Biology subjects

Tewari, J.

Publications and source records attributed to Tewari, J..

4 recordsLinked to original sources

bioRxiv2025

Benchmarking of signaling networks generated by large language models

Computational models of biochemical networks provide frameworks for predicting how molecular cues guide cell decisions. These models are typically limited by the time-intensive manual curation required to extract network mechanisms from incomplete literature. Here, we test whether general-purpose large language models (LLMs) can generate accurate models of signaling and metabolic networks. We find that general-purpose LLMs generate 24-65% of the reactions of literature-curated signaling networks for cardiomyocyte hypertrophy, myofibroblast activation, and mechanosignaling. Further, logic-based models based on these networks predict responses to perturbations with accuracies of 6-33%. In the context of metabolic modeling, LLMs are able to generate 64-91% of the reactions within the core Escherichia coli metabolic network and demonstrate highly variable accuracies in predicting substrate utilization. Current general-purpose LLMs generate biochemical networks with moderate accuracy, and this study provides a pipeline and benchmarks to guide future improvements.

systems biology↗

bioRxiv2023

Engineered odorant receptors illuminate structural principles of odor discrimination

A central challenge in olfaction is understanding how the olfactory system detects and distinguishes odorants with diverse physicochemical properties and molecular configurations. Vertebrate animals perceive odors via G protein-coupled odorant receptors (ORs). In humans, [~]400 ORs enable the sense of smell. The OR family is composed of two major classes: Class I ORs are tuned to carboxylic acids while Class II ORs, representing the vast majority of the human repertoire, respond to a wide variety of odorants. How ORs recognize chemically diverse odorants remains poorly understood. A fundamental bottleneck is the inability to visualize odorant binding to ORs. Here, we uncover fundamental molecular properties of odorant-OR interactions by employing engineered ORs crafted using a consensus protein design strategy. Because such consensus ORs (consORs) are derived from the 17 major subfamilies of human ORs, they provide a template for modeling individual native ORs with high sequence and structural homology. The biochemical tractability of consORs enabled four cryoEM structures of distinct consORs with unique ligand recognition properties. The structure of a Class I consOR, consOR51, showed high structural similarity to the native human receptor OR51E2 and yielded a homology model of a related member of the human OR51 family with high predictive power. Structures of three Class II consORs revealed distinct modes of odorant-binding and activation mechanisms between Class I and Class II ORs. Thus, the structures of consORs lay the groundwork for understanding molecular recognition of odorants by the OR superfamily.

neuroscience↗

bioRxiv2022

Structural basis of odorant recognition by a human odorant receptor

Our sense of smell enables us to navigate a vast space of chemically diverse odor molecules. This task is accomplished by the combinatorial activation of approximately 400 olfactory G protein-coupled receptors (GPCRs) encoded in the human genome1-3. How odorants are recognized by olfactory receptors (ORs) remains mysterious. Here we provide mechanistic insight into how an odorant binds a human olfactory receptor. Using cryogenic electron microscopy (cryo-EM), we determined the structure of active human OR51E2 bound to the fatty acid propionate. Propionate is bound within an occluded pocket in OR51E2 and makes specific contacts critical to receptor activation. Mutation of the odorant binding pocket in OR51E2 alters the recognition spectrum for fatty acids of varying chain length, suggesting that odorant selectivity is controlled by tight packing interactions between an odorant and an olfactory receptor. Molecular dynamics simulations demonstrate propionate-induced conformational changes in extracellular loop 3 to activate OR51E2. Together, our studies provide a high-resolution view of chemical recognition of an odorant by a vertebrate OR, providing insight into how this large family of GPCRs enables our olfactory sense.

biochemistry↗

bioRxiv2020

Estrogen and sex-dependent loss of the vocal learning system in female zebra finches

Sex hormones alter the organization of the brain during early development and coordinate various behaviors throughout life. In zebra finches, song learning is limited to males, and the associated song learning brain pathway only matures in males and atrophies in females. This atrophy can be reversed by giving females exogenous estrogen during early post-hatch development, but whether normal male song system development requires estrogen is uncertain. For the first time in songbirds, we administered exemestane, a potent third generation estrogen synthesis inhibitor, from the day of hatching until adulthood. We examined the behavior, brain, and transcriptome of individual song nuclei of these pharmacologically manipulated animals. We found that males with long-term exemestane treatment had diminished male-specific plumage, impaired song learning, but retained normal song nuclei sizes and most, but not all, of their specialized transcriptome. Consistent with prior findings, females with long-term estrogen treatment retained a functional song system, and we further observed their song nuclei had specialized gene expression profiles similar, but not identical to males. We also observed that different song nuclei responded to estrogen manipulation differently, with Area X in the striatum being the most altered by estrogen modulation. These findings support the hypothesis that song learning is an ancestral trait in both sexes, which was subsequently suppressed in females of some species, and that estrogen has come to play a critical role in modulating this suppression as well as refinement of song learning.

neuroscience↗