AIMC Topic: RNA, Messenger

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Deep learning-assisted discovery of a potent and cell-active inhibitor of RNA N-methyladenosine recognition protein YTHDC2.

Nature communications
YTHDC2, a unique YTH-domain-containing protein that recognizes N6-methyladenosine (mA) on RNA, plays critical roles in diverse pathological processes and represents a promising therapeutic target. Despite its potential, no potent small-molecule inhib...

Machine Learning for the Prediction of Size and Encapsulation Efficiency of mRNA-Loaded Lipid Nanoparticles Following a Postencapsulation Approach.

ACS applied bio materials
Lipid nanoparticles (LNPs) have gained significant attention thanks to their ability to encapsulate and deliver mRNA. Exploring a variety of lipid compositions and different preparation processes is essential for a better understanding of the mRNA en...

mRNA-LNP vaccines: rational design, delivery optimization, and clinical translation.

Journal of materials chemistry. B
Messenger RNA (mRNA) vaccines face core challenges including low-delivery efficiency and immunogenicity, limiting their wide-ranging applications in infectious disease prevention and cancer therapy. Lipid nanoparticles (LNPs), the most clinically val...

ceRNA regulatory network and immune-neurodegenerative mechanisms of peripheral CD4+ T cells in parkinson's disease.

PloS one
Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss and neuroinflammation, with emerging roles of peripheral immune dysregulation in disease progression. This study aimed to investigate the regulatory ne...

Conditional deep learning model reveals translation elongation determinants during amino acid deprivation.

Communications biology
Translation elongation plays a key role in cellular homeostasis, and dysregulation of this process has been implicated in various diseases and metabolic disorders. Uncovering the causes of intragenic heterogeneity of translation, especially in contex...

Deep generative models design mRNA sequences with enhanced translational capacity and stability.

Science (New York, N.Y.)
Despite the success of messenger RNA (mRNA) COVID-19 vaccines, extending this modality to more diseases necessitates substantial enhancements. We present GEMORNA, a generative RNA model that uses transformer architectures tailored for mRNA coding seq...

Plasma multi-omics and machine learning reveal predictive biomarkers for type 2 diabetes and retinopathy in Qatar biobank cohort.

Journal of translational medicine
BACKGROUND: Type 2 diabetes (T2D) and its vascular complications, including diabetic retinopathy (DR), are escalating in prevalence globally, with disproportionately high prevalence in Middle Eastern populations, where genetic predispositions and lif...

Ionizable Lipid Nanoparticles for mRNA Delivery: Internal Self-Assembled Inverse Mesophase Structure and Endosomal Escape.

Accounts of chemical research
ConspectusThe clinical use of mRNA COVID-19 vaccines developed by Moderna and Pfizer-BioNTech has highlighted the critical role of ionizable lipid nanoparticles (LNPs) in the efficient loading, intracellular delivery, and cytoplasmic release of mRNAs...

Prediction of high-performing spleen-targeted lipid nanoparticles using a deep learning model for robust anticancer immunotherapy.

Journal of materials chemistry. B
Messenger RNA (mRNA) therapeutics hold significant potential across a wide range of medical applications. LNPs are the most clinically advanced mRNA delivery vehicles, but challenges such as off-target effects and liver accumulation limit their broad...

E2-regulated transcriptome complexity revealed by long-read direct RNA sequencing: from isoform discovery to truncated proteins.

RNA biology
Oestrogen receptor alpha (ERα)-positive (ER+) breast cancers are driven by the binding of 17β-oestradiol (E2) to ERα, which transcriptionally regulates target genes. Although microarrays and conventional RNA sequencing have identified E2 target genes...