Department of Integrative Structural Biology, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Institut National de la Santé et de la Recherche Médicale (INSERM) U964, Centre National de la Recherche Scientifique (CNRS) UMR 7104, Université de Strasbourg, Illkirch, France.
Published: August 2017
AI Article Synopsis
Article Abstract
Retinoic acid (RA) plays key roles in cell differentiation and growth arrest through nuclear retinoic acid receptors (RARs), which are ligand-dependent transcription factors. While the main trigger of RAR activation is the binding of RA, phosphorylation of the receptors has also emerged as an important regulatory signal. Phosphorylation of the RARγ N-terminal domain (NTD) is known to play a functional role in neuronal differentiation. In this work, we investigated the phosphorylation of RARγ ligand binding domain (LBD), and present evidence that the phosphorylation status of the LBD affects the phosphorylation of the NTD region. We solved the X-ray structure of a phospho-mimetic mutant of the LBD (RARγ S371E), which we used in molecular dynamics simulations to characterize the consequences of the S371E mutation on the RARγ structural dynamics. Combined with simulations of the wild-type LBD, we show that the conformational equilibria of LBD salt bridges (notably R387-D340) are affected by the S371E mutation, which likely affects the recruitment of the kinase complex that phosphorylates the NTD. The molecular dynamics simulations also showed that a conservative mutation in this salt bridge (R387K) affects the dynamics of the LBD without inducing large conformational changes. Finally, cellular assays showed that the phosphorylation of the NTD of RARγ is differentially regulated by retinoic acid in RARγWT and in the S371N, S371E and R387K mutants. This multidisciplinary work highlights an allosteric coupling between phosphorylations of the LBD and the NTD of RARγ and supports the importance of structural dynamics involving electrostatic interactions in the regulation of RARs activity.
Cardiac development is a complex and intricate process involving numerous molecular signals and pathways. Researchers have explored cardiac development through a long journey, starting with early studies observing morphological changes and progressing to the exploration of molecular mechanisms using various molecular biology methods. Currently, advancements in stem cell technology and sequencing technology, such as the generation of human pluripotent stem cells and cardiac organoids, multi-omics sequencing, and artificial intelligence (AI) technology, have enabled researchers to understand the molecular mechanisms of cardiac development better.
Aims: Acute promyelocytic leukemia (APL) progresses quickly and often leads to early hemorrhagic death. Treatment with all-trans retinoic acid (ATRA) promotes differentiation of APL cells and clinical remission, making APL a potentially curable malignancy. Understanding how ATRA works may lead to new treatments for other types of leukemia.
Purpose: Ambient light exposure is linked to myopia development in children and affects myopia susceptibility in animal models. Currently, it is unclear which signals mediate the effects of light on myopia. All- retinoic acid (atRA) and dopamine (DA) oppositely influence experimental myopia and may be involved in the retino-scleral signaling cascade underlying myopic eye growth.
Background And Purpose: Cellulite is caused by changes in the metabolism of the fatty tissue beneath the skin. Methylxanthines and retinoids are commonly added to the different anticellulite products. However, their topical permeation into the dermis is limited.
Background: Due to limited treatment options, cutaneous warts caused by human papillomavirus (HPV) remain a significant clinical challenge. Furthermore, the genetic susceptibility and molecular basis of viral warts are not yet fully understood.
Methods: We utilized a multi-omics integration approach, encompassing genome-wide association study (GWAS) meta-analysis, summary data-based Mendelian randomization (SMR) analysis, and transcriptomic validation using the GSE136347 dataset.
