary for processing complex growth factor signals.

EGFR Ligands Differentially Stabilize Receptor Dimers to Specify Signaling Kinetics.

Epidermal growth factor receptor (EGFR) regulates many crucial cellular programs, with seven different activating ligands shaping cell signaling in distinct ways. Using crystallography and other approaches, we show how the EGFR ligands epiregulin (EREG) and epigen (EPGN) stabilize different dimeric conformations of the EGFR extracellular region. As a consequence, EREG or EPGN induce less stable EGFR dimers than EGF-making them partial agonists of EGFR dimerization. Unexpectedly, this weakened dimerization elicits more sustained EGFR signaling than seen with EGF, provoking responses in breast cancer cells associated with differentiation rather than proliferation. Our results reveal how responses to different EGFR ligands are defined by receptor dimerization strength and signaling dynamics. These findings have broad implications for understanding receptor tyrosine kinase (RTK) signaling specificity. Our results also suggest parallels between partial and/or biased agonism in RTKs and G-protein-coupled receptors, as well as new therapeutic opportunities for correcting RTK signaling output.

EGFR Dynamics Change during Activation in Native Membranes as Revealed by NMR.

The epidermal growth factor receptor (EGFR) represents one of the most common target proteins in anti-cancer therapy. To directly examine the structural and dynamical properties of EGFR activation by the epidermal growth factor (EGF) in native membranes, we have developed a solid-state nuclear magnetic resonance (ssNMR)-based approach supported by dynamic nuclear polarization (DNP). In contrast to previous crystallographic results, our experiments show that the ligand-free state of the extracellular domain (ECD) is highly dynamic, while the intracellular kinase domain (KD) is rigid. Ligand binding restricts the overall and local motion of EGFR domains, including the ECD and the C-terminal region. We propose that the reduction in conformational entropy of the ECD by ligand binding favors the cooperative binding required for receptor dimerization, causing allosteric activation of the intracellular tyrosine kinase.

A structural perspective on the regulation of the epidermal growth factor receptor.

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase that plays a critical role in the pathogenesis of many cancers. The structure of intact forms of this receptor has yet to be determined, but intense investigations of fragments of the receptor have provided a detailed view of its activation mechanism, which we review here. Ligand binding converts the receptor to a dimeric form, in which contacts are restricted to the receptor itself, allowing heterodimerization of the four EGFR family members without direct ligand involvement. Activation of the receptor depends on the formation of an asymmetric dimer of kinase domains, in which one kinase domain allosterically activates the other. Coupling between the extracellular and intracellular domains may involve a switch between alternative crossings of the transmembrane helices, which form dimeric structures. We also discuss how receptor regulation is compromised by oncogenic mutations and the structural basis for negative cooperativity in ligand binding.

Conformational coupling across the plasma membrane in activation of the EGF receptor.

How the epidermal growth factor receptor (EGFR) activates is incompletely understood. The intracellular portion of the receptor is intrinsically active in solution, and to study its regulation, we measured autophosphorylation as a function of EGFR surface density in cells. Without EGF, intact EGFR escapes inhibition only at high surface densities. Although the transmembrane helix and the intracellular module together suffice for constitutive activity even at low densities, the intracellular module is inactivated when tethered on its own to the plasma membrane, and fluorescence cross-correlation shows that it fails to dimerize. NMR and functional data indicate that activation requires an N-terminal interaction between the transmembrane helices, which promotes an antiparallel interaction between juxtamembrane segments and release of inhibition by the membrane. We conclude that EGF binding removes steric constraints in the extracellular module, promoting activation through N-terminal association of the transmembrane helices.

Architecture and membrane interactions of the EGF receptor.

Dimerization-driven activation of the intracellular kinase domains of the epidermal growth factor receptor (EGFR) upon extracellular ligand binding is crucial to cellular pathways regulating proliferation, migration, and differentiation. Inactive EGFR can exist as both monomers and dimers, suggesting that the mechanism regulating EGFR activity may be subtle. The membrane itself may play a role but creates substantial difficulties for structural studies. Our molecular dynamics simulations of membrane-embedded EGFR suggest that, in ligand-bound dimers, the extracellular domains assume conformations favoring dimerization of the transmembrane helices near their N termini, dimerization of the juxtamembrane segments, and formation of asymmetric (active) kinase dimers. In ligand-free dimers, by holding apart the N termini of the transmembrane helices, the extracellular domains instead favor C-terminal dimerization of the transmembrane helices, juxtamembrane segment dissociation and membrane burial, and formation of symmetric (inactive) kinase dimers. Electrostatic interactions of EGFR's intracellular module with the membrane are critical in maintaining this coupling.

Oncogenic mutations counteract intrinsic disorder in the EGFR kinase and promote receptor dimerization.

The mutation and overexpression of the epidermal growth factor receptor (EGFR) are associated with the development of a variety of cancers, making this prototypical dimerization-activated receptor tyrosine kinase a prominent target of cancer drugs. Using long-timescale molecular dynamics simulations, we find that the N lobe dimerization interface of the wild-type EGFR kinase domain is intrinsically disordered and that it becomes ordered only upon dimerization. Our simulations suggest, moreover, that some cancer-linked mutations distal to the dimerization interface, particularly the widespread L834R mutation (also referred to as L858R), facilitate EGFR dimerization by suppressing this local disorder. Corroborating these findings, our biophysical experiments and kinase enzymatic assays indicate that the L834R mutation causes abnormally high activity primarily by promoting EGFR dimerization rather than by allowing activation without dimerization. We also find that phosphorylation of EGFR kinase domain at Tyr845 may suppress the intrinsic disorder, suggesting a molecular mechanism for autonomous EGFR signaling.

MREDTA: A BERT and transformer-based molecular representation encoder for predicting drug-target binding affinity.

Drug-target binding affinity (DTA) prediction is vital for drug repositioning. The accuracy and generalizability of DTA models remain a major challenge. Here, we develop a model composed of BERT-Trans Block, Multi-Trans Block, and DTI Learning modules, referred to as Molecular Representation Encoder-based DTA prediction (MREDTA). MREDTA has three advantages: (1) extraction of both local and global molecular features simultaneously through skip connections; (2) improved sensitivity to molecular structures through the Multi-Trans Block; (3) enhanced generalizability through the introduction of BERT. Compared with 12 advanced models, benchmark testing of KIBA and Davis datasets demonstrated optimal performance of MREDTA. In case study, we applied MREDTA to 2034 FDA-approved drugs for treating non-small-cell lung cancer (NSCLC), all of which act on mutant EGFRT790M protein. The corresponding molecular docking results demonstrated the robustness of MREDTA.

Structural basis for negative cooperativity in growth factor binding to an EGF receptor.

Transmembrane signaling by the epidermal growth factor receptor (EGFR) involves ligand-induced dimerization and allosteric regulation of the intracellular tyrosine kinase domain. Crystallographic studies have shown how ligand binding induces dimerization of the EGFR extracellular region but cannot explain the "high-affinity" and "low-affinity" classes of cell-surface EGF-binding sites inferred from curved Scatchard plots. From a series of crystal structures of the Drosophila EGFR extracellular region, we show here how Scatchard plot curvature arises from negatively cooperative ligand binding. The first ligand-binding event induces formation of an asymmetric dimer with only one bound ligand. The unoccupied site in this dimer is structurally restrained, leading to reduced affinity for binding of the second ligand, and thus negative cooperativity. Our results explain the cell-surface binding characteristics of EGF receptors and suggest how individual EGFR ligands might stabilize distinct dimeric species with different signaling properties.

Allele-specific activation, enzyme kinetics, and inhibitor sensitivities of EGFR exon 19 deletion mutations in lung cancer.

Oncogenic mutations within the epidermal growth factor receptor (EGFR) are found in 15 to 30% of all non-small-cell lung carcinomas. The term exon 19 deletion (ex19del) is collectively used to refer to more than 20 distinct genomic alterations within exon 19 that comprise the most common EGFR mutation subtype in lung cancer. Despite this heterogeneity, clinical treatment decisions are made irrespective of which EGFR ex19del variant is present within the tumor, and there is a paucity of information regarding how individual ex19del variants influence protein structure and function. Herein, we identified allele-specific functional differences among ex19del variants attributable to recurring sequence and structure motifs. We built all-atom structural models of 60 ex19del variants identified in patients and combined molecular dynamics simulations with biochemical and biophysical experiments to analyze three ex19del mutations (E746_A750, E746_S752 > V, and L747_A750 > P). We demonstrate that sequence variation in ex19del alters oncogenic cell growth, dimerization propensity, enzyme kinetics, and tyrosine kinase inhibitor (TKI) sensitivity. We show that in contrast to E746_A750 and E746_S752 > V, the L747_A750 > P variant forms highly active ligand-independent dimers. Enzyme kinetic analysis and TKI inhibition experiments suggest that E746_S752 > V and L747_A750 > P display reduced TKI sensitivity due to decreased adenosine 5'-triphosphate Km. Through these analyses, we propose an expanded framework for interpreting ex19del variants and considerations for therapeutic intervention.

Simultaneous Protein Colorful Imaging via Raman Signal Classification.

Protein imaging aids diagnosis and drug development by revealing protein-drug interactions or protein levels. However, the challenges of imaging multiple proteins, reduced sensitivity, and high reliance on specific protein properties such as Raman peaks or refractive index hinder the understanding. Here, we introduce multiprotein colorful imaging through Raman signal classification. Our method utilized machine learning-assisted classification of Raman signals, which are the distinctive features of label-free proteins. As a result, three types of proteins could be imaged simultaneously. In addition, we could quantify individual proteins from a mixture of multiple proteins over a wide detection range (10 fg/mL-1 µg/mL). These results showed a 1000-fold improvement in sensitivity and a 30-fold increase in the upper limit of detection compared to existing methods. These advances will enhance our understanding of biology and facilitate the development of disease diagnoses and treatments.

Confinement energy landscape classification reveals membrane receptor nano-organization mechanisms.

The cell membrane organization has an essential functional role through the control of membrane receptor confinement in micro- or nanodomains. Several mechanisms have been proposed to account for these properties, although some features have remained controversial, notably the nature, size, and stability of cholesterol- and sphingolipid-rich domains or lipid rafts. Here, we probed the effective energy landscape acting on single-nanoparticle-labeled membrane receptors confined in raft nanodomains- epidermal growth factor receptor (EGFR), Clostridium perfringens ε-toxin receptor (CPεTR), and Clostridium septicum α-toxin receptor (CSαTR)-and compared it with hop-diffusing transferrin receptors. By establishing a new analysis pipeline combining Bayesian inference, decision trees, and clustering approaches, we systematically classified single-protein trajectories according to the type of effective confining energy landscape. This revealed the existence of only two distinct organization modalities: confinement in a quadratic energy landscape for EGFR, CPεTR, and CSαTR (A), and free diffusion in confinement domains resulting from the steric hindrance due to F-actin barriers for transferrin receptor (B). The further characterization of effective confinement energy landscapes by Bayesian inference revealed the role of interactions with the domain environment in cholesterol- and sphingolipid-rich domains with (EGFR) or without (CPεTR and CSαTR) interactions with F-actin to regulate the confinement energy depth. These two distinct mechanisms result in the same organization type (A). We revealed that the apparent domain sizes for these receptor trajectories resulted from Brownian exploration of the energy landscape in a steady-state-like regime at a common effective temperature, independently of the underlying molecular mechanisms. These results highlight that confinement domains may be adequately described as interaction hotspots rather than rafts with abrupt domain boundaries. Altogether, these results support a new model for functional receptor confinement in membrane nanodomains and pave the way to the constitution of an atlas of membrane protein organization.

Allosteric inhibition of the epidermal growth factor receptor through disruption of transmembrane interactions.

The epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase (RTK) commonly targeted for inhibition by anticancer therapeutics. Current therapeutics target EGFR's kinase domain or extracellular region. However, these types of inhibitors are not specific for tumors over healthy tissue and therefore cause undesirable side effects. Our lab has recently developed a new strategy to regulate RTK activity by designing a peptide that specifically binds to the transmembrane (TM) region of the RTK to allosterically modify kinase activity. These peptides are acidity-responsive, allowing them to preferentially target acidic environments like tumors. We have applied this strategy to EGFR and created the PET1 peptide. We observed that PET1 behaves as a pH-responsive peptide that modulates the configuration of the EGFR TM through a direct interaction. Our data indicated that PET1 inhibits EGFR-mediated cell migration. Finally, we investigated the mechanism of inhibition through molecular dynamics simulations, which showed that PET1 sits between the two EGFR TM helices; this molecular mechanism was additionally supported by AlphaFold-Multimer predictions. We propose that the PET1-induced disruption of native TM interactions disturbs the conformation of the kinase domain in such a way that it inhibits EGFR's ability to send migratory cell signals. This study is a proof-of-concept that acidity-responsive membrane peptide ligands can be generally applied to RTKs. In addition, PET1 constitutes a viable approach to therapeutically target the TM of EGFR.

GraphEGFR: Multi-task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family proteins on data scarcity.

The proteins within the human epidermal growth factor receptor (EGFR) family, members of the tyrosine kinase receptor family, play a pivotal role in the molecular mechanisms driving the development of various tumors. Tyrosine kinase inhibitors, key compounds in targeted therapy, encounter challenges in cancer treatment due to emerging drug resistance mutations. Consequently, machine learning has undergone significant evolution to address the challenges of cancer drug discovery related to EGFR family proteins. However, the application of deep learning in this area is hindered by inherent difficulties associated with small-scale data, particularly the risk of overfitting. Moreover, the design of a model architecture that facilitates learning through multi-task and transfer learning, coupled with appropriate molecular representation, poses substantial challenges. In this study, we introduce GraphEGFR, a deep learning regression model designed to enhance molecular representation and model architecture for predicting the bioactivity of inhibitors against both wild-type and mutant EGFR family proteins. GraphEGFR integrates a graph attention mechanism for molecular graphs with deep and convolutional neural networks for molecular fingerprints. We observed that GraphEGFR models employing multi-task and transfer learning strategies generally achieve predictive performance comparable to existing competitive methods. The integration of molecular graphs and fingerprints adeptly captures relationships between atoms and enables both global and local pattern recognition. We further validated potential multi-targeted inhibitors for wild-type and mutant HER1 kinases, exploring key amino acid residues through molecular dynamics simulations to understand molecular interactions. This predictive model offers a robust strategy that could significantly contribute to overcoming the challenges of developing deep learning models for drug discovery with limited data and exploring new frontiers in multi-targeted kinase drug discovery for EGFR family proteins.

Targeting EGFR and VEGFR-2 Kinases With Nanoparticles: A Computational Approach for Cancer Therapy Advancement.

The study investigates titanium and zinc nanoparticles as inhibitors for the epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor-2 (VEGFR-2), pivotal regulators of cell processes. VEGFR-2 activation fuels tumor angiogenesis in cancer cells, sustaining malignant tissue expansion. Molecular docking analysis illustrates the nanoparticles' binding to the active sites, inhibiting the phosphorylation of key proteins in downstream signaling. This inhibition offers a promising therapeutic approach to impede cancer-related signaling, potentially slowing down aberrant protein cascades controlled by EGFR and VEGFR-2. The findings propose a novel avenue for cancer treatment, targeting abnormal growth pathways using titanium and zinc nanoparticles.

Computational Analysis of Activation of Dimerized Epidermal Growth Factor Receptor Kinase Using the String Method and Markov State Model.

Epidermal growth factor receptor (EGFR) activation is accompanied by dimerization. During the activation of the intracellular kinase domain, two EGFR kinases form an asymmetric dimer, and one side of the dimer (receiver) is activated. Using the string method and Markov state model (MSM), we performed a computational analysis of the structural changes in the activation of the EGFR dimer in this study. The string method reveals the minimum free-energy pathway (MFEP) from the inactive to active structure. The MSM was constructed from numerous trajectories of molecular dynamics simulations around the MFEP, which revealed the free-energy map of structural changes. In the activation of the receiver kinase, the unfolding of the activation loop (A-loop) is followed by the rearrangement of the C-helix, as observed in other kinases. However, unlike other kinases, the free-energy map of EGFR at the asymmetric dimer showed that the active state yielded the highest stability and revealed how interactions at the dimer interface induced receiver activation. As the H-helix of the activator approaches the C-helix of the receiver during activation, the A-loop unfolds. Subsequently, L782 of the receiver enters the pocket between the G- and H-helices of the activator, leading to a rearrangement of the hydrophobic residues around L782 of the receiver, which constitutes a structural rearrangement of the C-helix of the receiver from an outward to an inner position. The MSM analysis revealed long-time scale trajectories via kinetic Monte Carlo.

The juxtamembrane region of EGFR takes center stage.

The activation process for the epidermal growth factor receptor (EGFR) involves formation of an asymmetric dimer of the tyrosine kinase domains. Jura et al. (2009) in this issue and Brewer et al. (2009) in Molecular Cell now demonstrate that the juxtamembrane region of EGFR plays a crucial role in stabilizing this dimer.

Mechanism for activation of the EGF receptor catalytic domain by the juxtamembrane segment.

Signaling by the epidermal growth factor receptor requires an allosteric interaction between the kinase domains of two receptors, whereby one activates the other. We show that the intracellular juxtamembrane segment of the receptor, known to potentiate kinase activity, is able to dimerize the kinase domains. The C-terminal half of the juxtamembrane segment latches the activated kinase domain to the activator, and the N-terminal half of this segment further potentiates dimerization, most likely by forming an antiparallel helical dimer that engages the transmembrane helices of the activated receptor. Our data are consistent with a mechanism in which the extracellular domains block the intrinsic ability of the transmembrane and cytoplasmic domains to dimerize and activate, with ligand binding releasing this block. The formation of the activating juxtamembrane latch is prevented by the C-terminal tails in a structure of an inactive kinase domain dimer, suggesting how alternative dimers can prevent ligand-independent activation.

Probing conformational dynamics of EGFR mutants via SEIRA spectroscopy: potential implications for tyrosine kinase inhibitor design.

Missense mutations in EGFR's catalytic domain alter its function, promoting cancer. SEIRA spectroscopy, supported by MD simulations, reveals structural differences in the compactness and hydration of helical motifs between active and inactive EGFR conformations models. These findings provide novel insights into the biophysical mechanisms driving EGFR activation and drug resistance, offering a robust method for studying emerging EGFR mutations and their structural impacts on TKIs' efficacy.

Inhibition of DHHC20-Mediated EGFR Palmitoylation Creates a Dependence on EGFR Signaling.

Inappropriate activation of the receptor tyrosine kinase EGFR contributes to a variety of human malignancies. Here we show a mechanism to induce vulnerability to an existing first line treatment for EGFR-driven cancers. We find that inhibiting the palmitoyltransferase DHHC20 creates a dependence on EGFR signaling for cancer cell survival. The loss of palmitoylation increases sustained EGFR signal activation and sensitizes cells to EGFR tyrosine kinase inhibition. Our work shows that the reversible modification of EGFR with palmitate "pins" the unstructured C-terminal tail to the plasma membrane, impeding EGFR activation. We identify by mass spectrometry palmitoylated cysteine residues within the C-terminal tail where mutation of the cysteine residues to alanine is sufficient to activate EGFR signaling promoting cell migration and transformation. Our results reveal that the targeting of a peripheral modulator of EGFR signaling, DHHC20, causes a loss of signal regulation and susceptibility to EGFR inhibitor-induced cell death.