Browsing by Subject "Protein-protein interaction"

The identification and quantification of protein-protein interactions in large scale is critical to understanding biological processes at a systems level. Current approaches for the analysis of protein -protein interactions are generally not quantitative and largely limited to certain types of interactions such as binary and strong binding interactions. They also have high false-positive and false-negative rates. Described here is the development of and application of mass spectrometry-based proteomics metehods to detect and quantify the strength of protein-protein and protein-ligand interactions in the context of their interaction networks. Characterization of protein-protein and protein-ligand interactions can directly benefit diseased state analyses and drug discovery efforts.

The methodologies and protocols developed and applied in this work are all related to the Stability of Unpurified Proteins from Rates of amide H/D Exchange (SUPREX) and Stability of Protein from Rates of Oxidation (SPROX) techniques, which have been previously established for the thermodynamic analysis of protein folding reactions and protein-ligand binding interactions. The work in this thesis is comprised of four parts. Part I involves the development of a Histidine Slow H/D exchange protocol to facility SURPEX-like measurements on the proteomic scale. The Histidine Slow H/D exchange protocol is developed in the context of selected model protein systems and used to investigate the thermodynamic properties of proteins in a yeast cell lysate.

In Part II an isobaric mass tagging strategy is used in combination with SPROX (i.e., a so-called iTRAQ-SPROX protocol) is used to characterize the altered protein interactions networks associated with lung cancer. This work involved differential thermodynamic analyses on the proteins in two different cell lines, including ADLC-5M2 and ADLC-5M2-C2.

Parts III and IV of this thesis describe the development and application of a SPROX protocol for proteome-wide thermodynamic analyses that involves the use of Stable Isotope Labeling by Amino acid in cell Culture (SILAC) quantitation. A solution-based SILAC-SPROX protocol is described in Part III and a SILAC-SPROX protocol involving the use of cyanogen bromide and a gel-based fractionation step is described in Part IV. The SILAC-SPROX-Cyanogen bromide (SILAC-SPROX-CnBr) protocol is demonstrated to significantly improve the peptide and protein coverage in proteome-wide SPROX experiments. Both the SILAC-SPROX and SILAC-SPROX-CnBr porotocols were used to characterize the ATP binding properties of yeast proteins. Ultimately, the two protocols enabled 526 yeast proteins to be assayed for binding to AMP-PNP, an ATP mimic. A total of 140 proteins, including 37 known ATP-binding proteins, were found to have ATP binding interactions.

The cell cycle is one of the fundamental processes in all living organisms, and all cells arise from the division of existing cells. To better understand the regulation of the cell cycle, synchrony experiments are widely used to monitor cellular dynamics during this process. In such experiments, a large population of cells is generally arrested or selected at one stage of the cycle, and then released to progress through subsequent division stages. Measurements are then taken in this population at a variety of time points after release to provide insight into the dynamics of the cell cycle. However, due to cell-to-cell variability and asymmetric cell division, cells in a synchronized population lose synchrony over time. As a result, the time-series measurements from the synchronized cell populations do not accurately reflect the underlying dynamics of cell-cycle processes.

In this thesis, we introduce a deconvolution algorithm that learns a more accurate view of cell-cycle dynamics, free from the convolution effects associated with imperfect cell synchronization. Through wavelet-basis regularization, our method sharpens signal without sharpening noise, and can remarkably increase both the dynamic range and the temporal resolution of time-series data. Though it can be applied to any such data, we demonstrate the utility of our method by applying it to a recent cell-cycle transcription time course in the eukaryote Saccharomyces cerevisiae. We show that our method more sensitively detects cell-cycle-regulated transcription, and reveals subtle timing differences that are masked in the original population measurements. Our algorithm also explicitly learns distinct transcription programs for both mother and daughter cells, enabling us to identify 82 genes transcribed almost entirely in the early G1 in a daughter-specific manner.

In addition to the cell-cycle deconvolution algorithm, we introduce DOMAIN, a protein-protein interaction (PPI) network alignment method, which employs a novel direct-edge-alignment paradigm to detect conserved functional modules (e.g., protein complexes, molecular pathways) from pairwise PPI networks. By applying our approach to detect protein complexes conserved in yeast-fly and yeast-worm PPI networks, we show that our approach outperforms two widely used approaches in most alignment performance metrics. We also show that our approach enables us to identify conserved cell-cycle-related functional modules across yeast-fly PPI networks.

Eukaryotic Topoisomerase 2 is an essential enzyme that solves DNA topological problems such as DNA knotting, catenation, and supercoiling. It alters the DNA topology by introducing transient double strand break in one DNA duplex as a gate for the passage of another DNA duplex. Two different aspects of studies about eukaryotic Topoisomerase 2 will be covered in this thesis. In the first half of the thesis, we investigated conformational changes of human Topoisomerase 2 (hsTop2) in the presence of cofactors and inhibitors. In the second half, we focused on an unknown regulatory function in the C-terminal domain (CTD) of Drosophila Topoisomerase 2 (Top2).

In the project of studying enzyme conformational changes, we adapted a previously developed methodology, Pulse-Alkylation Mass Spectrometry, with monobromobimane to study the protein dynamics of hsTop2. Using this method, we captured the evidence of conformational changes in the presence of ATP and Mg2+ or the Top2 inhibitor, ICRF-193 which were not previously observed. Last, by using CTD truncated hsTop2, the increasing reactivity of Cys427 suggested the CTD domain might be tethered adjacent to the core enzyme.

Following the study of enzyme conformational changes, we switched gear to examine an interaction between Drosophila Top2 and Mus101, homolog of human TopBP1. We first found that Mus101 interacts with CTD of Top2 in a phosphorylation-dependent manner. Next, in the co-immunoprecipitation and pull-down experiments using truncated or mutant Top2 with various Ser to Ala substitutions, we mapped the binding motif to the last amino acids of Top2 and identified that phosphorylation of Ser1428 and Ser1443 is important for Top2 to interact with the N-terminus of Mus101, which contains BRCT1/2 domains (BRCT, BRCA1 C-terminus). The binding affinity of the N-terminal Mus101 with a synthetic phosphorylated peptide covering the last 25 amino acids of Top2 (with pS1428 and pS1443) was determined by surface plasmon resonance with a Kd of 0.57 μM. In an in vitro decatenation assay, Mus101 can specifically reduce the decatenation activity of Top2, and dephosphorylation of Top2 attenuates this response to Mus101. Next, we endeavored to establish a cellular system for testing the biological function of Top2-Mus101 interaction. Top2-silenced S2 cells rescued by Top220, truncation of 20 amino acids from the C-terminus of Top2, developed abnormally high chromosome numbers, which implies an infidelity in chromosome segregation during mitosis. Lastly, Top2-null flies rescued by Top2 with S1428A and S1443A were found to be viable but sterile. After investigating spermatogenesis, telophase of meiosis I was delayed, indicating Top2-Mus101 interaction is also important in segregating DNA in meiosis.

Lysine-specific demethylase 1 (LSD1/KDM1A) regulates transcriptional events by post-translational modifications of histone H3 tails at residues K4 an K9. This enzyme plays a vast number of roles in both normal cellular functions and diseases states. Increasingly it is appreciated that this enzyme, like most epigenetic regulators, does not function alone, but rather forms a catalytic subunit of much larger protein assemblies that congregate on chromatin to concertedly mediate transcriptional events. LSD1 in particular has been found in many different complexes, in many different tissues and can facilitate both activation and repression events.

Because of these roles, LSD1 is viewed as a potential therapeutic target. Significant effort has recently led to the development of highly selective and potent active-site inhibitors. These inhibitors have particularly shed light on the cancer-promoting activities of LSD1 in acute myeloid leukemia and small cell lung carcinoma. However, one failing of these strategies is that active site inhibition is incapable of differentiating between the multitude of functions LSD1 performs. We sought to address this issue by instead developing first-generation tools to explore protein-protein interaction disruption as an alternative strategy for inhibiting the enzyme.

To this end, we have carefully examined a well-characterized interaction between LSD1 and the scaffolding protein CoREST. Using this interaction as a template, we developed a probe we show can compete with CoREST for interaction with LSD1. Furthermore, we generated cell permeable versions of this probe and examined the effects in a model of breast cancer. We find that our probe can selectively inhibit estrogen signaling, a feat that was not possible with current small molecule inhibition or RNA interference technologies. We therefore we propose that disrupting interactions such as this is an excellent alternative for targeting “undruggable” proteins, but also may also expand the current therapeutic space by granting precise control over the individual functions of proteins.