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Science Papers Present Approach to Predict 3D RNA Structures, Endometrial Therapeutic Target

A new computational method for predicting three-dimensional RNA structures is reported in Science this week. RNA molecules fold into well-defined 3D structures that are critical to their function and are of interest in drug discovery. Yet few RNA structures are known and predicting them remains challenging. To address this, a group of Stanford University researchers developed a machine learning approach, trained on 18 known RNA structures, that enables identification of accurate structural models without assumptions about their defining characteristics. Called the Atomic Rotationally Equivariant Scorer, or ARES, this neural network outperforms previous methods and consistently produces the best results in community-wide blind RNA structure prediction challenges, its developers write. "Because [ARES] uses only atomic coordinates as inputs and incorporates no RNA-specific information, this approach is applicable to diverse problems in structural biology, chemistry, materials science, and beyond," they add.

By comparing the genetics of humans and rhesus macaques, a group led by scientists from the University of Oxford has identified a nonhormonal therapeutic target for endometriosis. Endometriosis is a chronic condition, characterized by the growth of endometrial-like tissues outside of the uterus, with significant heritability and treatment options limited to hormonal therapy or surgery. Aiming to better understand the disorder, the investigators sequenced DNA from 32 human families with endometriosis and compared the findings to a genetic analysis in a large, multigenerational pedigree of rhesus macaques that spontaneously develop the condition. As reported in Science Translational Medicine, they identify NPSR1, the gene encoding neuropeptide S receptor 1, as associated with disease. In follow-on experiments, a NPSR1 inhibitor led to reduction of inflammatory cell infiltrate and pain in mouse models of peritoneal inflammation and endometriosis. While additional study is needed, the findings point to a genetically validated, nonhormonal target for the treatment of endometriosis with likely increased relevance to later-stage disease, the study authors write.

The Scan

Genetic Tests Lead to Potential Prognostic Variants in Dutch Children With Dilated Cardiomyopathy

Researchers in Circulation: Genomic and Precision Medicine found that the presence of pathogenic or likely pathogenic variants was linked to increased risk of death and poorer outcomes in children with pediatric dilated cardiomyopathy.

Fragile X Syndrome Mutations Found With Comprehensive Testing Method

Researchers in Clinical Chemistry found fragile X syndrome expansions and other FMR1 mutations with ties to the intellectual disability condition using a long-range PCR and long-read sequencing approach.

Team Presents Strategy for Speedy Species Detection in Metagenomic Sequence Data

A computational approach presented in PLOS Computational Biology produced fewer false-positive species identifications in simulated and authentic metagenomic sequences.

Genetic Risk Factors for Hypertension Can Help Identify Those at Risk for Cardiovascular Disease

Genetically predicted high blood pressure risk is also associated with increased cardiovascular disease risk, a new JAMA Cardiology study says.