Targeting ligand–receptor interactions for development of cancer therapeutics

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Quantitative affinity electrophoresis of RNA–small molecule interactions by cross-linking the ligand to acrylamide

We show that the affinity electrophoresis analysis of RNA–small molecule interactions can be made quantifiable by cross-linking the ligand to the gel matrix. Using an RNA–aminoglycoside model system to verify our method, we attached an acryloyl chloride molecule to the aminoglycosides paromomycin and neomycin B to synthesize an acrylamide–aminoglycoside monomer. This molecule was then used as a component in gel polymerization for affinity electrophoresis, covalently attaching an aminoglycoside molecule to the gel matrix. To test RNA binding to the cross-linked aminoglycosides, we used the aminoglycoside binding RNA molecule derived from thymidylate synthase messenger RNA (mRNA) that contains a C–C mismatch. Binding is indicated by the difference in RNA mobility between gels with cross-linked ligand, with ligand embedded during polymerization, and with no ligand present. Critically, the predicted straight line relationship between the reciprocal of the relative migration of the RNA and the ligand concentration is obtained when using cross-linked aminoglycosides, whereas a straight line is not obtained using embedded aminoglycosides. Average apparent dissociation constants are determined from the slope of the line from these plots. This method allows an easy quantitative comparison between different nucleic acid molecules for a small molecule ligand.     

Trimethylsilyl tag for probing protein–ligand interactions by NMR

Protein–ligand titrations can readily be monitored with a trimethylsilyl (TMS) tag. Owing to the intensity, narrow line shape and unique chemical shift of a TMS group, dissociation constants can be determined from straightforward 1D ¹H-NMR spectra not only in the fast but also in the slow exchange limit. The tag is easily attached to cysteine residues and a sensitive reporter of ligand binding also at sites where it does not interfere with ligand binding or catalytic efficiency of the target protein. Its utility is demonstrated for the Zika virus NS2B–NS3 protease and the human prolyl isomerase FK506 binding protein.     

LigandRNA: computational predictor of RNA–ligand interactions

RNA molecules have recently become attractive as potential drug targets due to the increased awareness of their importance in key biological processes. The increase of the number of experimentally determined RNA 3D structures enabled structure-based searches for small molecules that can specifically bind to defined sites in RNA molecules, thereby blocking or otherwise modulating their function. However, as of yet, computational methods for structure-based docking of small molecule ligands to RNA molecules are not as well established as analogous methods for protein-ligand docking. This motivated us to create LigandRNA, a scoring function for the prediction of RNA–small molecule interactions. Our method employs a grid-based algorithm and a knowledge-based potential derived from ligand-binding sites in the experimentally solved RNA–ligand complexes. As an input, LigandRNA takes an RNA receptor file and a file with ligand poses. As an output, it returns a ranking of the poses according to their score. The predictive power of LigandRNA favorably compares to five other publicly available methods. We found that the combination of LigandRNA and Dock6 into a “meta-predictor” leads to further improvement in the identification of near-native ligand poses. The LigandRNA program is available free of charge as a web server at http://ligandrna.genesilico.pl.     

A simple method for monitoring protein–DNA interactions

A simple, efficient and cheap method is reported for monitoring interactions between single stranded desoxyribonucleic acids and proteins, using fluorescence spectroscopy and complexes of 5′-dye–DNA conjugates with bovine serum albumin as probes. In the presence of a single stranded DNA-binding protein the complexes with bovine serum albumin are disrupted, which results in a reduction of fluorescence intensity.     

Baculovirus display for discovery of low-affinity extracellular receptor–ligand interactions using protein microarrays

When used in conjunction with multivalent protein probes, protein microarrays offer a robust technology for discovery of low-affinity extracellular protein–protein interactions. Probes for receptor-matching screens generally consist of purified extracellular domains fused to affinity tags. Given that approximately two-thirds of extracellular proteins are transmembrane domain-containing proteins, it would be desirable to develop a system to express and display probe receptors in a native-like membrane environment. Toward this end, we evaluated baculovirus display as a platform for generating multivalent probes for protein microarray screens. Virion particles were generated displaying single-transmembrane domain receptors BTLA, CD200, and EFNB2, representing a range of affinities for their interacting partners. Virions directly labeled with Cy5 fluorophore were screened against a microarray containing more than 600 extracellular proteins, and the results were compared with data derived from soluble Fc protein or probe-coated protein A microbeads. An optimized protocol employing a blocking step with a nonrelated probe-expressing control baculovirus allowed identification of the expected interactions with a signal-to-noise ratio similar to or higher than those obtained with the other formats. Our results demonstrate that baculovirus display is suitable for detection of high- and low-affinity extracellular protein–protein interactions on protein microarrays. This platform eliminates the need for protein purification and provides a native-like lipid environment for membrane-associated receptors.     

Evaluation of protein–ligand affinity prediction using steered molecular dynamics simulations

In computational drug design, ranking a series of compound analogs in a manner that is consistent with experimental affinities remains a challenge. In this study, we evaluated the prediction of protein–ligand binding affinities using steered molecular dynamics simulations. First, we investigated the appropriate conditions for accurate predictions in these simulations. A conic harmonic restraint was applied to the system for efficient sampling of work values on the ligand unbinding pathway. We found that pulling velocity significantly influenced affinity predictions, but that the number of collectable trajectories was less influential. We identified the appropriate pulling velocity and collectable trajectories for binding affinity predictions as 1.25 Å/ns and 100, respectively, and these parameters were used to evaluate three target proteins (FK506 binding protein, trypsin, and cyclin-dependent kinase 2). For these proteins using our parameters, the accuracy of affinity prediction was higher and more stable when Jarzynski’s equality was employed compared with the second-order cumulant expansion equation of Jarzynski’s equality. Our results showed that steered molecular dynamics simulations are effective for predicting the rank order of ligands; thus, they are a potential tool for compound selection in hit-to-lead and lead optimization processes.     

Validation of a new restraint docking method for solution structure determinations of protein–ligand complexes

A new method is proposed for docking ligands into proteins in cases where an NMR-determined solution structure of a related complex is available. The method uses a set of experimentally determined values for protein–ligand, ligand–ligand, and protein–protein restraints for residues in or near to the binding site, combined with a set of protein–protein restraints involving all the other residues which is taken from the list of restraints previously used to generate the reference structure of a related complex. This approach differs from ordinary docking methods where the calculation uses fixed atomic coordinates from the reference structure rather than the restraints used to determine the reference structure. The binding site residues influenced by replacing the reference ligand by the new ligand were determined by monitoring differences in ¹H chemical shifts. The method has been validated by showing the excellent agreement between structures of L. casei dihydrofolate reductase.trimetrexate calculated by conventional methods using a full experimentally determined set of restraints and those using this new restraint docking method based on an L. casei dihydrofolate reductase.methotrexate reference structure.     

Development of tryptophan-modified human serum albumin columns for site-specific studies of drug–protein interactions by high-performance affinity chromatography

Human serum albumin (HSA) is one of the main proteins involved in the binding of drugs and small solutes in blood or serum. This study examined the changes in chromatographic properties that occur for immobilized HSA following the chemical modification of HSA's lone tryptophan residue (Trp-214). Trp-214 was reacted with o-nitrophenylsulfenyl chloride, followed by immobilization of the modified protein and normal HSA onto separate silica-based HPLC supports. The binding properties of the modified and normal HSA were then analyzed and compared by using frontal analysis and zonal elution experiments employing R/S-warfarin and l-tryptophan as probe compounds for the warfarin and indole binding regions of HSA. The modified HSA was found to have the same number of binding sites as normal HSA for R-warfarin and l-tryptophan but lower association equilibrium constants for these test solutes. Zonal elution studies with R- and S-warfarin on the modified HSA column demonstrated the importance of Trp-214 in determining the stereoselective binding of HSA for these agents. These studies also indicated that tryptophan modification can alter HSA-based separations for chiral solutes.     

Mass spectrometry-based approaches to protein–ligand interactions

One of the greatest current challenges in proteomics is to develop an understanding of cellular communication and regulation processes, most of which involve noncovalent interactions of proteins with various binding partners. Mass spectrometry plays an important role in all aspects of these research efforts. This article provides a survey of mass spectrometry-based approaches for exploring protein–ligand interactions. A wide array of techniques is available, and the choice of method depends on the specific problem at hand. For example, the high-throughput screening of compound libraries for binding to a specific receptor requires different approaches than structural studies on multiprotein complexes. This review is directed to readers wishing to obtain a concise yet comprehensive overview of existing experimental techniques. Specific emphasis is placed on emerging methods that have been developed within the last few years.     

Modeling of cell adhesion and deformation mediated by receptor–ligand interactions

The current work is devoted to studying adhesion and deformation of biological cells mediated by receptors and ligands in order to enhance the existing models. Due to the sufficient in-plane continuity and fluidity of the phospholipid molecules, an isotropic continuum fluid membrane is proposed for modeling the cell membrane. The developed constitutive model accounts for the influence of the presence of receptors on the deformation and adhesion of the cell membrane through the introduction of spontaneous area dilation. Motivated by physics, a nonlinear receptor–ligand binding force is introduced based on charge-induced dipole interaction. Diffusion of the receptors on the membrane is governed by the receptor–ligand interaction via Fick’s Law and receptor-ligand interaction. The developed model is then applied to study the deformation and adhesion of a biological cell. The proposed model is used to study the role of the material, binding, spontaneous area dilation and environmental properties on the deformation and adhesion of the cell.     

Detection of protein–ligand interactions by NMR using reductive methylation of lysine residues

We show that reductive methylation of proteins can be used for highly sensitive NMR identification of conformational changes induced by metal- and small molecule binding, as well as protein-protein interactions. Reductive methylation of proteins introduces two (13)C-methyl groups on each lysine in the protein of interest. This method works well even when the lysines are not actively involved in the interaction, due to changes in the microenvironments of lysine residues. Most lysine residues are located on the protein exterior, and the exposed (13)C-methyl groups may exhibit rapid localized motions. These motions could be faster than the tumbling rate of the molecule as a whole. Thus, this technique has great potential in the study of large molecular weight systems which are currently beyond the scope of conventional NMR methods.     

NLDB: a database for 3D protein–ligand interactions in enzymatic reactions

NLDB (Natural Ligand DataBase; URL: http://nldb.hgc.jp) is a database of automatically collected and predicted 3D protein–ligand interactions for the enzymatic reactions of metabolic pathways registered in KEGG. Structural information about these reactions is important for studying the molecular functions of enzymes, however a large number of the 3D interactions are still unknown. Therefore, in order to complement such missing information, we predicted protein–ligand complex structures, and constructed a database of the 3D interactions in reactions. NLDB provides three different types of data resources; the natural complexes are experimentally determined protein–ligand complex structures in PDB, the analog complexes are predicted based on known protein structures in a complex with a similar ligand, and the ab initio complexes are predicted by docking simulations. In addition, NLDB shows the known polymorphisms found in human genome on protein structures. The database has a flexible search function based on various types of keywords, and an enrichment analysis function based on a set of KEGG compound IDs. NLDB will be a valuable resource for experimental biologists studying protein–ligand interactions in specific reactions, and for theoretical researchers wishing to undertake more precise simulations of interactions.     

Urinary analyte screening: a noninvasive detection method for Down syndrome?

Prenatal screening for Down syndrome using maternal serum markers achieves detection rates of 60-80% with a 5% false positive rate. Improvement in the accuracy of screening, as well as its ease and safety, will increase the use of such tests. The most effective of the current serum markers is human chorionic gonadotropin (hCG). Studies on beta core fragment (beta CF), the major urinary metabolite of hCG, have indicated that screening with beta CF and other markers measured in maternal urine might improve the detection of Down syndrome and provide a less expensive and simpler test. However, recent results have been unusually variable. Although it has great potential, the true clinical value of maternal urine screening to detect Down syndrome still remains to be determined.     

Surface plasmon resonance analysis of antimicrobial peptide–membrane interactions: affinity & mechanism of action

Antimicrobial peptides are being increasingly recognised as potential candidates for antibacterial drugs in the face of the rapidly emerging bacterial resistance to conventional antibiotics in recent years. However, a precise understanding of the relationship between antimicrobial peptide structure and their cytolytic function in a range of organisms is still lacking. This is a result of the complex nature of the interactions of antimicrobial peptides with the cell membrane, the mechanism of which can vary considerably between different classes of antimicrobial peptides. A wide range of biophysical techniques have been used to study the influence of a number of peptide and membrane properties on the cytolytic activity of these peptides model membrane systems. Until recently, however, very few studies had reported measurements of the affinity of antimicrobial peptides for different membrane systems mainly due to the difficulty in obtaining this information. Surface plasmon resonance (SPR) spectroscopy has recently been applied to the study of biomembrane-based systems which has allowed a real-time analysis of binding affinity and kinetics. This mini review provides an overview of the recent applications that demonstrate the potential of SPR to study the membrane interactions of antimicrobial peptides.