Inhibitors of Fumarylacetoacetate Hydrolase Domain Containing Protein 1 (FAHD1).

FAH domain containing protein 1 (FAHD1) acts as oxaloacetate decarboxylase in mitochondria, contributing to the regulation of the tricarboxylic acid cycle. Guided by a high-resolution X-ray structure of FAHD1 liganded by oxalate, the enzymatic mechanism of substrate processing is analyzed in detail. Taking the chemical features of the FAHD1 substrate oxaloacetate into account, the potential inhibitor structures are deduced. The synthesis of drug-like scaffolds afforded first-generation FAHD1-inhibitors with activities in the low micromolar IC50 range. The investigations disclosed structures competing with the substrate for binding to the metal cofactor, as well as scaffolds, which may have a novel binding mode to FAHD1.

Identification of FAH domain-containing protein 1 (FAHD1) as oxaloacetate decarboxylase.

Fumarylacetoacetate hydrolase (FAH) domain-containing proteins occur in both prokaryotes and eukaryotes, where they carry out diverse enzymatic reactions, probably related to structural differences in their respective FAH domains; however, the precise relationship between structure of the FAH domain and the associated enzyme function remains elusive. In mammals, three FAH domain-containing proteins, FAHD1, FAHD2A, and FAHD2B, are known; however, their enzymatic function, if any, remains to be demonstrated. In bacteria, oxaloacetate is subject to enzymatic decarboxylation; however, oxaloacetate decarboxylases (ODx) were so far not identified in eukaryotes. Based on molecular modeling and subsequent biochemical investigations, we identified FAHD1 as a eukaryotic ODx enzyme. The results presented here indicate that dedicated oxaloacetate decarboxylases exist in eukaryotes.

Specificity of a protein-protein interface: local dynamics direct substrate recognition of effector caspases.

Proteases are prototypes of multispecific protein-protein interfaces. Proteases recognize and cleave protein and peptide substrates at a well-defined position in a substrate binding groove and a plethora of experimental techniques provide insights into their substrate recognition. We investigate the caspase family of cysteine proteases playing a key role in programmed cell death and inflammation, turning caspases into interesting drug targets. Specific ligand binding to one particular caspase is difficult to achieve, as substrate specificities of caspase isoforms are highly similar. In an effort to rationalize substrate specificity of two closely related caspases, we investigate the substrate promiscuity of the effector Caspases 3 and 7 by data mining (cleavage entropy) and by molecular dynamics simulations. We find a strong correlation between binding site rigidity and substrate readout for individual caspase subpockets explaining more stringent substrate readout of Caspase 7 via its narrower conformational space. Caspase 3 subpockets S3 and S4 show elevated local flexibility explaining the more unspecific substrate readout of that isoform in comparison to Caspase 7. We show by in silico exchange mutations in the S3 pocket of the proteases that a proline residue in Caspase 7 contributes to the narrowed conformational space of the binding site. These findings explain the substrate specificities of caspases via a mechanism of conformational selection and highlight the crucial importance of binding site local dynamics in substrate recognition of proteases. Proteins 2014; 82:546-555. © 2013 Wiley Periodicals, Inc.

Substrate-driven mapping of the degradome by comparison of sequence logos.

Sequence logos are frequently used to illustrate substrate preferences and specificity of proteases. Here, we employed the compiled substrates of the MEROPS database to introduce a novel metric for comparison of protease substrate preferences. The constructed similarity matrix of 62 proteases can be used to intuitively visualize similarities in protease substrate readout via principal component analysis and construction of protease specificity trees. Since our new metric is solely based on substrate data, we can engraft the protease tree including proteolytic enzymes of different evolutionary origin. Thereby, our analyses confirm pronounced overlaps in substrate recognition not only between proteases closely related on sequence basis but also between proteolytic enzymes of different evolutionary origin and catalytic type. To illustrate the applicability of our approach we analyze the distribution of targets of small molecules from the ChEMBL database in our substrate-based protease specificity trees. We observe a striking clustering of annotated targets in tree branches even though these grouped targets do not necessarily share similarity on protein sequence level. This highlights the value and applicability of knowledge acquired from peptide substrates in drug design of small molecules, e.g., for the prediction of off-target effects or drug repurposing. Consequently, our similarity metric allows to map the degradome and its associated drug target network via comparison of known substrate peptides. The substrate-driven view of protein-protein interfaces is not limited to the field of proteases but can be applied to any target class where a sufficient amount of known substrate data is available.

Cleavage entropy as quantitative measure of protease specificity.

A purely information theory-guided approach to quantitatively characterize protease specificity is established. We calculate an entropy value for each protease subpocket based on sequences of cleaved substrates extracted from the MEROPS database. We compare our results with known subpocket specificity profiles for individual proteases and protease groups (e.g. serine proteases, metallo proteases) and reflect them quantitatively. Summation of subpocket-wise cleavage entropy contributions yields a measure for overall protease substrate specificity. This total cleavage entropy allows ranking of different proteases with respect to their specificity, separating unspecific digestive enzymes showing high total cleavage entropy from specific proteases involved in signaling cascades. The development of a quantitative cleavage entropy score allows an unbiased comparison of subpocket-wise and overall protease specificity. Thus, it enables assessment of relative importance of physicochemical and structural descriptors in protease recognition. We present an exemplary application of cleavage entropy in tracing substrate specificity in protease evolution. This highlights the wide range of substrate promiscuity within homologue proteases and hence the heavy impact of a limited number of mutations on individual substrate specificity.

Heteroaromatic π-stacking energy landscapes.

In this study we investigate π-stacking interactions of a variety of aromatic heterocycles with benzene using dispersion corrected density functional theory. We calculate extensive potential energy surfaces for parallel-displaced interaction geometries. We find that dispersion contributes significantly to the interaction energy and is complemented by a varying degree of electrostatic interactions. We identify geometric preferences and minimum interaction energies for a set of 13 5- and 6-membered aromatic heterocycles frequently encountered in small drug-like molecules. We demonstrate that the electrostatic properties of these systems are a key determinant for their orientational preferences. The results of this study can be applied in lead optimization for the improvement of stacking interactions, as it provides detailed energy landscapes for a wide range of coplanar heteroaromatic geometries. These energy landscapes can serve as a guide for ring replacement in structure-based drug design.

Computer-guided approach to access the anti-influenza activity of licorice constituents.

Neuraminidase (NA), a key enzyme in viral replication, is the first-line drug target to combat influenza. On the basis of a shape-focused virtual screening, the roots of Glycyrrhiza glabra (licorice) were identified as plant species with an accumulation of constituents that show 3D similarities to known influenza NA inhibitors (NAIs). Phytochemical investigation revealed 12 constituents identified as (E)-1-[2,4-dihydroxy-3-(3-methyl-2-butenyl)phenyl]-3-(8-hydroxy-2,2-dimethyl-2H-1-benzopyran-6-yl)-2-propen-1-one (1), 3,4-dihydro-8,8-dimethyl-2H,8H-benzo[1,2-b:3,4-b']dipyran-3-ol (2), biochanin B (3), glabrol (4), glabrone (5), hispaglabridin B (6), licoflavone B (7), licorice glycoside B (8), licorice glycoside E (9), liquiritigenin (10), liquiritin (11), and prunin (12). Eleven of these constituents showed significant influenza virus NA inhibition in a chemiluminescence (CL)-based assay. Additional tests, including (i) a cell-based cytopathic effect inhibition assay (general antiviral activity), (ii) the evaluation of cytotoxicity, (iii) the inhibition of the NA of Clostridium perfringens (CL- and fluorescence (FL)-based assay), and (iv) the determination of self-fluorescence and quenching, provided further perspective on their anti-influenza virus potential, revealing possible assay interference problems and false-positive results. Compounds 1, 3, 5, and 6 showed antiviral activity, most likely caused by the inhibition of NA. Of these, compounds 1, 3, and 6 were highly ranked in shape-focused virtual screening.

Characterisation of Nox4 inhibitors from edible plants.

NADPH oxidases transport electrons from cytosolic NADPH through biological membranes to generate reactive oxygen species. NADPH oxidase 4, broadly expressed in humans, is an interesting pharmacological target, since its activity is deregulated in several diseases, including pulmonary fibrosis, diabetic nephropathy, and cardiac hypertrophy. Whereas several candidate NADPH oxidase 4 inhibitors were recently described, most of these compounds are either unspecific or toxic. Here we set out to identify new NADPH oxidase 4 inhibitors from edible plants, in an attempt to decrease the number of hits with toxic side effects. We screened a compound library prepared from edible plants for new bioactives with the ability to inhibit the activity of NADPH oxidase 4. Using both cell-based and cell-free assays, we identified several compounds with significant inhibitory activity towards NADPH oxidase 4. For selected compounds, the activity profile towards NADPH oxidase 2 and NADPH oxidase 5 was established, and controls were carried out to exclude general reactive oxygen species scavengers. A number of promising NADPH oxidase 4 inhibitors from edible plants was identified and characterised. Several new chemical entities are disclosed which act as NADPH oxidase 4 inhibitors, and the efficacies of our best hits, in particular several diarylheptanoids and lignans, are comparable to the best available pharmacological NADPH oxidase 4 inhibitors. These findings will provide valuable tools to study mechanisms of NADPH oxidase inhibition.

Influenza neuraminidase: a druggable target for natural products.

The imminent threat of influenza pandemics and repeatedly reported emergence of new drug-resistant influenza virus strains demonstrate the urgent need for developing innovative and effective antiviral agents for prevention and treatment. At present, influenza neuraminidase (NA), a key enzyme in viral replication, spread, and pathogenesis, is considered to be one of the most promising targets for combating influenza. Despite the substantial medical potential of NA inhibitors (NAIs), only three of these drugs are currently on the market (zanamivir, oseltamivir, and peramivir). Moreover, sudden changes in NAI susceptibility revealed the urgent need in the discovery/identification of novel inhibitors. Nature offers an abundance of biosynthesized compounds comprising chemical scaffolds of high diversity, which present an infinite pool of chemical entities for target-oriented drug discovery in the battle against this highly contagious pathogen. This review illuminates the increasing research efforts of the past decade (2000-2011), focusing on the structure, function and druggability of influenza NA, as well as its inhibition by natural products. Following a critical discussion of publications describing some 150 secondary plant metabolites tested for their inhibitory potential against influenza NA, the impact of three different strategies to identify and develop novel NAIs is presented: (i) bioactivity screening of herbal extracts, (ii) exploitation of empirical knowledge, and (iii) computational approaches. This work addresses the latest developments in theoretical and experimental research on properties of NA that are and will be driving anti-influenza drug development now and in the near future.

Identification of novel liver X receptor activators by structure-based modeling.

Liver X receptors (LXRs) are members of the nuclear receptor family. Activators of LXRs are of high pharmacological interest as LXRs regulate cholesterol, fatty acid, and carbohydrate metabolism as well as inflammatory processes. On the basis of different X-ray crystal structures, we established a virtual screening workflow for the identification of novel LXR modulators. A two-step screening concept to identify active compounds included 3D-pharmacophore filters and rescoring by shape alignment. Eighteen virtual hits were tested in vitro applying a reporter gene assay, where concentration-dependent activity was proven for four novel lead structures. The most active compound 10, a 1,4-naphthochinone, has an estimated EC50 of around 5 µM.

Phase Diagram of a Stratum Corneum Lipid Mixture.

Computational modeling of lipid ternary mixtures is challenging because of their complicated and segmented phase diagram, the long timescales required for mixing the system components, and the necessity to sufficiently sample the three-dimensional phase space. Here, we investigate a ternary system, which mimics the lipid matrix of the stratum corneum, the outermost layer of the epidermis and the primary barrier for transdermal drug absorption. Our system consists of ceramide, cholesterol, and lignoceric acid at 23 different composition ratios, which we study at two different temperatures using coarse-grained molecular dynamics (CG MD) simulations. As CG MD simulations heavily depend on the choice of parameters, first an improved set of ceramide CG parameters was developed that reproduces experimental and all-atom simulation data. Second, the performance of the recently updated MARTINI 2015 cholesterol force field was systematically evaluated and compared to the 2007 model. We provide a detailed analysis of the structural and dynamic properties of the ternary system, such as area per lipid, area compressibility modulus, lipid order parameters, bilayer thickness, lipid tail interdigitation, and lateral self-diffusion. Based on the analysis of these properties, we devise a phase diagram of the ternary system, where three different phases, namely, liquid-disordered, gel, and liquid-ordered, are observed. The individual occurrence of a certain phase not only depends on the component molar ratio and the temperature but also decisively on the employed cholesterol force field.

Discovery and Characterization of Diazenylaryl Sulfonic Acids as Inhibitors of Viral and Bacterial Neuraminidases.

Viral neuraminidases are an established drug target to combat influenza. Severe complications observed in influenza patients are primarily caused by secondary infections with e.g., Streptococcus pneumoniae. These bacteria engage in a lethal synergism with influenza A viruses (IAVs) and also express neuraminidases. Therefore, inhibitors with dual activity on viral and bacterial neuraminidases are expected to be advantageous for the treatment of influenza infections. Here we report on the discovery and characterization of diazenylaryl sulfonic acids as dual inhibitors of viral and Streptococcus pneumoniae neuraminidase. The initial hit came from a virtual screening campaign for inhibitors of viral neuraminidases. For the most active compound, 7-[2-[4-[2-[4-[2-(2-hydroxy-3,6-disulfo-1-naphthalenyl)diazenyl]-2-methylphenyl]diazenyl]-2-methylphenyl]diazenyl]-1,3-naphthalenedisulfonic acid (NSC65847; 1), the Ki-values measured in a fluorescence-based assay were lower than 1.5 µM for both viral and pneumococcal neuraminidases. The compound also inhibited N1 virus variants containing neuraminidase inhibitor resistance-conferring substitutions. Via enzyme kinetics and nonlinear regression modeling, 1 was suggested to impair the viral neuraminidases and pneumococcal neuraminidase with a mixed-type inhibition mode. Given its antiviral and antipneumococcal activity, 1 was identified as a starting point for the development of novel, dual-acting anti-infectives.

Sequence diversity of NanA manifests in distinct enzyme kinetics and inhibitor susceptibility.

Streptococcus pneumoniae is the leading pathogen causing bacterial pneumonia and meningitis. Its surface-associated virulence factor neuraminidase A (NanA) promotes the bacterial colonization by removing the terminal sialyl residues from glycoconjugates on eukaryotic cell surface. The predominant role of NanA in the pathogenesis of pneumococci renders it an attractive target for therapeutic intervention. Despite the highly conserved activity of NanA, our alignment of the 11 NanAs revealed the evolutionary diversity of this enzyme. The amino acid substitutions we identified, particularly those in the lectin domain and in the insertion domain next to the catalytic centre triggered our special interest. We synthesised the representative NanAs and the mutagenized derivatives from E. coli for enzyme kinetics study and neuraminidase inhibitor susceptibility test. Via molecular docking we got a deeper insight into the differences between the two major variants of NanA and their influence on the ligand-target interactions. In addition, our molecular dynamics simulations revealed a prominent intrinsic flexibility of the linker between the active site and the insertion domain, which influences the inhibitor binding. Our findings for the first time associated the primary sequence diversity of NanA with the biochemical properties of the enzyme and with the inhibitory efficiency of neuraminidase inhibitors.

Quantitative Correlation of Conformational Binding Enthalpy with Substrate Specificity of Serine Proteases.

Members of the same protease family show different substrate specificity, even if they share identical folds, depending on the physiological processes they are part of. Here, we investigate the key factors for subpocket and global specificity of factor Xa, elastase, and granzyme B which despite all being serine proteases and sharing the chymotrypsin-fold show distinct substrate specificity profiles. We determined subpocket interaction potentials with GRID for static X-ray structures and an in silico generated ensemble of conformations. Subpocket interaction potentials determined for static X-ray structures turned out to be insufficient to explain serine protease specificity for all subpockets. Therefore, we generated conformational ensembles using molecular dynamics simulations. We identified representative binding site conformations using distance-based hierarchical agglomerative clustering and determined subpocket interaction potentials for each representative conformation of the binding site. Considering the differences in subpocket interaction potentials for these representative conformations as well as their abundance allowed us to quantitatively explain subpocket specificity for the nonprime side for all three example proteases on a molecular level. The methods to identify key regions determining subpocket specificity introduced in this study are directly applicable to other serine proteases, and the results provide starting points for new strategies in rational drug design.

Independent Metrics for Protein Backbone and Side-Chain Flexibility: Time Scales and Effects of Ligand Binding.

Conformational dynamics are central for understanding biomolecular structure and function, since biological macromolecules are inherently flexible at room temperature and in solution. Computational methods are nowadays capable of providing valuable information on the conformational ensembles of biomolecules. However, analysis tools and intuitive metrics that capture dynamic information from in silico generated structural ensembles are limited. In standard work-flows, flexibility in a conformational ensemble is represented through residue-wise root-mean-square fluctuations or B-factors following a global alignment. Consequently, these approaches relying on global alignments discard valuable information on local dynamics. Results inherently depend on global flexibility, residue size, and connectivity. In this study we present a novel approach for capturing positional fluctuations based on multiple local alignments instead of one single global alignment. The method captures local dynamics within a structural ensemble independent of residue type by splitting individual local and global degrees of freedom of protein backbone and side-chains. Dependence on residue type and size in the side-chains is removed via normalization with the B-factors of the isolated residue. As a test case, we demonstrate its application to a molecular dynamics simulation of bovine pancreatic trypsin inhibitor (BPTI) on the millisecond time scale. This allows for illustrating different time scales of backbone and side-chain flexibility. Additionally, we demonstrate the effects of ligand binding on side-chain flexibility of three serine proteases. We expect our new methodology for quantifying local flexibility to be helpful in unraveling local changes in biomolecular dynamics.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

FAH domain containing protein 1 (FAHD-1) is required for mitochondrial function and locomotion activity in C. elegans.

The fumarylacetoacetate hydrolase (FAH) protein superfamily of metabolic enzymes comprises a diverse set of enzymatic functions, including ß-diketone hydrolases, decarboxylases, and isomerases. Of note, the FAH superfamily includes many prokaryotic members with very distinct functions that lack homologs in eukaryotes. A prokaryotic member of the FAH superfamily, referred to as Cg1458, was shown to encode a soluble oxaloacetate decarboxylase (ODx). Based on sequence homologies to Cg1458, we recently identified human FAH domain containing protein-1 (FAHD1) as the first eukaryotic oxaloacetate decarboxylase. The physiological functions of ODx in eukaryotes remain unclear. Here we have probed the function of fahd-1, the nematode homolog of FAHD1, in the context of an intact organism. We found that mutation of fahd-1 resulted in reduced brood size, a deregulation of the egg laying process and a severe locomotion deficit, characterized by a reduced frequency of body bends, reduced exploratory movements and reduced performance in an endurance exercise test. Notably, mitochondrial function was altered in the fahd-1(tm5005) mutant strain, as shown by a reduction of mitochondrial membrane potential and a reduced oxygen consumption of fahd-1(tm5005) animals. Mitochondrial dysfunction was accompanied by lifespan extension in worms grown at elevated temperature; however, unlike in mutant worms with a defect in the electron transport chain, the mitochondrial unfolded protein response was not upregulated in worms upon inactivation of fahd-1. Together these data establish a role of fahd-1 to maintain mitochondrial function and consequently physical activity in nematodes.

Interface dynamics explain assembly dependency of influenza neuraminidase catalytic activity.

Influenza virus neuraminidase (iNA) is a homotetrameric surface protein of the influenza virus and an established target for antiviral drugs. In contrast to neuraminidases (NAs) of other biological systems (non-iNAs), enzymatic activity of iNA is only observed in a quaternary assembly and iNA needs the tetramerization to mediate enzymatic activity. Obviously, differences on a molecular level between iNA and non-iNAs are responsible for this intriguing observation. Comparison between protein structures and multiple sequence alignment allow the identification of differences in amino acid composition in crucial regions of the enzyme, such as next to the conserved D151 and the 150-loop. These differences in amino acid sequence and protein tetramerization are likely to alter the dynamics of the system. Therefore, we performed molecular dynamics simulations to investigate differences in the molecular flexibility of monomers, dimers, and tetramers of iNAs of subtype N1 (avian 2004, pandemic 1918 and pandemic 2009 iNA) and as comparison the non-iNA monomer from Clostridium perfringens. We show that conformational transitions of iNA are crucially influenced by its assembly state. The protein-protein interface induces a complex hydrogen-bonding network between the 110-helix and the 150-loop, which consequently stabilizes the structural arrangement of the binding site. Therefore, we claim that these altered dynamics are responsible for the dependence of iNA's catalytic activity on the tetrameric assembly. Only the tetramerization-induced balance between stabilization and altered local flexibility in the binding site provides the appropriate arrangement of key residues for iNA's catalytic activity.