Bioinformatics & Molecular Design Research Center

Wild soybean (WB; Glycine soja Sieb. & Zucc.) is the ancestor of cultivated soybean (CB; G. max (L.) Merr.) and possesses greater genetic diversity.It is important to explore the phenolic compounds present in WB, specifically flavonoids, for potential utilization.To examine the extensive flavonoid diversity of WB, we conducted a comprehensive flavonoid profiling using liquid chromatog.-high resolution mass spectrometer with integrated ion filtering strategies.Furthermore, we investigated the antioxidant capacity of soybean flavonoids.A total of 72 flavonoids were identified, including isoflavones, flavanols, procyanidins, flavones, flavanones, and anthocyanins.WB had significantly (p < 0.05) higher total flavonoid content compared to CB, especially in terms of flavanols, procyanidins, and anthocyanins.Results of antioxidant capacity assays (ABTS, DPPH, and DCFH-DA) and correlation anal. demonstrated that WB exhibited higher antioxidant capacities than CB, primarily due to flavanols, procyanidins, and anthocyanins.This study represents that WB is a valuable genetic resource with potent antioxidant activity, which can be utilized for the development of functional food ingredients.

Greenhouse gas emissions, particularly carbon dioxide (CO₂), pose a significant threat to the climate, driving global warming and numerous environmental issues.Ionic liquids (ILs) have gained attention for CO₂ capture due to their tunable properties, which can be optimized through the selection of specific cation-anion combinations.Traditional methods for discovering effective ILs are time-consuming and costly, necessitating the development of innovative computational approaches.This study extended the Scoring-Assisted Generative Exploration for Ionic Liquids (SAGE-IL) to generate novel ILs tailored for CO₂ capture.SAGE-IL combines deep learning-based generative models with quant. structure-property relationship models to design ILs with desired properties.Notably, SAGE-IL successfully performed single property optimization, either increasing or decreasing viscosity and m.p., through iterative interactions between generative and evaluation models.Furthermore, it achieved multiple property optimization, improving either CO₂ solubility or activity coefficient while simultaneously optimizing d., m.p., viscosity, and synthetic accessibility.This approach not only accelerates the discovery of high-performance ILs but also highlights the potential of generative models in de novo mol. design, paving the way for future advancements in materials discovery.

In the Hippo signaling pathway, the palmitoylated transcriptional enhanced associated domain (TEAD) protein interacts with the coactivator Yes-associated protein/PDZ-binding motif, leading to transcriptional upregulation of oncogenes such as Ctgf and Cyr61. Consequently, targeting the palmitoylation sites of TEAD has emerged as a promising strategy for treating TEAD-dependent cancers. Compound 1 was identified using a structure-based drug design approach, leveraging the molecular insights gained from the known TEAD palmitoylation site inhibitor, K-975. Optimization of the initial hit compound resulted in the development of compound 3, a covalent pan-TEAD inhibitor characterized by high potency and oral bioavailability.