Biology subjects

Han, J. M.

Publications and source records attributed to Han, J. M..

5 recordsLinked to original sources

bioRxiv2026

Synthesis-aware generative design in trillion-scale chemical spaces for automated drug discovery

Autonomous drug discovery via generative molecular design is critically bottlenecked by the production of chemically intractable structures. Multi-trillion-scale make-on-demand libraries guarantee synthetic feasibility, but conventional virtual screening cannot efficiently navigate these vast spaces or address multi-parameter optimization. We introduce Hyper Screening X, a generative AI framework integrating structure-based design with automated synthesis hardware. By encoding deterministic reaction logic in a generative flow network, the framework evaluates only 10 million candidates to navigate an 11-trillion-compound space, jointly optimizing physicochemical properties while ensuring compatibility with automated synthesis. Prospective validation against an SLC1A5 variant with a cryptic interface yielded a 96% synthesis success rate and a 50% functional hit rate, identifying two first-in-class lead compounds. This synthesis-aware strategy advances autonomous, closed-loop drug discovery.

bioinformatics↗

bioRxiv2026

Metabolic signals regulate resuscitation speed of antibiotic persister bacteria during infection

All living organisms adjust their metabolism in response to environmental changes. Under unfavorable conditions, organisms enter a state of dormancy by halting metabolism, enabling survival. Dormant bacteria become highly tolerant to antibiotics-a phenomenon called persistence. Here, we demonstrate that selective metabolic reprogramming controls the resuscitation speed of persister after antibiotic exposure. Using multi-omics and in silico modeling, we found that dormant bacteria reprogram metabolic pathways to modulate persister awakening. Accumulation of L-serine and reduction of arginine drive rapid resuscitation. L-serine promotes cysteine biosynthesis and motility while reducing energy metabolism to facilitate rapid resuscitation. In contrast, arginine slows regrowth from dormancy by enhancing ethanol-aldehyde and energy metabolism. L-serine and arginine can, respectively, promote or inhibit the regrowth of antibiotic persister cells in macrophages and mouse models, and regulate the awakening speed of Salmonella, E. coli, and methicillin-resistant Staphylococcus aureus (MRSA). These findings suggest new strategies to target chronic bacterial infections. TeaserL-serine speeds and arginine slows the awakening of antibiotic persisters, revealing targets for chronic infection.

microbiology↗

bioRxiv2021

Mechanistic Gene Networks Inferred from Single-Cell Data are Better Predictors than Neural Networks.

AO_SCPLOWBSTRACTC_SCPLOWWith advances in single-cell techniques, measuring gene dynamics at cellular resolution has become practicable. In contrast, the increased complexity of data has made it more challenging computationally to unravel underlying biological mechanisms. Thus, it is critical to develop novel computational methods capable of dealing with such complexity and of providing predictive deductions from such data. Many methods have been developed to address such challenges, each with its own advantages and limitations. We present an iterative regression algorithm for inferring a mechanistic gene network from single-cell data. Using this regression, we infer a developmental model for the gene dynamics in Drosophila melanogaster blastoderm embryo. Our results show that the predictive power of the inferred model is higher than that of other models inferred with least squares and ridge regressions. Furthermore, model predictions of the gene dynamics are more accurate than predictions made with neural networks. This holds true even in the limit of small sample sizes. We compare predictions for various gene knockouts with published experimental results, finding substantial agreement. We also make predictions for gene dynamics under various gene network perturbations, impossible in non-mechanistic models.

systems biology↗

bioRxiv2021

Regulation of Interorganellar Ca2+ Transfer and NFAT Activation by the Mitochondrial Ca2+ Uniporter

Mitochondrial Ca2+ uptake is crucial for coupling receptor stimulation to cellular bioenergetics. Further, Ca2+ uptake by respiring mitochondria prevents Ca2+-dependent inactivation (CDI) of store-operated Ca2+ release-activated Ca2+ (CRAC) channels and inhibits Ca2+ extrusion to sustain cytosolic Ca2+ signaling. However, how Ca2+ uptake by the mitochondrial Ca2+ uniporter (MCU) shapes receptor-evoked interorganellar Ca2+ signaling is unknown. Here, we generated several cell lines with MCU-knockout (MCU-KO) as well as tissue-specific MCU-knockdown mice. We show that mitochondrial depolarization, but not MCU-KO, inhibits store-operated Ca2+ entry (SOCE). Paradoxically, despite enhancing Ca2+ extrusion and promoting CRAC channel CDI, MCU-KO increased cytosolic Ca2+ in response to store depletion. Further, physiological agonist stimulation in MCU-KO cells led to enhanced frequency of cytosolic Ca2+ oscillations, endoplasmic reticulum Ca2+ refilling, NFAT nuclear translocation and proliferation. However, MCU-KO did not affect inositol-1,4,5-trisphosphate receptor activity. Mathematical modeling supports that MCU-KO enhances cytosolic Ca2+, despite limiting CRAC channel activity.

cell biology↗

bioRxiv2018

A mathematical model of calcium dynamics: Obesity and mitochondria-associated ER membranes

Multiple cellular organelles tightly orchestrate intracellular calcium (Ca2+) dynamics to regulate cellular activities and maintain homeostasis. The interplay between the endoplasmic reticulum (ER), a major store of intracellular Ca2+, and mitochondria, an important source of adenosine triphosphate (ATP), has been the subject of much research, as their dysfunctionality has been linked with metabolic diseases. Interestingly, through out the cells cytosolic domain, these two organelles share common microdomains called mitochondria-associated ER membranes (MAMs), where their membranes are in close apposition. The role of MAMs is critical for intracellular Ca2+ dynamics as they provide hubs for direct Ca2+ exchange between the organelles. A recent experimental study reported correlation between obesity and MAM formation in mouse liver cells, and obesity-related cellular changes that are closely associated with the regulation of Ca2+ dynamics. We constructed a mathematical model to study the effects of MAM Ca2+ dynamics on global Ca2+ activities. Through a series of model simulations, we investigated cellular mechanisms underlying the altered Ca2+ dynamics in the cells under obesity. We found that the formation of MAMs is negatively correlated with the amplitude of cytosolic Ca2+ activities, but positively correlated with that of mitochondrial Ca2+ dynamics and the overall frequency of Ca2+ oscillations. We predict that, as the dosage of stimulus gradually increases, liver cells from obese mice will reach the state of saturated cytosolic Ca2+ concentration at a lower stimulus concentration, compared to cells from healthy mice.\n\nAuthor summaryIt is well known that intracellular Ca2+ oscillations carry encoded signals in their amplitude and frequency to regulate various cellular processes, and accumulating evidence supports the importance of the interplay between the ER and mitochondria in cellular Ca2+ homeostasis. Miscommunications between the organelles may be involved in the development of metabolic diseases. Based on a recent experimental study that spotlighted a correlation between obesity and physical interactions of the ER and mitochondria in mouse hepatic cells, we constructed a mathematical model as a probing tool that can be used to computationally investigate the effects of the cellular changes linked with obesity on global cellular Ca2+ dynamics. Our model successfully reproduced the experimental study that observed a positive correlation between the ER-mitochondrial junctions and the magnitude of mitochondrial Ca2+ responses. We postulate that hepatic cells from lean animals exhibit Ca2+ oscillations that are more robust under higher concentrations of stimulus, compared to cells from obese animals.

cell biology↗