Targeting cancer-specific glycans by cyclic peptide lectinomimics.

The transformation from normal to malignant phenotype in human cancers is associated with aberrant cell-surface glycosylation. Thus, targeting glycosylation changes in cancer is likely to provide not only better insight into the roles of carbohydrates in biological systems, but also facilitate the development of new molecular probes for bioanalytical and biomedical applications. In the reported study, we have synthesized lectinomimics based on odorranalectin 1; the smallest lectin-like cyclic peptide isolated from the frog Odorrana grahami skin, and assessed the ability of these peptides to bind specific carbohydrates on molecular and cellular levels. In addition, we have shown that the disulfide bond found in 1 can be replaced with a lactam bridge. However, the orientation of the lactam bridge, peptides 2 and 3, influenced cyclic peptide's conformation and thus these peptides' ability to bind carbohydrates. Naturally occurring 1 and its analog 3 that adopt similar conformation in water bind preferentially L-fucose, and to a lesser degree D-galactose and N-acetyl-D-galactosamine, typically found within the mucin O-glycan core structures. In cell-based assays, peptides 1 and 3 showed a similar binding profile to Aleuria aurantia lectin and these two peptides inhibited the migration of metastatic breast cancer cell lines in a Transwell assay. Altogether, the reported data demonstrate the feasibility of designing lectinomimics based on cyclic peptides.

Design and synthesis of α-conotoxin GID analogues as selective α4ß2 nicotinic acetylcholine receptor antagonists.

The α4ß2 nicotinic acetylcholine receptor (nAChR) is an important target for currently approved smoking cessation therapeutics. However, the development of highly selective α4ß2 nAChR antagonists remains a significant challenge. α-Conotoxin GID is an antagonist of α4ß2 nAChRs, though it is significantly more potent toward the α3ß2 and α7 subtypes. With the goal of obtaining further insights into α-conotoxin GID/nAChR interactions that could lead to the design of GID analogues with improved affinity for α4ß2 nAChRs, we built a homology model of the GID/α4ß2 complex using an X-ray co-crystal structure of an α-conotoxin/acetylcholine binding protein (AChBP) complex. Several additional interactions that could potentially enhance the affinity of GID for α4ß2 nAChRs were observed in our model, which led to the design and synthesis of 22 GID analogues. Seven analogues displayed inhibitory activity toward α4ß2 nAChRs that was comparable to GID. Significantly, both GID[A10S] and GID[V13I] demonstrated moderately improved selectivity toward α4ß2 over α3ß2 when compared with GID, while GID[V18N] exhibited no measurable inhibitory activity for the α3ß2 subtype, yet retained inhibitory activity for α4ß2. In this regard, GID[V18N] is the most α4ß2 nAChR selective α-conotoxin analogue identified to date.

Toward an efficient approach to identify molecular scaffolds possessing selective or promiscuous compounds.

The concept of a recurrent scaffold present in a series of structures is common in medicinal drug discovery. We present a scaffold analysis of compounds screened across 100 sequence-unrelated proteins to identify scaffolds that drive promiscuity or selectivity. Selectivity and promiscuity play a major role in traditional and poly-pharmacological drug design considerations. The collection employed here is the first publicly available data set containing the complete screening profiles of more than 15 000 compounds from different sources. In addition, no scaffold analysis of this data set has been reported. The protocol described here employs the Molecular Equivalence Index tool to facilitate the selection of Bemis-Murcko frameworks in the data set, which contain at least five compounds and Scaffold Hunter to generate a hierarchical tree of scaffolds. The annotation of the scaffold tree with protein-binding profile data enabled the successful identification of mostly highly specific compounds, due to data set constraints. We also applied this approach to a public set of 1497 small molecules screened non-uniformly across a panel of 172 protein kinases. The approach is general and can be applied to any other data sets and activity readout.

Molecular recognition of the Thomsen-Friedenreich antigen-threonine conjugate by adhesion/growth regulatory galectin-3: nuclear magnetic resonance studies and molecular dynamics simulations.

Nuclear magnetic resonance (NMR) spectroscopy and molecular modeling methods have been strategically combined to elucidate the molecular recognition features of the binding of threonine O-linked Thomsen-Friedenreich (TF) antigen to chimera-type avian galectin-3 (CG-3). Saturation transfer difference (STD) NMR experiments revealed the highest intensities for the H4 protons of both the ß-D-Galp and α-D-GalpNAc moieties, with 100 and 71% of relative STD, respectively. The methyl protons of the threonine residue exhibited a small STD effect, <15%, indicating that the interaction of the amino acid with the protein is rather transient. Two-dimensional transferred nuclear Overhauser effect spectroscopy NMR experiments and molecular modeling suggested some differences in conformer populations between the free and bound states. A dynamic binding mode for the TF antigen-CG-3 complex consisting of two poses has been deduced. In one pose, intermolecular interactions were formed between the terminal threonine residue and the receptor. In the second pose, intermolecular interactions involved the internal GalpNAc. The difference in the trend of some shifts in the heteronuclear single-quantum coherence titration spectra indicates some disparities in the binding interactions of CG-3 with lactose and TF antigen. The results obtained from this model of the avian orthologue of human galectin-3 will allow detailed interspecies comparison to give sequence deviations in phylogeny a structural and functional meaning. Moreover, the results indicate that the peptide scaffold presenting TF antigen could be relevant for binding and thus provides a possible route for the design of galectin-3 inhibitors with improved affinity and selectivity.

Consensus models of activity landscapes with multiple chemical, conformer, and property representations.

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.