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Target identification by chemical proteomics and bioinformatic investigations with small molecule ligands
No full textUnderstanding the protein targets and mechanisms of action of bioactive small molecules remains a central goal in chemical biology and drug discovery. Unbiased approaches, particularly chemical proteomics and systems-level bioinformatics, have emerged as powerful strategies to uncover the molecular interactions and biological consequences of small molecule engagement in cells. In this thesis, I apply these complementary methodologies—activity-based protein profiling (ABPP), photo-affinity labeling (PAL), and bioinformatic analyses—to investigate two distinct but mechanistically rich chemical spaces: opioid analgesics such as heroin and morphine, and cereblon (CRBN)-binding immunomodulatory drugs (IMiDs) that induce targeted protein degradation.
Chapter 1 introduces the conceptual and methodological foundation for this work, beginning with a background on ABPP and PAL, highlighting their ability to turn small molecules into molecular probes that illuminate their target landscapes through quantitative mass spectrometry. The chapter also introduces gene ontology (GO) annotations and the database for annotation, visualization, and integrated discovery (DAVID) bioinformatics suite, which are essential for contextualizing proteomic hit lists. Further, I provide an overview of machine learning principles and illustrate how these computational tools can accelerate target identification and therapeutic discovery. The chapter concludes with two thematic deep dives: a historical and pharmacological overview of opioids and their receptors and the development of chemical probes to study them, and a survey of CRBN biology, including the evolution of IMiD-based molecular glues and the discovery of the endogenous CRBN degron—the cyclic imide degron—formed either spontaneously from protein damage or enzymatically via Protein-L-isoaspartate O-methyltransferase (PCMT1).
Chapter 2 describes the design, synthesis, and characterization of novel chemical probes for morphine and heroin, including photo-click morphine (PCM-1, PCM-2) and the acyl-donating probe Di-Alkynyl-Acyl-Morphine (DAAM). These tools were validated for their ability to engage opioid receptors and induce G-protein signaling. Confocal imaging revealed receptor-independent localization of these probes to lysosomes across diverse cell lines. Chemoproteomic analysis uncovered voltage-dependent anion channel 1 (VDAC1) as a shared target across all probes and identified lysine 234 of solute carrier family 25 member 3 (SLC25A3) as a selective site of acylation by DAAM. This residue was later confirmed to be directly acetylated by heroin itself, representing one of the first demonstrations of small-molecule-mediated post-translational modification by heroin. These findings suggest potential mechanisms for the mitochondrial and metabolic dysfunctions associated with chronic heroin use.
Chapter 3 focuses on the proteomic and computational reanalysis of the Broad Institute’s PRISM screen using the CRBN-dependent degrader DEG-35. By separating wild-type from mutant populations and refining statistical comparisons, I report biologically meaningful indicators of sensitivity, including intact p53 signaling, protein Mdm4 (MDM4) dependency, and alterations in the switch/sucrose non-fermentable (SWI/SNF) complex. I report the development of a multilayer perceptron (MLP) model trained on the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) viability data to predict DEG-35 sensitivity across the extended DepMap cell line repository. The model achieved strong performance (Area under the Receiver Operative Characteristic Curve (AUROC) = 0.98) and accurately identified sensitive cell lines, including SCCOHT-1, which is actively being experimentally validated. This work highlights the potential of integrating chemogenomics data with machine learning to stratify responders and uncover mechanistic biomarkers.
Chapter 4 presents a novel inversion of traditional GO analysis using the DAVID tool: instead of applying GO terms post hoc to hit lists, I used it as a filtering method for hypothesis generation. Starting with all human proteins ending in C-terminal asparagine or glutamine—potential substrates for PCMT1-mediated cyclic imide formation—I performed annotation clustering and literature-driven prioritization. From this list, Hairy and Enhancer of Split 1 (HES1) emerged as a top candidate. In vitro assays confirmed that PCMT1 catalyzes the formation of the cyclic imide degron on the HES1 C-terminus, enabling CRBN binding. Full-length HES1 showed PCMT1-dependent CRBN engagement, and follow-up experiments in SH-SY5Y cells demonstrated that knockout of either PCMT1 or CRBN led to impaired neuronal differentiation, suggesting a role for this degradation pathway in developmental timing. These findings advance our understanding of CRBN’s endogenous substrates and open new directions for exploring its role in neurodevelopment.
Together, this thesis demonstrates how integrative chemical biology—uniting chemical proteomics, computational modeling, and bioinformatics—can illuminate the complex interactions between small molecules and the proteome, uncover new biological mechanisms, and inspire new directions for therapeutic or biological discovery.Chemistry and Chemical Biolog
The Production of Democracy
No full textOur economic cooperation is marked by hierarchical relationships. Most people work under the authority of unaccountable managers, while a minority of wealthy investors shape the future of productive enterprises. Yet, economic hierarchy is rarely considered as problematic as political hierarchy such as oligarchy or restrictions on voting rights. Democracy is thought to impose demanding requirements on state political institutions, but at best overridable recommendations on economic institutions. Behind this view lies the idea that the democratic state controls and regulates the economy from a higher standpoint of equality. However powerful economic superiors may be, they are ultimately subject to a political system that treats everyone as equals. Thus, democratizing the economy is unnecessary; political democracy can justify economic hierarchy. I call this line of thought the State-above-the-Economy Argument. My dissertation argues against it, in favor of what I call a dual-core theory of democracy.
My argument proceeds in three steps. First, I clarify the political nature of the modern economy and the kind of justification it demands. Our economic cooperation is structured through asymmetrical subjection to power and authority, effected through society’s overarching institutional framework. These institutionalized relations of subjection constitute an informal political system, which must therefore be evaluated according to the principles of democracy, not just efficiency.
Second, while economic institutions are often thought to be exempt from the requirements of democracy by virtue of being governed by a democratic state, I argue that this view is mistaken. The democratic state is itself constrained in its power, legitimacy, and knowledge by the very economic structure it is supposed to govern. Democracy’s demands on the economy cannot be outsourced to the state; economic institutions themselves must be brought within the scope of democratic justification.
Finally, how are we to recover the democratic ideal in light of the economy’s profound constraint on politics? A common response demands moral discipline: economic actors must subordinate themselves to the sovereign democratic state’s will. I reject this view. Contestation in and through the economy, when properly structured, can be a force for democracy. Thus, the question is not whether but how economic rights constrain political decision-making. Rather than seeking to insulate politics from economic power, we must theorize democracy as a justifiable form of interdependence between the state and the economy.Philosoph
Designing for Decentralized Finance through Differentiable Optimization, and a Study of Bayesian Optimization
No full textDecentralized finance (DeFi) is the concept of building financial infrastructures without relying on centralized intermediaries. A notable development in DeFi is the creation of decentralized exchanges (DEXs), which operate as smart contracts on a blockchain. Due to the high cost of on-chain operations, automated market makers (AMMs) such as Uniswap v3 have emerged as the prevailing model of liquidity provision on DEXs. Two closely related research questions arise in the DeFi space: (1) What are the optimal strategies of liquidity providers given an AMM design such as Uniswap v3? (2) How should the design of AMMs be optimized to achieve objectives such as profit maximization? This thesis addresses these two central research questions using computational methods, in particular, through differentiable optimization.
Chapters 2 and 3 study the optimal strategies of liquidity providers (LPs) in Uniswap v3. In both chapters' formulations, the expected utility of an LP is differentiable with respect to its liquidity allocation under any exogenous price sequence, enabling differentiable optimization of LP strategies. With the formulation of a convex stochastic optimization problem that can be solved in a differentiable manner, Chapter 2 explores optimal static LP strategies in economic settings with varying factors such as an LP's belief about price dynamics, risk aversion, and for different specifications of the Uniswap v3 liquidity pool. Understanding LP strategies also leads to insights into the design of Uniswap v3 liquidity pools. Under a similar optimization framework, Chapter 3 extends from static LP strategies to dynamic LP strategies, specifically LP strategies that reallocate liquidity whenever the price movement reaches a certain threshold. These proposed dynamic strategies—particularly context-dependent variants modeled by a neural network, which adapt the shape of liquidity allocation to contextual information such as price and moving average of non-arbitrage trade volume at the time of reallocation—are shown to lead to significant gains compared to static LP strategies.
Taking a broader perspective on AMM design, Chapter 4 optimizes market-making mechanisms for a single trade in settings with multiple traded goods, seeking market maker profit maximization under adverse selection. Conjectures of optimal mechanisms are generated using tools of differentiable economics, which uses differentiable optimization for economic design. To prove the optimality of proposed mechanisms, a duality theorem is established between the market-making mechanism design problem and an optimal transport problem. This approach of combining differentiable economics with theoretical analysis is used to develop a parameterized class of optimal market-making mechanisms. These results also establish that, in some cases, the optimal market maker across multiple goods must use complex bundling. Additional conjectures about the structure of optimal mechanisms are presented, and an empirical optimality bound is established for some conjectures by approximately solving the dual with linear programming.
The second part of this thesis studies transfer learning of the Gaussian process (GP) prior in Bayesian optimization (BO), a widely used black-box function optimization method. Previous GP-based transfer learning methods for BO are limited to utilizing historical data collected from black-box functions with the same domain as the new black-box function to be optimized. The proposed method, model pre-training on heterogeneous domains (MPHD), employs a neural network that maps from domain-specific contextual information to specifications of hierarchical GPs for a given domain. As a result, MPHD is able to transfer knowledge across heterogeneous domains such as hyperparameter-tuning for different machine learning models. It is shown through theoretical analysis and empirical results that MPHD is a practical transfer learning method for BO, with demonstrations of competitive performance on challenging real-world hyperparameter-tuning tasks.Engineering and Applied Sciences - Computer Scienc
ボリビア 2025 年大統領選挙を読み解く―経済危機のなかでの政権交代（論稿）
Get PDFボリビアでは、2025 年8 月17 日の第一回投票、同年10 月19 日の決選投票を経て、ロドリゴ・パスが新大統領に選ばれた。2006-19 年および2021-25 年の長期にわたり政権を握ってきた社会主義運動党（Movimiento al Socialismo: MAS）は、第一回投票で低い得票率しか得られず、決選投票にも進めなかった。本稿は、この2025 年選挙のプロセスを概説し、政権交代に至った原因を読み解くことを目的とする。最大の理由と考えられるのは経済投票である。2024 年頃から、中銀の外貨準備が底をついたことによる為替下落や燃料不足に端を発した経済危機が目にみえるようになった。経済危機は構造的な原因を背景とするものであり、経済財務大臣から大統領となったルイス・アルセもマクロ経済の不均衡を是正することができなかった。他方で、与党のMAS はエボ・モラレス元大統領の復権を求めるグループとそれ以外とに分裂した。足元の経済課題への拙い対応とMAS および野党における候補者の乱立が、政権交代を促したと考えられる。PJa/33/Ra2articl
Shadow Economies and State Disconnection: Myanmar’s Policy Paradox
Get PDFapplication/pdfIDP000993_001This paper examines how well-intentioned economic policies have contributed to the growth of the shadow economy in Myanmar. The shadow economy includes informal activities in trade, investment, and foreign exchange that operate outside effective regulation. Many of these practices lie in an ambiguous space that is neither fully legal nor entirely illegal. The study argues that policy interventions designed to reduce informality frequently produce the opposite outcome. Evidence from periods before and after the 2021 coup shows that unrealistic policies detached from market realities and administrative capacity alienate economic actors from formal institutions. These dynamics make informality a rational response to structural limitations. As informal responses deepen, the shadow economy becomes increasingly entrenched.technical repor
Impact of Brexit on the Utilization of Regional Trade Agreements: Evidence from Japan’s Imports
Get PDFapplication/pdfIDP000987_001After Brexit, the rules of origin specified in the Japan-European Union (EU) Economic Partnership Agreement (EPA) disallow the accumulation of inputs from the UK. Similarly, the Japan-United Kingdom (UK) EPA does not permit the accumulation of EU inputs in the export of certain products. Therefore, Brexit could have reduced the use of preferential tariffs established by these EPAs. We investigate this hypothesis by examining the utilization rates of the Japan-EU and Japan-UK EPAs for imports from the EU and the UK in Japan from 2019 to 2024. We found that Brexit did not significantly affect the utilization rates of the Japan-EU EPA for exports from European nations to Japan. Conversely, Brexit significantly adversely impacted EPA utilization rates for exporting products that did not allow the accumulation of EU inputs from the UK to Japan. However, this unfavorable effect was observed only in the first year of the Japan-UK EPA.technical repor
Structural Reorganization of ASEAN Price Transmission Networks: A Network Perspective on Global Shock Propagation
No full textapplication/pdfIDP000995_001This study examines structural changes in international price transmission within an ASEAN-centered network using an input–output price framework and network analysis for 2007–2023. The results show that dominant hub roles have weakened and become more dispersed, while the network’s center of gravity has shifted toward East Asia, placing ASEAN economies in more peripheral positions. Although the number of transmission linkages has not fully recovered after global shocks at the network level, link-strength distributions within ASEAN have become more dispersed, indicating that these economies reconnect through a limited set of diversified relationships rather than maximizing linkages. This selective reorganization has important implications for the resilience of regional price systems to international inflationary shocks.technical repor
Physiological, morphological, synaptic, and behavioral analyses of genetically defined myelinated nociceptors
No full textPain can be both devastating to individuals and costly to the healthcare system. Yet, our understanding of pain biology and the primary sensory neurons that drive pain, nociceptors, is incomplete. We recently generated two mouse lines, Smr2Cre and Bmpr1bCre, that label A fiber high-threshold mechanoreceptors (A-HTMRs) in hairy skin and hypothesized that the labeled neurons are myelinated nociceptors. Here, we report on physiological, morphological, functional, and synaptic analyses of genetically defined myelinated nociceptors in non-hairy, or glabrous, skin to understand their unique contribution to the experience of pain. The A-HTMRs are found to be among the few somatosensory neuron types capable of evoking place aversion and nocifensive behaviors in response to minimal stimulation. Consistent with the original definition of a
nociceptor, these neurons are activated only by very intense stimuli. Both A-HTMR populations are necessary for protective responses to sharp mechanical stimuli. These protective neurons densely innervate the skin and a variety of other organs, including joints and cranial meninges. Centrally, A-HTMRs form unique projections that span multiple spinal segments and terminate in the superficial and deep laminae of the spinal cord dorsal horn, where they form monosynaptic connections on projection neurons of the anterolateral tract. A-HTMRs also engage a local spinal reflex circuit that enables quick paw withdrawal in response to damaging stimuli. Thus, A-HTMRs are bona fide myelinated nociceptors with unique physiological, morphological, and synaptic properties. Future work on characterizing and manipulating these neurons may yield important insights for the development of analgesics.Neuroscienc