Identification of Interacting Hot Spots in the β3 Integrin Stalk Using Comprehensive Interface Design*

Protein-protein interfaces are usually large and complementary surfaces, but specific side chains, representing energetic “hot spots,” often contribute disproportionately to binding free energy. We used a computational method, comprehensive interface design, to identify hot spots in the interface between the stalk regions of the β3 and the complementary αIIb and αv integrin subunits. Using the Rosetta alanine-scanning and design algorithms to predict destabilizing, stabilizing, and neutral mutations in the β3 region extending from residues Lys532 through Gly690, we predicted eight alanine mutations that would destabilize the αIIbβ3 interface as well as nine predicted to destabilize the αvβ3 interface, by at least 0.3 kcal/mol. The mutations were widely and unevenly distributed, with four between residues 552 and 563 and five between 590 and 610, but none between 565 and 589, and 611 and 655. Further, mutations destabilizing the αvβ3 and αIIbβ3 interfaces were not identical. The predictions were then tested by introducing selected mutations into the full-length integrins expressed in Chinese hamster ovary cells. Five mutations predicted to destabilize αIIb and β3 caused fibrinogen binding to αIIbβ3, whereas three of four predicted to be neutral or stabilizing did not. Conversely, a mutation predicted to destabilize αvβ3, but not αIIbβ3 (D552A), caused osteopontin binding to αvβ3, but not fibrinogen binding to αIIbβ3. These results indicate that stability of the distal stalk interface is involved in constraining integrins in stable, inactive conformations. Further, they demonstrate the ability of comprehensive interface design to identify functionally significant integrin mutations.

Integrins are transmembrane (TM) 4 heterodimers that transmit signals bidirectionally across cell membranes and reside on cell surfaces in a finely tuned equilibrium between resting low affinity and active high affinity conformations (1). Thus, binding of ligands to integrin extracellular domains initiates intracellular signaling pathways ("outside-in signaling"), whereas intracellular signaling increases the affinity of integrin extracellular domains for ligands ("inside-out signaling"). Integrin-mediated bidirectional signaling has been particularly well studied for the integrin ␣IIb␤3 and the homologous integrin ␣v␤3 because of the role these integrins play in hemostasis, thrombosis, and angiogenesis (2).
Electron microscope images of rotary-shadowed ␣IIb␤3 depict an extended heterodimer consisting of an 8 ϫ 12-nm nodular head containing its ligand-binding site and two 18-nm flexible stalks containing its TM and cytoplasmic domains (3). However, crystal structures of the extracellular portions of inactive ␣IIb␤3 (4) and ␣v␤3 (5) revealed that the molecules in the crystals were severely bent with their ligandbinding site on the nodular head oriented toward the cell surface. Thus, large conformational changes appear to occur upon ␣IIb␤3 and ␣v␤3 activation (6). A preponderance of evidence suggests that these changes result in a shift from the bent to a fully extended conformation (7). Other results, however, suggest that bent integrins are fully capable of binding ligands (8). Regardless, physiologic ␣IIb␤3 activation is initiated when the cytoplasmic proteins talin and kindlin-3 bind to the ␤3 cytoplasmic tail (9) and is thought to be followed by cytoplasmic and TM domain separation, as well as separation of the membrane-proximal portions of the ␣ and ␤ subunit extracellular stalks (4, 6) ( Fig. 1). This suggests that an extended interface involving portions of the juxtamembrane cytoplasmic, TM, and extracellular stalk domains constrains ␣IIb␤3 in its inactive conformation.
Site-directed mutagenesis has allowed the identification of interactions that maintain integrins in the resting state. Activating mutations are widely distributed throughout the proteins and result in remodeling or dissociation of subunitsubunit interactions spanning from the extracellular, ligandbinding domain to the cytoplasmic domains. As a result, mutations that disrupt subunit-subunit and interdomain interactions of the resting state appear to activate the protein by destabilizing the default resting state. For example, disruption of intersubunit interactions near the juxtamembrane cytoplasmic domains (10,11) and the TM (12, 13) domains leads to integrin activation. Similarly, disruption of interactions between the head and stalk domains that appear to stabilize the bent conformation also causes integrin activation (14,15).
What has been less clear is the extent to which dissociation of the extracellular stalk domains is needed for integrin activation. Experiments in which disulfides and/or coiled coils have been used to hold the C-terminal ends of the extracellular stalks in proximity lead to inactive integrins (6,16), although it is not entirely clear whether the lack of activity re-flects mere proximity effects or constraining the integrin to a nonnatively cross-linked conformation. In this case, a complementary strategy to destabilize the intersubunit stalk interface should lead to activation rather than inactivation.
Point mutations often provide substantial insight into the folding, association, and function of proteins (17,18). However, it is often not clear in advance which mutations will be most informative. A potential solution for this problem is to use computational methods that predict the energetic effect of mutations (19). If such methods are sufficiently robust, stabilizing or destabilizing mutants could be selected computationally when a structure is known, and experiments could focus on determining the biological effects of mutations, rather than iteratively searching for informative ones. In particular, with a comprehensive set of accurate predictions, not only disruptive, but also stabilizing mutations could be introduced into proteins and the biological effects studied.
To test whether destabilizing the intersubunit stalk interface results in integrin activation, we used the Rosetta energy functions to predict mutations in distinct regions of the ␤3 stalk that would destabilize, stabilize, or have little effect on its interactions with ␣IIb or ␣v (20,21). Using these computational methods, we identified energetic "hot spots" that contribute disproportionately to the binding free energy between the distal ␤3 stalk and ␣IIb and ␣v. We then tested whether mutating these hot spots would result in integrin activation by measuring the activation state of full-length integrins containing mutated hot spots expressed in CHO cells. The results of these experiments demonstrate that maintaining the interface between the membrane-proximal region of the ␤3 stalk with ␣IIb and ␣v is critical for maintaining the resting, low affinity state of ␣IIb␤3 and ␣v␤3. Further, they suggest that small molecules designed to stabilize this extracellular interface could be useful inhibitors of integrin activation.

EXPERIMENTAL PROCEDURES
Computational Design-Predicted disruptive mutations were identified using the interface alanine-scanning Rosetta server (20,21). For the structure of ␣IIb␤3 (4), chains A and B were selected for the calculation because these chains are more complete than chains C and D. For the structure of ␣v␤3, the original structure (5) was used. Residues in the stalk where alanine substitutions were predicted to destabilize both interfaces by greater than 0.3 kcal/mol were selected for mutagenesis.
Other calculations were performed using the Rosetta molecular modeling program (22). The arguments interface and pmut_scan were used for all calculations. Following Sammond et al. (23), for dampened repulsion energies, the soft_ rep_design was used (24). Calculations that allowed side chains to repack also included the argument repack_neighbors.
CHO cells were cultured in Ham's F-12 medium (Invitrogen) supplemented with 10% fetal bovine serum (Hyclone Laboratories). Plasmids containing cDNAs for ␣IIb and ␤3 were introduced into CHO cells using FuGENE 6 according to the manufacturer's instructions (Roche Applied Science). Two days after transfection, cells were transferred to selection medium containing 500 g/ml G418 (Invitrogen) and 300 g/ml Zeocin (Invitrogen). After 3 weeks of selection, ␣IIb␤3 expression was assessed by flow cytometry using A2A9, a monoclonal antibody (mAb) that recognizes the human ␣IIb␤3 heterodimer. Transfected cells were sorted by fluorescence-activated cell sorting (FACS) to obtain cell lines expressing high levels of ␣IIb␤3. CHO cells also express endogenous hamster ␣v that can form ␣v␤3 heterodimers with transfected human ␤3. The amount of ␣v␤3 on the transfected cells was assessed by flow cytometry using the ␣v␤3specific monoclonal antibody LM609 (Chemicon International) (supplemental Fig. 1).
Fibrinogen Binding to CHO Cells Expressing ␣IIb␤3-Fibrinogen binding to ␣IIb␤3 expressed on the CHO cell surface was measured as described previously (25). Briefly, CHO cells (2 ϫ 10 6 cells/ml) were incubated with the ␤3-specific mAb SSA6 on ice for 30 min. Labeled cells were washed and incubated for 30 min at 37°C with phycoerythrin-conjugated anti-mouse IgG (Molecular Probes), 200 g/ml fibrinogen conjugated with Alexa Fluor 488 (Molecular Probes), and freshly made 5 mM dithiothreitol (DTT) Ϯ 5 mM EDTA. The ␣IIb is shown in green, ␤3 in cyan. The models are based on an extensive body of evidence that activation converts ␣IIb␤3 from a bent to an extended molecule (4, 6), including our own rotary-shadowed electron microscope images of ␣IIb␤3 bound to fibrinogen in which ␣IIb␤3 is fully extended with separated stalks (3,6). Nonetheless, there is also evidence that integrins in the bent conformation are able to interact with ligands (8).
cells were washed, fixed with 0.37% formalin in phosphatebuffered saline (PBS), and examined by two-color FACS analysis. Fibrinogen specifically bound to ␣IIb␤3 was defined as fibrinogen binding inhibited by EDTA.
Specific fibrinogen binding data were used to calculate a fibrinogen binding index (F i ), using the equation where FB c mut represents constitutive fibrinogen binding to ␣IIb␤3; FB DTT mut, fibrinogen binding to mutant ␣IIb␤3 induced by 5 mM DTT; FB c WT, constitutive fibrinogen binding to wild-type (WT) ␣IIb␤3; and FB DTT WT, fibrinogen binding to WT ␣IIb␤3 induced by 5 mM DTT.
Rupture Force Spectroscopy (Laser Tweezers)-A custombuilt laser tweezers apparatus assembled from a Nikon Diaphot 300 inverted microscope, 100 ϫ 1.3 NA Fluor lens, and a Spectra Physics FCBar Nd:YAG laser was used to measure the strength of osteopontin (OPN) binding to CHO cells, as described previously for fibrinogen binding to platelets and CHO cells and OPN binding to platelets (26 -28). Briefly, recombinant human OPN (R & D Systems) was covalently bound to 1.87-m carboxylate-modified latex beads. Transfected CHO cells were permitted to settle and attach spontaneously to the polylysine-coated bottom of the chamber. An OPN-coated bead, trapped by the laser light, was brought into proximity of an immobilized cell, oscillated at 10 Hz with a 0.8-m peak-to-peak amplitude, and then brought into repeated intermittent contact with the cell by micromanipulation. Data collection was initiated at the first contact. Rupture forces following repeated contacts were collected into 5-pNwide bins. The percentage of events in a particular bin (frequency, %) represents the probability of rupture events at that tension. Optical artifacts observed with or without trapped latex beads produced signals that appear as forces below 10 pN; rupture forces in this range were not considered when data were analyzed.

RESULTS
Comprehensive Interface Design-Although protein-protein interfaces are usually composed of relatively large and complementary surfaces, specific side chains in the interface often contribute disproportionately to the binding free energy (18,29). Thus, despite the presence of crystal and solution structures for these interfaces, the residues responsible for the binding affinity may not be apparent, and extensive mutagenesis is commonly required to identify these energetic hot spots. However, computational algorithms have reached the point where destabilizing (20,21) and stabilizing mutations (23) can be successfully predicted, in many cases obviating the need for time-consuming and expensive experimental effort. Here, we have employed a combined strategy, which we term "comprehensive interface design," to select a set of destabilizing, stabilizing, and neutral mutations that characterize the extracellular stalk interfaces of the integrins ␣IIb␤3 and ␣v␤3.
Structures for the ␣IIb␤3 and ␣v␤3 stalk interfaces are available (4,5). Consequently, we inputted these structures, extending from ␤3 residues Lys 532 through Gly 690 , into the Rosetta alanine-scanning algorithm to identify alanine substitutions that would be predicted to destabilize the ␣IIb␤3 and ␣v␤3 extracellular stalk interfaces (20,21). This algorithm mutates every residue in a protein-protein interface to alanine and reports a predicted change in binding free energy, optimized to reproduce experimental changes in free energy of binding observed for alanine mutants. Using this algorithm, we identified eight alanine replacements predicted to destabilize the ␣IIb␤3 interface, as well as nine replacements predicted to destabilize the ␣v␤3 interface, by at least 0.3 kcal/ mol (Table 1; Figs. 2 and 3). It is noteworthy that these replacements were widely but unevenly distributed along the ␤3 sequence examined. Thus, there were four destabilizing replacements between residues 552 and 563 and five between residues 590 and 609, but none between residues 565 and 589 and residues 610 and 655. Moreover, there were often notable differences in the effects on the free energy of ␤3 binding to ␣v and ␣IIb. For example, although Asp 552 is present in the vicinity of the interface of ␤3 with the ␣IIb and ␣v ␤ propeller domains, D552A was predicted to destabilize the interaction of ␤3 with ␣v by 0.77 kcal/mol, but have no effect on its interaction with ␣IIb. Conversely, a T609A replacement was predicted to destabilize ␤3 binding to ␣IIb by 1.4 kcal/mol, but only destabilize its binding to ␣v by 0.3 kcal/mol.
We then employed three strategies to select negative control mutations. First, we selected D552A as an alanine substitution predicted to destabilize the ␣v␤3, but not the ␣IIb␤3, interface. Second, we sought stabilizing mutations using a protocol previously shown to be successful in detecting such mutations (23) and searched for a residue predicted to have no change on the binding free energy. H626A met this criterion as it was predicted to have no effect on the binding interface when the protein side chains were repacked.
In the third strategy, we used the Rosetta design program to predict additional stabilizing mutations. The protocol of Sammond et al. (23) uses dampening repulsive energies to identify mutations that increase hydrophobicity without requiring repacking of nearby side chains. Thus, we sought hydrophobic residues that could be mutated to larger hydrophobic residues or polar residues not involved in hydrogen bonds that could be mutated to hydrophobic residues. The most stabilizing mutation of a residue fitting these criteria was V664L. We also tried a modified protocol that allowed nearby protein side chains to repack, potentially identifying larger residues that could further stabilize the interface. Thus, the same Rosetta energy function was used, but repulsive forces were not  E534  Q552  Y556  Y557  Y594  R563  T603  Q590  D606  Y594  T609  T603  K658  T609  V664 K658 V664 ␤3 Integrin Distal Stalk Hot Spots dampened, and side chains were allowed to repack. The most stabilizing prediction changed hydrophobic Thr 656 to Trp, a much larger residue that provides a greater buried hydrophobic surface area. Effect of ␤3 Stalk Mutations on the ␣IIb␤3 Activity State-In most current models of integrin regulation, the resting low affinity state of ␣IIb␤3 has a large protein-protein interface, including an interface involving the extracellular stalks of ␣IIb and ␤3, whereas in the active high affinity state, the stalks are separated (6) (Fig. 1). If these models are accurate, then destabilizing the resting stalk interface should shift ␣IIb␤3 toward its high affinity state, which can be accessed experimentally by its ability to bind fibrinogen constitutively (13). To test this hypothesis, we selected nine computationally identified mutations: five predicted to be destabilizing, two predicted to be neutral, and two predicted to be stabilizing (Table 2) and introduced them into WT ␤3 by site-directed mutagenesis. The mutants were co-expressed with WT ␣IIb in CHO cells, after which unstimulated and DTT-stimulated fibrinogen binding to the recombinant ␣IIb␤3 was measured by flow cytometry. The resulting fibrinogen-binding measurements were then expressed as a fibrinogen binding index which compares the magnitude of constitutive fibrinogen binding to the mutant ␣IIb␤3 with that to WT ␣IIb␤3.
The four alanine mutations in ␤3 predicted to destabilize the stalk interface caused ␣IIb␤3 activation when introduced into the full-length integrin, although the alanine-scanning algorithm did not correctly rank order the mutation effects (Fig. 4). Thus, although the mutation predicted to be most destabilizing, T603A with a predicted ⌬⌬G of 2.89 kcal/mol,  ␣v (open bars). Arrows indicate the locations of ␤3 mutations whose effect on ␣IIb␤3 and ␣v␤3 function was subsequently studied.   (Table 1). Val 664 is of particular interest because although V664A was correctly predicted to destabilize the stalk interface (Fig. 2), a V664L mutation was predicted to be stabilizing. To clarify these results, we replaced Val 664 with positively charged Lys and found that the mutation caused constitutive fibrinogen binding to an extent that was similar to V664A, implying that this mutation disrupted the stalk interface as well. Taken together, the results indicate that residue 664 is a hot spot at which the large hydrophobic side chains of Val or Leu contribute significantly to the binding free energy.
The alanine-scanning algorithm also accurately predicted neutral substitutions (D552A and H626A) that have no effect on ␣IIb␤3 activity. D552A is noteworthy because although it was predicted to have no effect on the free energy of ␤3 binding to ␣IIb, its ⌬⌬G for ␤3 binding to ␣v was 0.8 kcal/mol. However, the Rosetta design program was less successful in predicting stabilizing mutations. Although it accurately predicted that V664L would not activate ␣IIb␤3 (whereas both V664A and V664K are activating), it also predicted that T656W would be stabilizing. However, T656W induced fibrinogen binding to ␣IIb␤3 that was not statistically different from K658A (t test, p ϭ 0.73), a mildly activation mutation.
Effect of ␤3 Stalk Mutations on OPN Binding to ␣v␤3-To verify that D552A, as well as V664A, destabilize ␣v␤3 (Fig. 2), we used laser tweezers-based force spectroscopy to detect the interaction of WT or mutant ␣v␤3 expressed by CHO cells (supplemental Fig. 1) with OPN, an ␣v-specific ligand. Previously, we used laser tweezers to measure rupture forces between OPN and single ␣v␤3 molecules expressed on the sur-face of human platelets (27). In that case, we found that the rupture forces could be segregated into two populations: a larger population with a rupture force range of 10 -30 pN that resulted predominantly from the nonspecific interactions of the OPN-coated beads with the cell surface, and a smaller population with a rupture force range of 30 -60 pN that resulted from specific interaction of OPN with active ␣v␤3 (27). As shown in Fig. 5A, the vast majority of the interactions between cells expressing WT ␣v␤3 and OPN had exponentially declining rupture forces Ͻ30 pN that were not inhibited by the ␣v␤3-specific inhibitory peptide XJ735, indicating that they were nonspecific. However, preincubating the cells with 1 mM MnCl 2 resulted in a new broad peak of rupture forces with a maximum at Ϸ50 pN and that overlapped to a small extent with the lower rupture force range. This confirms that the WT ␣v␤3 expressed by the CHO cells was able to bind OPN when activated. By contrast, CHO cells expressing ␤3 D552A or ␤3 V664A exhibited the 50-pN rupture force peak in the absence of MnCl 2. Further, these rupture forces were inhibited by XJ735, indicating that they resulted from the constitutive binding of OPN to active ␣v␤3. To confirm these results, we calculated the cumulative probability of ␤3 D552A and ␤3 V664A causing rupture forces Ͼ10 pN. As shown in Fig. 5B, both the D552A and V664A mutations significantly increased the probability of specific (i.e. XJ735-inhibited) interactions between OPN and ␣v␤3, although to a lesser extent than exposing the cells to MnCl 2 .

DISCUSSION
Crystal structures of the bent extracellular domains of inactive ␣v␤3 and ␣IIb␤3 revealed contacts between the distal portion of the ␤3 stalk and the ␤-propeller, thigh, calf-1, and calf-2 domains of ␣v and ␣IIb (4, 5) (Fig. 1). To circumvent the expensive and time-consuming site-directed mutagenesis required to determine the physiologic significance of these contacts, we used computational protein design methods to identify interacting hot spots whose role in regulating ␤3 integrin function could be tested (20,21). Recently, Luo et al. used a similar approach to successfully predict mutations that destabilize the closed conformation of the resting ␤3 headpiece and enhance ␣IIb␤3 ligand binding affinity (30). Using the Rosetta alanine-scanning program, we predicted four alanine replacements in the ␤3 stalk that would destabilize the ␣IIb␤3 interface and subsequently found that these replacements caused ␣IIb␤3 activation. Conversely, we identified two alanine replacements that were predicted to have no effect on ␤3 binding to ␣IIb and found that neither replacement altered the ␣IIb␤3 activation state. Thus, these results confirm the utility of the Rosetta alanine-scanning method for identifying functionally significant regions in integrins. Further, they indicate that stability of the distal stalk interface is involved in constraining integrins in stable, inactive conformations.
Although there is an extended interface between the distal extracellular portion of ␤3 and the ␣ subunits of resting ␣v␤3 and ␣IIb␤3, we were able to pinpoint residues in predicted hot spots in the ␤3 ␤TD domain that contribute significantly to the interaction energy (Fig. 3). Previous reports, when taken together, corroborate our findings. Takagi et al. reported that acidic and basic coiled peptides, fused to the C termini of the ␣5␤1 extracellular domain, maintained close apposition of the distal ␣5 and ␤1 stalks and prevented binding of a fibronectin fragment to the ␣5␤1 headpiece, indicating that apposition of the distal stalks can regulate integrin activity (16). Concurrently, Zang and Springer found that ␤2 residues Gln 525 and Val 526 , located in the third ␤2 EGF-like repeat and corresponding to ␤3 residues Glu 534 and Met 535 , constrained human ␣X␤2 in an inactive state (31). It is noteworthy in this regard that replacing Glu 534 with alanine is predicted to destabilize the ␣IIb␤3 interface. Kashiwagi et al. also reported an ␣IIb␤3 variant, T562N, that produced constitutively active ␣IIb␤3 in CHO cells (32). Nonetheless, as we have predicted, T562A was inactive, as was T562Q. Thus, the mechanism by which T562N activates ␣IIb␤3 is unclear. Lastly, Arnaout and co-workers have suggested that a loop extending from the ␤TD domain of ␤3 (the CD loop) prevents ␤3 integrin activation by interacting with and preventing downward movement of the ␣7 helix of the ␤-I domain (33). However, Zhu et al. either deleted the CD loop in ␣IIb␤3 (␤3 residues 672-676) or replaced residues 672-674 individually with alanine and found, as we predicted, that none of the mutations had an effect on ␣IIb␤3 or ␣v␤3 activity (34).
Despite our ability to identify destabilizing and neutral mutations, we had less success using the Rosetta design program to predict stabilizing mutations. Although the program accurately predicted that V664L would not destabilize the ␣IIb␤3 interface, it predicted that T656W would be stabilizing. However, T656W caused fibrinogen binding to ␣IIb␤3 that was comparable with a mildly activating mutation, K658A. This finding is consistent with observations that Rosetta is only ϳ50% successful at recovering known stabilizing mutations in protein/protein interfaces (23). Moreover, because it is likely more difficult to predict strongly stabilizing mutations than it is to predict destabilizing or neutral ones, our overall agreement between prediction and experiment is larger than might be expected, perhaps reflecting the fact that most of the mutations tested were predicted to be destabilizing rather than stabilizing. In the development of their method, Sammond et al. tested whether increased flexibility, such as repacking side chains, would increase their ability to find stabilizing mutations (23). Unexpectedly, they observed the opposite behavior: repacking side chains reduced their ability to predict stabilizing mutations. Our data support this conclusion as T656W, predicted to stabilize the interface if nearby side chains are allowed to repack, appears to mildly destabilize the interface instead.
Previous computational approaches to identify interface hot spots used a change in binding free energy of 1 kcal/mol to differentiate between neutral and destabilizing alanine substitutions (20,21). However, we found that a change in predicted binding free energy of 0.3 kcal/mol was sufficient to identify alanine substitutions causing ␣IIb␤3 and/or ␣v␤3 activation. The substantially weaker affinity of the predicted ␤3 hot spots is likely a reflection of the physiologic function of ␤3 integrins. These integrins, ␣IIb␤3 in particular, are poised for activation because they must shift from their resting to their active conformations during the exceedingly short time they are exposed to damaged vasculature in flowing blood. Previously, using laser tweezers, we found that ␣IIb␤3 activation is an all-or-none phenomenon such that individual ␣IIb␤3 molecules are either in a resting or fully active conformation (35). Thus, any sufficient destabilizing event, regardless of its magnitude, should enable ␣IIb␤3 to bind fibrinogen. The similar levels of ␣IIb␤3 activation caused by Y594A, T603A, and V664A imply that these mutations are sufficiently destabilizing, whereas K658A is not. However, unlike mutations that remove hydrophobic interactions at the ␣IIb␤3 interface, Lys 658 removes a side chain to a backbone hydrogen bond that may be alternately satisfied by water molecules. Thus, careful balancing of hydrophobic and hydrogen bonding energy terms will be an important consideration for improving predictive methods. It is also noteworthy that the amounts of fibrinogen binding caused by mutations disrupting the interaction of the ␤3 TM domain with the ␣IIb TM domain were comparable to the fibrinogen binding caused by Y594A, T603A, and V664A (25). This provides additional support for the all-or-none nature of ␣IIb␤3 activation.
In summary, our results confirm the utility of an integrated interface design strategy in identifying functionally significant integrin mutations. Further, they indicate that the stability of the distal stalk interface, like the interfaces of integrin TM and membrane-proximal cytoplasmic domains, is critical for maintaining integrins in stable, inactive conformations. Moreover, because the stalk interfaces of ␣IIb␤3 and ␣v␤3 are present in an extracellular location, they could be apt targets for the development of ␣IIb␤3 and ␣v␤3 activation inhibitors.