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UrduThe invention of a tool capable of unlocking previously impossible organic chemical reactions has opened new pathways in the pharmaceutical industry to create effective drugs more quickly.
Tag: Amino Acid
Patients with Unexplainable Chronic Itch Have Unique Blood Biomarkers that Could Eventually Lead to New Targeted Treatments
Millions of patients worldwide suffer from a chronic itching condition with no identifiable cause – a condition known as chronic pruritus of unknown origin (CPUO) – that has no targeted therapies approved to treat it. Many of these patients suffer for years with little relief, but a new University of Maryland School of Medicine study may provide hope for future treatments. Patients were found to have lower than normal levels of metabolite biomarkers in the blood plasma that could point to a cause of their excruciating symptoms.
Eating too much protein is bad for your arteries, and this amino acid is to blame
University of Pittsburgh School of Medicine researchers discovered a molecular mechanism by which excessive dietary protein could increase atherosclerosis risk.
Rutgers Researchers Publish Paper Examining the Structure of Proteins Linked to Diseases
Rutgers researcher, Grace Brannigan, has co-authored a study published in The Proceedings of the National Academy of Sciences (PNAS) that centers around the connection between gene mutations in protein sequences and diseases.
Machine Learning Helps Predict Protein Functions
To engineer proteins for specific functions, scientists change a protein sequence and experimentally test how that change alters its function. Because there are too many possible amino acid sequence changes to test them all in the laboratory, researchers build computational models that predict protein function based on amino acid sequences. Scientists have now combined multiple machine learning approaches for building a simple predictive model that often works better than established, complex methods.
Spontaneous Mammary Neoplasia, Cannabidiol Exposure, Aryl Hydrocarbon Receptors, and More Featured in July 2021 Toxicological Sciences
Toxicological Sciences delivers the latest toxicology research in the July 2021 issue. The issue features investigations in delivers the latest toxicology research in areas such as exposure to delta-9-tetrahydrocannabinol and cannabidiol, effects of ENDS vapors on amino acid metabolism, and more.
Exploring Amino Acids Signaling as Intervention for Diabetes and Pancreatic Cancers
Researchers from Rutgers Cancer Institute of New Jersey previously identified a small protein called Rab1A that regulates amino acid signaling. In a recent study, researchers explored the physiological role of Rab1A in mammals using mice though a technique in which one of an organism’s genes is made inoperative, known as genetic knockout.
Positive Data Reported in a Multinational Clinical Trial Investigating New Treatment of Niemann-Pick disease Type C
A multinational clinical trial of for the treatment of Niemann-Pick disease Type C (NPC) demonstrated a statistically significant and clinically meaningful improvement in symptoms, functioning, and quality of life in both primary and topline secondary endpoints for both pediatric and adult patients with NPC.
Does Leucine Supplementation Contribute to Muscle Growth in Exercising, Healthy Adults?
Protein intake and resistance exercise are the cornerstone to muscle growth. Following protein ingestion, increased blood and/or intramuscular leucine concentration is considered the main nutrient-derived driver of muscle protein synthesis, leading to a speculation that leucine supplementation could improve muscle…
Composing New Proteins with Artificial Intelligence
Proteins are the building blocks of life and scientists have long studied how to improve them or design new ones. Traditionally, new proteins are created by mimicking existing proteins or manually editing their amino acids. This process is time-consuming, and it is difficult to predict the impact of changing an amino acid. In APL Bioengineering, researchers explore how to create new proteins by using machine learning to translate protein structures into musical scores, presenting an unusual way to translate physics concepts across domains.