Discovery of Nanomolar Melanocortin-3 Receptor (MC3R)-Selective Small Molecule Pyrrolidine Bis-Cyclic Guanidine Agonist Compounds Via a High-Throughput "Unbiased" Screening Campaign.

The central melanocortin-3 and melanocortin-4 receptors (MC3R, MC4R) are key regulators of body weight and energy homeostasis. Herein, the discovery and characterization of first-in-class small molecule melanocortin agonists with selectivity for the melanocortin-3 receptor over the melanocortin-4 receptor are reported. Identified via "unbiased" mixture-based high-throughput screening approaches, pharmacological evaluation of these pyrrolidine bis-cyclic guanidines resulted in nanomolar agonist activity at the melanocortin-3 receptor. The pharmacological profiles at the remaining melanocortin receptor subtypes tested indicated similar agonist potencies at both the melanocortin-1 and melanocortin-5 receptors and antagonist or micromolar agonist activities at the melanocortin-4 receptor. This group of small molecules represents a new area of chemical space for the melanocortin receptors with mixed receptor pharmacology profiles that may serve as novel lead compounds to modulate states of dysregulated energy balance.

Discovery of Mixed Pharmacology Melanocortin-3 Agonists and Melanocortin-4 Receptor Tetrapeptide Antagonist Compounds (TACOs) Based on the Sequence Ac-Xaa1-Arg-(pI)DPhe-Xaa4-NH2.

The centrally expressed melanocortin-3 and -4 receptors (MC3R/MC4R) have been studied as possible targets for weight management therapies, with a preponderance of studies focusing on the MC4R. Herein, a novel tetrapeptide scaffold [Ac-Xaa1-Arg-(pI)DPhe-Xaa4-NH2] is reported. The scaffold was derived from results obtained from a MC3R mixture-based positional scanning campaign. From these results, a set of 48 tetrapeptides were designed and pharmacologically characterized at the mouse melanocortin-1, -3, -4, and -5 receptors. This resulted in the serendipitous discovery of nine compounds that were MC3R agonists (EC50 < 1000 nM) and MC4R antagonists (5.7 < pA2 < 7.8). The three most potent MC3R agonists, 18 [Ac-Arg-Arg-(pI)DPhe-Tic-NH2], 1 [Ac-His-Arg-(pI)DPhe-Tic-NH2], and 41 [Ac-Arg-Arg-(pI)DPhe-DNal(2')-NH2] were more potent (EC50 < 73 nM) than the melanocortin tetrapeptide Ac-His-DPhe-Arg-Trp-NH2. This template contains a sequentially reversed "Arg-(pI)DPhe" motif with respect to the classical "Phe-Arg" melanocortin signaling motif, which results in pharmacology that is first-in-class for the central melanocortin receptors.

Identification of tetrapeptides from a mixture based positional scanning library that can restore nM full agonist function of the L106P, I69T, I102S, A219V, C271Y, and C271R human melanocortin-4 polymorphic receptors (hMC4Rs).

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 α-, ß-, and γ2-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.

The mathematics of a successful deconvolution: a quantitative assessment of mixture-based combinatorial libraries screened against two formylpeptide receptors.

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.

Selective agonists and antagonists of formylpeptide receptors: duplex flow cytometry and mixture-based positional scanning libraries.

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 EC50 of 131 nM (4 nM K(i)) and an IC50 of 81 nM (1 nM K(i)), respectively, in intracellular Ca²âº response determinations. Comparative analyses of other previous screening approaches clearly illustrate the efficiency of identifying receptor selective, individual compounds from mixture-based combinatorial libraries.

Rapid scanning structure-activity relationships in combinatorial data sets: identification of activity switches.

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.

Identification of a small molecule that selectively inhibits mouse PC2 over mouse PC1/3: a computational and experimental study.

The calcium-dependent serine endoproteases prohormone convertase 1/3 (PC1/3) and prohormone convertase 2 (PC2) play important roles in the homeostatic regulation of blood glucose levels, hence implicated in diabetes mellitus. Specifically, the absence of PC2 has been associated with chronic hypoglycemia. Since there is a reasonably good conservation of the catalytic domain between species translation of inhibitory effects is likely. In fact, similar results have been found using both mouse and human recombinant enzymes. Here, we employed computational structure-based approaches to screen 14,400 compounds from the Maybridge small molecule library towards mouse PC2. Our most remarkable finding was the identification of a potent and selective PC2 inhibitor. Kinetic data showed the compound to be an allosteric inhibitor. The compound identified is one of the few reported selective, small-molecule inhibitors of PC2. In addition, this new PC2 inhibitor is structurally different and of smaller size than those reported previously. This is advantageous for future studies where structural analogues can be built upon.

The Multi-Leu peptide inhibitor discriminates between PACE4 and furin and exhibits antiproliferative effects on prostate cancer cells.

The proprotein convertases (PCs) play an important role in protein precursor activation through processing at paired basic residues. However, significant substrate cleavage redundancy has been reported between PCs. The question remains whether specific PC inhibitors can be designed. This study describes the identification of the sequence LLLLRVKR, named Multi-Leu (ML)-peptide, that displayed a 20-fold selectivity on PACE4 over furin, two enzymes with similar structural characteristics. We have previously demonstrated that PACE4 plays an important role in prostate cancer and could be a druggable target. The present study demonstrates that the ML-peptide significantly reduced the proliferation of DU145 and LNCaP prostate cancer-derived cell lines and induced G0/G1 cell cycle arrest. However, the ML-peptide must enter the cell to inhibit proliferation. It is concluded that peptide-based inhibitors can yield specific PC inhibitors and that the ML-peptide is an important lead compound that could potentially have applications in prostate cancer.

Identification of B cell and T cell epitopes using synthetic peptide combinatorial libraries.

This unit presents a combinatorial library method that consists of the synthesis and screening of mixture-based synthetic combinatorial libraries of peptide molecules. The protocols employ peptide libraries to identify peptides recognized by MAbs and T cells. The first protocol uses a positional scanning peptide library made up of hexapeptides to identify antigenic determinants recognized by MAbs. The 120 mixtures in the hexapeptide library are tested for their inhibitory activity in a competitive ELISA. The second protocol uses a decapeptide library to identify T cell peptide ligands. The 200 mixtures of the decapeptide library are tested for their ability to induce T cell activation. Support protocols cover optimization of the assay conditions for each MAb or T cell, to achieve the best level of sensitivity and reproducibility, and preparation of a hexapeptide library, along with deconvolution approaches.

GM-CSF production allows the identification of immunoprevalent antigens recognized by human CD4+ T cells following smallpox vaccination.

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-γ 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-α 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.

Inhibitor screening of proprotein convertases using positional scanning libraries.

Proprotein convertases represent an important class of biosynthetic enzymes that are increasingly viewed as targets for therapeutic approaches to infection, cancer, and potentially endocrine disorders. The identification of potent inhibitors can be accomplished by screening synthetic combinatorial libraries containing thousands of small molecules to millions of peptides. In this chapter, the screening of positional scanning libraries is described for the identification of PC1/3 and PC2 inhibitors.

Use and implications of the harmonic mean model on mixtures for basic research and drug discovery.

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.

Integrating computational and mixture-based screening of combinatorial libraries.

Mixture-based synthetic combinatorial library (MB-SCL) screening is a well-established experimental approach for rapidly retrieving structure-activity relationships (SAR) and identifying hits. Virtual screening is also a powerful approach that is increasingly being used in drug discovery programs and has a growing number of successful applications. However, limited efforts have been made to integrate both techniques. To this end, we combined experimental data from a MB-SCL of bicyclic guanidines screened against the κ-opioid receptor and molecular similarity methods. The activity data and similarity analyses were integrated in a biometric analysis-similarity map. Such a map allows the molecules to be categorized as actives, activity cliffs, low similarity to the reference compounds, or missed hits. A compound with IC(50) = 309 nM was found in the "missed hits" region, showing that active compounds can be retrieved from a MS-SCL via computational approaches. The strategy presented in this work is general and is envisioned as a general-purpose approach that can be applied to other MB-SCLs.

Identification, structure-activity relationships and molecular modeling of potent triamine and piperazine opioid ligands.

Opioid receptors are important targets for pain management. Here, we report the synthesis and biological evaluation of three positional scanning combinatorial libraries, consisting of linear triamines and piperazines. A highly potent (14 nM) and selective (IC(50(mu))/IC(50(kappa))=71; IC(50(delta))/IC(50(kappa))=714) triamine for the kappa-opioid receptor was found. In addition, non-selective mu-kappa binders were obtained, with binding affinities of 54 nM and 22 nM for mu- and kappa-opioid receptors, respectively. Structure-activity relationships of each subset are described. 3D molecular alignments based on shape similarity to internal and external query molecules were carried out. For the combinatorial chemistry dataset studied here a 1.3 similarity cut-off value was observed to be efficient in the rocs-based alignment method. Interactions from the overlays analyzed in the binding sites of homology models of the receptors revealed specific substitution patterns for enhancing binding affinity in the piperazine series. Pharmacophore modeling of the compounds found from the three combinatorial libraries was also performed. The pharmacophore model indicated that the important feature for receptor binding activity with the mu-receptor was the presence of at least one hydrogen bond acceptor and one aromatic hydrophobic group. Whereas for the kappa-receptor two binding modes emerged with one set of compounds employing the hydrogen bond acceptor and aromatic hydrophobic group, and a second set possibly via interactions with the receptor by hydrophobic and ionic salt-bridges.

Synthetic small-molecule prohormone convertase 2 inhibitors.

The proprotein convertases are believed to be responsible for the proteolytic maturation of a large number of peptide hormone precursors. Although potent furin inhibitors have been identified, thus far, no small-molecule prohormone convertase 1/3 or prohormone convertase 2 (PC2) inhibitors have been described. After screening 38 small-molecule positional scanning libraries against recombinant mouse PC2, two promising chemical scaffolds were identified: bicyclic guanidines, and pyrrolidine bis-piperazines. A set of individual compounds was designed from each library and tested against PC2. Pyrrolidine bis-piperazines were irreversible, time-dependent inhibitors of PC2, exhibiting noncompetitive inhibition kinetics; the most potent inhibitor exhibited a K(i) value for PC2 of 0.54 microM. In contrast, the most potent bicyclic guanidine inhibitor exhibited a K(i) value of 3.3 microM. Cross-reactivity with other convertases was limited: pyrrolidine bis-piperazines exhibited K(i) values greater than 25 microM for PC1/3 or furin, whereas the K(i) values of bicyclic guanidines for these other convertases were more than 15 microM. We conclude that pyrrolidine bis-piperazines and bicyclic guanidines represent promising initial leads for the optimization of therapeutically active PC2 inhibitors. PC2-specific inhibitors may be useful in the pharmacological blockade of PC2-dependent cleavage events, such as glucagon production in the pancreas and ectopic peptide production in small-cell carcinoma, and to study PC2-dependent proteolytic events, such as opioid peptide production.

Conformation-opioid activity relationships of bicyclic guanidines from 3D similarity analysis.

Conformation of bicyclic guanidines with kappa-opioid receptor activity derived in our laboratory from a positional scanning synthetic combinatorial library is presented in this work. We propose a common bioactive conformation and putative pharmacophoric features by means of 3D similarity methods. Our 'Y' shape molecular binding model explains structure-activity relationships and suggests that the guanidine functionality and a 4-methoxybenzyl group may be involved in key interactions with the receptor. Comparison of our model with known opiates suggest a similar binding mode showing that the bicyclic guanidines presented in this work are suitable scaffolds for further development of new opioid receptors ligands.

Identification of potent and highly selective chiral tri-amine and tetra-amine mu opioid receptors ligands: an example of lead optimization using mixture-based libraries.

The generation of chiral polyamine libraries has been successfully accomplished in our laboratory following exhaustive reduction of resin-bound peptides. Herein, we report the synthesis and screening results of a positional scanning mixture-based library of chiral hepta-amines in a radioreceptor assay for the opioid receptor. The positional scanning hepta-amine library was generated by the exhaustive reduction of a library of 34,012,070 hexapeptides. Following screening of the entire library, combinations of the most active functionalities found at each position were used to synthesize and screen 40 individual hepta-amines and served as starting 'hits' for further SAR studies. The individual compounds showed IC(50) values ranging from 14 to 345 nM. As might be anticipated by the known studies of mu opiate antagonists, the identified active hepta-amines possessed aromatic rings derived from phenylalanine and tyrosine amino acid side chains. Following SAR studies, a truncation analog, reduced and permethylated YYF-NH(2), was found to be highly active (0.5 nM) as a selective mu antagonist in the guinea pig ileum bioassay.

In vitro and direct in vivo testing of mixture-based combinatorial libraries for the identification of highly active and specific opiate ligands.

The use of combinatorial libraries for the identification of novel opiate and related ligands in opioid receptor assays is reviewed. Case studies involving opioid assays used to demonstrate the viability of combinatorial libraries are described. The identification of new opioid peptides composed of L-amino acids, D-amino acids, or L-, D-, and unnatural amino acids is reviewed. New opioid compounds have also been identified from peptidomimetic libraries, such as peptoids and alkylated dipeptides, and those identified from acyclic (eg, polyamine, urea) and heterocyclic (eg, bicyclic guanidine) libraries are reviewed.