Identification and Development of Cyclic Peptide Inhibitors of Hypoxia Inducible Factors 1 and 2 That Disrupt Hypoxia-Response Signaling in Cancer Cells.

Hypoxia inducible factor (HIF) is a heterodimeric transcription factor composed of an oxygen-regulated α subunit and a constitutively expressed ß subunit that serves as the master regulator of the cellular response to low oxygen concentrations. The HIF transcription factor senses and responds to hypoxia by significantly altering transcription and reprogramming cells to enable adaptation to a hypoxic microenvironment. Given the central role played by HIF in the survival and growth of tumors in hypoxia, inhibition of this transcription factor serves as a potential therapeutic approach for treating a variety of cancers. Here, we report the identification, optimization, and characterization of a series of cyclic peptides that disrupt the function of HIF-1 and HIF-2 transcription factors by inhibiting the interaction of both HIF-1α and HIF-2α with HIF-1ß. These compounds are shown to bind to HIF-α and disrupt the protein-protein interaction between the α and ß subunits of the transcription factor, resulting in disruption of hypoxia-response signaling by our lead molecule in several cancer cell lines.

Reducing affinity as a strategy to boost immunomodulatory antibody agonism.

Antibody responses during infection and vaccination typically undergo affinity maturation to achieve high-affinity binding for efficient neutralization of pathogens1,2. Similarly, high affinity is routinely the goal for therapeutic antibody generation. However, in contrast to naturally occurring or direct-targeting therapeutic antibodies, immunomodulatory antibodies, which are designed to modulate receptor signalling, have not been widely examined for their affinity-function relationship. Here we examine three separate immunologically important receptors spanning two receptor superfamilies: CD40, 4-1BB and PD-1. We show that low rather than high affinity delivers greater activity through increased clustering. This approach delivered higher immune cell activation, in vivo T cell expansion and antitumour activity in the case of CD40. Moreover, an inert anti-4-1BB monoclonal antibody was transformed into an agonist. Low-affinity variants of the clinically important antagonistic anti-PD-1 monoclonal antibody nivolumab also mediated more potent signalling and affected T cell activation. These findings reveal a new paradigm for augmenting agonism across diverse receptor families and shed light on the mechanism of antibody-mediated receptor signalling. Such affinity engineering offers a rational, efficient and highly tuneable solution to deliver antibody-mediated receptor activity across a range of potencies suitable for translation to the treatment of human disease.

Advancing our knowledge of antigen processing with computational modelling, structural biology, and immunology.

Antigen processing is an immunological mechanism by which intracellular peptides are transported to the cell surface while bound to Major Histocompatibility Complex molecules, where they can be surveyed by circulating CD8+ or CD4+ T-cells, potentially triggering an immunological response. The antigen processing pathway is a complex multistage filter that refines a huge pool of potential peptide ligands derived from protein degradation into a smaller ensemble for surface presentation. Each stage presents unique challenges due to the number of ligands, the polymorphic nature of MHC and other protein constituents of the pathway and the nature of the interactions between them. Predicting the ensemble of displayed peptide antigens, as well as their immunogenicity, is critical for improving T cell vaccines against pathogens and cancer. Our predictive abilities have always been hindered by an incomplete empirical understanding of the antigen processing pathway. In this review, we highlight the role of computational and structural approaches in improving our understanding of antigen processing, including structural biology, computer simulation, and machine learning techniques, with a particular focus on the MHC-I pathway.

A novel variant in GATM causes idiopathic renal Fanconi syndrome and predicts progression to end-stage kidney disease.

Renal Fanconi syndrome (RFS) is a generalised disorder of the proximal convoluted tubule. Many genes have been associated with RFS including those that cause systemic disorders such as cystinosis, as well as isolated RFS. We discuss the case of a 10-year-old female who presented with leg pain and raised creatinine on a screening blood test. Her mother has RFS and required a kidney transplant in her thirties. Further investigations confirmed RFS in the daughter. Exome sequencing was performed on the affected mother, child, and unaffected father. We identified a novel variant in GATM; c.965G>C p.(Arg322Pro) segregating dominantly in the mother and daughter. We validated our finding with molecular dynamics simulations and demonstrated a dynamic signature that differentiates our variant and two previously identified pathogenic variants in GATM from wildtype. Genetic testing has uncovered a novel pathogenic variant that predicts progression to end stage kidney failure and has important implications for family planning and cascade testing. We recommend that GATM is screened for in children presenting with RFS, in addition to adults, particularly with kidney failure, who may have had previous negative gene testing.

Mycobacterium tuberculosis senses host Interferon-γ via the membrane protein MmpL10.

Mycobacterium tuberculosis (Mtb) is one of the most successful human pathogens. Several cytokines are known to increase virulence of bacterial pathogens, leading us to investigate whether Interferon-γ (IFN-γ), a central regulator of the immune defense against Mtb, has a direct effect on the bacteria. We found that recombinant and T-cell derived IFN-γ rapidly induced a dose-dependent increase in the oxygen consumption rate (OCR) of Mtb, consistent with increased bacterial respiration. This was not observed in attenuated Bacillus Calmette-Guérin (BCG), and did not occur for other cytokines tested, including TNF-α. IFN-γ binds to the cell surface of intact Mtb, but not BCG. Mass spectrometry identified mycobacterial membrane protein large 10 (MmpL10) as the transmembrane binding partner of IFN-γ, supported by molecular modelling studies. IFN-γ binding and the OCR response was absent in Mtb Δmmpl10 strain and restored by complementation with wildtype mmpl10. RNA-sequencing and RT-PCR of Mtb exposed to IFN-γ revealed a distinct transcriptional profile, including genes involved in virulence. In a 3D granuloma model, IFN-γ promoted Mtb growth, which was lost in the Mtb Δmmpl10 strain and restored by complementation, supporting the involvement of MmpL10 in the response to IFN-γ. Finally, IFN-γ addition resulted in sterilization of Mtb cultures treated with isoniazid, indicating clearance of phenotypically resistant bacteria that persist in the presence of drug alone. Together our data are the first description of a mechanism allowing Mtb to respond to host immune activation that may be important in the immunopathogenesis of TB and have use in novel eradication strategies.

Hinge disulfides in human IgG2 CD40 antibodies modulate receptor signaling by regulation of conformation and flexibility.

Antibodies protect from infection, underpin successful vaccines and elicit therapeutic responses in otherwise untreatable cancers and autoimmune conditions. The human IgG2 isotype displays a unique capacity to undergo disulfide shuffling in the hinge region, leading to modulation of its ability to drive target receptor signaling (agonism) in a variety of important immune receptors, through hitherto unexplained molecular mechanisms. To address the underlying process and reveal how hinge disulfide orientation affects agonistic activity, we generated a series of cysteine to serine exchange variants in the hinge region of the clinically relevant monoclonal antibody ChiLob7/4, directed against the key immune receptor CD40. We report how agonistic activity varies with disulfide pattern and is afforded by the presence of a disulfide crossover between F(ab) arms in the agonistic forms, independently of epitope, as observed in the determined crystallographic structures. This structural "switch" affects directly on antibody conformation and flexibility. Small-angle x-ray scattering and ensemble modeling demonstrated that the least flexible variants adopt the fewest conformations and evoke the highest levels of receptor agonism. This covalent change may be amenable for broad implementation to modulate receptor signaling in an epitope-independent manner in future therapeutics.

BRIDGE: An Open Platform for Reproducible High-Throughput Free Energy Simulations.

Biomolecular Reaction and Interaction Dynamics Global Environment (BRIDGE) is an open-source web platform developed with the aim to provide an environment for the design of reliable methods to conduct reproducible biomolecular simulations. It is built on the well-known Galaxy bioinformatics platform. Through this, BRIDGE hosts computational chemistry tools on public web servers for internet use and provides machine- and operating-system-independent portability using the Docker container platform for local use. This construction improves the accessibility, shareability, and reproducibility of computational methods for molecular simulations. Here we present integrated free energy tools (or apps) to calculate absolute binding free energies (ABFEs) and relative binding free energies (RBFEs), as illustrated through use cases. We present free energy perturbation (FEP) methods contained in various software packages such as GROMACS and YANK that are independent of hardware configuration, software libraries, or operating systems when ported in the Galaxy-BRIDGE Docker container platform. By performing cyclin-dependent kinase 2 (CDK2) FEP calculations on geographically dispersed web servers (in Africa and Europe), we illustrate that large-scale computations can be performed using the exact same codes and methodology by collaborating groups through publicly shared protocols and workflows. The ease of public sharing and independent reproduction of simulations via BRIDGE makes possible an open review of methods and complete simulation protocols. This makes the discovery of inhibitors for drug targets accessible to nonexperts and the computer experiments that are used to arrive at leads verifiable by experts and reviewers. We illustrate this on ß-galactoside α-2,3-sialyltransferase I (ST3Gal-I), a breast cancer drug target, where a combination of RBFE and ABFE methods are used to compute the binding free energies of three inhibitors.

Ligand Binding Free Energies with Adaptive Water Networks: Two-Dimensional Grand Canonical Alchemical Perturbations.

Computational methods to calculate ligand binding affinities are increasing in popularity, due to improvements in simulation algorithms, computational resources, and easy-to-use software. However, issues can arise in relative ligand binding free energy simulations if the ligands considered have different active site water networks, as simulations are typically performed with a predetermined number of water molecules (fixed N ensembles) in preassigned locations. If an alchemical perturbation is attempted where the change should result in a different active site water network, the water molecules may not be able to adapt appropriately within the time scales of the simulations-particularly if the active site is occluded. By combining the grand canonical ensemble (µVT) to sample active site water molecules, with conventional alchemical free energy methods, the water network is able to dynamically adapt to the changing ligand. We refer to this approach as grand canonical alchemical perturbation (GCAP). In this work we demonstrate GCAP for two systems; Scytalone Dehydratase (SD) and Adenosine A2 A receptor. For both systems, GCAP is shown to perform well at reproducing experimental binding affinities. Calculating the relative binding affinities with a naïve, conventional attempt to solvate the active site illustrates how poor results can be if proper consideration of water molecules in occluded pockets is neglected. GCAP results are shown to be consistent with time-consuming double decoupling simulations. In addition, by obtaining the free energy surface for ligand perturbations, as a function of both the free energy coupling parameter and water chemical potential, it is possible to directly deconvolute the binding energetics in terms of protein-ligand direct interactions and protein binding site hydration.

CD1b-restricted GEM T cell responses are modulated by Mycobacterium tuberculosis mycolic acid meromycolate chains.

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major human pandemic. Germline-encoded mycolyl lipid-reactive (GEM) T cells are donor-unrestricted and recognize CD1b-presented mycobacterial mycolates. However, the molecular requirements governing mycolate antigenicity for the GEM T cell receptor (TCR) remain poorly understood. Here, we demonstrate CD1b expression in TB granulomas and reveal a central role for meromycolate chains in influencing GEM-TCR activity. Meromycolate fine structure influences T cell responses in TB-exposed individuals, and meromycolate alterations modulate functional responses by GEM-TCRs. Computational simulations suggest that meromycolate chain dynamics regulate mycolate head group movement, thereby modulating GEM-TCR activity. Our findings have significant implications for the design of future vaccines that target GEM T cells.

Conformation and Dynamics of Human Urotensin II and Urotensin Related Peptide in Aqueous Solution.

Conformation and dynamics of the vasoconstrictive peptides human urotensin II (UII) and urotensin related peptide (URP) have been investigated by both unrestrained and enhanced-sampling molecular-dynamics (MD) simulations and NMR spectroscopy. These peptides are natural ligands of the G-protein coupled urotensin II receptor (UTR) and have been linked to mammalian pathophysiology. UII and URP cannot be characterized by a single structure but exist as an equilibrium of two main classes of ring conformations, open and folded, with rapidly interchanging subtypes. The open states are characterized by turns of various types centered at K8Y9 or F6W7 predominantly with no or only sparsely populated transannular hydrogen bonds. The folded conformations show multiple turns stabilized by highly populated transannular hydrogen bonds comprising centers F6W7K8 or W7K8Y9. Some of these conformations have not been characterized previously. The equilibrium populations that are experimentally difficult to access were estimated by replica-exchange MD simulations and validated by comparison of experimental NMR data with chemical shifts calculated with density-functional theory. UII exhibits approximately 72% open:28% folded conformations in aqueous solution. URP shows very similar ring conformations as UII but differs in an open:folded equilibrium shifted further toward open conformations (86:14) possibly arising from the absence of folded N-terminal tail-ring interaction. The results suggest that the different biological effects of UII and URP are not caused by differences in ring conformations but rather by different interactions with UTR.

G protein coupled receptor interactions with cholesterol deep in the membrane.

G protein coupled receptors (GPCRs) are located in membranes rich in cholesterol. The membrane spanning surfaces of GPCRs contain exposed backbone carbonyl groups and residue side chains potentially capable of forming hydrogen bonds to cholesterol molecules buried deep within the hydrophobic core of the lipid bilayer. Coarse-grained molecular dynamics (CGMD) simulations allow the observation of GPCRs in cholesterol-containing lipid bilayers for long times (50µs), sufficient to ensure equilibration of the system. We have detected a number of deep cholesterol binding sites on ß2 adrenergic and A2A adenosine receptors, and shown changes in these sites on agonist binding. The requirements for binding are modest, just a potential hydrogen bond partner close to a cleft or hole in the surface. This makes it likely that similar binding sites for cholesterol will exist on other classes of membrane protein.

Reactivation of mutant p53: Constraints on mechanism highlighted by principal component analysis of the DNA binding domain.

Most p53 mutations associated with cancer are located in its DNA binding domain (DBD). Many structures (X-ray and NMR) of this domain are available in the protein data bank (PDB) and a vast conformational heterogeneity characterizes the various free and complexed states. The major difference between the apo and the holo-complexed states appears to lie in the L1 loop. In particular, the conformations of this loop appear to depend intimately on the sequence of DNA to which it binds. This conclusion builds upon recent observations that implicate the tetramerization and the C-terminal domains (respectively TD and Cter) in DNA binding specificity. Detailed PCA analysis of the most recent collection of DBD structures from the PDB have been carried out. In contrast to recommendations that small molecules/drugs stabilize the flexible L1 loop to rescue mutant p53, our study highlights a need to retain the flexibility of the p53 DNA binding surface (DBS). It is the adaptability of this region that enables p53 to engage in the diverse interactions responsible for its functionality. Proteins 2016; 84:1443-1461. © 2016 Wiley Periodicals, Inc.

A simple and transferable all-atom/coarse-grained hybrid model to study membrane processes.

We present an efficient all-atom/coarse-grained hybrid model and apply it to membrane processes. This model is an extension of the all-atom/ELBA model applied previously to processes in water. Here, we improve the efficiency of the model by implementing a multiple-time step integrator that allows the atoms and the coarse-grained beads to be propagated at different timesteps. Furthermore, we fine-tune the interaction between the atoms and the coarse-grained beads by computing the potential of mean force of amino acid side chain analogs along the membrane normal and comparing to atomistic simulations. The model was independently validated on the calculation of small-molecule partition coefficients. Finally, we apply the model to membrane peptides. We studied the tilt angle of the Walp23 and Kalp23 helices in two different model membranes and the stability of the glycophorin A dimer. The model is efficient, accurate, and straightforward to use, as it does not require any extra interaction particles, layers of atomistic solvent molecules or tabulated potentials, thus offering a novel, simple approach to study membrane processes.

X-ray crystallographic and EPR spectroscopic analysis of HydG, a maturase in [FeFe]-hydrogenase H-cluster assembly.

Hydrogenases use complex metal cofactors to catalyze the reversible formation of hydrogen. In [FeFe]-hydrogenases, the H-cluster cofactor includes a diiron subcluster containing azadithiolate, three CO, and two CN(-) ligands. During the assembly of the H cluster, the radical S-adenosyl methionine (SAM) enzyme HydG lyses the substrate tyrosine to yield the diatomic ligands. These diatomic products form an enzyme-bound Fe(CO)x(CN)y synthon that serves as a precursor for eventual H-cluster assembly. To further elucidate the mechanism of this complex reaction, we report the crystal structure and EPR analysis of HydG. At one end of the HydG (ßα)8 triosephosphate isomerase (TIM) barrel, a canonical [4Fe-4S] cluster binds SAM in close proximity to the proposed tyrosine binding site. At the opposite end of the active-site cavity, the structure reveals the auxiliary Fe-S cluster in two states: one monomer contains a [4Fe-5S] cluster, and the other monomer contains a [5Fe-5S] cluster consisting of a [4Fe-4S] cubane bridged by a µ2-sulfide ion to a mononuclear Fe(2+) center. This fifth iron is held in place by a single highly conserved protein-derived ligand: histidine 265. EPR analysis confirms the presence of the [5Fe-5S] cluster, which on incubation with cyanide, undergoes loss of the labile iron to yield a [4Fe-4S] cluster. We hypothesize that the labile iron of the [5Fe-5S] cluster is the site of Fe(CO)x(CN)y synthon formation and that the limited bonding between this iron and HydG may facilitate transfer of the intact synthon to its cognate acceptor for subsequent H-cluster assembly.

Direct validation of the single step classical to quantum free energy perturbation.

The use of the Zwanzig equation in the calculation of single-step perturbations to provide first-principles (ab initio) quantum mechanics (QM) correction terms to molecular mechanics (MM) free energy cycles is well established. A rigorous test of the ability to converge such calculations would be very useful in this context. In this work, we perform a direct assessment of the convergence of the MM to QM perturbation, by attempting the reverse QM to MM perturbation. This required the generation of extensive QM molecular dynamics trajectories, using density functional theory (DFT), within the representative biological system of a DNA adenosine-thymidine dimer. Over 100 ps of dynamics with the PBE functional and 6.25 ps with the LDA functional were generated. We demonstrate that calculations with total potential energies are very poorly convergent due to a lack of overlap of phase space distributions between ensembles. While not theoretically rigorous, the use of interaction energies provides far superior convergence, despite the presence of nonclassical charge transfer effects within the DFT trajectories. The source of poor phase space overlap for total energies is diagnosed, the approximate quantification of overlaps suggesting that even for the comparatively simple system considered here convergence of total energy calculations within a reasonable simulation time is unfeasible.

Structures of lipoyl synthase reveal a compact active site for controlling sequential sulfur insertion reactions.

Lipoyl cofactors are essential for living organisms and are produced by the insertion of two sulfur atoms into the relatively unreactive C-H bonds of an octanoyl substrate. This reaction requires lipoyl synthase, a member of the radical S-adenosylmethionine (SAM) enzyme superfamily. In the present study, we solved crystal structures of lipoyl synthase with two [4Fe-4S] clusters bound at opposite ends of the TIM barrel, the usual fold of the radical SAM superfamily. The cluster required for reductive SAM cleavage conserves the features of the radical SAM superfamily, but the auxiliary cluster is bound by a CX4CX5C motif unique to lipoyl synthase. The fourth ligand to the auxiliary cluster is an extremely unusual serine residue. Site-directed mutants show this conserved serine ligand is essential for the sulfur insertion steps. One crystallized lipoyl synthase (LipA) complex contains 5'-methylthioadenosine (MTA), a breakdown product of SAM, bound in the likely SAM-binding site. Modelling has identified an 18 Å (1 Å=0.1 nm) deep channel, well-proportioned to accommodate an octanoyl substrate. These results suggest that the auxiliary cluster is the likely sulfur donor, but access to a sulfide ion for the second sulfur insertion reaction requires the loss of an iron atom from the auxiliary cluster, which the serine ligand may enable.

Water network perturbation in ligand binding: adenosine A(2A) antagonists as a case study.

Recent efforts in the computational evaluation of the thermodynamic properties of water molecules have resulted in the development of promising new in silico methods to evaluate the role of water in ligand binding. These methods include WaterMap, SZMAP, GRID/CRY probe, and Grand Canonical Monte Carlo simulations. They allow the prediction of the position and relative free energy of the water molecule in the protein active site and the analysis of the perturbation of an explicit water network (WNP) as a consequence of ligand binding. We have for the first time extended these approaches toward the prediction of kinetics for small molecules and of relative free energy of binding with a focus on the perturbation of the water network and application to large diverse data sets. Our results support a qualitative correlation between the residence time of 12 related triazine adenosine A(2A) receptor antagonists and the number and position of high energy trapped solvent molecules. From a quantitative viewpoint, we successfully applied these computational techniques as an implicit solvent alternative, in linear combination with a molecular mechanics force field, to predict the relative ligand free energy of binding (WNP-MMSA). The applicability of this linear method, based on the thermodynamics additivity principle, did not extend to 375 diverse A(2A) receptor antagonists. However, a fast but effective method could be enabled by replacing the linear approach with a machine learning technique using probabilistic classification trees, which classified the binding affinity correctly for 90% of the ligands in the training set and 67% in the test set.

Study of the Conformational Dynamics of the Catalytic Loop of WT and G140A/G149A HIV-1 Integrase Core Domain Using Reversible Digitally Filtered Molecular Dynamics.

The HIV-1 IN enzyme is one of three crucial virally encoded enzymes (HIV-1 IN, HIV-1 PR, and HIV-1 RT) involved in the life-cycle of the HIV-1 virus, making it an attractive target in the development of drugs against the AIDS virus. The structure and mechanism of the HIV-1 IN enzyme is the least understood of the three enzymes due to the lack of three-dimensional structural information. X-ray cystallographic studies have not yet been able to resolve the full-length structure, and studies have been mainly focused on the catalytic domain. This central domain possesses an important catalytic loop observed to overhang the active site, and experimental studies have shown that its dynamics affects the catalytic activity of mutant HIV-1 IN enzymes. In this study, the enhanced sampling technique, Reversible Digitally Filtered Molecular Dynamics (RDFMD), has been applied to the catalytic domain of the WT and G140A/G149A HIV-1 IN enzymes and has highlighted significant differences between the behavior of the catalytic loop which may explain the decrease of activity observed in experimental studies for this mutant.

Hit identification and binding mode predictions by rigorous free energy simulations.

The identification of lead molecules using computational modeling often relies on approximate, high-throughput approaches, of limited accuracy. We show here that, with a methodology we recently developed, it is possible to predict the relative binding free energies of structurally diverse ligands of the estrogen receptor-alpha using a rigorous statistical thermodynamics approach. Predictions obtained from the simulations with an explicit solvation model are in good qualitative agreement with experimental data, while simulations with implicit solvent models or rank ordering by empirical scoring functions yield predictions of lower quality. In addition, it is shown that free energy techniques can be used to select the most likely binding mode from a set of possible orientations generated by a docking program. It is suggested that the free energy techniques outlined in this study can be used to rank-order, by potency, structurally diverse compounds identified by virtual screening, de novo design or scaffold hopping programs.

Optimal probe length varies for targets with high sequence variation: implications for probe library design for resequencing highly variable genes.

BACKGROUND: Sequencing by hybridisation is an effective method for obtaining large amounts of DNA sequence information at low cost. The efficiency of SBH depends on the design of the probe library to provide the maximum information for minimum cost. Long probes provide a higher probability of non-repeated sequences but lead to an increase in the number of probes required whereas short probes may not provide unique sequence information due to repeated sequences. We have investigated the effect of probe length, use of reference sequences, and thermal filtering on the design of probe libraries for several highly variable target DNA sequences. RESULTS: We designed overlapping probe libraries for a range of highly variable drug target genes based on known sequence information and develop a formal terminology to describe probe library design. We find that for some targets these libraries can provide good coverage of a previously unseen target whereas for others the coverage is less than 30%. The optimal probe length varies from as short at 12 nt to as large as 19 nt and depends on the sequence, its variability, and the stringency of thermal filtering. It cannot be determined from inspection of an example gene sequence. CONCLUSIONS: Optimal probe length and the optimal number of reference sequences used to design a probe library are highly target specific for highly variable sequencing targets. The optimum design cannot be determined simply by inspection of input sequences or of alignments but only by detailed analysis of the each specific target. For highly variable sequences, shorter probes can in some cases provide better information than longer probes. Probe library design would benefit from a general purpose tool for analysing these issues. The formal terminology developed here and the analysis approaches it is used to describe will contribute to the development of such tools.