Austin B. Yongye

Multitarget Structure–Activity Relationships Characterized by Activity-Difference Maps and Consensus Similarity Measure

Dual and triple activity-difference (DAD/TAD) maps are tools for the systematic characterization of structure-activity relationships (SAR) of compound data sets screened against two or three targets. DAD and TAD maps are two- and three- dimensional representations of the pairwise activity differences of compound data sets, respectively. Adding pairwise structural similarity information into these maps readily reveals activity cliff regions in the SAR for one, two, or three targets. In addition, pairs of compounds in the smooth regions of the SAR and scaffold hops are also easily identified in these maps. Herein, DAD and TAD maps are employed for the systematic characterization of the SAR of a benchmark set of 299 compounds screened against dopamine, norepinephrine, and serotonin transporters. To reduce the well-known dependence of the activity landscape on the structural representation, five selected 2D and 3D structure representations were used to characterize the SAR. Systematic analysis of the DAD and TAD maps reveals regions in the landscape with similar SAR for two or the three targets as well as regions with inverse SAR, i.e., changes in structure that increase activity for one target, but decrease activity for the other target. Focusing the analysis on pairs of compounds with high structure similarity revealed the presence of single-, dual-, and triple-target activity cliffs, i.e., small changes in structure with high changes in potency for one, two, or the three targets, respectively. Triple-target scaffold hops are also discussed. Activity cliffs and scaffold hops were also quantified and represented using two recently proposed approaches namely, mean Structure Activity Landscape Index (mean SALI) and Consensus Structure-Activity Similarity (SAS) maps.

Molecular scaffold analysis of natural products databases in the public domain.

Natural products represent important sources of bioactive compounds in drug discovery efforts. In this work, we compiled five natural products databases available in the public domain and performed a comprehensive chemoinformatic analysis focused on the content and diversity of the scaffolds with an overview of the diversity based on molecular fingerprints. The natural products databases were compared with each other and with a set of molecules obtained from in‐house combinatorial libraries, and with a general screening commercial library. It was found that publicly available natural products databases have different scaffold diversity. In contrast to the common concept that larger libraries have the largest scaffold diversity, the largest natural products collection analyzed in this work was not the most diverse. The general screening library showed, overall, the highest scaffold diversity. However, considering the most frequent scaffolds, the general reference library was the least diverse. In general, natural products databases in the public domain showed low molecule overlap. In addition to benzene and acyclic compounds, flavones, coumarins, and flavanones were identified as the most frequent molecular scaffolds across the different natural products collections. The results of this work have direct implications in the computational and experimental screening of natural product databases for drug discovery.

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 β-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.

Characterization of a comprehensive flavor database

Flavor perception involves, among a number of physiological and psychological processes, the recognition of chemicals by olfactory and taste receptors. The highly complex and multidimensional nature of flavor perception challenges our ability to both predict and design new flavor entities. Toward this endeavor, classifications of flavor descriptors have been proposed. Here, we developed a fingerprint‐based representation of a large data set comprising 4181 molecules taken from the commercially available Leffingwell & Associates Canton, Georgia, USA database marketed as Flavor‐Base Pro© 2010. Flavor descriptions of the materials in this database were composite descriptions, collected from numerous sources over the course of more than 40 years. The flavor descriptors were referenced against a detailed and authoritative sensory lexicon (ASTM, American Society for Testing and Materials publication DS 66) comprising 662 flavor attributes. Comparison of clustering analysis, principal component analysis, and descriptor associations provided similar conclusions for various mutually correlated descriptors. Regarding analysis of the flavor similarity of the molecules, the clustering performed provided a means for the quick selection of molecules with either high or low flavor similarity description. Preliminary comparison of the chemical structures to the flavor description demonstrated the feasibility but also the complexity of this task. Additional studies including different structural representations, careful selection of subsets from this data set, as well as the use of a number of classification methods will demonstrate the utility of structure–flavor associations. This work shows that the flavor information contained in databases, such as that used in the present study, can be analyzed following standard chemoinformatics methods. Copyright

Data mining of protein-binding profiling data identifies structural modifications that distinguish selective and promiscuous compounds.

Activity profiling of compound collections across multiple targets is increasingly being used in probe and drug discovery. Herein, we discuss an approach to systematically analyzing the structure-activity relationships of a large screening profile data with emphasis on identifying structural changes that have a significant impact on the number of proteins to which a compound binds. As a case study, we analyzed a recently released public data set of more than 15 000 compounds screened across 100 sequence-unrelated proteins. The screened compounds have different origins and include natural products, synthetic molecules from academic groups, and commercial compounds. Similar synthetic structures from academic groups showed, overall, greater promiscuity differences than do natural products and commercial compounds. The method implemented in this work readily identified structural changes that differentiated highly specific from promiscuous compounds. This approach is general and can be applied to analyze any other large-scale protein-binding profile data.

Systematic Mining of Generally Recognized as Safe (GRAS) Flavor Chemicals for Bioactive Compounds

Bioactive food compounds can be both therapeutically and nutritionally relevant. Screening strategies are widely employed to identify bioactive compounds from edible plants. Flavor additives contained in the so-called FEMA GRAS (generally recognized as safe) list of approved flavoring ingredients is an additional source of potentially bioactive compounds. This work used the principles of molecular similarity to identify compounds with potential mood-modulating properties. The ability of certain GRAS molecules to inhibit histone deacetylase-1 (HDAC1), proposed as an important player in mood modulation, was assayed. Two GRAS chemicals were identified as HDAC1 inhibitors in the micromolar range, results similar to what was observed for the structurally related mood prescription drug valproic acid. Additional studies on bioavailability, toxicity at higher concentrations, and off-target effects are warranted. The methodology described in this work could be employed to identify potentially bioactive flavor chemicals present in the FEMA GRAS list.

Synthesis of Cyclic Peptides through Direct Aminolysis of Peptide Thioesters Catalyzed by Imidazole in Aqueous Organic Solutions

A promising method for the synthesis of cyclic peptides through the direct aminolysis of peptide thioesters is presented. The cyclization step was carried out in a mixture of acetonitrile and 1.5 M aqueous imidazole solution with no observable oligomers. Studies on the N- and C-terminal residues show that the choice of C-terminal residue has a more significant effect on the success rate of cyclization than the choice at the N-terminal residue.

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.

Design and synthesis of α-conotoxin GID analogues as selective α4β2 nicotinic acetylcholine receptor antagonists

The α4β2 nicotinic acetylcholine receptor (nAChR) is an important target for currently approved smoking cessation therapeutics. However, the development of highly selective α4β2 nAChR antagonists remains a significant challenge. α‐Conotoxin GID is an antagonist of α4β2 nAChRs, though it is significantly more potent toward the α3β2 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 α4β2 nAChRs, we built a homology model of the GID/α4β2 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 α4β2 nAChRs were observed in our model, which led to the design and synthesis of 22 GID analogues. Seven analogues displayed inhibitory activity toward α4β2 nAChRs that was comparable to GID. Significantly, both GID[A10S] and GID[V13I] demonstrated moderately improved selectivity toward α4β2 over α3β2 when compared with GID, while GID[V18N] exhibited no measurable inhibitory activity for the α3β2 subtype, yet retained inhibitory activity for α4β2. In this regard, GID[V18N] is the most α4β2 nAChR selective α‐conotoxin analogue identified to date.

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.