Fluorescent probes for bioimaging of potential biomarkers in Parkinson's disease

This review comprehensively summarizes various types of fluorescent probes for PD and their applications for detection of various PD biomarkers.

Protein-Protein Interaction Inhibitors of BRCA1 Discovered Using Small Molecule Microarrays

Microarray screening technology has transformed the life sciences arena over the last decade. The platform is widely used in the area of mapping interaction networks, to molecular fingerprinting and small molecular inhibitor discovery. The technique has significantly impacted both basic and applied research. The microarray platform can likewise enable high-throughput screening and discovery of protein-protein interaction (PPI) inhibitors. Herein we demonstrate the application of microarray-guided PPI inhibitor discovery, using human BRCA1 as an example. Mutations in BRCA1 have been implicated in ~50 % of hereditary breast cancers. By targeting the (BRCT)₂ domain, we showed compound 15a and its prodrug 15b inhibited BRCA1 activities in tumor cells. Unlike previously reported peptide-based PPI inhibitors of BRCA1, the compounds identified could be directly administered to tumor cells, thus making them useful in targeting BRCA1/PARP-related pathways involved in DNA damage and repair response, for cancer therapy.

Identification of 14-3-3 Proteins Phosphopeptide-Binding Specificity Using an Affinity-Based Computational Approach

The 14-3-3 proteins are a highly conserved family of homodimeric and heterodimeric molecules, expressed in all eukaryotic cells. In human cells, this family consists of seven distinct but highly homologous 14-3-3 isoforms. 14-3-3σ is the only isoform directly linked to cancer in epithelial cells, which is regulated by major tumor suppressor genes. For each 14-3-3 isoform, we have 1,000 peptide motifs with experimental binding affinity values. In this paper, we present a novel method for identifying peptide motifs binding to 14-3-3σ isoform. First, we propose a sampling criteria to build a predictor for each new peptide sequence. Then, we select nine physicochemical properties of amino acids to describe each peptide motif. We also use auto-cross covariance to extract correlative properties of amino acids in any two positions. Finally, we consider elastic net to predict affinity values of peptide motifs, based on ridge regression and least absolute shrinkage and selection operator (LASSO). Our method tests on the 1,000 known peptide motifs binding to seven 14-3-3 isoforms. On the 14-3-3σ isoform, our method has overall pearson-product-moment correlation coefficient (PCC) and root mean squared error (RMSE) values of 0.84 and 252.31 for N-terminal sublibrary, and 0.77 and 269.13 for C-terminal sublibrary. We predict affinity values of 16,000 peptide sequences and relative binding ability across six permutated positions similar with experimental values. We identify phosphopeptides that preferentially bind to 14-3-3σ over other isoforms. Several positions on peptide motifs are in the same amino acid category with experimental substrate specificity of phosphopeptides binding to 14-3-3σ. Our method is fast and reliable and is a general computational method that can be used in peptide-protein binding identification in proteomics research.

Proton chemical shift tensors determined by 3D ultrafast MAS double-quantum NMR spectroscopy

Proton NMR spectroscopy in the solid state has recently attracted much attention owing to the significant enhancement in spectral resolution afforded by the remarkable advances in ultrafast magic angle spinning (MAS) capabilities. In particular, proton chemical shift anisotropy (CSA) has become an important tool for obtaining specific insights into inter/intra-molecular hydrogen bonding. However, even at the highest currently feasible spinning frequencies (110-120 kHz), (1)H MAS NMR spectra of rigid solids still suffer from poor resolution and severe peak overlap caused by the strong (1)H-(1)H homonuclear dipolar couplings and narrow (1)H chemical shift (CS) ranges, which render it difficult to determine the CSA of specific proton sites in the standard CSA/single-quantum (SQ) chemical shift correlation experiment. Herein, we propose a three-dimensional (3D) (1)H double-quantum (DQ) chemical shift/CSA/SQ chemical shift correlation experiment to extract the CS tensors of proton sites whose signals are not well resolved along the single-quantum chemical shift dimension. As extracted from the 3D spectrum, the F1/F3 (DQ/SQ) projection provides valuable information about (1)H-(1)H proximities, which might also reveal the hydrogen-bonding connectivities. In addition, the F2/F3 (CSA/SQ) correlation spectrum, which is similar to the regular 2D CSA/SQ correlation experiment, yields chemical shift anisotropic line shapes at different isotropic chemical shifts. More importantly, since the F2/F1 (CSA/DQ) spectrum correlates the CSA with the DQ signal induced by two neighboring proton sites, the CSA spectrum sliced at a specific DQ chemical shift position contains the CSA information of two neighboring spins indicated by the DQ chemical shift. If these two spins have different CS tensors, both tensors can be extracted by numerical fitting. We believe that this robust and elegant single-channel proton-based 3D experiment provides useful atomistic-level structural and dynamical information for a variety of solid systems that possess high proton density.

Integrate Omics Data and Molecular Dynamics Simulations toward Better Understanding of Human 14-3-3 Interactomes and Better Drugs for Cancer Therapy

The 14-3-3 protein family is among the most extensively studied, yet still largely mysterious protein families in mammals to date. As they are well recognized for their roles in apoptosis, cell cycle regulation, and proliferation in healthy cells, aberrant 14-3-3 expression has unsurprisingly emerged as instrumental in the development of many cancers and in prognosis. Interestingly, while the seven known 14-3-3 isoforms in humans have many similar functions across cell types, evidence of isoform-specific functions and localization has been observed in both healthy and diseased cells. The strikingly high similarity among 14-3-3 isoforms has made it difficult to delineate isoform-specific functions and for isoform-specific targeting. Here, we review our knowledge of 14-3-3 interactome(s) generated by high-throughput techniques, bioinformatics, structural genomics and chemical genomics and point out that integrating the information with molecular dynamics (MD) simulations may bring us new opportunity to the design of isoform-specific inhibitors, which can not only be used as powerful research tools for delineating distinct interactomes of individual 14-3-3 isoforms, but also can serve as potential new anti-cancer drugs that selectively target aberrant 14-3-3 isoform.

A small-molecule protein-protein interaction inhibitor of PARP1 that targets its BRCT domain

Poly(ADP-ribose)polymerase-1 (PARP1) is a BRCT-containing enzyme (BRCT = BRCA1 C-terminus) mainly involved in DNA repair and damage response and a validated target for cancer treatment. Small-molecule inhibitors that target the PARP1 catalytic domain have been actively pursued as anticancer drugs, but are potentially problematic owing to a lack of selectivity. Compounds that are capable of disrupting protein-protein interactions of PARP1 provide an alternative by inhibiting its activities with improved selectivity profiles. Herein, by establishing a high-throughput microplate-based assay suitable for screening potential PPI inhibitors of the PARP1 BRCT domain, we have discovered that (±)-gossypol, a natural product with a number of known biological activities, possesses novel PARP1 inhibitory activity both in vitro and in cancer cells and presumably acts through disruption of protein-protein interactions. As the first known cell-permeable small-molecule PPI inhibitor of PAPR1, we further established that (-)-gossypol was likely the causative agent of PARP1 inhibition by promoting the formation of a 1:2 compound/PARP1 complex by reversible formation of a covalent imine linkage.

Recent advances in microarray technologies for proteomics

Proteins are fundamental components of all living systems and critical drivers of biological functions. The large-scale study of proteins, their structures and functions, is defined as proteomics. This systems-wide analysis leads to a more comprehensive view of the intricate signaling transduction pathways that proteins engage in and improves the overall understanding of the complex processes supporting the living systems. Over the last two decades, the development of high-throughput analytical tools, such as microarray technologies, capable of rapidly analyzing thousands of protein-functioning and protein-interacting events, has fueled the growth of this important field. Herein, we review the most recent advancements in microarray technologies, with a special focus on peptide microarray, small molecule microarray, and protein microarray. These technologies have become prominent players in proteomics and have made significant changes to the landscape of life science and biomedical research. We will elaborate on their performance, advantages, challenges, and future directions.

Microarray-guided discovery of two-photon (2P) small molecule probes for live-cell imaging of cysteinyl cathepsin activities

A microarray immobilized with 105 aldehyde-containing small molecules was screened against mammalian cell lysates over-expressing cathepsin L to identify two potent inhibitors, which were subsequently converted into cell-permeable probes capable of live-cell imaging of endogenous cysteinyl cathepsin activities by two-photon fluorescence microscopy.

The application of modular protein domains in proteomics

The ability of modular protein domains to independently fold and bind short peptide ligands both in vivo and in vitro has allowed a significant number of protein-protein interaction studies to take advantage of them as affinity and detection reagents. Here, we refer to modular domain based proteomics as "domainomics" to draw attention to the potential of using domains and their motifs as tools in proteomics. In this review we describe core concepts of domainomics, established and emerging technologies, and recent studies by functional category. Accumulation of domain-motif binding data should ultimately provide the foundation for domain-specific interactomes, which will likely reveal the underlying substructure of protein networks as well as the selectivity and plasticity of signal transduction.

Current chemical biology tools for studying protein phosphorylation and dephosphorylation

Amongst different posttranslational events involved in cellular-signaling pathways, phosphorylation and dephosphorylation of proteins are the most prevalent. Aberrant regulations in the cellular phosphoproteome network are implicated in most major human diseases. Consequently, kinases and phosphatases are two of the most important groups of drug targets in medicinal research today. A major challenge in the understanding of protein phosphorylation and dephosphorylation is the sheer complexity of the phosphoproteome network and the lack of tools capable of studying protein phosphorylation and dephosphorylation as they occur in cells. We highlight herein various chemical biology tools that have emerged in the last decade for such studies. First, we discuss the use of small-molecule mimics of phosphoamino acids and their use in elucidating the function of protein phosphorylation and dephosphorylation. We also introduce recent advances in the field of activity-based protein profiling (ABPP) for proteome-wide detection of protein phosphorylation and dephosphorylation. We next discuss the key concepts in the design of peptide- and protein-based biosensors capable of real-time reporting of phosphorylation/dephosphorylation events. Finally, we highlight the application of peptide and small-molecule microarrays (SMMs), and their applications in high-throughput screening and discovery of new compounds related to phosphorylation/dephosphorylation.

A peptide aldehyde microarray for high-throughput profiling of cellular events

Microarrays provide exciting opportunities in the field of large-scale proteomics. With the aim to elucidate enzymatic activity and profiles within native biological samples, we developed a microarray comprising a focused positional-scanning library of enzyme inhibitors. The library was diversified across P(1)-P(4) positions, creating 270 different inhibitor sublibraries which were immobilized onto avidin slides. The peptide aldehyde-based small-molecule microarray (SMM) specifically targeted cysteine proteases, thereby enabling large-scale functional assessment of this subgroup of proteases, within fluorescently labeled samples, including pure proteins, cellular lysates, and infected samples. The arrays were shown to elicit binding fingerprints consistent with those of model proteins, specifically caspases and purified cysteine proteases from parasites (rhodesein and cruzain). When tested against lysates from apoptotic Hela and red blood cells infected with Plasmodium falciparum, clear signatures were obtained that were readily attributable to the activity of constituent proteases within these samples. Characteristic binding profiles were further able to distinguish various stages of the parasite infection in erythrocyte lysates. By converting one of our brightest microarray hits into a probe, putative protein markers were identified and pulled down from within apoptotic Hela lysates, demonstrating the potential of target validation and discovery. Taken together, these results demonstrate the utility of targeted SMMs in dissecting cellular biology in complex proteomic samples.

Small molecule microarrays: the first decade and beyond

Molecular Bits and Chips: Profiling and discovering the next generation of small molecule ligands.

Next generation chemical proteomic tools for rapid enzyme profiling

Sequencing of the human genome provided a wealth of information about the genomic blueprint of a cell. But genes do not tell the entire story of life and living processes; identifying the roles of enzymes and mapping out their interactions is also crucial. Enzymes catalyze virtually every cellular process and metabolic exchange. They not only are instrumental in sustaining life but also are required for its regulation and diversification. Diseases such as cancer can be caused by minor changes in enzyme activities. In addition, the unique enzymes of pathogenic organisms are ripe targets for combating infections. Consequently, nearly one-third of all current drug targets are enzymes. An estimated 18-29% of eukaryotic genes encode enzymes, but only a limited proportion of enzymes have thus far been characterized. Therefore, little is understood about the physiological roles, substrate specificity, and downstream targets of the vast majority of these important proteins. A key step toward the biological characterization of enzymes, as well as their adoption as drug targets, is the development of global solutions that bridge the gap in understanding these proteins and their interactions. We herein present technological advances that facilitate the study of enzymes and their properties in a high-throughput manner. Over the years, our group has introduced and developed a variety of such enabling platforms for many classes of enzymes, including kinases, phosphatases, and proteases. For each of these different types of enzymes, specific design considerations are required to develop the appropriate chemical tools to characterize each class. These tools include activity-based probes and chemical compound libraries, which are rapidly assembled using efficient combinatorial synthesis or "click chemistry" strategies. The resulting molecular assortments may then be screened against the target enzymes in high-throughput using microplates or microarrays. These techniques offer powerful means to study, profile, and discover potent small molecules that can modulate enzyme activity. This Account will describe the concepts involved in designing chemical probes and libraries for comparative enzyme screening and drug discovery applications, as well as highlight how these technologies are changing the way in which enzymes may be rapidly profiled and characterized.