Structure of a 14-3-3ε:FOXO3apS253 Phosphopeptide Complex Reveals 14-3-3 Isoform-Specific Binding of Forkhead Box Class O Transcription Factor (FOXO) Phosphoproteins.

The transcriptional activity of Forkhead Box O3 (FOXO3a) is inactivated by AKT-mediated phosphorylation on Serine 253 (S253), which enables FOXO3a binding to 14-3-3. Phosphorylated FOXO3a binding to 14-3-3 facilitates the nuclear exclusion of FOXO3a, causing cancer cell proliferation. The FOXO3a/14-3-3 interaction has, therefore, emerged as an important therapeutic target. Here, we report a comprehensive analysis using fluorescence polarization, isothermal titration calorimetry, small-angle X-ray scattering, X-ray crystallography, and molecular dynamics simulations to gain molecular-level insights into the interaction of FOXO3apS253 phosphopeptide with 14-3-3ε. A high-resolution structure of the fluorophore-labeled FOXO3apS253:14-3-3ε complex revealed a distinct mode of interaction compared to other 14-3-3 phosphopeptide complexes. FOXO3apS253 phosphopeptide showed significant structural difference in the positions of the -3 and -4 Arg residues relative to pSer, compared to that of a similar phosphopeptide, FOXO1pS256 bound to 14-3-3σ. Moreover, molecular dynamics studies show that the significant structural changes and molecular interactions noticed in the crystal structure of FOXO3apS253:14-3-3ε are preserved over the course of the simulation. Thus, this study reveals structural differences between the binding to 14-3-3 isoforms of FOXO1pS256 versus FOXO3apS253, providing a framework for the rational design of isoform-specific FOXO/14-3-3 protein-protein interaction inhibitors for therapy.

Identification of Mtb GlmU Uridyltransferase Domain Inhibitors by Ligand-Based and Structure-Based Drug Design Approaches.

Targeting enzymes that play a role in the biosynthesis of the bacterial cell wall has long been a strategy for antibacterial discovery. In particular, the cell wall of Mycobacterium tuberculosis (Mtb) is a complex of three layers, one of which is Peptidoglycan, an essential component providing rigidity and strength. UDP-GlcNAc, a precursor for the synthesis of peptidoglycan, is formed by GlmU, a bi-functional enzyme. Inhibiting GlmU Uridyltransferase activity has been proven to be an effective anti-bacterial, but its similarity with human enzymes has been a deterrent to drug development. To develop Mtb selective hits, the Mtb GlmU substrate binding pocket was compared with structurally similar human enzymes to identify selectivity determining factors. Substrate binding pockets and conformational changes upon substrate binding were analyzed and MD simulations with substrates were performed to quantify crucial interactions to develop critical pharmacophore features. Thereafter, two strategies were applied to propose potent and selective bacterial GlmU Uridyltransferase domain inhibitors: (i) optimization of existing inhibitors, and (ii) identification by virtual screening. The binding modes of hits identified from virtual screening and ligand growing approaches were evaluated further for their ability to retain stable contacts within the pocket during 20 ns MD simulations. Hits that are predicted to be more potent than existing inhibitors and selective against human homologues could be of great interest for rejuvenating drug discovery efforts towards targeting the Mtb cell wall for antibacterial discovery.

Target identification for small-molecule discovery in the FOXO3a tumor-suppressor pathway using a biodiverse peptide library.

Genetic screening technologies to identify and validate macromolecular interactions (MMIs) essential for complex pathways remain an important unmet need for systems biology and therapeutics development. Here, we use a library of peptides from diverse prokaryal genomes to screen MMIs promoting the nuclear relocalization of Forkhead Box O3 (FOXO3a), a tumor suppressor more frequently inactivated by post-translational modification than mutation. A hit peptide engages the 14-3-3 family of signal regulators through a phosphorylation-dependent interaction, modulates FOXO3a-mediated transcription, and suppresses cancer cell growth. In a crystal structure, the hit peptide occupies the phosphopeptide-binding groove of 14-3-3ε in a conformation distinct from its natural peptide substrates. A biophysical screen identifies drug-like small molecules that displace the hit peptide from 14-3-3ε, providing starting points for structure-guided development. Our findings exemplify "protein interference," an approach using evolutionarily diverse, natural peptides to rapidly identify, validate, and develop chemical probes against MMIs essential for complex cellular phenotypes.

Structure-Guided Synthesis and Evaluation of Small-Molecule Inhibitors Targeting Protein-Protein Interactions of BRCA1 tBRCT Domain.

The tandem BRCT domains (tBRCT) of BRCA1 engage phosphoserine-containing motifs in target proteins to propagate intracellular signals initiated by DNA damage, thereby controlling cell cycle arrest and DNA repair. Recently, we identified Bractoppin, the first small-molecule inhibitor of the BRCA1 tBRCT domain, which selectively interrupts BRCA1-mediated cellular responses evoked by DNA damage. Here, we combine structure-guided chemical elaboration, protein mutagenesis and cellular assays to define the structural features responsible for Bractoppin's activity. Bractoppin fails to bind mutant forms of BRCA1 tBRCT bearing K1702A, a key residue mediating phosphopeptide recognition, or F1662R or L1701K that adjoin the pSer-recognition site. However, the M1775R mutation, which engages the Phe residue in the consensus phosphopeptide motif pSer-X-X-Phe, does not affect Bractoppin binding, confirming a binding mode distinct from the substrate phosphopeptide binding. We explored these structural features through structure-guided chemical elaboration and characterized structure-activity relationships (SARs) in biochemical assays. Two analogues, CCBT2088 and CCBT2103 were effective in abrogating BRCA1 foci formation and inhibiting G2 arrest induced by irradiation of cells. Collectively, our findings reveal structural features underlying the activity of a novel inhibitor of phosphopeptide recognition by the BRCA1 tBRCT domain, providing fresh insights to guide the development of inhibitors that target protein-protein interactions.

Targeting Phosphopeptide Recognition by the Human BRCA1 Tandem BRCT Domain to Interrupt BRCA1-Dependent Signaling.

Intracellular signals triggered by DNA breakage flow through proteins containing BRCT (BRCA1 C-terminal) domains. This family, comprising 23 conserved phosphopeptide-binding modules in man, is inaccessible to small-molecule chemical inhibitors. Here, we develop Bractoppin, a drug-like inhibitor of phosphopeptide recognition by the human BRCA1 tandem (t)BRCT domain, which selectively inhibits substrate binding with nanomolar potency in vitro. Structure-activity exploration suggests that Bractoppin engages BRCA1 tBRCT residues recognizing pSer in the consensus motif, pSer-Pro-Thr-Phe, plus an abutting hydrophobic pocket that is distinct in structurally related BRCT domains, conferring selectivity. In cells, Bractoppin inhibits substrate recognition detected by Förster resonance energy transfer, and diminishes BRCA1 recruitment to DNA breaks, in turn suppressing damage-induced G2 arrest and assembly of the recombinase, RAD51. But damage-induced MDC1 recruitment, single-stranded DNA (ssDNA) generation, and TOPBP1 recruitment remain unaffected. Thus, an inhibitor of phosphopeptide recognition selectively interrupts BRCA1 tBRCT-dependent signals evoked by DNA damage.

Discovery of Small Molecules that Inhibit the Disordered Protein, p27(Kip1).

Disordered proteins are highly prevalent in biological systems, they control myriad signaling and regulatory processes, and their levels and/or cellular localization are often altered in human disease. In contrast to folded proteins, disordered proteins, due to conformational heterogeneity and dynamics, are not considered viable drug targets. We challenged this paradigm by identifying through NMR-based screening small molecules that bound specifically, albeit weakly, to the disordered cell cycle regulator, p27(Kip1) (p27). Two groups of molecules bound to sites created by transient clusters of aromatic residues within p27. Conserved chemical features within these two groups of small molecules exhibited complementarity to their binding sites within p27, establishing structure-activity relationships for small molecule:disordered protein interactions. Finally, one compound counteracted the Cdk2/cyclin A inhibitory function of p27 in vitro, providing proof-of-principle that small molecules can inhibit the function of a disordered protein (p27) through sequestration in a conformation incapable of folding and binding to a natural regulatory target (Cdk2/cyclin A).

Active site coupling in PDE:PKA complexes promotes resetting of mammalian cAMP signaling.

Cyclic 3'5' adenosine monophosphate (cAMP)-dependent-protein kinase (PKA) signaling is a fundamental regulatory pathway for mediating cellular responses to hormonal stimuli. The pathway is activated by high-affinity association of cAMP with the regulatory subunit of PKA and signal termination is achieved upon cAMP dissociation from PKA. Although steps in the activation phase are well understood, little is known on how signal termination/resetting occurs. Due to the high affinity of cAMP to PKA (KD ∼ low nM), bound cAMP does not readily dissociate from PKA, thus begging the question of how tightly bound cAMP is released from PKA to reset its signaling state to respond to subsequent stimuli. It has been recently shown that phosphodiesterases (PDEs) can catalyze dissociation of bound cAMP and thereby play an active role in cAMP signal desensitization/termination. This is achieved through direct interactions with the regulatory subunit of PKA, thereby facilitating cAMP dissociation and hydrolysis. In this study, we have mapped direct interactions between a specific cyclic nucleotide phosphodiesterase (PDE8A) and a PKA regulatory subunit (RIα isoform) in mammalian cAMP signaling, by a combination of amide hydrogen/deuterium exchange mass spectrometry, peptide array, and computational docking. The interaction interface of the PDE8A:RIα complex, probed by peptide array and hydrogen/deuterium exchange mass spectrometry, brings together regions spanning the phosphodiesterase active site and cAMP-binding sites of RIα. Computational docking combined with amide hydrogen/deuterium exchange mass spectrometry provided a model for parallel dissociation of bound cAMP from the two tandem cAMP-binding domains of RIα. Active site coupling suggests a role for substrate channeling in the PDE-dependent dissociation and hydrolysis of cAMP bound to PKA. This is the first instance, to our knowledge, of PDEs directly interacting with a cAMP-receptor protein in a mammalian system, and highlights an entirely new class of binding partners for RIα. This study also highlights applications of structural mass spectrometry combined with computational docking for mapping dynamics in transient signaling protein complexes. Together, these results present a novel and critical role for phosphodiesterases in moderating local concentrations of cAMP in microdomains and signal resetting.

Ligand binding mode prediction by docking: mdm2/mdmx inhibitors as a case study.

The p53-binding domains of Mdm2 and Mdmx, two negative regulators of the tumor suppressor p53, are validated targets for cancer therapeutics, but correct binding poses of some proven inhibitors, particularly the nutlins, have been difficult to obtain with standard docking procedures. Virtual screening pipelines typically draw from a database of compounds represented with 1D or 2D structural information from which one or more 3D conformations must be generated. These conformations are then passed to a docking algorithm that searches for optimal binding poses on the target protein. This work tests alternative pipelines using several commonly used conformation generation programs (LigPrep, ConfGen, MacroModel, and Corina/Rotate) and docking programs (GOLD, Glide, MOE-dock, and AutoDock Vina) for their ability to reproduce known poses for a series of Mdmx and/or Mdm2 inhibitors, including several nutlins. Most combinations of these programs using default settings fail to find correct poses for the nutlins but succeed for all other compounds. Docking success for the nutlin class requires either computationally intensive conformational exploration or an "anchoring" procedure that incorporates knowledge of the orientation of the central imidazoline ring.

Metabolic activation of CaMKII by coenzyme A.

Active metabolism regulates oocyte cell death via calcium/calmodulin-dependent protein kinase II (CaMKII)-mediated phosphorylation of caspase-2, but the link between metabolic activity and CaMKII is poorly understood. Here we identify coenzyme A (CoA) as the key metabolic signal that inhibits Xenopus laevis oocyte apoptosis by directly activating CaMKII. We found that CoA directly binds to the CaMKII regulatory domain in the absence of Ca(2+) to activate CaMKII in a calmodulin-dependent manner. Furthermore, we show that CoA inhibits apoptosis not only in X. laevis oocytes but also in Murine oocytes. These findings uncover a direct mechanism of CaMKII regulation by metabolism and further highlight the importance of metabolism in preserving oocyte viability.

Cube-DB: detection of functional divergence in human protein families.

Cube-DB is a database of pre-evaluated results for detection of functional divergence in human/vertebrate protein families. The analysis is organized around the nomenclature associated with the human proteins, but based on all currently available vertebrate genomes. Using full genomes enables us, through a mutual-best-hit strategy, to construct comparable taxonomical samples for all paralogues under consideration. Functional specialization is scored on the residue level according to two models of behavior after divergence: heterotachy and homotachy. In the first case, the positions on the protein sequence are scored highly if they are conserved in the reference group of orthologs, and overlap poorly with the residue type choice in the paralogs groups (such positions will also be termed functional determinants). The second model additionally requires conservation within each group of paralogs (functional discriminants). The scoring functions are phylogeny independent, but sensitive to the residue type similarity. The results are presented as a table of per-residue scores, and mapped onto related structure (when available) via browser-embedded visualization tool. They can also be downloaded as a spreadsheet table, and sessions for two additional molecular visualization tools. The database interface is available at http://epsf.bmad.bii.a-star.edu.sg/cube/db/html/home.html.

Determinants, discriminants, conserved residues--a heuristic approach to detection of functional divergence in protein families.

In this work, belonging to the field of comparative analysis of protein sequences, we focus on detection of functional specialization on the residue level. As the input, we take a set of sequences divided into groups of orthologues, each group known to be responsible for a different function. This provides two independent pieces of information: within group conservation and overlap in amino acid type across groups. We build our discussion around the set of scoring functions that keep the two separated and the source of the signal easy to trace back to its source.We propose a heuristic description of functional divergence that includes residue type exchangeability, both in the conservation and in the overlap measure, and does not make any assumptions on the rate of evolution in the groups other than the one under consideration. Residue types acceptable at a certain position within an orthologous group are described as a distribution which evolves in time, starting from a single ancestral type, and is subject to constraints that can be inferred only indirectly. To estimate the strength of the constraints, we compare the observed degrees of conservation and overlap with those expected in the hypothetical case of a freely evolving distribution.Our description matches the experiment well, but we also conclude that any attempt to capture the evolutionary behavior of specificity determining residues in terms of a scalar function will be tentative, because no single model can cover the variety of evolutionary behavior such residues exhibit. Especially, models expecting the same type of evolutionary behavior across functionally divergent groups tend to miss a portion of information otherwise retrievable by the conservation and overlap measures they use.

deconSTRUCT: general purpose protein database search on the substructure level.

deconSTRUCT webserver offers an interface to a protein database search engine, usable for a general purpose detection of similar protein (sub)structures. Initially, it deconstructs the query structure into its secondary structure elements (SSEs) and reassembles the match to the target by requiring a (tunable) degree of similarity in the direction and sequential order of SSEs. Hierarchical organization and judicious use of the information about protein structure enables deconSTRUCT to achieve the sensitivity and specificity of the established search engines at orders of magnitude increased speed, without tying up irretrievably the substructure information in the form of a hash. In a post-processing step, a match on the level of the backbone atoms is constructed. The results presented to the user consist of the list of the matched SSEs, the transformation matrix for rigid superposition of the structures and several ways of visualization, both downloadable and implemented as a web-browser plug-in. The server is available at http://epsf.bmad.bii.a-star.edu.sg/struct_server.html.

Molecular dynamics simulation study of valyl-tRNA synthetase with its pre- and post-transfer editing substrates.

The main role of aminoacyl-tRNA synthetases (aaRSs) is to transfer the cognate amino acids to the 3'-end of their tRNA by strictly discriminating from non-cognate amino acids. Some aaRSs accomplish this via proofreading and editing mechanisms, among which valyl-tRNA synthetase (ValRS) hydrolyses the non-cognate amino acid, threonine. In ValRS, existence of pre-transfer editing process is still unclear, although crystal structure of editing site with pre-transfer substrate analog (Thr-AMS) was released. In the case of isoleucyl-tRNA synthetase (IleRS), editing mechanism is well studied and mutational analyses revealed the existence of post- and pre-transfer editing mechanisms. Our aim is to investigate the possibility of pre-transfer editing process by performing molecular dynamics (MD) simulation studies. Simulations were carried out for ValRS with pre-transfer substrates (Thr-AMP/Val-AMP) and post-transfer substrates (Thr-A76/Val-A76) to understand their binding pattern. Two important point mutation studies were performed to observe their effect on editing process. This study also intends to compare and contrast the pre-transfer editing with post-transfer editing of ValRS. Interestingly, the MD simulation results revealed that non-cognate substrates (Thr-AMP/Thr-A76) bind more strongly than the cognate substrates (Val-AMP/Val-A76) in both pre- and post-transfer editing respectively. The editing site mutations (Lys270Ala and Asp279Ala) severely affected the binding ability of pre-transfer substrate (Thr-AMP) by different ways. Even though pre- and post-transfer substrates bind to the same site, specific differences were observed which has led us to believe the existence of the pre-transfer editing process in ValRS.

Molecular dynamics simulation study of PTP1B with allosteric inhibitor and its application in receptor based pharmacophore modeling.

Allosteric inhibition of protein tyrosine phosphatase 1B (PTP1B), has paved a new path to design specific inhibitors for PTP1B, which is an important drug target for the treatment of type II diabetes and obesity. The PTP1B1-282-allosteric inhibitor complex crystal structure lacks alpha7 (287-298) and moreover there is no available 3D structure of PTP1B1-298 in open form. As the interaction between alpha7 and alpha6-alpha3 helices plays a crucial role in allosteric inhibition, alpha7 was modeled to the PTP1B1-282 in open form complexed with an allosteric inhibitor (compound-2) and a 5 ns MD simulation was performed to investigate the relative orientation of the alpha7-alpha6-alpha3 helices. The simulation conformational space was statistically sampled by clustering analyses. This approach was helpful to reveal certain clues on PTP1B allosteric inhibition. The simulation was also utilized in the generation of receptor based pharmacophore models to include the conformational flexibility of the protein-inhibitor complex. Three cluster representative structures of the highly populated clusters were selected for pharmacophore model generation. The three pharmacophore models were subsequently utilized for screening databases to retrieve molecules containing the features that complement the allosteric site. The retrieved hits were filtered based on certain drug-like properties and molecular docking simulations were performed in two different conformations of protein. Thus, performing MD simulation with alpha7 to investigate the changes at the allosteric site, then developing receptor based pharmacophore models and finally docking the retrieved hits into two distinct conformations will be a reliable methodology in identifying PTP1B allosteric inhibitors.

Binding mode analyses and pharmacophore model development for sulfonamide chalcone derivatives, a new class of alpha-glucosidase inhibitors.

Sulfonamide chalcone derivatives are a new class of non-saccharide compounds that effectively inhibit glucosidases which are the major targets in the treatment of Type 2 diabetes and HIV infection. Our aim is to explore their binding mode of interaction at the active site by comparing with the sugar derivatives and to develop a pharmacophore model which would represent the critical features responsible for alpha-glucosidase inhibitory activity. The homology modeled structure of Saccharomyces cerevisiae alpha-glucosidase was built and used for molecular docking of non-sugar/sugar derivatives. The validated docking results projected the crucial role of NH group in the binding of sugar/non-sugar derivatives to the active site. Ligplot analyses revealed that Tyr71, and Phe177 form hydrophobic interactions with sugar/non-sugar derivatives by holding the terminal glycosidic ring mimics. Molecular dynamic (MD) simulation studies were performed for protein alone and with chalcone derivative to prove its binding mechanism as shown by docking/Ligplot results. It would also help to substantiate the homology modeled structure stability. With the knowledge of the crucial interactions between ligand and protein from docking and MD simulation studies, features for pharmacophore model development were chosen. The CATALYST/HipHop was used to generate a five featured pharmacophore model with a training set of five non-sugar derivatives. As validation, all the crucial features of the model were perfectly mapped onto the 3D structures of the sugar derivatives as well as the newly tested non-sugar derivatives. Thus, it can be useful in virtual screening for finding new non-sugar derivatives as alpha-glucosidase inhibitors.

Pharmacophore modeling for protein tyrosine phosphatase 1B inhibitors.

A three dimensional chemical feature based pharmacophore model was developed for the inhibitors of protein tyrosine phosphatase 1B (PTP1B) using the CATALYST software, which would provide useful knowledge for performing virtual screening to identify new inhibitors targeted toward type II diabetes and obesity. A dataset of 27 inhibitors, with diverse structural properties, and activities ranging from 0.026 to 600 microM, was selected as a training set. Hypol, the most reliable quantitative four featured pharmacophore hypothesis, was generated from a training set composed of compounds with two H-bond acceptors, one hydrophobic aromatic and one ring aromatic features. It has a correlation coefficient, RMSD and cost difference (null cost-total cost) of 0.946, 0.840 and 65.731, respectively. The best hypothesis (Hypol) was validated using four different methods. Firstly, a cross validation was performed by randomizing the data using the Cat-Scramble technique. The results confirmed that the pharmacophore models generated from the training set were valid. Secondly, a test set of 281 molecules was scored, with a correlation of 0.882 obtained between the experimental and predicted activities. Hypol performed well in correctly discriminating the active and inactive molecules. Thirdly, the model was investigated by mapping on two PTP1B inhibitors identified by different pharmaceutical companies. The Hypol model correctly predicted these compounds as being highly active. Finally, docking simulations were performed on few compounds to substantiate the role of the pharmacophore features at the binding site of the protein by analyzing their binding conformations. These multiple validation approaches provided confidence in the utility of this pharmacophore model as a 3D query for virtual screening to retrieve new chemical entities showing potential as potent PTP1B inhibitors.

Pharmacophore identification and virtual screening for methionyl-tRNA synthetase inhibitors.

Aminoacyl-tRNA synthetases (aaRSs) are essential enzymes involved in protein biosynthesis in all living organisms and are an unexploited antibacterial targets, as many strains of bacteria have become resistant to all established classes of antibiotics. Therefore, the main aim of this study is to discover new lead molecules which would be useful as anti-bacterial compounds. Pharmacophore models were developed by using CATALYST HypoGen with a training set of 29 diverse methionyl-tRNA synthetase (MetRS) inhibitors. The best quantitative pharmacophore hypothesis (Hypo1) obtained a correlation coefficient of 0.975, root mean square deviation (RMSD) of 0.55 and cost difference (null cost-total cost) of 70.32. This Hypo1 was validated by two methods, first by using 104 test set molecules which resulted a correlation of 0.926 between HypoGen estimated activities versus experimental activities and secondly by Cat-Scramble validation method. This validated pharmacophore model was further used for screening databases for discovery of new MetRS inhibitors. The new lead compounds were further analyzed for drug-like properties. Homology modeled structure of Staphylococcus aureus MetRS was built and molecular docking studies were performed with many inhibitors using the newly built protein structure. Finally, it was found that the new leads exhibited good estimated inhibitory activity, calculated binding properties similar to experimentally proven compounds and also favorable drug-like properties.