Global analysis of small RNA and mRNA targets of Hfq

Hfq, a bacterial member of the Sm family of RNA-binding proteins, is required for the action of many small regulatory RNAs that act by basepairing with target mRNAs. Hfq binds this family of small RNAs efficiently. We have used co-immunoprecipitation with Hfq and direct detection of the bound RNAs on genomic microarrays to identify members of this small RNA family. This approach was extremely sensitive; even Hfq-binding small RNAs expressed at low levels were readily detected. At least 15 of 46 known small RNAs in E. coli interact with Hfq. In addition, high signals in other intergenic regions suggested up to 20 previously unidentified small RNAs bind Hfq; five were confirmed by Northern analysis. Strong signals within genes and operons also were detected, some of which correspond to known Hfq targets. Within the argX-hisR-leuT-proM operon, Hfq appears to compete with RNase E and modulate RNA processing and degradation. Thus Hfq immunoprecipitation followed by microarray analysis is a highly effective method for detecting a major class of small RNAs as well as identifying new Hfq functions.     

Proteome-wide prediction of overlapping small molecule and protein binding sites using structure

Small molecules that modulate protein-protein interactions are of great interest for chemical biology and therapeutics. Here I present a structure-based approach to predict 'bi-functional' sites able to bind both small molecule ligands and proteins, in proteins of unknown structure. First, I develop a homology-based annotation method that transfers binding sites of known three-dimensional structure onto protein sequences, predicting residues in ligand and protein binding sites with estimated true positive rates of 98% and 88%, respectively, at 1% false positive rates. Applying this method to the human proteome predicts 8463 proteins with bi-functional residues and correctly recovers the targets of known interaction modulators. Proteins with significantly (p < 0.01) more bi-functional residues than expected were found to be enriched in regulatory and depleted in metabolism functions. Finally, I demonstrate the utility of the method by describing examples of predicted overlap and evidence of their biological and therapeutic relevance. The results suggest that combining the structures of known binding sites with established fold detection algorithms can predict regions of protein-protein interfaces that are amenable to small molecule modulation. Open-source software and the results for several complete proteomes are available at http://pibase.janelia.org/homolobind.     

Domain-based small molecule binding site annotation

Background  

Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites.     

THERPA: A small molecule database related to prion protein regulation and prion diseases progression

Prion diseases are fatal neurodegenerative disorders that affect humans and animals. Although various small molecules have been evaluated for application in the treatment of prion diseases, none have been shown to be efficacious. Expanding our knowledge of these molecules is important for understanding of the complex mechanisms of prion diseases. To improve access to the scattered information on small molecules related to prion diseases, we built a database of therapeutic molecules associated with prion diseases (THERPA, therpa.pythonanywhere.com). THERPA includes 119 small molecules and their 283 relationships with prion diseases. THERPA is an interactive visual database and useful for improving search efficiency which can help researchers identify intrinsic small molecules that can be used for developing therapeutics for prion diseases.     

A small molecule ligand of the glucagon-like peptide 1 receptor targets its amino-terminal hormone binding domain

The glucagon-like peptide 1 receptor (GLP-1R) belongs to a distinct subgroup of G protein-coupled peptide hormone receptors (class B) that has been difficult to target by small molecule drugs. Here, we report that a non-peptide compound, T-0632, binds with micromolar affinity to the human GLP-1R and blocks GLP-1-induced cAMP production. Furthermore, the observation that T-0632 has almost 100-fold selectivity for the human versus the highly homologous rat GLP-1R provided an opportunity to map determinants of non-peptide binding. Radioligand competition experiments utilizing a series of chimeric human/rat GLP-1R constructs revealed that partial substitution of the amino terminus of the rat GLP-1R with the corresponding sequence from the human homolog was sufficient to confer high T-0632 affinity. Follow-up analysis of receptors where individual candidate amino acids had been exchanged between the human and rat GLP-1Rs identified a single residue that explained species selectivity of non-peptide binding. Replacement of tryptophan 33 in the human GLP-1R by serine (the homologous amino acid in the rat GLP-1R) resulted in a 100-fold loss of T-0632 affinity, whereas the converse mutation in the rat GLP-1R led to a reciprocal gain-of-function phenotype. These observations suggest that in a class B receptor, important determinants of non-peptide affinity reside within the extracellular amino-terminal domain. Compound T-0632 may mimic, and thereby interfere with, the putative "pseudo-tethering" mechanism by which the amino terminus of class B receptors initiates the binding of cognate hormones.     

Acceleration of protein backbone NMR assignment by combinatorial labeling: Application to a small molecule binding study

Selective labeling with stable isotopes has long been recognized as a valuable tool in protein NMR to alleviate signal overlap and sensitivity limitations. In this study, combinatorial ¹⁵N‐, ¹³C^α‐, and ¹³C'‐selective labeling has been used during the backbone assignment of human cyclophilin D to explore binding of an inhibitor molecule. Using a cell‐free expression system, a scheme that involves ¹⁵N, 1‐¹³C, 2‐¹³C, fully ¹⁵N/¹³C, and unlabeled amino acids was optimized to gain a maximum of assignment information from three samples. This scheme was combined with time‐shared triple‐resonance NMR experiments, which allows a fast and efficient backbone assignment by giving the unambiguous assignment of unique amino acid pairs in the protein, the identity of ambiguous pairs and information about all 19 non‐proline amino acid types. It is therefore well suited for binding studies where de novo assignments of amide ¹H and ¹⁵N resonances need to be obtained, even in cases where sensitivity is the limiting factor.     

Structure-based druggability assessment--identifying suitable targets for small molecule therapeutics

A target is druggable if it can be modulated in vivo by a drug-like molecule. The general properties of oral drugs are summarized by the 'rule of 5' which specifies parameters related to size and lipophilicity. Structure-based target druggability assessment consists of predicting ligand-binding sites on the protein that are complementary to these drug-like properties. Automated identification of ligand-binding sites can use geometrical considerations alone or include specific physicochemical properties of the protein surface. Features of a pocket's size and shape, together with measures of its hydrophobicity, are most informative in identifying suitable drug-binding pockets. The recent availability of several validation sets of druggable versus undruggable targets has helped fuel the development of more elaborate methods.     

Protein-protein interactions as targets for small molecule drug discovery

Protein-protein interactions represent a highly populated class of targets for drug discovery. However, such systems present a number of unique challenges. This review presents an analysis of individual protein-protein interaction systems which have recently yielded success in discovering drug-like inhibitors. The structural characteristics of the protein binding sites and the attributes of the small molecule ligands are focused upon, in an attempt to derive commonly shared principles that may be of general usefulness in future drug discovery efforts within this target class.     

Unveiling the druggable RNA targets and small molecule therapeutics

The increasing appreciation for the crucial roles of RNAs in infectious and non-infectious human diseases makes them attractive therapeutic targets. Coding and non-coding RNAs frequently fold into complex conformations which, if effectively targeted, offer opportunities to therapeutically modulate numerous cellular processes, including those linked to undruggable protein targets. Despite the considerable skepticism as to whether RNAs can be targeted with small molecule therapeutics, overwhelming evidence suggests the challenges we are currently facing are not outside the realm of possibility. In this review, we highlight the most recent advances in molecular techniques that have sparked a revolution in understanding the RNA structure-to-function relationship. We bring attention to the application of these modern techniques to identify druggable RNA targets and to assess small molecule binding specificity. Finally, we discuss novel screening methodologies that support RNA drug discovery and present examples of therapeutically valuable RNA targets.     

Effect of LNA modifications on small molecule binding to nucleic acids

Locked nucleic acid (LNA) is a conformationally constrained DNA analogue that exhibits exceptionally high affinity for complementary DNA and RNA strands. The deoxyribose sugar is modified by a 2'-O, 4'-C oxymethylene bridge, which projects into the minor groove. In addition to changing the distribution of functional groups in the groove and the overall helical geometry relative to unmodified DNA, the bridge likely alters the hydration of the groove. Each of these factors will impact the ability of small molecules, proteins and other nucleic acids to recognize LNA-containing hybrids. This report describes the ability of several DNA-intercalating ligands and one minor groove binder to recognize LNA-DNA and LNA-RNA hybrid duplexes. Using UV-vis, fluorescence and circular dichroism spectroscopies, we find that the minor groove binder as well as the intercalators exhibit significantly lower affinity for LNA-containing duplexes. The lone exception is the alkaloid ellipticine, which intercalates into LNA-DNA and LNA-RNA duplexes with affinities comparable to unmodified DNA-DNA and RNA-DNA duplexes.     

Kinetics of small molecule inhibitor binding to p38 kinase.

p38 mitogen-activated protein kinase (MAPK) (p38/p38-alpha/CSBP2/RK) has been implicated in the regulation of many proinflammatory pathways. Because of this, it has received much attention as a potential drug target for controlling diseases such as rheumatoid arthritis, endotoxic shock, inflammatory bowel disease, osteoporosis, and many others. A number of small molecule inhibitors of this kinase have been described, and in this paper we have used surface plasmon resonance to directly measure and quantitate their binding to p38. Despite the relatively low molecular mass (approximately 400 Da) of these inhibitors, specific binding can be observed. For the two most potent inhibitors studied, SB 203580 and RWJ 67657, dissociation constants, K(d)'s, of 22 and 10 nm, respectively, were obtained. These values closely match the IC(5)0 values observed in a cell-based TNF alpha release assay implying that p38 plays a major role in TNF alpha release. The association and dissociation rates for the binding of these inhibitors to p38 have also been quantitated. SB 203580 and RWJ 67657 have very similar association rates of around 8 x 10(5) m(-1) x s(-1), and the differences in affinity are determined by different dissociation rates. The weaker binding compounds have dissociation rates similar to SB 203580, but the association rates vary by an order of magnitude or more. The direct measurement of compounds binding to p38 may help in understanding the difference between potency and efficacy for these inhibitors. This in turn may yield clues on how to develop better inhibitors.     

Affinity characterization-mass spectrometry methodology for quantitative analyses of small molecule protein binding in solution

Affinity characterization by mass spectrometry (AC–MS) is a novel LC–MS methodology for quantitative determination of small molecule ligand binding to macromolecules. Its most distinguishing feature is the direct determination of all three concentration terms of the equilibrium binding equation, i.e., (M), (L), and (ML), which denote the macromolecule, ligand, and the corresponding complex, respectively. Although it is possible to obtain the dissociation constant from a single mixing experiment, saturation analyses are still valuable for assessing the overall binding phenomenon based on an established formalism. In addition to providing the prerequisite dissociation constant and binding stoichiometry, the technique also provides valuable information about the actual solubility of both macromolecule and ligand upon dilution and mixing in binding buffers. The dissociation constants and binding mode for interactions of DNA primase and thymidylate synthetase (TS) with high and low affinity small molecule ligands were obtained using the AC–MS method. The data were consistent with the expected affinity of TS for these ligands based on dissociation constants determined by alternative thermal-denaturation techniques: TdF or TdCD, and also consistent enzyme inhibition constants reported in the literature. The validity of AC–MS was likewise extended to a larger set of soluble protein–ligand systems. It was established as a valuable resource for counter screen and structure–activity relationship studies in drug discovery, especially when other classical techniques could only provide ambiguous results.     

Discriminating small molecule DNA binding modes by single molecule force spectroscopy

Drugs may interact with double stranded DNA via a variety of binding modes, each mode giving rise to a specific pharmacological function. Here we demonstrate the ability of single molecule force spectroscopy to discriminate between different interaction modes by measuring the mechanical properties of DNA and their modulation upon the binding of small molecules. Due to the unique topology of double stranded DNA and due to its base pair stacking pattern, DNA undergoes several well-characterised structural transitions upon stretching. We show that small molecule binding markedly affects these transitions in ways characteristic to the binding mode and that these effects can be detected at the level of an individual molecule. The minor groove binder berenil, the crosslinker cisplatin and the intercalator ethidium bromide are compared.     

Application of an allosteric model to describe the interactions among retinol binding protein 4, transthyretin, and small molecule retinol binding protein 4 ligands

Retinol binding protein 4 (RBP4) is a serum protein that serves as the major transport protein for retinol (vitamin A). Recent reports suggest that elevated levels of RBP4 are associated with insulin resistance and that insulin sensitivity may be improved by reducing serum RBP4 levels. This can be accomplished by administration of small molecules, such as fenretinide, that compete with retinol for binding to RBP4 and disrupt the protein-protein interaction between RBP4 and transthyretin (TTR), another serum protein that protects RBP4 from renal clearance. We developed a fluorescence resonance energy transfer (FRET) assay that measures the interaction between RBP4 and TTR and can be used to determine the binding affinities of RBP4 ligands. We present an allosteric model that describes the pharmacology of interaction among RBP4, TTR, retinol, and fenretinide, and we show data that support the model. We show that retinol increases the affinity of RBP4 for TTR by a factor of 4 and determine the affinity constants of fenretinide and retinyl acetate. The assay may be useful for characterizing small molecule ligands that bind to RBP4 and disrupt its interaction with TTR. In addition, such a model could be used to describe other protein-protein interactions that are modulated by small molecules.     

A guest molecule-host cavity fitting algorithm to mine PDB for small molecule targets

Inhaled anesthetic molecule occupancy of a protein internal cavity depends in part on the volumes of the guest molecule and the host site. Current algorithms to determine volume and surface area of cavities in proteins whose structures have been determined and cataloged make no allowance for shape or small degrees of shape adjustment to accommodate a guest. We developed an algorithm to determine spheroid dimensions matching cavity volume and surface area and applied it to screen the cavities of 6,658 nonredundant structures stored in the Protein Data Bank (PDB) for potential targets of halothane (2-bromo-2-chloro-1,1,1-trifluoroethane). Our algorithm determined sizes of prolate and oblate spheroids matching dimensions of each cavity found. If those spheroids could accommodate halothane (radius 2.91 A) as a guest, we determined the packing coefficient. 394,766 total cavities were identified. Of 58,681 cavities satisfying the fit criteria for halothane, 11,902 cavities had packing coefficients in the range of 0.46-0.64. This represents 20.3% of cavities large enough to hold halothane, 3.0% of all cavities processed, and found in 2,432 protein structures. Our algorithm incorporates shape dependence to screen guest-host relationships for potential small molecule occupancy of protein cavities. Proteins with large numbers of such cavities are more likely to be functionally altered by halothane.     

A Biacore biosensor method for detailed kinetic binding analysis of small molecule inhibitors of p38alpha mitogen-activated protein kinase

Protein kinases are emerging as one of the most intensely studied classes of enzymes as their central roles in physiologically and clinically important cellular signaling events become more clearly understood. We report here the development of a real-time, label-free method to study protein kinase inhibitor binding kinetics using surface plasmon resonance-based biomolecular interaction analysis (Biacore). Utilizing p38alpha mitogen-activated protein kinase as a model system, we studied the binding properties of two known small molecule p38alpha inhibitors (SB-203580 and SKF-86002). Direct coupling of p38alpha to the biosensor surface in the presence of a reversible structure-stabilizing ligand (SB-203580) consistently produced greater than 90% active protein on the biosensor surface. The dissociation and kinetic constants derived using this Biacore method are in excellent agreement with values determined by other methods. Additionally, we extend the method to study the thermodynamics of small molecule binding to p38alpha and derive a detailed thermodynamic reaction pathway for SB-203580. The Biacore method reported here provides an efficient way to directly and reproducibly examine dissociation constants, kinetics, and thermodynamics for small molecules binding to p38alpha and possibly other protein kinases. Immobilization in the presence of a stabilizing ligand may further represent a broadly applicable paradigm for creation of highly active biosensor surfaces.     

Knowledge-based annotation of small molecule binding sites in proteins

Background  

The study of protein-small molecule interactions is vital for understanding protein function and for practical applications in drug discovery. To benefit from the rapidly increasing structural data, it is essential to improve the tools that enable large scale binding site prediction with greater emphasis on their biological validity.