Discovery of novel steroidal histamine H3 receptor antagonists/inverse agonists

Emerging from an HTS campaign, novel steroid-based histamine H₃ receptor antagonists were identified and characterized. Structural moieties of the hit compounds were combined to improve binding affinities which resulted in compound 4 as lead molecule. During the lead optimization due to the versatile modifications of diamino steroid derivatives, several in vitro potent compounds with subnanomolar binding affinities to histamine H₃ receptors were found. The unfavorable binding to rat muscarinic receptors was successfully reduced by tuning the basicity. Compound 20 showed significant in vivo activity in the rat dipsogenia model and could serve as a pharmacological tool in the future.     

Characterization of the Chemokine CXCL11-Heparin Interaction Suggests Two Different Affinities for Glycosaminoglycans

Chemokines orchestrate the migration of leukocytes in the context of homeostasis and inflammation. In addition to interactions of chemokines with receptors on migrating cells, these processes require interactions of chemokines with glycosaminoglycans (GAGs) for cell surface localization. Most chemokines are basic proteins with Arg/Lys/His residue clusters functioning as recognition epitopes for GAGs. In this study we characterized the GAG-binding epitopes of the chemokine I-TAC/CXCL11. Four separate clusters of basic residues were mutated to alanine and tested for their ability to bind to GAGs in vitro and to activate the receptor, CXCR3. Mutation of a set of basic residues in the C-terminal helix (the 50s cluster, ⁵⁷KSKQAR⁶²) along with Lys¹⁷, significantly impaired heparin binding in vitro, identifying these residues as components of the dominant epitope. However, this GAG mutant retained nearly wild type receptor binding affinity, and its ability to induce cell migration in vitro was only mildly perturbed. Nevertheless, the mutant was unable to induce cell migration in vivo, establishing a requirement of CXCL11 for GAG binding for in vivo function. These studies also led to some interesting findings. First, CXCL11 exhibits conformational heterogeneity, as evidenced by the doubling of peaks in its HSQC spectra. Second, it exhibits more than one affinity state for both heparin and CXCR3, which may be related to its structural plasticity. Finally, although the binding affinities of chemokines for GAGs are typically weaker than interactions with receptors, the high affinity GAG binding state of CXCL11 is comparable with typical receptor binding affinities, suggesting some unique properties of this chemokine.     

Structural studies of human purine nucleoside phosphorylase: towards a new specific empirical scoring function

Human purine nucleoside phosphorylase (HsPNP) is a target for inhibitor development aiming at T-cell immune response modulation. In this work, we report the development of a new set of empirical scoring functions and its application to evaluate binding affinities and docking results. To test these new functions, we solved the structure of HsPNP and 2-mercapto-4(3H)-quinazolinone (HsPNP:MQU) binary complex at 2.7 Å resolution using synchrotron radiation, and used these functions to predict ligand position obtained in docking simulations. We also employed molecular dynamics simulations to analyze HsPNP in two conditions, as apoenzyme and in the binary complex form, in order to assess the structural features responsible for stability. Analysis of the structural differences between systems provides explanation for inhibitor binding. The use of these scoring functions to evaluate binding affinities and molecular docking results may be used to guide future efforts on virtual screening focused on HsPNP.     

Blind Prediction of Charged Ligand Binding Affinities in a Model Binding Site

Predicting absolute protein–ligand binding affinities remains a frontier challenge in ligand discovery and design. This becomes more difficult when ionic interactions are involved because of the large opposing solvation and electrostatic attraction energies. In a blind test, we examined whether alchemical free-energy calculations could predict binding affinities of 14 charged and 5 neutral compounds previously untested as ligands for a cavity binding site in cytochrome c peroxidase. In this simplified site, polar and cationic ligands compete with solvent to interact with a buried aspartate. Predictions were tested by calorimetry, spectroscopy, and crystallography. Of the 15 compounds predicted to bind, 13 were experimentally confirmed, while 4 compounds were false negative predictions. Predictions had a root-mean-square error of 1.95 kcal/mol to the experimental affinities, and predicted poses had an average RMSD of 1.7 Å to the crystallographic poses. This test serves as a benchmark for these thermodynamically rigorous calculations at predicting binding affinities for charged compounds and gives insights into the existing sources of error, which are primarily electrostatic interactions inside proteins. Our experiments also provide a useful set of ionic binding affinities in a simplified system for testing new affinity prediction methods.     

Integrated microfluidic approach for quantitative high-throughput measurements of transcription factor binding affinities

Protein binding to DNA is a fundamental process in gene regulation. Methodologies such as ChIP-Seq and mapping of DNase I hypersensitive sites provide global information on this regulation in vivo. In vitro methodologies provide valuable complementary information on protein–DNA specificities. However, current methods still do not measure absolute binding affinities. There is a real need for large-scale quantitative protein–DNA affinity measurements. We developed QPID, a microfluidic application for measuring protein–DNA affinities. A single run is equivalent to 4096 gel-shift experiments. Using QPID, we characterized the different affinities of ATF1, c-Jun, c-Fos and AP-1 to the CRE consensus motif and CRE half-site in two different genomic sequences on a single device. We discovered that binding of ATF1, but not of AP-1, to the CRE half-site is highly affected by its genomic context. This effect was highly correlated with ATF1 ChIP-seq and PBM experiments. Next, we characterized the affinities of ATF1 and ATF3 to 128 genomic CRE and CRE half-site sequences. Our affinity measurements explained that in vivo binding differences between ATF1 and ATF3 to CRE and CRE half-sites are partially mediated by differences in the minor groove width. We believe that QPID would become a central tool for quantitative characterization of biophysical aspects affecting protein–DNA binding.     

Blinded predictions of binding modes and energies of HSP90-α ligands for the 2015 D3R grand challenge

In the framework of the 2015 D3R inaugural grand challenge, blind binding pose and affinity predictions were performed for a set of 180 ligands of the Heat Shock Protein HSP90-α protein, a relevant cancer target. Spectral clustering was used to rapidly identify alternative binding site conformations in publicly available crystallographic HSP90-α structures. Subsequently, multiple docking and scoring protocols employing the software Autodock Vina and rDock were applied to predict binding modes and rank order ligands. Alchemical free energy calculations were performed with the software FESetup and Sire/OpenMM to predict binding affinities for three congeneric series subsets. Some of the protocols used here were ranked among the top submissions according to most of the evaluation metrics. Docking performance was excellent, but the scoring results were disappointing. A critical assessment of the results is reported, as well as suggestions for future similar competitions.     

In Vivo Mutational Characterization of DndE Involved in DNA Phosphorothioate Modification

DNA phosphorothioate (PT) modification is a recently identified epigenetic modification that occurs in the sugar-phosphate backbone of prokaryotic DNA. Previous studies have demonstrated that DNA PT modification is governed by the five DndABCDE proteins in a sequence-selective and R _P stereo-specific manner. Bacteria may have acquired this physiological modification along with dndFGH as a restriction-modification system. However, little is known about the biological function of Dnd proteins, especially the smallest protein, DndE, in the PT modification pathway. DndE was reported to be a DNA-binding protein with a preference for nicked dsDNA in vitro; the binding of DndE to DNA occurs via six positively charged lysine residues on its surface. The substitution of these key lysine residues significantly decreased the DNA binding affinities of DndE proteins to undetectable levels. In this study, we conducted site-directed mutagenesis of dndE on a plasmid and measured DNA PT modifications under physiological conditions by mass spectrometry. We observed distinctive differences from the in vitro binding assays. Several mutants with lysine residues mutated to alanine decreased the total frequency of PT modifications, but none of the mutants completely eliminated PT modification. Our results suggest that the nicked dsDNA-binding capacity of DndE may not be crucial for PT modification and/or that DndE may have other biological functions in addition to binding to dsDNA.     

Synthesis and evaluation of novel opioid ligands with a C-homomorphinan skeleton

As the reports about C-homomorphinans with the seven-membered C-ring are much fewer than those of morphinan derivatives with a six-membered C-ring, we attempted to synthesize C-homomorphinan derivatives and to evaluate their opioid activities. C-Homomorphinan 5 showed sufficient binding affinities to the opioid receptors. C-Homomorphinan derivatives possessing the δ address moiety such as indole (NTI-type), quinoline, or benzylidene (BNTX-type) functionalities showed the strongest binding affinities for the δ receptor among the three types of opioid receptors, which indicated that the C-homomorphinan skeleton sufficiently functions as a message-part in the ligand. Although NTI-type compound 8 and quinoline compound 9 with C-homomorphinan scaffold exhibited lower affinities and selectivities for the δ receptor than the corresponding morphinan derivatives did, both the binding affinity and selectivity for the δ receptor of BNTX-type compound 12 with a seven-membered C-ring were improved compared with the corresponding compounds with a six-membered C-ring including BNTX itself. BNTX-Type compound 12 was the most selective δ receptor antagonist among the tested compounds.     

An affinity-based scoring scheme for predicting DNA-binding activities of modularly assembled zinc-finger proteins

Zinc-finger proteins (ZFPs) have long been recognized for their potential to manipulate genetic information because they can be engineered to bind novel DNA targets. Individual zinc-finger domains (ZFDs) bind specific DNA triplet sequences; their apparent modularity has led some groups to propose methods that allow virtually any desired DNA motif to be targeted in vitro. In practice, however, ZFPs engineered using this ‘modular assembly’ approach do not always function well in vivo. Here we report a modular assembly scoring strategy that both identifies combinations of modules least likely to function efficiently in vivo and provides accurate estimates of their relative binding affinities in vitro. Predicted binding affinities for 53 ‘three-finger’ ZFPs, computed based on energy contributions of the constituent modules, were highly correlated (r = 0.80) with activity levels measured in bacterial two-hybrid assays. Moreover, K_d values for seven modularly assembled ZFPs and their intended targets, measured using fluorescence anisotropy, were also highly correlated with predictions (r = 0.91). We propose that success rates for ZFP modular assembly can be significantly improved by exploiting the score-based strategy described here.     

Downstream sequence elements with different affinities for the hnRNP H/H' protein influence the processing efficiency of mammalian polyadenylation signals

Auxiliary factors likely play an important role in determining the polyadenylation efficiency of mammalian pre-mRNAs. We previously identified an auxiliary factor, hnRNP H/H′, which stimulates 3′-end processing through an interaction with sequences downstream of the core elements of the SV40 late polyadenylation signal. Using in vitro reconstitution assays we have demonstrated that hnRNP H/H′ can stimulate processing of two additional model polyadenylation signals by binding at similar relative downstream locations but with significantly different affinities. A short tract of G residues was determined to be a common property of all three hnRNP H/H′ binding sites. A survey of mammalian polyadenylation signals identified potential G-rich hnRNP H/H′ binding sites at similar downstream locations in ~34% of these signals. All of the novel G-rich elements tested were found to bind hnRNP H/H′ protein and the processing of selected signals identified in the survey was stimulated by the protein both in vivo and in vitro. Downstream G-rich tracts, therefore, are a common auxiliary element in mammalian polyadenylation signals. Sequences capable of binding hnRNP H protein with varying affinities may play a role in determining the processing efficiency of a significant number of mammalian polyadenylation signals.     

Isozyme-Specific Ligands for O-acetylserine sulfhydrylase,a Novel Antibiotic Target

The last step of cysteine biosynthesis in bacteria and plants is catalyzed by O-acetylserine sulfhydrylase. In bacteria, two isozymes, O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B, have been identified that share similar binding sites, although the respective specific functions are still debated. O-acetylserine sulfhydrylase plays a key role in the adaptation of bacteria to the host environment, in the defense mechanisms to oxidative stress and in antibiotic resistance. Because mammals synthesize cysteine from methionine and lack O-acetylserine sulfhydrylase, the enzyme is a potential target for antimicrobials. With this aim, we first identified potential inhibitors of the two isozymes via a ligand- and structure-based in silico screening of a subset of the ZINC library using FLAP. The binding affinities of the most promising candidates were measured in vitro on purified O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B from Salmonella typhimurium by a direct method that exploits the change in the cofactor fluorescence. Two molecules were identified with dissociation constants of 3.7 and 33 µM for O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B, respectively. Because GRID analysis of the two isoenzymes indicates the presence of a few common pharmacophoric features, cross binding titrations were carried out. It was found that the best binder for O-acetylserine sulfhydrylase-B exhibits a dissociation constant of 29 µM for O-acetylserine sulfhydrylase-A, thus displaying a limited selectivity, whereas the best binder for O-acetylserine sulfhydrylase-A exhibits a dissociation constant of 50 µM for O-acetylserine sulfhydrylase-B and is thus 8-fold selective towards the former isozyme. Therefore, isoform-specific and isoform-independent ligands allow to either selectively target the isozyme that predominantly supports bacteria during infection and long-term survival or to completely block bacterial cysteine biosynthesis.     

Binding Pocket Optimization by Computational Protein Design

Engineering specific interactions between proteins and small molecules is extremely useful for biological studies, as these interactions are essential for molecular recognition. Furthermore, many biotechnological applications are made possible by such an engineering approach, ranging from biosensors to the design of custom enzyme catalysts. Here, we present a novel method for the computational design of protein-small ligand binding named PocketOptimizer. The program can be used to modify protein binding pocket residues to improve or establish binding of a small molecule. It is a modular pipeline based on a number of customizable molecular modeling tools to predict mutations that alter the affinity of a target protein to its ligand. At its heart it uses a receptor-ligand scoring function to estimate the binding free energy between protein and ligand. We compiled a benchmark set that we used to systematically assess the performance of our method. It consists of proteins for which mutational variants with different binding affinities for their ligands and experimentally determined structures exist. Within this test set PocketOptimizer correctly predicts the mutant with the higher affinity in about 69% of the cases. A detailed analysis of the results reveals that the strengths of PocketOptimizer lie in the correct introduction of stabilizing hydrogen bonds to the ligand, as well as in the improved geometric complemetarity between ligand and binding pocket. Apart from the novel method for binding pocket design we also introduce a much needed benchmark data set for the comparison of affinities of mutant binding pockets, and that we use to asses programs for in silico design of ligand binding.