Topological side-chain classification of β-turns: Ideal motifs for peptidomimetic development

Clustering of disulfide-rich peptides provides scaffolds for hit discovery by phage display: application to interleukin-23

BACKGROUND

Disulfide-rich peptides (DRPs) are found throughout nature. They are suitable scaffolds for drug development due to their small cores, whose disulfide bonds impart extraordinary chemical and biological stability. A challenge in developing a DRP therapeutic is to engineer binding to a specific target. This challenge can be overcome by (i) sampling the large sequence space of a given scaffold through a phage display library and by (ii) panning multiple libraries encoding structurally distinct scaffolds. Here, we implement a protocol for defining these diverse scaffolds, based on clustering structurally defined DRPs according to their conformational similarity.

RESULTS

We developed and applied a hierarchical clustering protocol based on DRP structural similarity, followed by two post-processing steps, to classify 806 unique DRP structures into 81 clusters. The 20 most populated clusters comprised 85% of all DRPs. Representative scaffolds were selected from each of these clusters; the representatives were structurally distinct from one another, but similar to other DRPs in their respective clusters. To demonstrate the utility of the clusters, phage libraries were constructed for three of the representative scaffolds and panned against interleukin-23. One library produced a peptide that bound to this target with an IC₅₀ of 3.3 μM.

CONCLUSIONS

Most DRP clusters contained members that were diverse in sequence, host organism, and interacting proteins, indicating that cluster members were functionally diverse despite having similar structure. Only 20 peptide scaffolds accounted for most of the natural DRP structural diversity, providing suitable starting points for seeding phage display experiments. Through selection of the scaffold surface to vary in phage display, libraries can be designed that present sequence diversity in architecturally distinct, biologically relevant combinations of secondary structures. We supported this hypothesis with a proof-of-concept experiment in which three phage libraries were constructed and panned against the IL-23 target, resulting in a single-digit μM hit and suggesting that a collection of libraries based on the full set of 20 scaffolds increases the potential to identify efficiently peptide binders to a protein target in a drug discovery program.

Discovery and Characterization of a Potent Interleukin-6 Binding Peptide with Neutralizing Activity In Vivo

Interleukin-6 (IL-6) is an important member of the cytokine superfamily, exerting pleiotropic actions on many physiological processes. Over-production of IL-6 is a hallmark of immune-mediated inflammatory diseases such as Castleman's Disease (CD) and rheumatoid arthritis (RA). Antagonism of the interleukin IL-6/IL-6 receptor (IL-6R)/gp130 signaling complex continues to show promise as a therapeutic target. Monoclonal antibodies (mAbs) directed against components of this complex have been approved as therapeutics for both CD and RA. To potentially provide an additional modality to antagonize IL-6 induced pathophysiology, a peptide-based antagonist approach was undertaken. Using a combination of molecular design, phage-display, and medicinal chemistry, disulfide-rich peptides (DRPs) directed against IL-6 were developed with low nanomolar potency in inhibiting IL-6-induced pSTAT3 in U937 monocytic cells. Targeted PEGylation of IL-6 binding peptides resulted in molecules that retained their potency against IL-6 and had a prolongation of their pharmacokinetic (PK) profiles in rodents and monkeys. One such peptide, PN-2921, contained a 40 kDa polyethylene glycol (PEG) moiety and inhibited IL-6-induced pSTAT3 in U937 cells with sub-nM potency and possessed 23, 36, and 59 h PK half-life values in mice, rats, and cynomolgus monkeys, respectively. Parenteral administration of PN-2921 to mice and cynomolgus monkeys potently inhibited IL-6-induced biomarker responses, with significant reductions in the acute inflammatory phase proteins, serum amyloid A (SAA) and C-reactive protein (CRP). This potent, PEGylated IL-6 binding peptide offers a new approach to antagonize IL-6-induced signaling and associated pathophysiology.

Fighting obesity with a sugar-based library: discovery of novel MCH-1R antagonists by a new computational-VAST approach for exploration of GPCR binding sites

Obesity is an increasingly common disease. While antagonism of the melanin-concentrating hormone-1 receptor (MCH-1R) has been widely reported as a promising therapeutic avenue for obesity treatment, no MCH-1R antagonists have reached the market. Discovery and optimization of new chemical matter targeting MCH-1R is hindered by reduced HTS success rates and a lack of structural information about the MCH-1R binding site. X-ray crystallography and NMR, the major experimental sources of structural information, are very slow processes for membrane proteins and are not currently feasible for every GPCR or GPCR-ligand complex. This situation significantly limits the ability of these methods to impact the drug discovery process for GPCR targets in "real-time", and hence, there is an urgent need for other practical and cost-efficient alternatives. We present here a conceptually pioneering approach that integrates GPCR modeling with design, synthesis, and screening of a diverse library of sugar-based compounds from the VAST technology (versatile assembly on stable templates) to provide structural insights on the MCH-1R binding site. This approach creates a cost-efficient new avenue for structure-based drug discovery (SBDD) against GPCR targets. In our work, a primary VAST hit was used to construct a high-quality MCH-1R model. Following model validation, a structure-based virtual screen yielded a 14% hit rate and 10 novel chemotypes of potent MCH-1R antagonists, including EOAI3367472 (IC50 = 131 nM) and EOAI3367474 (IC50 = 213 nM).

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

Chemogenomics with protein secondary-structure mimetics

During molecular recognition of proteins in biological systems, helices, reverse turns, and beta-sheets are dominant motifs. Often there are therapeutic reasons for blocking such recognition sites, and significant progress has been made by medicinal chemists in the design and synthesis of semirigid molecular scaffolds on which to display amino acid side chains. The basic premise is that preorganization of the competing ligand enhances the binding affinity and potential selectivity of the inhibitor. In this chapter, current progress in these efforts is reviewed.

A virtual library of constrained cyclic tetrapeptides that mimics all four side-chain orientations for over half the reverse turns in the protein data bank

Reverse turns are often recognition sites for protein/protein interactions and, therefore, valuable potential targets for determining recognition motifs in development of potential therapeutics. A virtual combinatorial library of cyclic tetrapeptides (CTPs) was generated and the bonds in the low-energy structures were overlapped with canonical reverse-turn Calpha-Cbeta bonds (Tran et al., J Comput Aided Mol Des 19(8):551-566, 2005) to determine the utility of CTPs as reverse-turn peptidomimetics. All reverse turns in the Protein Data Bank (PDB) with a crystal structures resolution < or = 3.0 A were classified into the same known canonical reverse-turn Calpha-Cbeta bond clusters (Tran et al., J Comput Aided Mol Des 19(8):551-566, 2005). CTP reverse-turn mimics were compiled that mimicked both the relative orientations of three of the four as well as all four Calpha-Cbeta bonds in the reverse turns of the PDB. 54% of reverse turns represented in the PDB had eight or more CTPs structures that mimicked the orientation of all four of the Calpha-Cbeta bonds in the reverse turn.

Back to the future: Ribonuclease A

Pancreatic ribonuclease A (EC 3.1.27.5, RNase) is, perhaps, the best-studied enzyme of the 20th century. It was isolated by René Dubos, crystallized by Moses Kunitz, sequenced by Stanford Moore and William Stein, and synthesized in the laboratory of Bruce Merrifield, all at the Rockefeller Institute/University. It has proven to be an excellent model system for many different types of experiments, both as an enzyme and as a well-characterized protein for biophysical studies. Of major significance was the demonstration by Chris Anfinsen at NIH that the primary sequence of RNase encoded the three-dimensional structure of the enzyme. Many other prominent protein chemists/enzymologists have utilized RNase as a dominant theme in their research. In this review, the history of RNase and its offspring, RNase S (S-protein/S-peptide), will be considered, especially the work in the Merrifield group, as a preface to preliminary data and proposed experiments addressing topics of current interest. These include entropy-enthalpy compensation, entropy of ligand binding, the impact of protein modification on thermal stability, and the role of protein dynamics in enzyme action. In continuing to use RNase as a prototypical enzyme, we stand on the shoulders of the giants of protein chemistry to survey the future.

Molecular modeling suggests conformational scaffolds specifically targeting five subtypes of somatostatin receptors

Several analogs of somatostatin with conformational constraints in their peptide backbones have been modeled to determine energetically feasible conformations. Comparison of low-energy backbone structures of these peptides suggested unique conformations of the central Phe/Ala(i)-D-Trp(i+1)-Lys(i+2)-Thr(i+3) fragment characteristic for specific interactions of somatostatin with each of the five distinct subtypes of somatostatin receptors (SSTRs). The conformations obtained were in good agreement with experimental data obtained earlier by NMR measurements and/or X-ray crystallography. The results help rationalize experimental observations on the specificity of binding of various somatostatin analogs with different subtypes of the SSTRs. They also serve as templates for the design of conformationally constrained non-peptide scaffolds that effectively and selectively interact with different subtypes of SSTRs. Such scaffolds can be convenient carriers of radiolabels and near-infrared labels in specific agents for imaging tumors expressing different SSTR subtypes.

Do benzodiazepines mimic reverse-turn structures?

The role of benzodiazepine derivatives (BZD) as a privileged scaffold that mimics beta-turn structures (Ripka et al. (1993) Tetrahedron 49:3593-3608) in peptide/protein recognition was reexamined in detail. Stable BZD ring conformers were determined with MM3, and experimental reverse-turn structures were extracted from the basis set of protein crystal structures previously defined by Ripka et al. Ideal beta-turns were also modeled and similarly compared with BZD conformers. Huge numbers of conformers were generated by systematically scanning the torsional degrees of freedom for BZDs, as well as those of ideal beta-turns for comparison. Using these structures, conformers of BZDs were fit to experimental structures as suggested by Ripka et al., or modeled classical beta-turn conformers, and the root-mean-square deviation (RMSD) values were calculated for each pairwise comparison. Pairs of conformers with the smallest RMSD values for overlap of the four alpha-beta side-chain orientations were selected. All overlaps of BZD conformers with experimental beta-turns yielded one or more comparisons where the least RMSD was significantly small, 0.48-0.86 angstroms, as previously suggested. Utilizing a different methodology, the overall conclusion that benzodiazepines could serve as reverse-turn mimetics of Ripka et al. is justified. The least RMSD values for the overlap of BZDs and modeled classical beta-turns were also less than 1 angstrom. When comparing BZDs with experimental or classical beta-turns, the set of experimental beta-turns selected by Ripka et al. fit the BZD scaffolds better than modeled classical beta-turns; however, all the experimental beta-turns did not fit a particular BZD scaffold better. A single BZD ring conformation, and/or chiral orientation, can mimic some, but not all, of the experimental beta-turn structures. BZD has two central ring conformations and one chiral center that explains why the four variations of the BZD scaffold can mimic all types of beta-turn structure examined. It was found, moreover, that the BZD scaffold also mimics each of the nine clusters of experimental orientations of side chains of reverse turns in the Protein Data Bank, when the new classification scheme for the four side-chain directions (the relative orientations of alpha-beta vectors of residues i through i+3) was considered (Tran et al. (2005) J Comput-Aided Mol Des 19:551-566).

Pharmacophore model for bile acids recognition by the FPR receptor

Formyl-peptide receptors (FPRs) belong to the family A of the G-protein coupled receptor superfamily and include three subtypes: FPR, FPR-like-1 and FPR-like-2. They have been involved in the control of many inflammatory processes promoting the recruitment and infiltration of leukocytes in regions of inflammation through the molecular recognition of chemotactic factors. A large number of structurally diverse chemotypes modulate the activity of FPRs. Newly identified antagonists include bile acids deoxycholic acid (DCA) and chenodeoxycholic acid (CDCA). The molecular recognition of these compounds at FPR receptor was computationally investigated using both ligand- and structure-based approaches. Our findings suggest that all antagonists bind at the first third of the seven helical bundles. A closer inspection of bile acid interaction reveals a number of unexploited anchor points in the binding site that may be used to aid the design of new potent and selective bile acids derivatives at FPR.

Development of small molecules designed to modulate protein-protein interactions

Protein-protein interactions are ubiquitous, essential to almost all known biological processes, and offer attractive opportunities for therapeutic intervention. Developing small molecules that modulate protein-protein interactions is challenging, owing to the large size of protein-complex interface, the lack of well-defined binding pockets, etc. We describe a general approach based on the "privileged-structure hypothesis" [Che, Ph.D. Thesis, Washington University, 2003] - that any organic templates capable of mimicking surfaces of protein-recognition motifs are potential privileged scaffolds as protein-complex antagonists--to address the challenges inherent in the discovery of small-molecule inhibitors of protein-protein interactions.