Effect of Lipid Bilayer Anchoring on the Conformational Properties of the Cytochrome P450 2D6 Binding Site.

Human cytochrome P450 (CYP) proteins metabolize 75% of small-molecule pharmaceuticals, which makes structure-based modeling of CYP metabolism and inhibition, bolstered by the current availability of X-ray crystal structures of CYP globular catalytic domains, an attractive prospect. Accounting for this broad metabolic capacity is a combination of the existence of multiple different CYP proteins and the capacity of a single CYP protein to metabolize multiple different small molecules. It is thought that structural plasticity and flexibility contribute to this latter property; therefore, incorporating diverse conformational states of a particular CYP is likely an important consideration in structure-based CYP metabolism and inhibition modeling. While all-atom explicit-solvent molecular dynamics simulations can be used to generate conformational ensembles under biologically relevant conditions, existing CYP crystal structures are of the globular domain only, whereas human CYPs contain N-terminal transmembrane and linker peptides that anchor the globular catalytic domain to the endoplasmic reticulum. To determine whether this can cause significant differences in the sampled binding site conformations, microsecond scale all-atom explicit-solvent molecular dynamics simulations of the CYP2D6 globular domain in an aqueous environment were compared with those of the full-length protein anchored in a POPC lipid bilayer. While bilayer-anchoring damped some structural fluctuations in the globular domain relative to the aqueous simulations, none of the affected residues included binding site pocket residues. Furthermore, clustering of molecular dynamics snapshots based on either pairwise binding site pocket RMSD or volume differences demonstrated a lack of separation of snapshots from the two simulation conditions into different clusters. These results suggest the substantially simpler and computationally cheaper aqueous simulation approach can be used to generate a relevant conformational ensemble of the CYP2D6 binding site for structure-based metabolism and inhibition modeling.

Water Exchange from the Buried Binding Sites of Cytochrome P450 Enzymes 1A2, 2D6, and 3A4 Correlates with Conformational Fluctuations.

Human cytochrome P450 enzymes (CYPs) are critical for the metabolism of small-molecule pharmaceuticals (drugs). As such, the prediction of drug metabolism by and drug inhibition of CYP activity is an important component of the drug discovery and design process. Relative to the availability of a wide range of experimental atomic-resolution CYP structures, the development of structure-based CYP activity models has been limited. To better characterize the role of CYP conformational fluctuations in CYP activity, we perform multiple microsecond-scale all-atom explicit-solvent molecular dynamics (MD) simulations on three CYP isoforms, 1A2, 2D6, and 3A4, which together account for the majority of CYP-mediated drug metabolism. The MD simulations employ a variety of positional restraints, ranging from keeping all CYP atoms close to their experimentally determined coordinates to allowing full flexibility. We find that, with full flexibility, large fluctuations in the CYP binding sites correlate with efficient water exchange from these buried binding sites. This is especially true for 1A2, which, when restrained to its crystallographic conformation, is unable to exchange water between the binding site and bulk solvent. These findings imply that, in addition to crystal structures, a representative ensemble of conformational states ought to be included when developing structure-based CYP activity models.

Site Identification by Ligand Competitive Saturation-Biologics Approach for Structure-Based Protein Charge Prediction.

Protein-based therapeutics typically require high concentrations of the active protein, which can lead to protein aggregation and high solution viscosity. Such solution behaviors can limit the stability, bioavailability, and manufacturability of protein-based therapeutics and are directly influenced by the charge of a protein. Protein charge is a system property affected by its environment, including the buffer composition, pH, and temperature. Thus, the charge calculated by summing the charges of each residue in a protein, as is commonly done in computational methods, may significantly differ from the effective charge of the protein as these calculations do not account for contributions from bound ions. Here, we present an extension of the structure-based approach termed site identification by ligand competitive saturation-biologics (SILCS-Biologics) to predict the effective charge of proteins. The SILCS-Biologics approach was applied on a range of protein targets in different salt environments for which membrane-confined electrophoresis-determined charges were previously reported. SILCS-Biologics maps the 3D distribution and predicted occupancy of ions, buffer molecules, and excipient molecules bound to the protein surface in a given salt environment. Using this information, the effective charge of the protein is predicted such that the concentrations of the ions and the presence of excipients or buffers are accounted for. Additionally, SILCS-Biologics also produces 3D structures of the binding sites of ions on the proteins, which enable further analyses such as the characterization of protein surface charge distribution and dipole moments in different environments. Notable is the capability of the method to account for competition between salts, excipients, and buffers on the calculated electrostatic properties in different protein formulations. Our study demonstrates the ability of the SILCS-Biologics approach to predict the effective charge of proteins and its applicability in uncovering protein-ion interactions and their contributions to protein solubility and function.

Atomic-Resolution Experimental Structural Biology and Molecular Dynamics Simulations of Hyaluronan and Its Complexes.

This review summarizes the atomic-resolution structural biology of hyaluronan and its complexes available in the Protein Data Bank, as well as published studies of atomic-resolution explicit-solvent molecular dynamics simulations on these and other hyaluronan and hyaluronan-containing systems. Advances in accurate molecular mechanics force fields, simulation methods and software, and computer hardware have supported a recent flourish in such simulations, such that the simulation publications now outnumber the structural biology publications by an order of magnitude. In addition to supplementing the experimental structural biology with computed dynamic and thermodynamic information, the molecular dynamics studies provide a wealth of atomic-resolution information on hyaluronan-containing systems for which there is no atomic-resolution structural biology either available or possible. Examples of these summarized in this review include hyaluronan pairing with other hyaluronan molecules and glycosaminoglycans, with ions, with proteins and peptides, with lipids, and with drugs and drug-like molecules. Despite limitations imposed by present-day computing resources on system size and simulation timescale, atomic-resolution explicit-solvent molecular dynamics simulations have been able to contribute significant insight into hyaluronan's flexibility and capacity for intra- and intermolecular non-covalent interactions.

Sulfation and Calcium Favor Compact Conformations of Chondroitin in Aqueous Solutions.

The effects of sulfation and calcium cations (Ca2+) on the atomic-resolution conformational properties of chondroitin carbohydrate polymers in aqueous solutions are not well studied owing to experimental challenges. Here, we compare all-atom explicit-solvent molecular dynamics simulations results for pairs of O-type (nonsulfated) and A-type (GlcNAc 4-O-sulfated) chondroitin 20-mers in 140 mM NaCl with and without Ca2+ and find that both sulfation and Ca2+ favor more compact polymer conformations. We also show that subtle differences in force-field parametrization can have dramatic effects on Ca2+ binding to chondroitin carboxylate and sulfate functional groups and thereby determine Ca2+-mediated intra- and interstrand association. In addition to providing an atomic-resolution picture of the interaction of Ca2+ with sulfated and nonsulfated chondroitin polymers, the molecular dynamics data emphasize the importance of careful force-field parametrization to balance ion-water and ion-chondroitin interactions and suggest additional parametrization efforts to tune interactions involving sulfate.

Pyranose Ring Puckering Thermodynamics for Glycan Monosaccharides Associated with Vertebrate Proteins.

The conformational properties of carbohydrates can contribute to protein structure directly through covalent conjugation in the cases of glycoproteins and proteoglycans and indirectly in the case of transmembrane proteins embedded in glycolipid-containing bilayers. However, there continue to be significant challenges associated with experimental structural biology of such carbohydrate-containing systems. All-atom explicit-solvent molecular dynamics simulations provide a direct atomic resolution view of biomolecular dynamics and thermodynamics, but the accuracy of the results depends on the quality of the force field parametrization used in the simulations. A key determinant of the conformational properties of carbohydrates is ring puckering. Here, we applied extended system adaptive biasing force (eABF) all-atom explicit-solvent molecular dynamics simulations to characterize the ring puckering thermodynamics of the ten common pyranose monosaccharides found in vertebrate biology (as represented by the CHARMM carbohydrate force field). The results, along with those for idose, demonstrate that the CHARMM force field reliably models ring puckering across this diverse set of molecules, including accurately capturing the subtle balance between 4C1 and 1C4 chair conformations in the cases of iduronate and of idose. This suggests the broad applicability of the force field for accurate modeling of carbohydrate-containing vertebrate biomolecules such as glycoproteins, proteoglycans, and glycolipids.

Constructing 3-Dimensional Atomic-Resolution Models of Nonsulfated Glycosaminoglycans with Arbitrary Lengths Using Conformations from Molecular Dynamics.

Glycosaminoglycans (GAGs) are the linear carbohydrate components of proteoglycans (PGs) and are key mediators in the bioactivity of PGs in animal tissue. GAGs are heterogeneous, conformationally complex, and polydisperse, containing up to 200 monosaccharide units. These complexities make studying GAG conformation a challenge for existing experimental and computational methods. We previously described an algorithm we developed that applies conformational parameters (i.e., all bond lengths, bond angles, and dihedral angles) from molecular dynamics (MD) simulations of nonsulfated chondroitin GAG 20-mers to construct 3-D atomic-resolution models of nonsulfated chondroitin GAGs of arbitrary length. In the current study, we applied our algorithm to other GAGs, including hyaluronan and nonsulfated forms of dermatan, keratan, and heparan and expanded our database of MD-generated GAG conformations. Here, we show that individual glycosidic linkages and monosaccharide rings in 10- and 20-mers of hyaluronan and nonsulfated dermatan, keratan, and heparan behave randomly and independently in MD simulation and, therefore, using a database of MD-generated 20-mer conformations, that our algorithm can construct conformational ensembles of 10- and 20-mers of various GAG types that accurately represent the backbone flexibility seen in MD simulations. Furthermore, our algorithm efficiently constructs conformational ensembles of GAG 200-mers that we would reasonably expect from MD simulations.

Efficient Construction of Atomic-Resolution Models of Non-Sulfated Chondroitin Glycosaminoglycan Using Molecular Dynamics Data.

Glycosaminoglycans (GAGs) are linear, structurally diverse, conformationally complex carbohydrate polymers that may contain up to 200 monosaccharides. These characteristics present a challenge for studying GAG conformational thermodynamics at atomic resolution using existing experimental methods. Molecular dynamics (MD) simulations can overcome this challenge but are only feasible for short GAG polymers. To address this problem, we developed an algorithm that applies all conformational parameters contributing to GAG backbone flexibility (i.e., bond lengths, bond angles, and dihedral angles) from unbiased all-atom explicit-solvent MD simulations of short GAG polymers to rapidly construct models of GAGs of arbitrary length. The algorithm was used to generate non-sulfated chondroitin 10- and 20-mer ensembles which were compared to MD-generated ensembles for internal validation. End-to-end distance distributions in constructed and MD-generated ensembles have minimal differences, suggesting that our algorithm produces conformational ensembles that mimic the backbone flexibility seen in simulation. Non-sulfated chondroitin 100- and 200-mer ensembles were constructed within a day, demonstrating the efficiency of the algorithm and reduction in time and computational cost compared to simulation.

Rigidity and flexibility in the tetrasaccharide linker of proteoglycans from atomic-resolution molecular simulation.

Proteoglycans (PGs) are covalent conjugates between protein and carbohydrate (glycosaminoglycans). Certain classes of glycosaminoglycans such as chondroitin sulfate/dermatan sulfate and heparan sulfate utilize a specific tetrasaccharide linker for attachment to the protein component: GlcAß1-3Galß1-3Galß1-4Xylß1-O-Ser. Toward understanding the conformational preferences of this linker, the present work used all-atom explicit-solvent molecular dynamics (MD) simulations combined with Adaptive Biasing Force (ABF) sampling to determine high-resolution, high-precision conformational free energy maps ΔG(φ, ψ) for each glycosidic linkage between constituent disaccharides, including the variant where GlcA is substituted with IdoA. These linkages are characterized by single, predominant (> 97% occupancy), and broad (45° × 60° for ΔG(φ, ψ) < 1 kcal/mol) free-energy minima, while the Xyl-Ser linkage has two such minima similar in free-energy, and additional flexibility from the Ser sidechain dihedral. Conformational analysis of microsecond-scale standard MD on the complete tetrasaccharide-O-Ser conjugate is consistent with ABF data, suggesting (φ, ψ) probabilities are independent of the linker context, and that the tetrasaccharide acts as a relatively rigid unit whereas significant conformational heterogeneity exists with respect to rotation about bonds connecting Xyl to Ser. © 2017 Wiley Periodicals, Inc.

Computational functional group mapping for drug discovery.

Computational functional group mapping (cFGM) is emerging as a high-impact complement to existing widely used experimental and computational structure-based drug discovery methods. cFGM provides comprehensive atomic-resolution 3D maps of the affinity of functional groups that can constitute drug-like molecules for a given target, typically a protein. These 3D maps can be intuitively and interactively visualized by medicinal chemists to rapidly design synthetically accessible ligands. Given that the maps can inform selection of functional groups for affinity, specificity, and pharmacokinetic properties, they are of utility for both the optimization of existing drug candidates and creating novel ones. Here, I review recent advances in cFGM with emphasis on the unique information content in the approach that offers the potential of broadly facilitating structure-based ligand design.

Folding of Fibroblast Growth Factor 1 Is Critical for Its Nonclassical Release.

Fibroblast growth factor 1 (FGF1), a ubiquitously expressed pro-angiogenic protein that is involved in tissue repair, carcinogenesis, and maintenance of vasculature stability, is released from the cells via a stress-dependent nonclassical secretory pathway. FGF1 secretion is a result of transmembrane translocation of this protein. It correlates with the ability of FGF1 to permeabilize membranes composed of acidic phospholipids. Like several other nonclassically exported proteins, FGF1 exhibits ß-barrel folding. To assess the role of folding of FGF1 in its secretion, we applied targeted mutagenesis in combination with a complex of biophysical methods and molecular dynamics studies, followed by artificial membrane permeabilization and stress-induced release experiments. It has been demonstrated that a mutation of proline 135 located in the C-terminus of FGF1 results in (i) partial unfolding of FGF1, (ii) a decrease in FGF1's ability to permeabilize bilayers composed of phosphatidylserine, and (iii) drastic inhibition of stress-induced FGF1 export. Thus, folding of FGF1 is critical for its nonclassical secretion.

Revealing the Mechanisms of Protein Disorder and N-Glycosylation in CD44-Hyaluronan Binding Using Molecular Simulation.

The extracellular N-terminal hyaluronan binding domain (HABD) of CD44 is a small globular domain that confers hyaluronan (HA) binding functionality to this large transmembrane glycoprotein. When recombinantly expressed by itself, HABD exists as a globular water-soluble protein that retains the capacity to bind HA. This has enabled atomic-resolution structural biology experiments that have revealed the structure of HABD and its binding mode with oligomeric HA. Such experiments have also pointed to an order-to-disorder transition in HABD that is associated with HA binding. However, it had remained unclear how this structural transition was involved in binding since it occurs in a region of HABD distant from the HA-binding site. Furthermore, HABD is known to be N-glycosylated, and such glycosylation can diminish HA binding when the associated N-glycans are capped with sialic acid residues. The intrinsic flexibility of disordered proteins and of N-glycans makes it difficult to apply experimental structural biology approaches to probe the molecular mechanisms of how the order-to-disorder transition and N-glycosylation can modulate HA binding by HABD. We review recent results from molecular dynamics simulations that provide atomic-resolution mechanistic understanding of such modulation to help bridge gaps between existing experimental binding and structural biology data. Findings from these simulations include: Tyr42 may function as a molecular switch that converts the HA-binding site from a low affinity to a high affinity state; in the partially disordered form of HABD, basic amino acids in the C-terminal region can gain sufficient mobility to form direct contacts with bound HA to further stabilize binding; and terminal sialic acids on covalently attached N-glycans can form charge-paired hydrogen bonding interactions with basic amino acids that could otherwise bind to HA, thereby blocking HA binding to glycosylated CD44 HABD.

Sulfation and cation effects on the conformational properties of the glycan backbone of chondroitin sulfate disaccharides.

Chondroitin sulfate (CS) is one of several glycosaminoglycans that are major components of proteoglycans. A linear polymer consisting of repeats of the disaccharide -4GlcAß1-3GalNAcß1-, CS undergoes differential sulfation resulting in five unique sulfation patterns. Because of the dimer repeat, the CS glycosidic "backbone" has two distinct sets of conformational degrees of freedom defined by pairs of dihedral angles: (ϕ1, ψ1) about the ß1-3 glycosidic linkage and (ϕ2, ψ2) about the ß1-4 glycosidic linkage. Differential sulfation and the possibility of cation binding, combined with the conformational flexibility and biological diversity of CS, complicate experimental efforts to understand CS three-dimensional structures at atomic resolution. Therefore, all-atom explicit-solvent molecular dynamics simulations with Adaptive Biasing Force sampling of the CS backbone were applied to obtain high-resolution, high-precision free energies of CS disaccharides as a function of all possible backbone geometries. All 10 disaccharides (ß1-3 vs ß1-4 linkage × five different sulfation patterns) were studied; additionally, ion effects were investigated by considering each disaccharide in the presence of either neutralizing sodium or calcium cations. GlcAß1-3GalNAc disaccharides have a single, broad, thermodynamically important free-energy minimum, whereas GalNAcß1-4GlcA disaccharides have two such minima. Calcium cations but not sodium cations bind to the disaccharides, and binding is primarily to the GlcA -COO(-) moiety as opposed to sulfate groups. This binding alters the glycan backbone thermodynamics in instances where a calcium cation bound to -COO(-) can act to bridge and stabilize an interaction with an adjacent sulfate group, whereas, in the absence of this cation, the proximity of a sulfate group to -COO(-) results in two like charges being both desolvated and placed adjacent to each other and is found to be destabilizing. In addition to providing information on sulfation and cation effects, the present results can be applied to building models of CS polymers and as a point of comparison in studies of CS polymer backbone dynamics and thermodynamics.

Site Identification by Ligand Competitive Saturation (SILCS) simulations for fragment-based drug design.

Fragment-based drug design (FBDD) involves screening low molecular weight molecules ("fragments") that correspond to functional groups found in larger drug-like molecules to determine their binding to target proteins or nucleic acids. Based on the principle of thermodynamic additivity, two fragments that bind nonoverlapping nearby sites on the target can be combined to yield a new molecule whose binding free energy is the sum of those of the fragments. Experimental FBDD approaches, like NMR and X-ray crystallography, have proven very useful but can be expensive in terms of time, materials, and labor. Accordingly, a variety of computational FBDD approaches have been developed that provide different levels of detail and accuracy.The Site Identification by Ligand Competitive Saturation (SILCS) method of computational FBDD uses all-atom explicit-solvent molecular dynamics (MD) simulations to identify fragment binding. The target is "soaked" in an aqueous solution with multiple fragments having different identities. The resulting computational competition assay reveals what small molecule types are most likely to bind which regions of the target. From SILCS simulations, 3D probability maps of fragment binding called "FragMaps" can be produced. Based on the probabilities relative to bulk, SILCS FragMaps can be used to determine "Grid Free Energies (GFEs)," which provide per-atom contributions to fragment binding affinities. For essentially no additional computational overhead relative to the production of the FragMaps, GFEs can be used to compute Ligand Grid Free Energies (LGFEs) for arbitrarily complex molecules, and these LGFEs can be used to rank-order the molecules in accordance with binding affinities.

Current status of protein force fields for molecular dynamics simulations.

The current status of classical force fields for proteins is reviewed. These include additive force fields as well as the latest developments in the Drude and AMOEBA polarizable force fields. Parametrization strategies developed specifically for the Drude force field are described and compared with the additive CHARMM36 force field. Results from molecular simulations of proteins and small peptides are summarized to illustrate the performance of the Drude and AMOEBA force fields.

Terminal sialic acids on CD44 N-glycans can block hyaluronan binding by forming competing intramolecular contacts with arginine sidechains.

Specific sugar residues and their linkages form the basis of molecular recognition for interactions of glycoproteins with other biomolecules. Seemingly small changes, like the addition of a single monosaccharide in the covalently attached glycan component of glycoproteins, can greatly affect these interactions. For instance, the sialic acid capping of glycans affects protein-ligand binding involved in cell-cell and cell-matrix interactions. CD44 is a single-pass transmembrane glycoprotein whose binding with its carbohydrate ligand hyaluronan (HA), an extracellular matrix component, mediates processes such as leukocyte homing, cell adhesion, and tumor metastasis. This binding is highly regulated by glycosylation of the N-terminal extracellular hyaluronan-binding domain (HABD); specifically, sialic acid capped N-glycans of HABD inhibit ligand binding. However, the molecular mechanism behind this sialic acid mediated regulation has remained unknown. Two of the five N-glycosyation sites of HABD have been previously identified as having the greatest inhibitory effect on HA binding, but only if the glycans contain terminal sialic acid residues. These two sites, Asn25 and Asn120, were chosen for in silico glycosylation in this study. Here, from extensive standard molecular dynamics simulations and biased simulations, we propose a molecular mechanism for this behavior based on spontaneously-formed charge-paired hydrogen bonding interactions between the negatively-charged sialic acid residues and positively-charged Arg sidechains known to be critically important for binding to HA, which itself is negatively charged. Such intramolecular hydrogen bonds would preclude associations critical to hyaluronan binding. This observation suggests how CD44 and related glycoprotein binding is regulated by sialylation as cellular environments fluctuate.

Supramolecular assemblies of a conjugate of nucleobase, amino acids, and saccharide act as agonists for proliferation of embryonic stem cells and development of zygotes.

The synthetic challenges in glycobiology and glycochemistry hamper the development of glycobiomaterials for biomedicine. Here we report the use of molecular self-assembly to sidestep the laborious synthesis of complex glycans for promoting the proliferation of murine embryonic stem (mES) cells. Our study shows that the supramolecular assemblies of a small molecule conjugate of nucleobase, amino acids, and saccharide, as a de novo glycoconjugate, promote the proliferation of mES cells and the development of zygotes into blastocysts of mouse. Molecular engineering confirms that each motif (i.e., adenine, Arg-Gly-Asp (RGD) domain, and glucosamine) is indispensable for the observed activity of the conjugate. As the first example of using assemblies of the molecular conjugates of multiple fundamental biological building blocks to control cell behaviors, this work illustrates an unprecedented approach to use supramolecular assemblies as multifunctional mimics of glycoconjugates.

Molecular mechanics.

Molecular Mechanics (MM) force fields are the methods of choice for protein simulations, which are essential in the study of conformational flexibility. Given the importance of protein flexibility in drug binding, MM is involved in most if not all Computational Structure-Based Drug Discovery (CSBDD) projects. This paper introduces the reader to the fundamentals of MM, with a special emphasis on how the target data used in the parametrization of force fields determine their strengths and weaknesses. Variations and recent developments such as polarizable force fields are discussed. The paper ends with a brief overview of common force fields in CSBDD.

CD44 receptor unfolding enhances binding by freeing basic amino acids to contact carbohydrate ligand.

The extracellular carbohydrate-binding domain of the Type I transmembrane receptor CD44 is known to undergo affinity switching, where change in conformation leads to enhanced binding of its carbohydrate ligand hyaluronan. Separate x-ray crystallographic and NMR experiments have led to competing explanations, with the former supporting minor conformational changes at the binding site and the latter a major order-to-disorder unfolding transition distant from the binding site. Here, all-atom explicit-solvent molecular dynamics studies employing adaptive biasing force sampling revealed a substantial favorable free-energy change associated with contact formation between the Arg(41) side chain and hyaluronan at the binding site, independent of whether the distant site was ordered or disordered. Analogous computational experiments on Arg(41)Ala mutants showed loss of this favorable free-energy change, consistent with existing experimental data. More provocatively, the simulation data revealed the molecular mechanism by which the order-to-disorder transition enhances hyaluronan binding: in the disordered state, a number of basic residues gain sufficient conformational freedom-lacking in the ordered state-to spontaneously form side-chain contacts with hyaluronan. Mutation of these residues to Ala had been known to decrease binding affinity, but there had previously been no structural explanation, given their lack of proximity to the carbohydrate-binding site in existing structures of the complex.

Targeting protein tyrosine phosphatase SHP2 for the treatment of PTPN11-associated malignancies.

Activating mutations in PTPN11 (encoding SHP2), a protein tyrosine phosphatase (PTP) that plays an overall positive role in growth factor and cytokine signaling, are directly associated with the pathogenesis of Noonan syndrome and childhood leukemias. Identification of SHP2-selective inhibitors could lead to the development of new drugs that ultimately serve as treatments for PTPN11-associated diseases. As the catalytic core of SHP2 shares extremely high homology to those of SHP1 and other PTPs that play negative roles in cell signaling, to identify selective inhibitors of SHP2 using computer-aided drug design, we targeted a protein surface pocket that is adjacent to the catalytic site, is predicted to be important for binding to phosphopeptide substrates, and has structural features unique to SHP2. From computationally selected candidate compounds, #220-324 effectively inhibited SHP2 activity with an IC50 of 14 µmol/L. Fluorescence titration experiments confirmed its direct binding to SHP2. This active compound was further verified for its ability to inhibit SHP2-mediated cell signaling and cellular function with minimal off-target effects. Furthermore, mouse myeloid progenitors with the activating mutation (E76K) in PTPN11 and patient leukemic cells with the same mutation were more sensitive to this inhibitor than wild-type cells. This study provides evidence that SHP2 is a "druggable" target for the treatment of PTPN11-associated diseases. As the small-molecule SHP2 inhibitor identified has a simple chemical structure, it represents an ideal lead compound for the development of novel anti-SHP2 drugs. Mol Cancer Ther; 12(9); 1738-48. ©2013 AACR.