SHP2-EGFR States in Dephosphorylation Can Inform Selective SHP2 Inhibitors, Dampening RasGAP Action.

SHP2 is a positive regulator of the EGFR-dependent Ras/MAPK pathway. It dephosphorylates a regulatory phosphorylation site in EGFR that serves as the binding site to RasGAP (RASA1 or p120RasGAP). RASA1 is activated by binding to the EGFR phosphate group. Active RASA1 deactivates Ras by hydrolyzing Ras-bound GTP to GDP. Thus, SHP2 dephosphorylation of EGFR effectively prevents RASA1-mediated deactivation of Ras, thereby stimulating proliferation. Despite knowledge of this vital regulation in cell life, mechanistic in-depth structural understanding of the involvement of SHP2, EGFR, and RASA1 in the Ras/MAPK pathway has largely remained elusive. Here we elucidate the interactions, the factors influencing EGFR's recruitment of RASA1, and SHP2's recognition of the substrate site in EGFR. We reveal that RASA1 specifically interacts with the DEpY992LIP motif in EGFR featuring a proline residue at the +3 position C-terminal to pY primarily through its nSH2 domain. This interaction is strengthened by the robust attraction of two acidic residues, E991 and D990, of EGFR to two basic residues in the BC-loop near the pY-binding pocket of RASA1's nSH2. In the stable precatalytic state of SHP2 with EGFR (DADEpY992LIPQ), the E-loop of SHP2's active site favors the interaction with the (-2)-position D990 and (-4)-position D988 N-terminal to pY992 in EGFR, while the pY-loop constrains the (+4)-position Q996 C-terminal to pY992. These specific interactions not only provide a structural basis for identifying negative regulatory sites in other RTKs but can inform selective, high-affinity active-site SHP2 inhibitors tailored for SHP2 mutants.

Slower CDK4 and faster CDK2 activation in the cell cycle.

Dysregulation of cyclin-dependent kinases (CDKs) impacts cell proliferation, driving cancer. Here, we ask why the cyclin-D/CDK4 complex governs cell cycle progression through the longer G1 phase, whereas cyclin-E/CDK2 regulates the shorter G1/S phase transition. We consider available experimental cellular and structural data including cyclin-E's high-level burst, sustained duration of elevated cyclin-D expression, and explicit solvent molecular dynamics simulations of the inactive monomeric and complexed states, to establish the conformational tendencies along the landscape of the distinct activation scenarios of cyclin-D/CDK4 and cyclin-E/CDK2 in the G1 phase and G1/S transition of the cell cycle, respectively. These lead us to propose slower activation of cyclin-D/CDK4 and rapid activation of cyclin-E/CDK2. We provide the mechanisms through which this occurs, offering innovative CDK4 drug design considerations. Our insightful mechanistic work addresses a compelling cell cycle regulation question and illuminates the distinct activation speeds between the G1 and the G1/S phases, which are crucial for function.

CDK2 and CDK4: Cell Cycle Functions Evolve Distinct, Catalysis-Competent Conformations, Offering Drug Targets.

Cyclin-dependent kinases (CDKs), particularly CDK4 and CDK2, are crucial for cell cycle progression from the Gap 1 (G1) to the Synthesis (S) phase by phosphorylating targets such as the Retinoblastoma Protein (Rb). CDK4, paired with cyclin-D, operates in the long G1 phase, while CDK2 with cyclin-E, manages the brief G1-to-S transition, enabling DNA replication. Aberrant CDK signaling leads to uncontrolled cell proliferation, which is a hallmark of cancer. Exactly how they accomplish their catalytic phosphorylation actions with distinct efficiencies poses the fundamental, albeit overlooked question. Here we combined available experimental data and modeling of the active complexes to establish their conformational functional landscapes to explain how the two cyclin/CDK complexes differentially populate their catalytically competent states for cell cycle progression. Our premise is that CDK catalytic efficiencies could be more important for cell cycle progression than the cyclin-CDK biochemical binding specificity and that efficiency is likely the prime determinant of cell cycle progression. We observe that CDK4 is more dynamic than CDK2 in the ATP binding site, the regulatory spine, and the interaction with its cyclin partner. The N-terminus of cyclin-D acts as an allosteric regulator of the activation loop and the ATP-binding site in CDK4. Integrated with a suite of experimental data, we suggest that the CDK4 complex is less capable of remaining in the active catalytically competent conformation, and may have a lower catalytic efficiency than CDK2, befitting their cell cycle time scales, and point to critical residues and motifs that drive their differences. Our mechanistic landscape may apply broadly to kinases, and we propose two drug design strategies: (i) allosteric Inhibition by conformational stabilization for targeting allosteric CDK4 regulation by cyclin-D, and (ii) dynamic entropy-optimized targeting which leverages the dynamic, entropic aspects of CDK4 to optimize drug binding efficacy.

Excitation generated preferential binding sites for ethane on porous carbon-copper porphyrin sorbents: ethane/ethylene adsorptive separation improved by light.

Energy-efficient separation of C2H6/C2H4 is a great challenge, for which adsorptive separation is very promising. C2H6-selective adsorption has big implications, while the design of C2H6-sorbents with ideal adsorption capability, particularly with the C2H6/C2H4-selectivity exceeded 2.0, is still challenging. Instead of the current strategies such as chemical modification or pore space modulation, we propose a new methodology for the design of C2H6-sorbents. With a Cu-TCPP [TCPP = 5,10,15,20-tetrakis(4-carboxyphenyl)porphyrin] framework dispersed onto a microporous carbon and a hierarchical-pore carbon, two composite sorbents are fabricated. The composite sorbents exhibit enhanced C2H6-selective adsorption capabilities with visible light, particularly the composite sorbent based on the hierarchical-pore carbon, whose C2H6 and C2H4 adsorption capacities (0 °C, 1 bar) are targetedly increased by 27% and only 1.8% with visible light, and therefore, an C2H6-selectivity (C2H6/C2H4 = 10/90, v/v) of 4.8 can be realized. With visible light, the adsorption force of the C2H6 molecule can be asymmetrically enhanced by the excitation enriched electron density over the adsorption sites formed via the close interaction between the Cu-TCPP and the carbon layer, whereas that of the C2H4 molecule is symmetrically altered and the forces cancelled each other out. This strategy may open up a new route for energy-efficient adsorptive separation of C2H6/C2H4 with light.

The allosteric mechanism of mTOR activation can inform bitopic inhibitor optimization.

mTOR serine/threonine kinase is a cornerstone in the PI3K/AKT/mTOR pathway. Yet, the detailed mechanism of activation of its catalytic core is still unresolved, likely due to mTOR complexes' complexity. Its dysregulation was implicated in cancer and neurodevelopmental disorders. Using extensive molecular dynamics (MD) simulations and compiled published experimental data, we determine exactly how mTOR's inherent motifs can control the conformational changes in the kinase domain, thus kinase activity. We also chronicle the critical regulation by the unstructured negative regulator domain (NRD). When positioned inside the catalytic cleft (NRD IN state), mTOR tends to adopt a deep and closed catalytic cleft. This is primarily due to the direct interaction with the FKBP-rapamycin binding (FRB) domain which restricts it, preventing substrate access. Conversely, when outside the catalytic cleft (NRD OUT state), mTOR favors an open conformation, exposing the substrate-binding site on the FRB domain. We further show how an oncogenic mutation (L2427R) promotes shifting the mTOR ensemble toward the catalysis-favored state. Collectively, we extend mTOR's "active-site restriction" mechanism and clarify mutation action. In particular, our mechanism suggests that RMC-5552 (RMC-6272) bitopic inhibitors may benefit from adjustment of the (PEG8) linker length when targeting certain mTOR variants. In the cryo-EM mTOR/RMC-5552 structure, the distance between the allosteric and orthosteric inhibitors is ∼22.7 Å. With a closed catalytic cleft, this linker bridges the sites. However, in our activation mechanism, in the open cleft it expands to ∼24.7 Å, offering what we believe to be the first direct example of how discovering an activation mechanism can potentially increase the affinity of inhibitors targeting mutants.

Perspectives on Theoretical Models and Molecular Simulations of Polymer Brushes.

Polymer brushes have witnessed extensive utilization and progress, driven by their distinct attributes in surface modification, tethered group functionality, and tailored interactions at the nanoscale, enabling them for various scientific and industrial applications of coatings, sensors, switchable/responsive materials, nanolithography, and lab-on-a-chips. Despite the wealth of experimental investigations into polymer brushes, this review primarily focuses on computational studies of antifouling polymer brushes with a strong emphasis on achieving a molecular-level understanding and structurally designing antifouling polymer brushes. Computational exploration covers three realms of thermotical models, molecular simulations, and machine-learning approaches to elucidate the intricate relationship between composition, structure, and properties concerning polymer brushes in the context of nanotribology, surface hydration, and packing conformation. Upon acknowledging the challenges currently faced, we extend our perspectives toward future research directions by delineating potential avenues and unexplored territories. Our overarching objective is to advance our foundational comprehension and practical utilization of polymer brushes for antifouling applications, leveraging the synergy between computational methods and materials design to drive innovation in this crucial field.

SHP2 clinical phenotype, cancer, or RASopathies, can be predicted by mutant conformational propensities.

SHP2 phosphatase promotes full activation of the RTK-dependent Ras/MAPK pathway. Its mutations can drive cancer and RASopathies, a group of neurodevelopmental disorders (NDDs). Here we ask how same residue mutations in SHP2 can lead to both cancer and NDD phenotypes, and whether we can predict what the outcome will be. We collected and analyzed mutation data from the literature and cancer databases and performed molecular dynamics simulations of SHP2 mutants. We show that both cancer and Noonan syndrome (NS, a RASopathy) mutations favor catalysis-prone conformations. As to cancer versus RASopathies, we demonstrate that cancer mutations are more likely to accelerate SHP2 activation than the NS mutations at the same genomic loci, in line with NMR data for K-Ras4B more aggressive mutations. The compiled experimental data and dynamic features of SHP2 mutants lead us to propose that different from strong oncogenic mutations, SHP2 activation by NS mutations is less likely to induce a transition of the ensemble from the SHP2 inactive state to the active state. Strong signaling promotes cell proliferation, a hallmark of cancer. Weak, or moderate signals are associated with differentiation. In embryonic neural cells, dysregulated differentiation is connected to NDDs. Our innovative work offers structural guidelines for identifying and correlating mutations with clinical outcomes, and an explanation for why bearers of RASopathy mutations may have a higher probability of cancer. Finally, we propose a drug strategy against SHP2 variants-promoting cancer and RASopathies.

Protein conformational ensembles in function: roles and mechanisms.

The sequence-structure-function paradigm has dominated twentieth century molecular biology. The paradigm tacitly stipulated that for each sequence there exists a single, well-organized protein structure. Yet, to sustain cell life, function requires (i) that there be more than a single structure, (ii) that there be switching between the structures, and (iii) that the structures be incompletely organized. These fundamental tenets called for an updated sequence-conformational ensemble-function paradigm. The powerful energy landscape idea, which is the foundation of modernized molecular biology, imported the conformational ensemble framework from physics and chemistry. This framework embraces the recognition that proteins are dynamic and are always interconverting between conformational states with varying energies. The more stable the conformation the more populated it is. The changes in the populations of the states are required for cell life. As an example, in vivo, under physiological conditions, wild type kinases commonly populate their more stable "closed", inactive, conformations. However, there are minor populations of the "open", ligand-free states. Upon their stabilization, e.g., by high affinity interactions or mutations, their ensembles shift to occupy the active states. Here we discuss the role of conformational propensities in function. We provide multiple examples of diverse systems, including protein kinases, lipid kinases, and Ras GTPases, discuss diverse conformational mechanisms, and provide a broad outlook on protein ensembles in the cell. We propose that the number of molecules in the active state (inactive for repressors), determine protein function, and that the dynamic, relative conformational propensities, rather than the rigid structures, are the hallmark of cell life.

Cell cycle progression mechanisms: slower cyclin-D/CDK4 activation and faster cyclin-E/CDK2.

Dysregulation of cyclin-dependent kinases (CDKs) impacts cell proliferation, driving cancer. Here, we ask why the cyclin-D/CDK4 complex governs cell cycle progression through the longer G1 phase, whereas cyclin-E/CDK2 regulates the short G1/S phase transition. We consider the experimentally established high-level bursting of cyclin-E, and sustained duration of elevated cyclin-D expression in the cell, available experimental cellular and structural data, and comprehensive explicit solvent molecular dynamics simulations to provide the mechanistic foundation of the distinct activation scenarios of cyclin-D/CDK4 and cyclin-E/CDK2 in the G1 phase and G1/S transition of the cell cycle, respectively. These lead us to propose slower activation of cyclin-D/CDK4 and rapid activation of cyclin-E/CDK2. Importantly, we determine the mechanisms through which this occurs, offering innovative CDK4 drug design considerations. Our insightful mechanistic work addresses the compelling cell cycle regulation question and illuminates the distinct activation speeds in the G1 versus G1/S phases, which are crucial for cell function.

Cell phenotypes can be predicted from propensities of protein conformations.

Proteins exist as dynamic conformational ensembles. Here we suggest that the propensities of the conformations can be predictors of cell function. The conformational states that the molecules preferentially visit can be viewed as phenotypic determinants, and their mutations work by altering the relative propensities, thus the cell phenotype. Our examples include (i) inactive state variants harboring cancer driver mutations that present active state-like conformational features, as in K-Ras4BG12V compared to other K-Ras4BG12X mutations; (ii) mutants of the same protein presenting vastly different phenotypic and clinical profiles: cancer and neurodevelopmental disorders; (iii) alterations in the occupancies of the conformational (sub)states influencing enzyme reactivity. Thus, protein conformational propensities can determine cell fate. They can also suggest the allosteric drugs efficiency.

Dual role of endophytic entomopathogenic fungi: induce plant growth and control tomato leafminer Phthorimaea absoluta.

BACKGROUND: Entomopathogenic fungi (EPF) are multifunctional microorganisms acting not only as biopesticides against insect pests but also as endophytes which regulate plant growth. The tomato leafminer, Phthorimaea absoluta (Tuta absoluta) is a devastating invasive pest of tomatoes worldwide. However, effective alternatives are needed for a sustainable management of this invasive pest. In this study, the functional effects of five EPF isolates Metarhizium flavoviride, M. anisopliae, M. rileyi, Cordyceps fumosorosea and Beauveria bassiana were evaluated on tomato growth promotion and pest protection against P. absoluta. RESULTS: When directly sprayed with conidia, P. absoluta larvae showed high cumulative mortality of 100% to M. anisopliae under 1 × 108 conidia/mL, whereas M. flavoviride, B. bassiana, C. fumosorosea and M. rileyi caused cumulative mortality of 92.65%, 92.62%, 92.16% and 68.95%, respectively. Moreover, all five EPF isolates can successfully colonize tomato plants, whilst the colonization rate for each EPF depends on the inoculation method used. The most efficient inoculation method for M. flavoviride and M. rileyi was root dipping, for M. anisopliae and C. fumosorosea it was coating seed, and for B. bassiana it was foliage spraying. The highest plant colonization was obtained by M. flavoviride. Meanwhile, all these isolates promoted tomato plant growth upon inoculation. Furthermore, endophytic colonization of plants by the five EPF negatively affected the performance of P. absoluta, among them M. anisopliae and C. fumosorosea showed strong negative effects on the performance of P. absoluta. CONCLUSION: Our results highlight the potential of incorporating entomopathogenic fungi as endophytes in integrated pest management practices to protect tomatoes against P. absoluta. © 2023 Society of Chemical Industry.

Neurodevelopmental disorders, like cancer, are connected to impaired chromatin remodelers, PI3K/mTOR, and PAK1-regulated MAPK.

Neurodevelopmental disorders (NDDs) and cancer share proteins, pathways, and mutations. Their clinical symptoms are different. However, individuals with NDDs have higher probabilities of eventually developing cancer. Here, we review the literature and ask how the shared features can lead to different medical conditions and why having an NDD first can increase the chances of malignancy. To explore these vital questions, we focus on dysregulated PI3K/mTOR, a major brain cell growth pathway in differentiation, and MAPK, a critical pathway in proliferation, a hallmark of cancer. Differentiation is governed by chromatin organization, making aberrant chromatin remodelers highly likely agents in NDDs. Dysregulated chromatin organization and accessibility influence the lineage of specific cell brain types at specific embryonic development stages. PAK1, with pivotal roles in brain development and in cancer, also regulates MAPK. We review, clarify, and connect dysregulated pathways with dysregulated proliferation and differentiation in cancer and NDDs and highlight PAK1 role in brain development and MAPK regulation. Exactly how PAK1 activation controls brain development, and why specific chromatin remodeler components, e.g., BAF170 encoded by SMARCC2 in autism, await clarification.

Enhanced CO Adsorption by Modulating the Electron Density Distribution of Graphite-Copper Porphyrin Sorbents with Light.

The photo-responsive adsorption has emerged as a vibrant area, but its current methodology is limited by the well-defined photochromic units and their molecular deformation driven by photo-stimuli. Herein, a methodology of nondeforming photo-responsiveness is successfully exploited. With the exploiting agent of Cu-TCPP framework assembled on the graphite and strongly interacted with it, the sorbent generates two kinds of adsorption sites, over which the electron density distribution of the graphite layer can be modulated at the c-axis direction, which can further evolve due to photo-stimulated excited states. The excited states are stable enough to meet the timescale of microscopic adsorption equilibrium. Independent of the ultra-low specific surface area of the sorbent (20 m2 g-1 ), the CO adsorption capability can be improved from 0.50 mmol g-1 at the ground state to 1.24 mmol g-1 (0 °C, 1 bar) with the visible light radiation, rather than the photothermal desorption.

AlphaFold, allosteric, and orthosteric drug discovery: Ways forward.

Drug discovery is arguably a highly challenging and significant interdisciplinary aim. The stunning success of the artificial intelligence-powered AlphaFold, whose latest version is buttressed by an innovative machine-learning approach that integrates physical and biological knowledge about protein structures, raised drug discovery hopes that unsurprisingly, have not come to bear. Even though accurate, the models are rigid, including the drug pockets. AlphaFold's mixed performance poses the question of how its power can be harnessed in drug discovery. Here we discuss possible ways of going forward wielding its strengths, while bearing in mind what AlphaFold can and cannot do. For kinases and receptors, an input enriched in active (ON) state models can better AlphaFold's chance of rational drug design success.

Strategy toward Kinase-Selective Drug Discovery.

Kinase drug selectivity is the ground challenge in cancer research. Due to the structurally similar kinase drug pockets, off-target inhibitor toxicity has been a major cause for clinical trial failures. The pockets are similar but not identical. Here, we describe a transformation invariant protocol to identify distinct geometric features in the drug pocket that can distinguish one kinase from all others. We integrate available experimental structures with the artificial intelligence-based structural kinome, performing a kinome-wide structural bioinformatic analysis to establish the structural principles of kinase drug selectivity. We generate the structural landscape from the experimental kinase-ligand complexes and propose a binary network that encapsulates the information. The results show that all kinases contain binary units that are shared by less than seven other kinases in the kinome. 331 kinases contain unique binary units that may distinguish them from all others. The structural features encoded by these binary units in the network represent the inhibitor-accessible geometric space that may capture the kinome-wide selectivity. Our proposed binary network with the unsupervised clustering can serve as a general structural bioinformatic protocol for extracting the distinguishing structural features for any protein from their families. We apply the binary network to epidermal growth factor receptor tyrosine kinase inhibitor selectivity by targeting the gate area and the AKT1 serine/threonine kinase selectivity by binding to the αC-helix region and the allosteric pocket. Finally, we develop the cross-platform software, KDS (Kinase Drug Selectivity), for customized visualization and analysis of the binary networks in the human kinome (https://github.com/CBIIT/KDS).

Higher-order interactions of Bcr-Abl can broaden chronic myeloid leukemia (CML) drug repertoire.

Bcr-Abl, a nonreceptor tyrosine kinase, is associated with leukemias, especially chronic myeloid leukemia (CML). Deletion of Abl's N-terminal region, to which myristoyl is linked, renders the Bcr-Abl fusion oncoprotein constitutively active. The substitution of Abl's N-terminal region by Bcr enables Bcr-Abl oligomerization. Oligomerization is critical: it promotes clustering on the membrane, which is essential for potent MAPK signaling and cell proliferation. Here we decipher the Bcr-Abl specific, step-by-step oligomerization process, identify a specific packing surface, determine exactly how the process is structured and identify its key elements. Bcr's coiled coil (CC) domain at the N-terminal controls Bcr-Abl oligomerization. Crystallography validated oligomerization via Bcr-Abl dimerization between two Bcr CC domains, with tetramerization via tight packing between two binary assemblies. However, the structural principles guiding Bcr CC domain oligomerization are unknown, hindering mechanistic understanding and drugs exploiting it. Using molecular dynamics (MD) simulations, we determine that the binary complex of the Bcr CC domain serves as a basic unit in the quaternary complex providing a specific surface for dimer-dimer packing and higher-order oligomerization. We discover that the small α1-helix is the key. In the binary assembly, the helix forms interchain aromatic dimeric packing, and in the quaternary assembly, it contributes to the specific dimer-dimer packing. Our mechanism is supported by the experimental literature. It offers the key elements controlling this process which can expand the drug discovery strategy, including by Bcr CC-derived peptides, and candidate residues for small covalent drugs, toward quenching oligomerization, supplementing competitive and allosteric tyrosine kinase inhibitors.

Allosteric regulation of autoinhibition and activation of c-Abl.

c-Abl, a non-receptor tyrosine kinase, regulates cell growth and survival in healthy cells and causes chronic myeloid leukemia (CML) when fused by Bcr. Its activity is blocked in the assembled inactive state, where the SH3 and SH2 domains dock into the kinase domain, reducing its conformational flexibility, resulting in the autoinhibited state. It is active in an extended 'open' conformation. Allostery governs the transitions between the autoinhibited and active states. Even though experiments revealed the structural hallmarks of the two states, a detailed grasp of the determinants of c-Abl autoinhibition and activation at the atomic level, which may help innovative drug discovery, is still lacking. Here, using extensive molecular dynamics simulations, we decipher exactly how these determinants regulate it. Our simulations confirm and extend experimental data that the myristoyl group serves as the switch for c-Abl inhibition/activation. Its dissociation from the kinase domain promotes the SH2-SH3 release, initiating c-Abl activation. We show that the precise SH2/N-lobe interaction is required for full activation of c-Abl. It stabilizes a catalysis-favored conformation, priming it for catalytic action. Bcr-Abl allosteric drugs elegantly mimic the endogenous myristoyl-mediated autoinhibition state of c-Abl 1b. Allosteric activating mutations shift the ensemble to the active state, blocking ATP-competitive drugs. Allosteric drugs alter the active-site conformation, shifting the ensemble to re-favor ATP-competitive drugs. Our work provides a complete mechanism of c-Abl activation and insights into critical parameters controlling at the atomic level c-Abl inactivation, leading us to propose possible strategies to counter reemergence of drug resistance.

AlphaFold, Artificial Intelligence (AI), and Allostery.

AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of biological sequence data and artificial intelligence (AI). AlphaFold has appended projects and research directions. The database it has been creating promises an untold number of applications with vast potential impacts that are still difficult to surmise. AI approaches can revolutionize personalized treatments and usher in better-informed clinical trials. They promise to make giant leaps toward reshaping and revamping drug discovery strategies, selecting and prioritizing combinations of drug targets. Here, we briefly overview AI in structural biology, including in molecular dynamics simulations and prediction of microbiota-human protein-protein interactions. We highlight the advancements accomplished by the deep-learning-powered AlphaFold in protein structure prediction and their powerful impact on the life sciences. At the same time, AlphaFold does not resolve the decades-long protein folding challenge, nor does it identify the folding pathways. The models that AlphaFold provides do not capture conformational mechanisms like frustration and allostery, which are rooted in ensembles, and controlled by their dynamic distributions. Allostery and signaling are properties of populations. AlphaFold also does not generate ensembles of intrinsically disordered proteins and regions, instead describing them by their low structural probabilities. Since AlphaFold generates single ranked structures, rather than conformational ensembles, it cannot elucidate the mechanisms of allosteric activating driver hotspot mutations nor of allosteric drug resistance. However, by capturing key features, deep learning techniques can use the single predicted conformation as the basis for generating a diverse ensemble.

The structural basis of BCR-ABL recruitment of GRB2 in chronic myelogenous leukemia.

BCR-ABL drives chronic myeloid leukemia (CML). BCR binding to GRB2 transduces signaling via the Ras/MAPK pathway. Despite considerable data confirming the binding, molecular-level understanding of exactly how the two proteins interact, and, especially, what are the determinants of the specificity of the SH2GRB2 domain-phosphorylated BCR (pBCR) recognition are still open questions. Yet, this is vastly important for understanding binding selectivity, and for predicting the phosphorylated receptors, or peptides, that are likely to bind. Here, we uncover these determinants and ascertain to what extent they relate to the affinity of the interaction. Toward this end, we modeled the complexes of the pBCR and SH2GRB2 and other pY/Y-peptide-SH2 complexes and compared their specificity and affinity. We observed that pBCR's 176FpYVNV180 motif is favorable and specific to SH2GRB2, similar to pEGFR, but not other complexes. SH2GRB2 contains two binding pockets: pY-binding recognition pocket triggers binding, and the specificity pocket whose interaction is governed by N179 in pBCR and W121 in SH2GRB2. Our proposed motif with optimal affinity to SH2GRB2 is E/D-pY-E/V-N-I/L. Collectively, we provide the structural basis of BCR-ABL recruitment of GRB2, outline its specificity hallmarks, and delineate a blueprint for prediction of BCR-binding scaffolds and for therapeutic peptide design.