Browsing by Author "Wang, Yi"
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Item Open Access Aqueous Desolvation and Molecular Recognition: Experimental and Computational Studies of a Novel Host-Guest System Based on Cucurbit[7]uril(2012) Wang, YiMolecular recognition is arguably the most elementary physical process essential for life that arises at the molecular scale. Molecular recognition drives events across virtually all length scales, from the folding of proteins and binding of ligands, to the organization of membranes and the function of muscles. Understanding such events at the molecular level is massively complicated by the unique medium in which life occurs: water. In contrast to recognition in non-aqueous solvents, which are driven largely by attractive interactions between binding partners, binding reactions in water are driven in large measure by the properties of the medium itself. Aqueous binding involves the loss of solute-solvent interactions (desolvation) and the concomitant formation of solute-solute interactions. Despite decades of research, aqueous binding remains poorly understood, a deficit that profoundly limits our ability to design effective pharmaceuticals and new enzymes. Particularly problematic is understanding the energetic consequences of aqueous desolvation, an area the Toone and Beratan groups have considered for many years.
In this dissertation, we embark on a quest to shed new light on aqueous desolvation from two perspectives. In one component of this research, we improve current computational tools to study aqueous desolvation, employing quantum mechanics (QM), molecular dynamics (MD) and Monte Carlo (MC) simulations to better understand the behavior of water near molecular surfaces. In the other, we use a synthetic host, cucurbit[7]uril (CB[7]), in conjunction with a de novo series of ligands to study the structure and thermodynamics of aqueous desolvation in the context of ligand binding with atomic precision, a feat hitherto impossible. A simple and rigid macrocycle, CB[7] alleviates the drawbacks of protein systems for the study of aqueous ligand binding, that arise from conformational heterogeneity and prohibitive computational costs to model.
We first constructed a novel host-guest system that facilitates internalization of the trimethylammonium (methonium) group from bulk water to the hydrophobic cavity of CB[7] with precise (atomic-scale) control over the position of the ligand with respect to the cavity. The process of internalization was investigated energetically using isothermal titration microcalorimetry and structurally by nuclear magnetic resonance (NMR) spectroscopy. We show that the transfer of methonium from bulk water to the CB[7] cavity is accompanied by an unfavorable desolvation enthalpy of just 0.49±0.27 kcal*mol-1, a value significantly less endothermic than those values suggested from previous gas-phase model studies. Our results offer a rationale for the wide distribution of methonium in biology and demonstrate important limitations to computational estimates of binding affinities based on simple solvent-accessible surface area approaches.
To better understand our experimental results, we developed a two-dimensional lattice model of water based on random cluster structures that successfully reproduces the temperature-density anomaly of water with minimum computational cost. Using reported well-characterized ligands of CB[7], we probed water structure within the CB[7] cavity and identified an energetically perturbed cluster of water. We offer both experimental and computational evidence that this unstable water cluster provides a significant portion of the driving force for encapsulation of hydrophobic guests.
The studies reported herein shed important light on the thermodynamic and structural nature of aqueous desolvation, and bring our previous understanding of the hydrophobic effect based on ordered water and buried surface area into question. Our approach provides new tools to quantify the thermodynamics of functional group desolvation in the context of ligand binding, which will be of tremendous value for future research on ligand/drug design.
Item Open Access Carbon Gain and Allocation in Five Shade Intolerant Pinus Species(2021-12-08) Wang, YiPinus virginiana (Virginia pine), Pinus echinata (shortleaf pine), Pinus taeda (loblolly pine), Pinus elliottii (slash pine), and Pinus palustris (longleaf pine) are five of the most dominant shade-intolerant pine species in the southeast region. These five species have overlapping geographic ranges, tolerate poor soil conditions and low water availability conditions, and have relatively high volume growth rate. Among the five species, P. virginiana and P. echinata have the shortest needles of around 5-7 cm. P. taeda and P. elliottii have the intermediate needle length of around 15-22 cm, while P. palustris has the longest needles of around 30 cm. To compare the among species differences in biomass growth rate based on their physiology, morphology, and hydraulics related leaf traits, shoot and crown structure, and biomass allocation, we collected the data from an experimental site in Duke Forest and compared the performance of these five species when trees of the same age were grown under the same climate and soil conditions. Our study revealed distinct differences in allometric relationships and biomass allocation patterns among the five species. Analysis of leaf functional traits and crown structure showed variation in the ability to support leaf area at a given leaf mass, branch mass, and sapwood area across species. Finally, the differences in total biomass and wood production among species reflected the combined effect of leaf area index and biomass allocation pattern. We found that, when growing in one environment, species with intermediate needle length (P. taeda and P. elliottii) were more efficient in biomass production and volume growth while balancing the investment in intercepting light and maintaining hydraulic system. The results of this study indicated that growth-related functional traits, combined with biomass allocation patterns that favor stem and aboveground production, make P. taeda and P. elliottii among the fastest growing conifers with high timber values, regionally and globally.Item Open Access Chromatin Remodeling of Colorectal Cancer Liver Metastasis is Mediated by an HGF-PU.1-DPP4 Axis.(Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2021-10) Wang, Lihua; Wang, Ergang; Prado Balcazar, Jorge; Wu, Zhenzhen; Xiang, Kun; Wang, Yi; Huang, Qiang; Negrete, Marcos; Chen, Kai-Yuan; Li, Wei; Fu, Yujie; Dohlman, Anders; Mines, Robert; Zhang, Liwen; Kobayashi, Yoshihiko; Chen, Tianyi; Shi, Guizhi; Shen, John Paul; Kopetz, Scott; Tata, Purushothama Rao; Moreno, Victor; Gersbach, Charles; Crawford, Gregory; Hsu, David; Huang, Emina; Bu, Pengcheng; Shen, XilingColorectal cancer (CRC) metastasizes mainly to the liver, which accounts for the majority of CRC-related deaths. Here it is shown that metastatic cells undergo specific chromatin remodeling in the liver. Hepatic growth factor (HGF) induces phosphorylation of PU.1, a pioneer factor, which in turn binds and opens chromatin regions of downstream effector genes. PU.1 increases histone acetylation at the DPP4 locus. Precise epigenetic silencing by CRISPR/dCas9KRAB or CRISPR/dCas9HDAC revealed that individual PU.1-remodeled regulatory elements collectively modulate DPP4 expression and liver metastasis growth. Genetic silencing or pharmacological inhibition of each factor along this chromatin remodeling axis strongly suppressed liver metastasis. Therefore, microenvironment-induced epimutation is an important mechanism for metastatic tumor cells to grow in their new niche. This study presents a potential strategy to target chromatin remodeling in metastatic cancer and the promise of repurposing drugs to treat metastasis.Item Open Access Evaluating the Value for Money of Precision Medicine from Early Cycle to Market Access: a comprehensive review of approaches and challenges.(Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 2023-05) Chen, Wenjia; Wang, Yi; Zemlyanska, Yaroslava; Butani, Dimple; Wong, Nigel Chong Boon; Virabhak, Suchin; Matchar, David Bruce; Teerawattananon, YotObjectives
This study aimed to perform a comprehensive review of modelling approaches, methodological and policy challenges in the economic evaluation (EE) of precision medicine (PM) across clinical stages.Methods
First, a systematic review was performed to assess the approaches of EEs in the past 10 years. Next, a targeted review of methodological papers was conducted for methodological and policy challenges in performing EEs of PM. All findings were synthesized into a structured framework that focused on Patient population, Intervention, Comparator, Outcome, Time, Equity and ethics, Adaptability and Modelling aspects, named the "PICOTEAM" framework. Finally, a stakeholder consultation was conducted to understand the major determinants of decision making in PM investment.Results
In 39 methodological papers, we identified major challenges to the EE of PM, including that PM applications involve complex and evolving clinical decision space, clinical evidence is sparse due to small subgroups and complex pathways in PM settings, a one-time PM application may have lifetime or intergenerational impacts but long-term evidence is often unavailable, equity and ethics concerns are exceptional. In 275 EEs of PM, current approaches did not sufficiently capture the value of PM but that of targeted therapies, nor differentiate Early EEs from Conventional EEs. Finally, policy makers perceived the budget impact, cost-savings and cost-effectiveness of PM as the most important determinants in decision-making.Conclusions
There is an urgent need to modify existing guidelines or develop new reference case that fits into the new healthcare paradigm of PM to guide decision making in R&D and market access.Item Open Access Innovation and Development of Biomedical Industry Clusters in Jiangsu Province: A Technological Perspective on Leading Enterprises(2023) Wang, YiAbstractBackground: The vibrant state of the biopharmaceutical industry in Jiangsu Province, China, showcasing its strategic focus and significant growth. The province has implemented various policies to accelerate high-quality development, emphasizing innovation, intelligent and digital transformation. The industry, organized around biological drugs, chemical drugs, traditional Chinese medicine, and medical equipment, has become a national leader, with impressive revenue and output values. The study identifies research gaps related to the role of patents in the industry, highlighting the need for a micro-level analysis, better linkage between patents and economic outcomes, exploration of innovation capabilities, consideration of patent quality, and understanding temporal and geographical specificities. The research aims to address these gaps by assessing the impact of patent indicators at national, provincial, and enterprise levels, providing insights for policymakers and industry stakeholders to foster innovation and growth in the biomedical sector in Jiangsu Province. Methods: This research employs a comprehensive three-tiered analysis to explore the intricate interplay between innovative indicators and economic output in the biomedical industry. The study spans the national, provincial, and enterprise levels, encompassing five diverse countries, all 31 provinces in mainland China, and the top ten pharmaceutical companies globally, domestically, and in Jiangsu Province. In collaboration with the Jiangsu Intellectual Property Protection Center, the study compiles an extensive dataset. This dataset, meticulously curated from publicly available and non-sensitive patent data, includes variables such as patent applications, authorizations, PCT applications, and application growth rates. Economic data, including GDP and market values, is sourced from reputable institutions like the World Bank, the National Bureau of Statistics of China, and Torreya, a renowned biomedical industry innovation consulting company. Inclusive approach ensures a comprehensive representation for a cohort of 30 biomedical enterprises. The study extracts pertinent patent information into STATA for detailed analysis. The economic outcomes are measured through GDP at the national and provincial levels and market value at the enterprise level. The study meticulously examines the nuances of GDP computation and derives the 2022 national GDP data from the World Bank and provincial GDP data from the Bureau of Statistics of the People's Republic of China. Market value, or Market Capitalization, is defined and measured based on the total value of shares issued by listed companies, mainly in US dollars, with data sourced from Torreya, China Securities Regulatory Commission, and the Information Registration Center of the State Administration for Market Regulation. The biomedical patent indicators, comprising patent application numbers, PCT application numbers, patent authorized numbers, and patent in-force numbers, are systematically analyzed at national, provincial, and enterprise levels. Statistical methods, including one-way analysis of variance (ANOVA), correlation analysis, and linear regression analysis, are consistently applied across all levels to scrutinize the association between patent data indicators and economic output. The combined approach of correlation and regression analysis aims to derive precise patent innovation indicators and their impact on economic output, enhancing the clarity and intuitiveness of the research findings. Results: On the global stage, the findings reveal a robust growth in biomedical patents from 2000 to 2022. China emerges as a major player, exhibiting substantial patent applications (1804099 pcs), authorizations (35131 pcs), and PCT patents (1115204 pcs). Correlation analyses indicate positive relationships between a country's GDP and patent-related metrics, further validated by linear regression. These results emphasize the importance of economic strength in fostering biomedical innovation. Turning our attention to Chinese provinces, our investigation spans 31 regions, unraveling diverse patterns in patent outputs. Provinces with higher GDP consistently demonstrate elevated patent activity, showcasing a symbiotic relationship between economic prosperity and biomedical innovation. Correlation and regression analyses reaffirm these findings, emphasizing the quantitative impact of economic factors on biomedical research and development. At the micro-level, the study scrutinizes the top 10 pharmaceutical companies globally, in China, and within Jiangsu province. Striking disparities in patent application numbers, patents in force, and PCT applications highlight China's accelerating innovation capabilities. The correlation analysis establishes positive associations between market value and key patent indices (Coef. for number of patent application, patent in force, and PCT application, respectively 0.74, 0.71, 0.73,) emphasizing the pivotal role of patents in driving economic success for pharmaceutical companies. Linear regression analyses provide nuanced insights into the impact of patent indices on market value. The positive coefficients for patents in force (Coeff =9.77; 95% CI, 8.57 ~ 10.97) and PCT applications (Coeff=21.13; 95% CI, 18.68 ~ 23.58) signify their significant contribution to market values. The accompanying scatterplots visually reinforce these relationships, illustrating a positive linear correlation. Conclusions: Particularly, conducting a micro-level analysis, this research reveals individual pharmaceutical companies' contributions often overlooked in macro-level studies. The nuanced exploration of the relationship between patent indicators and economic outcomes emphasizes the positive correlation between regional economic levels and patent indicators, particularly in the pharmaceutical industry. At the enterprise level, the research establishes a connection between patent numbers and market competitiveness, with more patents associated with stronger market positions. Comparisons with other countries and Chinese provinces highlight strategic gaps and position Jiangsu as a leader in innovation capabilities. The study underscores the critical importance of patent quality over quantity, advocating for strategies that prioritize high-quality patents to drive sustained growth and competitiveness in the biomedical industry.
Item Open Access Intravital imaging of mouse embryos(Science, 2020-04-10) Huang, Qiang; Cohen, Malkiel A; Alsina, Fernando C; Devlin, Garth; Garrett, Aliesha; McKey, Jennifer; Havlik, Patrick; Rakhilin, Nikolai; Wang, Ergang; Xiang, Kun; Mathews, Parker; Wang, Lihua; Bock, Cheryl; Ruthig, Victor; Wang, Yi; Negrete, Marcos; Wong, Chi Wut; Murthy, Preetish KL; Zhang, Shupei; Daniel, Andrea R; Kirsch, David G; Kang, Yubin; Capel, Blanche; Asokan, Aravind; Silver, Debra L; Jaenisch, Rudolf; Shen, XilingEmbryonic development is a complex process that is unamenable to direct observation. In this study, we implanted a window to the mouse uterus to visualize the developing embryo from embryonic day 9.5 to birth. This removable intravital window allowed manipulation and high-resolution imaging. In live mouse embryos, we observed transient neurotransmission and early vascularization of neural crest cell (NCC)–derived perivascular cells in the brain, autophagy in the retina, viral gene delivery, and chemical diffusion through the placenta. We combined the imaging window with in utero electroporation to label and track cell division and movement within embryos and observed that clusters of mouse NCC-derived cells expanded in interspecies chimeras, whereas adjacent human donor NCC-derived cells shrank. This technique can be combined with various tissue manipulation and microscopy methods to study the processes of development at unprecedented spatiotemporal resolution.Item Open Access Mapping the value for money of precision medicine: a systematic literature review and meta-analysis.(Frontiers in public health, 2023-01) Chen, Wenjia; Wong, Nigel Chong Boon; Wang, Yi; Zemlyanska, Yaroslava; Butani, Dimple; Virabhak, Suchin; Matchar, David Bruce; Prapinvanich, Thittaya; Teerawattananon, YotObjective
This study aimed to quantify heterogeneity in the value for money of precision medicine (PM) by application types across contexts and conditions and to quantify sources of heterogeneity to areas of particular promises or concerns as the field of PM moves forward.Methods
A systemic search was performed in Embase, Medline, EconLit, and CRD databases for studies published between 2011 and 2021 on cost-effectiveness analysis (CEA) of PM interventions. Based on a willingness-to-pay threshold of one-time GDP per capita of each study country, the net monetary benefit (NMB) of PM was pooled using random-effects meta-analyses. Sources of heterogeneity and study biases were examined using random-effects meta-regressions, jackknife sensitivity analysis, and the biases in economic studies checklist.Results
Among the 275 unique CEAs of PM, publicly sponsored studies found neither genetic testing nor gene therapy cost-effective in general, which was contradictory to studies funded by commercial entities and early stage evaluations. Evidence of PM being cost-effective was concentrated in a genetic test for screening, diagnosis, or as companion diagnostics (pooled NMBs, $48,152, $8,869, $5,693, p < 0.001), in the form of multigene panel testing (pooled NMBs = $31,026, p < 0.001), which only applied to a few disease areas such as cancer and high-income countries. Incremental effectiveness was an essential value driver for varied genetic tests but not gene therapy.Conclusion
Precision medicine's value for money across application types and contexts was difficult to conclude from published studies, which might be subject to systematic bias. The conducting and reporting of CEA of PM should be locally based and standardized for meaningful comparisons.