Jenna L. Wang

Probing Chemical Space with Alkaloid-Inspired Libraries

Screening of small molecule libraries is an important aspect of probe and drug discovery science. Numerous authors have suggested that bioactive natural products are attractive starting points for such libraries, due to their structural complexity and sp3-rich character. Here, we describe the construction of a screening library based on representative members of four families of biologically active alkaloids (Stemonaceae, the structurally related cyclindricine and lepadiformine families, lupin, and Amaryllidaceae). In each case, scaffolds were based on structures of the naturally occurring compounds or a close derivative. Scaffold preparation was pursued following the development of appropriate enabling chemical methods. Diversification provided 686 new compounds suitable for screening. The libraries thus prepared had structural characteristics, including sp3 content, comparable to a basis set of representative natural products and were highly rule-of-five compliant.

Small-molecule pyrimidine inhibitors of the cdc2-like (Clk) and dual specificity tyrosine phosphorylation-regulated (Dyrk) kinases: Development of chemical probe ML315

Substituted pyrimidine inhibitors of the Clk and Dyrk kinases have been developed, exploring structure-activity relationships around four different chemotypes. The most potent compounds have low-nanomolar inhibitory activity against Clk1, Clk2, Clk4, Dyrk1A and Dyrk1B. Kinome scans with 442 kinases using agents representing three of the chemotypes show these inhibitors to be highly selective for the Clk and Dyrk families. Further off-target pharmacological evaluation with ML315, the most selective agent, supports this conclusion.

Whither Combine? New Opportunities for Receptor-Based QSAR

Receptor based QSAR methods represent a computational marriage of structure activity relationship analysis and receptor structure based design that is providing valuable pharmacological insight to a wide range of therapeutic targets. One implementation, called Comparative Binding Energy (COMBINE) analysis, is particularly powerful by virtue of its explicit consideration of interatomic interactions between the ligand and receptor as the QSAR variable space. This review outlines the methodological basis for the COMBINE model, contrasts it relative to other 3D QSAR techniques, and discusses sample applications that illustrate recent key innovations. One major development discussed is the rigorous integration of multiple receptors into unified COMBINE models for probing bioactivity trends as a function of amino acid variation across a series of homologous protein receptors, and as a function of conformational variation within one single protein. Other important examples include a recent extension of the method to account for covalent effects arising from ligand binding, as well as successful application of a COMBINE model to high throughput virtual screening. This review concludes with discussions about possible future methodological refinements and their applications, including potential extensions to four-dimensional QSAR, and a potential role of quantum chemistry in addressing covalent bonding effects and parametric adaptivity.

Key Residues Controlling Binding of Diverse Ligands to Human Cytochrome P450 2A Enzymes

Although the human lung cytochrome P450 2A13 (CYP2A13) and its liver counterpart cytochrome P450 2A6 (CYP2A6) are 94% identical in amino acid sequence, they metabolize a number of substrates with substantially different efficiencies. To determine differences in binding for a diverse set of cytochrome P450 2A ligands, we have measured the spectral binding affinities (KD) for nicotine, phenethyl isothiocyanate (PEITC), coumarin, 2′-methoxyacetophenone (MAP), and 8-methoxypsoralen. The differences in the KD values for CYP2A6 versus CYP2A13 ranged from 74-fold for 2′-methoxyacetophenone to 1.1-fold for coumarin, with CYP2A13 demonstrating the higher affinity. To identify active site amino acids responsible for the differences in binding of MAP, PEITC, and coumarin, 10 CYP2A13 mutant proteins were generated in which individual amino acids from the CYP2A6 active site were substituted into CYP2A13 at the corresponding position. Titrations revealed that substitutions at positions 208, 300, and 301 individually had the largest effects on ligand binding. The collective relevance of these amino acids to differential ligand selectivity was verified by evaluating binding to CYP2A6 mutant enzymes that incorporate several of the CYP2A13 amino acids at these positions. Inclusion of four CYP2A13 amino acids resulted in a CYP2A6 mutant protein (I208S/I300F/G301A/S369G) with binding affinities for MAP and PEITC much more similar to those observed for CYP2A13 than to those for CYP2A6 without altering coumarin binding. The structure-based quantitative structure-activity relationship analysis using COMBINE successfully modeled the observed mutant-ligand trends and emphasized steric roles for active site residues including four substituted amino acids and an adjacent conserved Leu370.

Identification of potent and selective inhibitors of the plasmodium falciparum M18 aspartyl aminopeptidase (PfM18AAP) of human malaria via high-throughput screening

The target of this study, the PfM18 aspartyl aminopeptidase (PfM18AAP), is the only AAP present in the genome of the malaria parasite Plasmodium falciparum. PfM18AAP is a metallo-exopeptidase that exclusively cleaves N-terminal acidic amino acids glutamate and aspartate. It is expressed in parasite cytoplasm and may function in concert with other aminopeptidases in protein degradation, of, for example, hemoglobin. Previous antisense knockdown experiments identified a lethal phenotype associated with PfM18AAP, suggesting that it is a valid target for new antimalaria therapies. To identify inhibitors of PfM18AAP function, a fluorescence enzymatic assay was developed using recombinant PfM18AAP enzyme and a fluorogenic peptide substrate (H-Glu-NHMec). This was screened against the Molecular Libraries Probe Production Centers Network collection of ~292,000 compounds (the Molecular Libraries Small Molecule Repository). A cathepsin L1 (CTSL1) enzyme-based assay was developed and used as a counterscreen to identify compounds with nonspecific activity. Enzymology and phenotypic assays were used to determine mechanism of action and efficacy of selective and potent compounds identified from high-throughput screening. Two structurally related compounds, CID 6852389 and CID 23724194, yielded micromolar potency and were inactive in CTSL1 titration experiments (IC50 >59.6 µM). As measured by the Ki assay, both compounds demonstrated micromolar noncompetitive inhibition in the PfM18AAP enzyme assay. Both CID 6852389 and CID 23724194 demonstrated potency in malaria growth assays (IC50 4 µM and 1.3 µM, respectively).

On the Balance of Simplification and Reality in Molecular Modeling of the Electron Density.

Fused-sphere (van der Waals) surfaces and their variants such as solvent accessible surfaces and molecular surfaces are simple molecular models that are commonly used for many diverse purposes across a broad range of scientific disciplines due to their low computational resource demands. Fused-sphere models require atomic radii to be defined. Many different atomic radii have been proposed, with each set of radii being applicable to a relatively limited scope of molecular types or situations. The large number of differing radii sets actually serves to emphasize the simplicity of the model and its inability to accurately represent the reality of the molecule: its electron density. By measuring the similarity of fused-sphere, fuzzy fused-sphere, and calculated electron density representations of a set of small molecules via symmetric volume differences and the shape group method, it can be seen that fused-sphere models are very poor at representing the real electronic charge distribution of small molecules, especially where π bond systems, lone pair electrons, and aromatic rings are involved. Larger molecules, conceivably, will be even more poorly represented. With advances in computational power and modeling techniques to arrive at high-quality calculated electron density representations for large molecules already in existence, abandoning the use of fused-sphere models should be considered for many applications.

Ionic immobilization, diversification, and release: application to the generation of a library of methionine aminopeptidase inhibitors.

Development of an ionic immobilization, diversification, and release method for the generation of methionine aminopeptidase inhibitors is reported. This method involves the immobilization of 5-bromofuran-2-carboxylic acid and 5-bromothiophene-2-carboxylic acid onto PS-BEMP, followed by Suzuki reaction on a resin-bound intermediate and subsequent release to provide products in moderate yields and excellent purities. Compound potencies were evaluated on the Co(II), Mn(II), Ni(II), and Fe(II) forms of Escherichia coli MetAP1. The furoic-acid analogs were found to be Mn(II) selective with IC 50 values in the low micromolar range. Qualitative SAR analysis, supplemented by molecular modeling studies, provides valuable information on structural elements responsible for potency and selectivity.

Novel Algorithms for the Identification of Biologically Informative Chemical Diversity Metrics.

Despite great advances in the efficiency of analytical and synthetic chemistry, time and available starting material still limit the number of unique compounds that can be practically synthesized and evaluated as prospective therapeutics. Chemical diversity analysis (the capacity to identify finite diverse subsets that reliably represent greater manifolds of drug-like chemicals) thus remains an important resource in drug discovery. Despite an unproven track record, chemical diversity has also been used to posit, from preliminary screen hits, new compounds with similar or better activity. Identifying diversity metrics that demonstrably encode bioactivity trends is thus of substantial potential value for intelligent assembly of targeted screens. This paper reports novel algorithms designed to simultaneously reflect chemical similarity or diversity trends and apparent bioactivity in compound collections. An extensive set of descriptors are evaluated within large NCI screening data sets according to bioactivity differentiation capacities, quantified as the ability to co-localize known active species into bioactive-rich K-means clusters. One method tested for descriptor selection orders features according to relative variance across a set of training compounds, and samples increasingly finer subset meshes for descriptors whose exclusion from the model induces drastic drops in relative bioactive colocalization. This yields metrics with reasonable bioactive enrichment (greater than 50% of all bioactive compounds collected into clusters or cells with significantly enriched active/inactive rates) for each of the four data sets examined herein. A second method replaces variance by an active/inactive divergence score, achieving comparable enrichment via a much more efficient search process. Combinations of the above metrics are tested in 2D rectilinear diversity models, achieving similarly successful colocalization statistics, with metrics derived from the active/inactive divergence score typically outperforming those selected from the variance criterion and computed from the DiverseSolutions software.