We located the binding sites of antioxidants resveratrol, genistein and curcumin on tRNA in aqueous solution at physiological conditions using constant tRNA concentration and various polyphenol contents. FTIR, UV-visible, CD spectroscopic methods and molecular modeling were used to determine polyphenol binding sites, the binding constant and the effects of polyphenol complexation on tRNA conformation and particle formation. Structural analysis showed that polyphenols bind tRNA via G-C and A-U base pairs through hydrophilic, hydrophobic and H-bonding contacts with overall binding constants of K(res-tRNA)=8.95(±0.80)×10(3) M(-1), K(gen-tRNA)=3.07(±0.5)×10(3) M(-1) and K(cur-tRNA)=1.55(±0.3)×10(4) M(-1). Molecular modeling showed the participation of several nucleobases in polyphenol-tRNA adduct formation with free binding energy of -4.43 for resveratrol, -4.26 kcal/mol for genistein and -4.84 kcal/mol for curcumin, indicating that the interaction process is spontaneous at room temperature. While tRNA remains in A-family structure, major biopolymer aggregation and particle formation occurred at high polyphenol contents.
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http://dx.doi.org/10.1016/j.ijbiomac.2015.06.021 | DOI Listing |
Oncol Res
December 2024
China-America Cancer Research Institute, Guangdong Medical University, Dongguan, 523808, China.
Background: Immune checkpoint inhibitors play an important role in the treatment of solid tumors, but the currently used immune checkpoint inhibitors targeting programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), and cytotoxic T-lymphocyte antigen-4 (CTLA-4) show limited clinical efficacy in many breast cancers. B7H3 has been widely reported as an immunosuppressive molecule, but its immunological function in breast cancer patients remains unclear.
Methods: We analyzed the expression of B7H3 in breast cancer samples using data from the Cancer Genome Atlas Program (TCGA) and the Gene Expression Omnibus (GEO) databases.
Bioinform Biol Insights
December 2024
LIRMM, Univ Montpellier, CNRS, Montpellier, France.
In recent years, several machine learning (ML) approaches have been proposed to predict gene expression signal and chromatin features from the DNA sequence alone. These models are often used to deduce and, to some extent, assess putative new biological insights about gene regulation, and they have led to very interesting advances in regulatory genomics. This article reviews a selection of these methods, ranging from linear models to random forests, kernel methods, and more advanced deep learning models.
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December 2024
Department of Life Sciences, Pohang University of Science and Technology, Pohang, 37673, Kyungbook, Republic of Korea.
Alanine racemase (Alr) catalyzes the pyridoxal 5'-phosphate (PLP)-dependent racemization between L- and D-alanine in bacteria. Owing to the potential interest in targeting Alr for antibacterial drug development, several studies have determined the structures of Alr from different species, proposing models for the reaction mechanism. Insights into its reaction dynamics may be conducive to a better understanding of the Alr reaction mechanism.
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December 2024
Department of Biotechnology, Mahatma Gandhi Central University, Motihari, 845401, India.
Microtubules are dynamic cytoskeletal structures essential for cell architecture, cellular transport, cell motility, and cell division. Due to their dynamic nature, known as dynamic instability, microtubules can spontaneously switch between phases of growth and shortening. Disruptions in microtubule functions have been implicated in several diseases, including cancer, neurodegenerative disorders such as Alzheimer's and Parkinson's disease, and birth defects.
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December 2024
Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
Abscisic acid (ABA) is a crucial phytohormone that regulates plant growth and stress responses. While substantial knowledge exists about transcriptional regulation, the molecular mechanisms underlying ABA-triggered translational regulation remain unclear. Recent advances in deep sequencing of ribosome footprints (Ribo-seq) enable the mapping and quantification of mRNA translation efficiency.
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