Predictive energy landscapes for protein–protein association

We investigate protein–protein association using the associative-memory, water-mediated, structure, and energy model (AWSEM), a coarse-grained protein folding model that has been optimized using energy-landscape theory. The potential was originally parameterized by enforcing a funneled nature for a database of dimeric interfaces but was later further optimized to create funneled folding landscapes for individual monomeric proteins. The ability of the model to predict interfaces was not tested previously. The present results show that simulated annealing of the model indeed is able to predict successfully the native interfaces of eight homodimers and four heterodimers, thus amounting to a flexible docking algorithm. We go on to address the relative importance of monomer geometry, flexibility, and nonnative intermonomeric contacts in the association process for the homodimers. Monomer surface geometry is found to be important in determining the binding interface, but it is insufficient. Using a uniform binding potential rather than the water-mediated potential results in sampling of misbound structures that are geometrically preferred but are nonetheless energetically disfavored by AWSEM, as well as in nature. Depending on the stability of the unbound monomers, nonnative contacts play different roles in the association process. For unstable monomers, thermodynamic states stabilized by nonnative interactions correspond to productive, on-pathway intermediates and can, therefore, catalyze binding through a fly-casting mechanism. For stable monomers, in contrast, states stabilized by nonnative interactions generally correspond to traps that impede binding.     

Host–rabies virus protein–protein interactions as druggable antiviral targets

We present an unconventional approach to antiviral drug discovery, which is used to identify potent small molecules against rabies virus. First, we conceptualized viral capsid assembly as occurring via a host-catalyzed biochemical pathway, in contrast to the classical view of capsid formation by self-assembly. This suggested opportunities for antiviral intervention by targeting previously unappreciated catalytic host proteins, which were pursued. Second, we hypothesized these host proteins to be components of heterogeneous, labile, and dynamic multi-subunit assembly machines, not easily isolated by specific target protein-focused methods. This suggested the need to identify active compounds before knowing the precise protein target. A cell-free translation-based small molecule screen was established to recreate the hypothesized interactions involving newly synthesized capsid proteins as host assembly machine substrates. Hits from the screen were validated by efficacy against infectious rabies virus in mammalian cell culture. Used as affinity ligands, advanced analogs were shown to bind a set of proteins that effectively reconstituted drug sensitivity in the cell-free screen and included a small but discrete subfraction of cellular ATP-binding cassette family E1 (ABCE1), a host protein previously found essential for HIV capsid formation. Taken together, these studies advance an alternate view of capsid formation (as a host-catalyzed biochemical pathway), a different paradigm for drug discovery (whole pathway screening without knowledge of the target), and suggest the existence of labile assembly machines that can be rendered accessible as next-generation drug targets by the means described.     

Allosteric switch regulates protein–protein binding through collective motion

Many biological processes depend on allosteric communication between different parts of a protein, but the role of internal protein motion in propagating signals through the structure remains largely unknown. Through an experimental and computational analysis of the ground state dynamics in ubiquitin, we identify a collective global motion that is specifically linked to a conformational switch distant from the binding interface. This allosteric coupling is also present in crystal structures and is found to facilitate multispecificity, particularly binding to the ubiquitin-specific protease (USP) family of deubiquitinases. The collective motion that enables this allosteric communication does not affect binding through localized changes but, instead, depends on expansion and contraction of the entire protein domain. The characterization of these collective motions represents a promising avenue for finding and manipulating allosteric networks.Intermolecular interactions are one of the key mechanisms by which proteins mediate their biological functions. For many proteins, these interactions are enhanced or suppressed by allosteric networks that couple distant regions together (1). The mechanisms by which these networks function are just starting to be understood (2–4), and many of the important details have yet to be uncovered. In particular, the role of intrinsic protein motion and kinetics remains particularly poorly characterized. A number of structural ensembles representing ubiquitin motion have been recently proposed (5–9). Additionally, it has been suggested that through motion at the binding interface, its free state visits the same conformations found in complex with its many binding partners (5, 10). However, it remains an unanswered question if the dynamics that enable this multispecificity are only clustered around the canonical binding interface or whether this motion is allosterically coupled to the rest of the protein, especially given the presence of motion at distal sites (11).     

Phosphorylation of aquaporin-2 regulates its endocytosis and protein–protein interactions

The water channel aquaporin-2 (AQP2) is essential for urine concentration. Vasopressin regulates phosphorylation of AQP2 at four conserved serine residues at the COOH-terminal tail (S256, S261, S264, and S269). We used numerous stably transfected Madin–Darby canine kidney cell models, replacing serine residues with either alanine (A), which prevents phosphorylation, or aspartic acid (D), which mimics the charged state of phosphorylated AQP2, to address whether phosphorylation is involved in regulation of (i) apical plasma membrane abundance of AQP2, (ii) internalization of AQP2, (iii) AQP2 protein–protein interactions, and (iv) degradation of AQP2. Under control conditions, S256D- and 269D-AQP2 mutants had significantly greater apical plasma membrane abundance compared to wild type (WT)-AQP2. Activation of adenylate cyclase significantly increased the apical plasma membrane abundance of all S-A or S-D AQP2 mutants with the exception of 256D-AQP2, although 256A-, 261A-, and 269A-AQP2 mutants increased to a lesser extent than WT-AQP2. Biotin internalization assays and confocal microscopy demonstrated that the internalization of 256D- and 269D-AQP2 from the plasma membrane was slower than WT-AQP2. The slower internalization corresponded with reduced interaction of S256D- and 269D-AQP2 with several proteins involved in endocytosis, including Hsp70, Hsc70, dynamin, and clathrin heavy chain. The mutants with the slowest rate of internalization, 256D- and 269D-AQP2, had a greater protein half-life (t_1/2 = 5.1 h and t_1/2 = 4.4 h, respectively) compared to WT-AQP2 (t_1/2 = 2.9 h). Our results suggest that vasopressin-mediated membrane accumulation of AQP2 can be controlled via regulated exocytosis and endocytosis in a process that is dependent on COOH terminal phosphorylation and subsequent protein–protein interactions.     

H-Ras forms dimers on membrane surfaces via a protein–protein interface

The lipid-anchored small GTPase Ras is an important signaling node in mammalian cells. A number of observations suggest that Ras is laterally organized within the cell membrane, and this may play a regulatory role in its activation. Lipid anchors composed of palmitoyl and farnesyl moieties in H-, N-, and K-Ras are widely suspected to be responsible for guiding protein organization in membranes. Here, we report that H-Ras forms a dimer on membrane surfaces through a protein–protein binding interface. A Y64A point mutation in the switch II region, known to prevent Son of sevenless and PI3K effector interactions, abolishes dimer formation. This suggests that the switch II region, near the nucleotide binding cleft, is either part of, or allosterically coupled to, the dimer interface. By tethering H-Ras to bilayers via a membrane-miscible lipid tail, we show that dimer formation is mediated by protein interactions and does not require lipid anchor clustering. We quantitatively characterize H-Ras dimerization in supported membranes using a combination of fluorescence correlation spectroscopy, photon counting histogram analysis, time-resolved fluorescence anisotropy, single-molecule tracking, and step photobleaching analysis. The 2D dimerization K_d is measured to be ∼1 × 10³ molecules/µm², and no higher-order oligomers were observed. Dimerization only occurs on the membrane surface; H-Ras is strictly monomeric at comparable densities in solution. Analysis of a number of H-Ras constructs, including key changes to the lipidation pattern of the hypervariable region, suggest that dimerization is a general property of native H-Ras on membrane surfaces.In mammalian signal transduction, Ras functions as a binary switch in fundamental processes including proliferation, differentiation, and survival (1). Ras is a network hub; various upstream signaling pathways can activate Ras-GDP to Ras-GTP, which subsequently selects between multiple downstream effectors to elicit a varied but specific biochemical response (2, 3). Signaling specificity is achieved by a combination of conformational plasticity in Ras itself (4, 5) and dynamic control of Ras spatial organization (6, 7). Isoform-specific posttranslational lipidation targets the main H-, N-, and K-Ras isoforms to different subdomains of the plasma membrane (8–10). For example, H-Ras localizes to cholesterol-sensitive membrane domains, whereas K-Ras does not (11). A common C-terminal S-farnesyl moiety operates in concert with one (N-Ras) or two (H-Ras) palmitoyl groups, or with a basic sequence of six lysines in K-Ras4B (12), to provide the primary membrane anchorage. Importantly, the G-domain (residues 1–166) and the hypervariable region (HVR) (residues 167–189) dynamically modulate the lipid anchor localization preference to switch between distinct membrane populations (13). For example, repartitioning of H-Ras away from cholesterol-sensitive membrane domains is necessary for efficient activation of the effector Raf and GTP loading of the G-domain promotes this redistribution by a mechanism that requires the HVR (14). However, the molecular details of the coupling between lipid anchor partitioning and nucleotide-dependent protein–membrane interactions remain unclear.In addition to biochemical evidence for communication between the C-terminal membrane binding region and the nucleotide binding pocket, NMR and IR spectroscopic observations suggest that the HVR and lipid anchor membrane insertion affects Ras structure and orientation (15–17). Molecular dynamics (MD) modeling of bilayer-induced H-Ras conformations has identified two nucleotide-dependent states, which differ in HVR conformation, membrane contacts, and G-domain orientation (18). In vivo FRET measurements are consistent with a reorientation of Ras with respect to the membrane upon GTP binding (19, 20). Further modeling showed that the membrane binding region and the canonical switch I and II regions communicate across the protein via long-range side-chain interactions (21) in a conformational selection mechanism (22). Whereas these allosteric modes likely contribute to Ras partitioning and reorientation in vivo, direct functional consequences on Ras protein–protein interactions are poorly understood.Members of the Ras superfamily of small GTPases are widely considered to be monomeric (23). However, several members across the Ras GTPase subfamilies are now known to dimerize (24–28), and a class of small GTPases that use dimerization instead of GTPase activating proteins (GAPs) for GTPase activity has been identified (29). Recently, semisynthetic natively lipidated N-Ras was shown to cluster on supported membranes in vitro, in a manner broadly consistent with molecular mechanics (MM) modeling of dimers (30). For Ras, dimerization could be important because Raf, which is recruited to the membrane by binding to Ras, requires dimerization for activation. Soluble Ras does not activate Raf in vitro (31), but because artificial dimerization of GST-fused H-Ras leads to Raf activation in solution, it has been hypothesized that Ras dimers exist on membranes (32). However, presumed dimers were only detected after chemical cross-linking (32), and the intrinsic oligomeric properties of Ras remain unknown.Here, we use a combination of time-resolved fluorescence spectroscopy and microscopy to characterize H-Ras(C118S, 1–181) and H-Ras(C118S, 1–184) [referred to as Ras(C181) and Ras(C181,C184) from here on] anchored to supported lipid bilayers. By tethering H-Ras to membranes at cys181 (or both at cys181 and cys184) via a membrane-miscible lipid tail, we eliminate effects of lipid anchor clustering while preserving the HVR region between the G-domain and the N-terminal palmitoylation site at cys181 (or cys184), which is predicted to undergo large conformational changes upon membrane binding and nucleotide exchange (18). Labeling is achieved through a fluorescent Atto488-linked nucleotide. Fluorescence correlation spectroscopy (FCS) and time-resolved fluorescence anisotropy (TRFA) show that H-Ras forms surface density-dependent clusters. Photon counting histogram (PCH) analysis and single-molecule tracking (SMT) reveal that H-Ras clusters are dimers and that no higher-order oligomers are formed. A Y64A point mutation in the loop between beta strand 3 (β3) and alpha helix 2 (α2) abolishes dimer formation, suggesting that the corresponding switch II (SII) region is either part of, or allosterically coupled to, the dimer interface. The 2D dimerization K_d is measured to be on the order of 1 × 10³ molecules/µm², within the broad range of Ras surface densities measured in vivo (10, 33–35). Dimerization only occurs on the membrane surface; H-Ras is strictly monomeric at comparable densities in solution, suggesting that a membrane-induced structural change in H-Ras leads to dimerization. Comparing singly lipidated Ras(C181) and doubly lipidated Ras(C181,C184) reveals that dimer formation is insensitive to the details of HVR lipidation, suggesting that dimerization is a general property of H-Ras on membrane surfaces.     

Unbiased RNA–protein interaction screen by quantitative proteomics

Mass spectrometry (MS)-based quantitative interaction proteomics has successfully elucidated specific protein–protein, DNA–protein, and small molecule–protein interactions. Here, we developed a gel-free, sensitive, and scalable technology that addresses the important area of RNA–protein interactions. Using aptamer-tagged RNA as bait, we captured RNA-interacting proteins from stable isotope labeling by amino acids in cell culture (SILAC)-labeled mammalian cell extracts and analyzed them by high-resolution, quantitative MS. Binders specific to the RNA sequence were distinguished from background by their isotope ratios between bait and control. We demonstrated the approach by retrieving known and novel interaction partners for the HuR interaction motif, H4 stem loop, “zipcode” sequence, tRNA, and a bioinformatically-predicted RNA fold in DGCR-8/Pasha mRNA. In all experiments we unambiguously identified known interaction partners by a single affinity purification step. The 5′ region of the mRNA of DGCR-8/Pasha, a component of the microprocessor complex, specifically interacts with components of the translational machinery, suggesting that it contains an internal ribosome entry site.     

Mislocalization or low expression of mutated Shwachman–Bodian–Diamond syndrome protein

Shwachman–Diamond syndrome (SDS) is an autosomal-recessive disorder characterized by exocrine pancreatic insufficiency and bone marrow failure. Mutations in the SBDS gene are identified in most patients with SDS. Recent studies have shown that SBDS is involved in ribosome biogenesis and is localized to the nucleolus. The significance of cellular localization in SBDS is unknown, particularly as SBDS does not exhibit canonical nuclear localization signals. In this study, we have constructed wild-type deletion mutants of the critical domains and disease-associated mutants of the SBDS gene. These constructs were expressed in HeLa cells to explore the subcellular distribution of normal and mutant proteins. Wild-type SBDS was detected in the nucleus. However, constructs lacking N-terminal Domain I and two disease-associated mutants (C31W and N34I) failed to localize SBDS to the nucleus. Moreover, the amount of mutated SBDS protein was decreased. When N-terminal Domain I was overexpressed in HeLa cells, the localization of endogenous SBDS protein was changed from nuclei to cytosolic fraction. These data indicate that the N-terminal Domain I is responsible for nuclear localization. Furthermore, low expression of SBDS, as exhibited in some of the disease-associated mutants, may be associated with the pathogenesis of SDS.     

Analysing protein–protein interaction networks of human liver cancer cell lines with diverse metastasis potential

Purpose Human hepatocellular carcinoma (HCC) is one of the most mortal tumor. In a previous study, we had constructed glycoprotein expression profiles and glycoprotein databases of three human liver cancer cell lines with diverse metastasis potential. In order to discover vital glycoproteins related to pathogenesis and metastasis of HCC, in this study we analyzed previous data with bioinformatic approach. Methods We took previous data to draw the protein–protein interaction (PPI) networks of liver cell lines by searching IntACT database and then using Pajeck software. Further more, we compared the differences between the three PPI networks by drawing the PPI networks of differential glycoproteins and by naming differential display PPI networks. Results Large numbers of proliferation and apoptosis-relative proteins interact with the differential glycoproteins, and among the differential glycoproteins there are many interactions. Conclusions We conclude that neither single nor several proteins cause malignant proliferation of liver cells. “Molecule groups” concept should be introduced into diagnosis and metastasis prediction of the HCC.     

Origins of specificity and affinity in antibody–protein interactions

Natural antibodies are frequently elicited to recognize diverse protein surfaces, where the sequence features of the epitopes are frequently indistinguishable from those of nonepitope protein surfaces. It is not clearly understood how the paratopes are able to recognize sequence-wise featureless epitopes and how a natural antibody repertoire with limited variants can recognize seemingly unlimited protein antigens foreign to the host immune system. In this work, computational methods were used to predict the functional paratopes with the 3D antibody variable domain structure as input. The predicted functional paratopes were reasonably validated by the hot spot residues known from experimental alanine scanning measurements. The functional paratope (hot spot) predictions on a set of 111 antibody–antigen complex structures indicate that aromatic, mostly tyrosyl, side chains constitute the major part of the predicted functional paratopes, with short-chain hydrophilic residues forming the minor portion of the predicted functional paratopes. These aromatic side chains interact mostly with the epitope main chain atoms and side-chain carbons. The functional paratopes are surrounded by favorable polar atomistic contacts in the structural paratope–epitope interfaces; more that 80% these polar contacts are electrostatically favorable and about 40% of these polar contacts form direct hydrogen bonds across the interfaces. These results indicate that a limited repertoire of antibodies bearing paratopes with diverse structural contours enriched with aromatic side chains among short-chain hydrophilic residues can recognize all sorts of protein surfaces, because the determinants for antibody recognition are common physicochemical features ubiquitously distributed over all protein surfaces.It is incompletely understood as to how functional antibodies can almost always be elicited against unlimited possibilities of protein antigens from a limited repertoire of antibodies. Antibodies provide protection against foreign protein antigens by recognizing the antigen proteins with exquisite specificity and remarkable affinity, but the principles underlying the antibody affinity and specificity remain elusive. Consequently, current antibody discoveries are by and large limited by the uncontrollable animal immune systems (1) or by the recombinant antibody libraries with relatively infinitesimal coverage of the vast combinatorial sequence space in antibody–antigen interaction interfaces (2). In developing the efficacy of a therapeutic antibody, optimizing the affinity and specificity of the antibody–antigen interaction mostly relies on selecting and screening from a large pool of random candidates. As antibodies are becoming the most prominent class of protein therapeutics (3), a better understanding of the principles governing antibody affinity and specificity will facilitate in understanding humoral immunity and in developing novel antibody-based therapeutics.Antibody paratopes are enriched with aromatic residues. Tyrosyl side chains are overpopulated on the paratopes, noticeable on solving the first structures of antibody–antigen complexes (4). Surveys thereafter showed that Tyr and Trp frequently occur in the putative binding regions of antibodies as determined from structural and sequence data (5). Recent analyses of more than 100 high-resolution antibody–antigen complexes in the Protein Data Bank (PDB) confirm a similar conclusion that aromatic residues (Tyr, Trp, and Phe) are substantially enriched in antibody paratopes (6, 7). The fundamental role of the tyrosyl side chains in antibody–antigen recognition has been demonstrated (8), with the functional antibodies selected and screened from the minimalist designs of antibody complementarity determining region (CDR) libraries with only a small subset of amino acid types (Tyr, Ala, Asp, and Ser) (9) or with binary code (Tyr and Ser) (10).Interactions involving aromatic side chains on the CDRs of antibodies with epitope residues on protein antigens have been demonstrated to contribute energetically to antibody–antigen recognition. Alanine scanning of the antibody paratope residues of the FvD1.3-hen egg white lysozyme (HEL) and FvD1.3-FvE5.2 (anti-idiotype antibody) complexes and shotgun alanine scanning assessing the energetic contributions of paratope residues to VEGF and human epidermal growth factor receptor 2 (HER2) binding indicated that around half of the hot spots (ΔΔG ≥ 1 kcal/mol) are aromatic residues (20/40) (11, 12). Double-mutant cycle experiments dissecting the residue-pair coupling energies between the epitope and paratope for the two antibody–antigen complexes also indicated the predominant energetic contribution of the aromatic side chains (9/11) in the antibody–antigen interactions (13). These energetic assessments suggest that aromatic side chains contribute a substantial portion of the affinity of the antibody–antigen complexes in general. These results are consistent with the survey indicating that aromatic residues, in particular Tyr and Trp, account for a large portion of the hot spot residues in protein–protein interactions (14, 15).Aromatic side chains interact favorably with diverse functional groups in natural amino acids, underlying the affinity and specificity of the antibody–antigen recognition through a cumulative collection of relatively weak noncovalent interactions. The aromatic side chains interact with other aromatic side chains through face-to-edge or parallel π-stacking, with positively charged side chains through the cation–π interaction, with backbone and side-chain hydrogen bond donors through hydrogen bonding to aromatic π-systems (X–H–π interaction, X = N, O, S), with alkyl carbons through the C–H–π interaction, with sulfur-containing side chains through sulfur–arene interactions, and with negative charged side chains through anion–π interactions (16, 17). Although each of the above mentioned interactions is relatively weak, on the order of a few kilocalories per mole in model systems (16, 17), the cumulative sum of the interactions involving the aromatic side chains can reasonably account for the binding energy of 12 kcal/mol for a typical antibody–antigen interaction of K_d ∼1 nM at room temperature aqueous environment. Moreover, the specific preferences of the spatial geometries for the interacting functional groups involving aromatic side chains (see refs. 16–18 and references therein) also underlie the specificity of antibody–antigen recognitions. Direct hydrogen bonds bridging across the antibody–antigen interaction interface are expected to contribute to both the binding affinity and specificity, but the removal of an interface hydrogen bond is frequently inconsequential to the binding specificity and affinity due to compensating water-mediated interactions (13). These results suggest that the 3D distribution of the paratope aromatic side chains by and large determines the affinity and specificity of the antibody–antigen interaction.Known epitopes on antigens, on the other hand, are not easily distinguishable from the solvent accessible surfaces of protein structures. A recent review of the public domain conformational epitope prediction algorithms, for which the performances were compared with an independent test set for benchmarking, shows that the conformational epitope prediction problem remain challenging, with an area under the curve (AUC) ranging from 0.567 to 0.638 and accuracy from 15.5% to 25.6% (19). This moderate success rate was attributed to incomplete understanding of the essence of the epitopes (6). It has been well accepted that the solvent accessible and protruding surface regions are more likely to be conformational epitopes (20–23) and that the epitopes encompass substantially more loop residues than α-helix and β-strand residues (23, 24). By contrast, the conclusions from various studies on the amino acid composition of conformational epitopes are not consistent (6), in large part due to the fact that the epitope amino acid composition is not particularly distinguishable from the nonantigenic solvent accessible surface area (6, 7, 22, 23, 25). The contradiction has been discussed recently (25), indicating that the physicochemical complementarity between the paratopes and the epitopes are strikingly incomparable, with overwhelmingly emphasized tyrosyl side chains in all CDR loops (25).The goal of this work is to understand how a natural repertoire of antibodies, for which the sequence and structure are relatively limited in variation, can recognize protein antigens with seemly unlimited structural and sequence diversities. An extensive examination on the monoclonal antibodies elicited with a set of model antigens has concluded that a protein antigen surface consists of overlapping conformational epitopes forming a continuum; that is, no inherent property of the protein molecule could restrict antigenic site locations on the protein surface (26). It would be conceivable that antibodies recognize a common feature shared by all protein surface sites, and as such, a relatively limited population of antibodies could recognize limitless protein antigen surfaces. That is, protein surfaces are not as diverse as one would expect by looking at the protein sequences. However, this common feature on protein surface recognizable by antibodies is not known. Although aromatic side chains are known, in principle, to be able to interact favorably with wide varieties of functional groups in natural amino acids (see above), atomic details of the paratope aromatic side chains interacting favorably with diverse epitope surfaces have not been systematically analyzed. In addition, residues with short hydrophilic side chains (Ser, Thr, Asp, and Asn) are known to be enriched alongside the aromatic side chains in the paratopes (5, 24, 27), but the roles of these short hydrophilic side chains in antibody–antigen interactions have not been systematically investigated. More importantly, it has been well accepted that only hot spot residues in an antigen combining site of an antibody, i.e., the residues in the functional paratopes, are indispensable for the antibody–antigen interaction; side chains contacting the antigen (i.e., structural paratope residues) outside the functional paratope can frequently be truncated to Cβ carbon without affecting the antibody–antigen interaction (11, 13, 15, 28). To search for the relevant protein surface features recognizable by antibodies, it is desirable to first elucidate the principles governing the interactions for the functional paratopes with the corresponding functional epitopes. Such studies require a large number of well-defined functional paratopes and functional epitopes, but only a small number have been determined with the labor-intensive alanine scanning experiment (11–13, 29). To circumvent the scarcity of the experimental data, we use computational methods to predict the functional paratopes/epitopes in antibody–protein complex structures so that the key interactions involving the hot spots in the antibody–protein interactions can be elucidated, at least to the reliable extent depending on the functional paratope prediction accuracy.In this work, we applied computational methods to predict functional paratopes on antibody variable domains and analyzed the key atomistic contact pairs in the functional paratope–epitope interfaces. Although the structural paratope–epitope interfaces can be defined from the known complex structures, the functional binding interfaces involving hot spot residues are unknown experimentally and need to be defined with computational predictions. One set of predictions was carried out with our previously published computational method [In-silico Molecular Biology Lab–protein-protein interaction (ISMBLab-PPI)], where the protein–protein interaction confidence level (PPI_CL) for protein surface atoms to participate in protein–protein interaction is strongly correlated (r² = 0.99) with the averaged burial level of the atoms in the PPI interfaces (30). Another set of predictions was carried out with a recently published random forest algorithm, prediction of antibody contacts (proABC) (31), which was trained specifically with antibody–antigen complex structures in PDB with additional information from antibody germ-line family sequences, CDR residue positions, multiple antibody sequence alignments, CDR lengths and canonical structures, and antigen volume. Both sets of predicted functional paratope–epitope interfaces consistently led to the conclusion that antibodies, with relatively limited sequence and structural diversities in the antigen binding sites, can recognize unlimited protein antigens through recognizing the common and ubiquitous physicochemical features on all protein surfaces. The implication is that a limited repertoire of antibodies bearing paratopes with diverse structural contours enriched with aromatic side chains among short-chain hydrophilic residues can recognize all sorts of protein surfaces.     

Targeting diverse protein–protein interaction interfaces with α/β-peptides derived from the Z-domain scaffold

Peptide-based agents derived from well-defined scaffolds offer an alternative to antibodies for selective and high-affinity recognition of large and topologically complex protein surfaces. Here, we describe a strategy for designing oligomers containing both α- and β-amino acid residues (“α/β-peptides”) that mimic several peptides derived from the three-helix bundle “Z-domain” scaffold. We show that α/β-peptides derived from a Z-domain peptide targeting vascular endothelial growth factor (VEGF) can structurally and functionally mimic the binding surface of the parent peptide while exhibiting significantly decreased susceptibility to proteolysis. The tightest VEGF-binding α/β-peptide inhibits the VEGF₁₆₅-induced proliferation of human umbilical vein endothelial cells. We demonstrate the versatility of this strategy by showing how principles underlying VEGF signaling inhibitors can be rapidly extended to produce Z-domain–mimetic α/β-peptides that bind to two other protein partners, IgG and tumor necrosis factor-α. Because well-established selection techniques can identify high-affinity Z-domain derivatives from large DNA-encoded libraries, our findings should enable the design of biostable α/β-peptides that bind tightly and specifically to diverse targets of biomedical interest. Such reagents would be useful for diagnostic and therapeutic applications.Designed molecules that bind selectively to specific sites on proteins may serve as inhibitors of medically important macromolecular interactions or diagnostic tools for biomarker detection. Small molecules often fail for these applications because of the relatively large and irregularly shaped target surfaces (1–3). In contrast, large polypeptides (e.g., antibodies) can frequently be developed to recognize a protein surface with high affinity and selectivity and represent the state of the art for engineering ligands for specific biomacromolecular targets. Large polypeptides, however, suffer several disadvantages for in vivo applications, including costly production, low storage stability, and/or low bioavailability because of rapid proteolytic degradation (4, 5).Backbone-modified peptides, an underexplored class of molecules, are proving to be a fruitful source of tight-binding and specific protein ligands. Peptidic oligomers that contain β-amino acid residues interspersed among α-residues (“α/β-peptides”) can effectively mimic the recognition surface projected by an α-helix and thereby disrupt or augment protein–protein interactions in which one partner contributes a single helix to the interface (6, 7). The unnatural backbone diminishes α/β-peptide susceptibility to proteolytic degradation relative to conventional peptides (α-residues only, “α-peptides”). As a result, α/β-peptides can exhibit improved pharmacokinetic properties in vivo relative to analogous α-peptides (8, 9). To date, however, the α/β-peptide strategy has been restricted to mimicry of isolated α-helices, which is a significant limitation given that most protein–protein interactions are mediated by surfaces that are broader than can be covered by a single, regular helix (1–4, 10).Several small proteins have been explored as scaffolds that can be adapted to interact with structurally diverse protein-binding partners (11–13). The defined tertiary structures of such scaffolds allow them to present large binding surfaces that can engage large and complementary surfaces on target proteins. The “Z-domain” or “affibody” scaffold (14) is a widely studied example that is derived from domain B of staphylococcal protein A (15). The parent Z-domain (Z-IgG) (Fig. 1A) is a 58-residue engineered analog of domain B that retains affinity for the Fc portion of IgG, the natural binding partner of protein A (16). Z-IgG adopts a three-helix bundle tertiary structure, with a large surface (>600 Ų buried in the interface with Fc) formed by helices 1 and 2 contributing most of the Fc-contacting residues. Helix 3 stabilizes the Z-domain fold by packing against the other two helices (15, 17).Open in a separate windowFig. 1.Design of α/β-peptides based on the Z-domain scaffold. (A) Sequences of peptides previously derived from the Z-domain scaffold Z-VEGF, Z-IgG, and Z-TNFα targeting VEGF (19), IgG (16), and TNFα (20), respectively. Helices 1, 2, and 3 are indicated by brackets. For Z-VEGF and Z-TNFα, residues on the protein-binding face of helices 1 and 2 that were identified via randomization and selection (including the unintentionally incorporated Ala¹⁴ in Z-VEGF) are shown in red. For Z-IgG, the parent Z-domain, red positions indicate the corresponding residues that contact IgG. Sequences are arranged based on structural alignment of helical regions. (B) Strategy for the design of α/β-peptide mimics of Z-VEGF (shown in yellow and red). Red residues indicate selected residues that contact VEGF_8–109 (shown in gray) in the cocrystal structure. Sites targeted for nonnatural amino acid substitutions shown in teal. Figure is based on PDB ID code 3S1K.The composite surface displayed by helices 1 and 2 of the Z-domain scaffold can be crafted for specific binding to diverse protein partners because the three-helix bundle tertiary structure tolerates substitutions at solvent-exposed positions (18). Combinatorial randomization of as many as 13 solvent-exposed positions on helices 1 and 2, followed by affinity-based selection, has identified Z-domain derivatives that bind to a variety of targets (12, 14), including vascular endothelial growth factor (VEGF) (peptide Z-VEGF; Fig. 1 A and B) (19), tumor necrosis factor-α (TNFα) (peptide Z-TNFα; Fig. 1A) (20), and human epidermal growth factor receptor 2 (HER2) (21). Such Z-domain analogs might represent alternatives to antibodies for selective detection of disease marker proteins or for blocking deleterious signal transduction (11–14). In many cases, selection from a phage library has identified Z-domain derivatives that exhibit dissociation constants (K_D) in the nanomolar range for a chosen protein target. Affinity maturation can enhance binding to K_D values in the picomolar range (21). Recent clinical evaluations of radiolabeled Z-domain derivatives targeting HER2 revealed that these peptides could be safely used to image HER2-overexpressing lesions in breast cancer patients (22), a result that highlights the medical promise of the Z-domain scaffold.The high α-helix content of the Z-domain scaffold led us to envision that α/β-peptide analogs could be developed as binding partners for target proteins (23). We hypothesized that α→β replacements focused at sites distinct from the positions within helices 1 and 2 that mediate target recognition could reduce susceptibility to proteolytic degradation while maintaining high affinity for the partner. This design hypothesis is encouraged by two reports of Z-domain derivatives lacking helix 3 that retained affinity for their designated targets (24–26). Here, we describe the development of α/β-peptides that structurally and functionally mimic Z-VEGF. We demonstrate the versatility of this α/β-peptide strategy by showing how principles revealed in the VEGF-based effort can be extended to achieve functional mimicry of Z-domain peptides (Z-IgG and Z-TNFα) that bind to two other protein partners, IgG and TNFα.     

Thioredoxin-interacting protein and myocardial mitochondrial function in ischemia–reperfusion injury

Cellular metabolism and reactive oxygen species (ROS) formation are interrelated processes in mitochondria and are implicated in a variety of human diseases including ischemic heart disease. During ischemia, mitochondrial respiration rates fall. Though seemingly paradoxical, reduced respiration has been observed to be cardioprotective due in part to reduced generation of ROS. Enhanced myocardial glucose uptake is considered beneficial for the myocardium under stress, as glucose is the primary substrate to support anaerobic metabolism. Thus, inhibition of mitochondrial respiration and uncoupling oxidative phosphorylation can protect the myocardium from irreversible ischemic damage. Growing evidence now positions the TXNIP/thioredoxin system at a nodal point linking pathways of antioxidant defense, cell survival, and energy metabolism. This emerging picture reveals TXNIP’s function as a regulator of glucose homeostasis and may prove central to regulation of mitochondrial function during ischemia. In this review, we summarize how TXNIP and its binding partner thioredoxin act as regulators of mitochondrial metabolism. While the precise mechanism remains incompletely defined, the TXNIP–thioredoxin interaction has the potential to affect signaling that regulates mitochondrial bioenergetics and respiratory function with potential cardioprotection against ischemic injury.     

High carbohydrate–low protein consumption maximizes Drosophila lifespan

Dietary restriction extends lifespan in a variety of organisms, but the key nutritional components driving this process and how they interact remain uncertain. In Drosophila, while a substantial body of research suggests that protein is the major dietary component affecting longevity, recent studies claim that carbohydrates also play a central role. To clarify how nutritional factors influence longevity, nutrient consumption and lifespan were measured on a series of diets with varying yeast and sugar content. We show that optimal lifespan requires both high carbohydrate and low protein consumption, but neither nutrient by itself entirely predicts lifespan. Increased dietary carbohydrate or protein concentration does not always result in reduced feeding—the regulation of food consumption is best described by a constant daily caloric intake target. Moreover, due to differences in food intake, increased concentration of a nutrient within the diet does not necessarily result in increased consumption of that particular nutrient. Our results shed light on the issue of dietary effects on lifespan and highlight the need for accurate measures of nutrient intake in dietary manipulation studies.     

Entropy–enthalpy transduction caused by conformational shifts can obscure the forces driving protein–ligand binding

Molecular dynamics simulations of unprecedented duration now can provide new insights into biomolecular mechanisms. Analysis of a 1-ms molecular dynamics simulation of the small protein bovine pancreatic trypsin inhibitor reveals that its main conformations have different thermodynamic profiles and that perturbation of a single geometric variable, such as a torsion angle or interresidue distance, can select for occupancy of one or another conformational state. These results establish the basis for a mechanism that we term entropy–enthalpy transduction (EET), in which the thermodynamic character of a local perturbation, such as enthalpic binding of a small molecule, is camouflaged by the thermodynamics of a global conformational change induced by the perturbation, such as a switch into a high-entropy conformational state. It is noted that EET could occur in many systems, making measured entropies and enthalpies of folding and binding unreliable indicators of actual thermodynamic driving forces. The same mechanism might also account for the high experimental variance of measured enthalpies and entropies relative to free energies in some calorimetric studies. Finally, EET may be the physical mechanism underlying many cases of entropy–enthalpy compensation.     

Predicting weakly stable regions,oligomerization state,and protein–protein interfaces in transmembrane domains of outer membrane proteins

Although the structures of many β-barrel membrane proteins are available, our knowledge of the principles that govern their energetics and oligomerization states is incomplete. Here we describe a computational method to study the transmembrane (TM) domains of β-barrel membrane proteins. Our method is based on a physical interaction model, a simplified conformational space for efficient enumeration, and an empirical potential function from a detailed combinatorial analysis. Using this method, we can identify weakly stable regions in the TM domain, which are found to be important structural determinants for β-barrel membrane proteins. By calculating the melting temperatures of the TM strands, our method can also assess the stability of β-barrel membrane proteins. Predictions on membrane enzyme PagP are consistent with recent experimental NMR and mutant studies. We have also discovered that out-clamps, in-plugs, and oligomerization are 3 general mechanisms for stabilizing weakly stable TM regions. In addition, we have found that extended and contiguous weakly stable regions often signal the existence of an oligomer and that strands located in the interfaces of protein–protein interactions are considerably less stable. Based on these observations, we can predict oligomerization states and can identify the interfaces of protein–protein interactions for β-barrel membrane proteins by using either structure or sequence information. In a set of 25 nonhomologous proteins with known structures, our method successfully predicted whether a protein forms a monomer or an oligomer with 91% accuracy; in addition, our method identified with 82% accuracy the protein–protein interaction interfaces by using sequence information only when correct strands are given.