Receptor proteins, expressed on the cell surface or within the cell, bind to different signaling molecules, known as ligands, initiating cellular responses. Taste receptors, expressed in oral tissues, interact with tastants, the molecules responsible for the sensation of taste. Bitter taste receptors (T2Rs) are responsible for the sensation of bitter taste. However, apart from oral tissue, these receptors are also expressed in the neuropod cells of the gastrointestinal tract, which are responsible for transmitting signals from the gut to the brain. Thus, T2Rs might play a crucial role in maintaining the gut-brain axis.
25 types of human T2Rs have been identified to date. However, due to certain complexities, the structure of most of these receptors is not yet elucidated. In recent times, AI-based prediction models have been used to understand protein structure accurately. Previously, a Nobel Prize-winning artificial intelligence (AI)-based model, AlphaFold2 (AF2), was utilized to decipher the structures of T2Rs. However, with the advancement in technology, the model has been updated to its latest version, AlphaFold3 (AF3). The latest model allows a more detailed structural prediction compared to the previous version.
Hence, in this study, a group of researchers, led by Professor Naomi Osakabe from Shibaura Institute of Technology, decided to analyze the structure of T2Rs using the AF3 model and compare the accuracy with the results from the AF2-based prediction study and the available three-dimensional structures of the two T2Rs, T2R14 and T2R46. “The expression of bitter taste receptors in the gastrointestinal tract indicates that they are involved in maintaining the gut-brain axis, glucose tolerance, and appetite regulation. Hence, understanding the structure can provide a better insight into its function,” mentioned Prof. Osakabe as the main motivation behind this study. The paper was made available online on July 14, 2025, and was published in Volume 11 of the journal Current Research in Food Science on July 22, 2025. This article has been co-authored by Takafumi Shimizu and Rio Ohno, from Shibaura Institute of Technology, and Professor Vittorio Calabrese, from the University of Catania.
The researchers obtained the amino acid sequences of all human T2Rs from the UniProt database and used the AF3 model to predict their three-dimensional structures. For comparison, previously generated AF2 prediction data were retrieved from the AlphaFold database. The experimentally determined structures of T2R14 and T2R46 were sourced from the Protein Data Bank (PDB). Various software tools were employed for structure visualization, alignment, and accuracy assessment.
The analysis revealed that AF3 provided consistently more accurate structural predictions than AF2. For T2R14, predictions were benchmarked against 115 cryo-EM structures, and AF3 showed the higher agreement with experimental data. Similarly, for T2R46, comparisons with three experimentally resolved structures confirmed that AF3 achieved the closest match in all cases.
Similarities in the structure of the T2Rs were also analyzed for this study. For these receptors, part of the protein remains inside the cell, known as the intracellular region, while another part stays outside the cell (extracellular region). The interaction with signal molecules happens in the extracellular region. The study demonstrated that there are more structural similarities and consistencies among the intracellular regions of the T2Rs. The extracellular region of the receptors shows significant structural variation. “Clustering of proteins is based on their structural similarity and dissimilarity. Based on our findings, we divided the T2Rs into three different clusters,” states Prof. Osakabe. These patterns may help researchers understand how different T2Rs function and why certain receptors respond to specific compounds.
The structure of T2Rs probably allows them to recognize the thousands of different bitter substances via interaction with another taste receptor-specific G protein, α-gustducin. “With the receptors’ involvement in detecting bitter tastants and maintaining the gut-brain axis, this can play an important role in health and pharmaceutical-based research, specifically targeting lifestyle diseases like diabetes,” mentioned Prof. Osakabe, explaining the importance of this study. Further research, focusing on the relation between sequence and structure of the T2Rs and how individual perception of taste varies, will help in a more comprehensive understanding of T2R function.
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Reference
DOI: 10.1016/j.crfs.2025.101146
About Shibaura Institute of Technology (SIT), Japan
Shibaura Institute of Technology (SIT) is a private university with campuses in Tokyo and Saitama. Since the establishment of its predecessor, Tokyo Higher School of Industry and Commerce, in 1927, it has maintained “learning through practice” as its philosophy in the education of engineers. SIT was the only private science and engineering university selected for the Top Global University Project sponsored by the Ministry of Education, Culture, Sports, Science and Technology and had received support from the ministry for 10 years starting from the 2014 academic year. Its motto, “Nurturing engineers who learn from society and contribute to society,” reflects its mission of fostering scientists and engineers who can contribute to the sustainable growth of the world by exposing their over 9,500 students to culturally diverse environments, where they learn to cope, collaborate, and relate with fellow students from around the world.
Website: https://www.shibaura-it.ac.jp/en/
About Professor Naomi Osakabe from SIT, Japan
Dr. Naomi Osakabe is a professor at the Department of Bioscience and Engineering at Shibaura Institute of Technology, Japan. Her current research interests include pharmacology, toxicology, pharmaceutical science, polyphenols, and taste receptor-related topics. She has actively collaborated with researchers across the globe. Prof. Osakabe has authored more than 150 research papers to date and also serves on the editorial board of leading scientific journals. With over 30 years of experience, she is an expert in the field of food and nutrition.
Funding Information
This work was supported by JSPS KAKENHI (Grant Number: 23H02166).
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