Trypanosoma cruzi ribosomal P proteins, P2? and P0, induce high levels of antibodies in patients with chronic Chagas' disease Cardiomyopathy (CCC). It is well known that these antibodies alter the beating rate of cardiomyocytes and provoke apoptosis by their interaction with ?1-adrenergic and M2-muscarinic cardiac receptors. Based on these findings, we decided to study the cellular immune response to these proteins in CCC patients compared to non-infected individuals.
Human obesity has been linked to genetic factors and single nucleotide polymorphisms (SNPs). Melanocortin-4 receptor (MC4R) SNPs have been associated with up to 6% frequency in morbidly obese children and adults. A potential therapy for individuals possessing such genetic modifications is the identification of molecules that can restore proper receptor signaling and function. These compounds could serve as personalized medications improving quality of life issues as well as alleviating diseases symptoms associated with obesity including type 2 diabetes. Several hMC4 SNP receptors have been pharmacologically characterized in vitro to have a decreased, or a lack of response, to endogenous agonists such as ?-, ?-, and ?2-melanocyte stimulating hormones (MSH) and adrenocorticotropin hormone (ACTH). Herein we report the use of a mixture based positional scanning combinatorial tetrapeptide library to discover molecules with nM full agonist potency and efficacy to the L106P, I69T, I102S, A219V, C271Y, and C271R hMC4Rs. The most potent compounds at all these hMC4R SNPs include Ac-His-(pI)DPhe-Tic-(pNO2)DPhe-NH2, Ac-His-(pCl)DPhe-Tic-(pNO2)DPhe-NH2, Ac-His-(pCl)DPhe-Arg-(pI)Phe-NH2, and Ac-Arg-(pCl)DPhe-Tic-(pNO2)DPhe-NH2, revealing new ligand pharmacophore models for melanocortin receptor drug design strategies.
Nicotine binds to nicotinic acetylcholine receptors (nAChR), which can exist as many different subtypes. The ?4?2 nAChR is the most prevalent subtype in the brain and possesses the most evidence linking it to nicotine seeking behavior. Herein we report the use of mixture based combinatorial libraries for the rapid discovery of a series of ?4?2 nAChR selective compounds. Further chemistry optimization provided compound 301, which was characterized as a selective ?4?2 nAChR antagonist. This compound displayed no agonist activity but blocked nicotine-induced depolarization of HEK cells with an IC50 of approximately 430 nM. 301 demonstrated nearly 500-fold selectivity for binding and 40-fold functional selectivity for ?4?2 over ?3?4 nAChR. In total over 5 million compounds were assessed through the use of just 170 samples in order to identify a series of structural analogues suitable for future optimization toward the goal of developing clinically relevant smoking cessation medications.
Structure-property relationships and structure-activity relationships play an important role in many research areas, such as medicinal chemistry and drug discovery. Such methods, however, have focused on providing post-hoc descriptions of such relationships based on known data. The ability for these descriptions to remain relevant when considering compounds of unknown activity, and thus the prediction of activity and property landscapes using existing data, remains little explored. In this study, we present a novel method of evaluating the ability of a compound comparison methodology to provide accurate information about a set of unknown compounds and also explore the ability of these predicted activity landscapes to prioritize active compounds over inactive. These methods are applied to three distinct and diverse sets of compounds, each with activity data for multiple targets, for a total of eight target-compound set pairs. Six methodologically distinct compound comparison methods were evaluated. We show that overall, all compound comparison methods provided an improvement in structure-activity relationship prediction over random and were able to prioritize compounds in a superior manner to random sampling, but the degree of success and therefore applicability varied markedly.
Chronic beryllium disease (CBD) is a granulomatous disorder characterized by an influx of beryllium (Be)-specific CD4? T cells into the lung. The vast majority of these T cells recognize Be in an HLA-DP–restricted manner, and peptide is required for T cell recognition. However, the peptides that stimulate Be-specific T cells are unknown. Using positional scanning libraries and fibroblasts expressing HLA-DP2, the most prevalent HLA-DP molecule linked to disease, we identified mimotopes and endogenous self-peptides that bind to MHCII and Be, forming a complex recognized by pathogenic CD4? T cells in CBD. These peptides possess aspartic and glutamic acid residues at p4 and p7, respectively, that surround the putative Be-binding site and cooperate with HLA-DP2 in Be coordination. Endogenous plexin A peptides and proteins, which share the core motif and are expressed in lung, also stimulate these TCRs. Be-loaded HLA-DP2–mimotope and HLA-DP2–plexin A4 tetramers detected high frequencies of CD4? T cells specific for these ligands in all HLADP2+ CBD patients tested. Thus, our findings identify the first ligand for a CD4? T cell involved in metal-induced hypersensitivity and suggest a unique role of these peptides in metal ion coordination and the generation of a common antigen specificity in CBD.
The formylpeptide receptor (FPR1) and formylpeptide-like 1 receptor (FPR2) are G protein-coupled receptors that are linked to acute inflammatory responses, malignant glioma stem cell metastasis, and chronic inflammation. Although several N-formyl peptides are known to bind to these receptors, more selective small-molecule, high-affinity ligands are needed for a better understanding of the physiologic roles played by these receptors. High-throughput assays using mixture-based combinatorial libraries represent a unique, highly efficient approach for rapid data acquisition and ligand identification. We report the superiority of this approach in the context of the simultaneous screening of a diverse set of mixture-based small-molecule libraries. We used a single cross-reactive peptide ligand for a duplex flow cytometric screen of FPR1 and FPR2 in color-coded cell lines. Screening 37 different mixture-based combinatorial libraries totaling more than five million small molecules (contained in 5,261 mixture samples) resulted in seven libraries that significantly inhibited activity at the receptors. Using positional scanning deconvolution, selective high-affinity (low nM K(i)) individual compounds were identified from two separate libraries, namely, pyrrolidine bis-diketopiperazine and polyphenyl urea. The most active individual compounds were characterized for their functional activities as agonists or antagonists with the most potent FPR1 agonist and FPR2 antagonist identified to date with an EC?? of 131 nM (4 nM K(i)) and an IC?? of 81 nM (1 nM K(i)), respectively, in intracellular Ca²? response determinations. Comparative analyses of other previous screening approaches clearly illustrate the efficiency of identifying receptor selective, individual compounds from mixture-based combinatorial libraries.
We present a general approach to describe the structure-activity relationships (SAR) of combinatorial data sets with activity for two biological endpoints with emphasis on the rapid identification of substitutions that have a large impact on activity and selectivity. The approach uses dual-activity difference (DAD) maps that represent a visual and quantitative analysis of all pairwise comparisons of one, two, or more substitutions around a molecular template. Scanning the SAR of data sets using DAD maps allows the visual and quantitative identification of activity switches defined as specific substitutions that have an opposite effect on the activity of the compounds against two targets. The approach also rapidly identifies single- and double-target R-cliffs, i.e., compounds where a single or double substitution around the central scaffold dramatically modifies the activity for one or two targets, respectively. The approach introduced in this report can be applied to any analogue series with two biological activity endpoints. To illustrate the approach, we discuss the SAR of 106 pyrrolidine bis-diketopiperazines tested against two formylpeptide receptors obtained from positional scanning deconvolution methods of mixture-based libraries.
In the past 20 years, synthetic combinatorial methods have fundamentally advanced the ability to synthesize and screen large numbers of compounds for drug discovery and basic research. Mixture-based libraries and positional scanning deconvolution combine two approaches for the rapid identification of specific scaffolds and active ligands. Here we present a quantitative assessment of the screening of 32 positional scanning libraries in the identification of highly specific and selective ligands for two formylpeptide receptors. We also compare and contrast two mixture-based library approaches using a mathematical model to facilitate the selection of active scaffolds and libraries to be pursued for further evaluation. The flexibility demonstrated in the differently formatted mixture-based libraries allows for their screening in a wide range of assays.
The threat of bioterrorism with smallpox and the broad use of vaccinia vectors for other vaccines have led to the resurgence in the study of vaccinia immunological memory. The importance of the role of CD4+ T cells in the control of vaccinia infection is well known. However, more CD8+ than CD4+ T cell epitopes recognized by human subjects immunized with vaccinia virus have been reported. This could be, in part, due to the fact that most of the studies that have identified human CD4+ specific protein-derived fragments or peptides have used IFN-? production to evaluate vaccinia specific T cell responses. Based on these findings, we reasoned that analyzing a large panel of cytokines would permit us to generate a more complete analysis of the CD4 T cell responses. The results presented provide clear evidence that TNF-? is an excellent readout of vaccinia specificity and that other cytokines such as GM-CSF can be used to evaluate the reactivity of CD4+ T cells in response to vaccinia antigens. Furthermore, using these cytokines as readout of vaccinia specificity, we present the identification of novel peptides from immunoprevalent vaccinia proteins recognized by CD4+ T cells derived from smallpox vaccinated human subjects. In conclusion, we describe a "T cell-driven" methodology that can be implemented to determine the specificity of the T cell response upon vaccination or infection. Together, the single pathogen in vitro stimulation, the selection of CD4+ T cells specific to the pathogen by limiting dilution, the evaluation of pathogen specificity by detecting multiple cytokines, and the screening of the clones with synthetic combinatorial libraries, constitutes a novel and valuable approach for the elucidation of human CD4+ T cell specificity in response to large pathogens.
We report consensus Structure-Activity Similarity (SAS) maps that address the dependence of activity landscapes on molecular representation. As a case study, we characterized the activity landscape of 54 compounds with activities against human cathepsin B (hCatB), human cathepsin L (hCatL), and Trypanosoma brucei cathepsin B (TbCatB). Starting from an initial set of 28 descriptors we selected ten representations that capture different aspects of the chemical structures. These included four 2D (MACCS keys, GpiDAPH3, pairwise, and radial fingerprints) and six 3D (4p and piDAPH4 fingerprints with each including three conformers) representations. Multiple conformers are used for the first time in consensus activity landscape modeling. The results emphasize the feasibility of identifying consensus data points that are consistently formed in different reference spaces generated with several fingerprint models, including multiple 3D conformers. Consensus data points are not meant to eliminate data, disregarding, for example, "true" activity cliffs that are not identified by some molecular representations. Instead, consensus models are designed to prioritize the SAR analysis of activity cliffs and other consistent regions in the activity landscape that are captured by several molecular representations. Systematic description of the SARs of two targets give rise to the identification of pairs of compounds located in the same region of the activity landscape of hCatL and TbCatB suggesting similar mechanisms of action for the pairs involved. We also explored the relationship between property similarity and activity similarity and found that property similarities are suitable to characterize SARs. We also introduce the concept of structure-property-activity (SPA) similarity in SAR studies.
The use of the harmonic mean model for predicting the activities of a given mixture and its constituents has not previously been explored in the context of combinatorial libraries and drug discovery. Herein, the analyses of historical data confirm the harmonic mean as an accurate predictor of mixture activity. The implications of these results are discussed.
Parasitic infections caused by the protozoa Trichomonas vaginalis and Giardia intestinalis still represent a major problem in developing countries. Despite the fact that benzimidazoles are promising compounds with activity against both protozoa, systematic studies to characterize and compare their structure-activity relationships (SAR) are limited. Herein, we report a systematic characterization of the SAR of 32 benzimidazoles with activity against T. vaginalis and G. intestinalis. The analysis was based on pairwise comparisons of the activity similarity and molecular similarity using different molecular representations. Radial, MACCS keys, TGD and piDAPH3 fingerprints were used to develop consensus models of the landscape. The landscapes contained continuous regions and activity cliffs. Two deep consensus activity cliffs and several pairs of compounds in smooth regions of the SAR were identified in the landscape of T. vaginalis. In contrast, a number of apparent and shallow cliffs were found for G. intestinalis. Several compounds active for both parasites showed similar SAR suggesting a common mechanism of action. We also identified pairs of structurally similar molecules with dramatic changes in selectivity. Results suggested that while substitution at position 2 on the benzimidazole moiety plays an important role in increasing the potency against both parasites, substitutions at positions 4-7 could influence selectivity. This study represents a first step towards the systematic characterization of the antiprotozoal activity landscape of benzimidazoles, and has direct implications in the future development of other types of quantitative models. The landscape of larger data sets with other biological endpoints can be analyzed using the general approaches used in this work.
A novel method for the direct evaluation of the equimolarity of the compounds contained in a mixture is presented. We applied the method toward calculating isokinetic ratios for the reaction between the amine termini of a resin bound peptide fragment and a sulfonyl chloride to produce equal molar mixtures of sulfonamides. The results of this study and the application of the method to the synthesis of two new positional scanning synthetic combinatorial libraries (PS-SCL) are discussed.
Related JoVE Video
Journal of Visualized Experiments
What is Visualize?
JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.
How does it work?
We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.
Video X seems to be unrelated to Abstract Y...
In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.