Novel AI tool takes a DeepCE dive into potential drugs for COVID-19
A new phenotype-based compound screening technology, called DeepCE, identified 10 compounds that could be repurposed for COVID-19.
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A new phenotype-based compound screening technology, called DeepCE, identified 10 compounds that could be repurposed for COVID-19.
Disrupting the interaction between the MYC oncogene and its co-factor, host cell factor (HCF)–1, was sufficient to cause Burkitt’s lymphoma cells to self-destruct in vivo.
The N439K mutation improves the interaction between SARS-CoV-2 Spike protein and the viral receptor ACE2 and eludes antibody-mediated immunity, say investigators.
Drs Sam Cooper and Michael Briskin of Phenomic AI, discuss how artificial intelligence (AI) is enabling them to target multi-cellular interactions, such as those in the tumour stroma, for drug development.
A single change to the structure of bacterial ribosomes prevents macrolide antibiotics from binding and killing the bacteria, according to a study.
According to a Public Health England study, prior SARS-CoV-2 infection provides 83 percent protection against reinfection but may not stop individuals spreading COVID-19.
The natural language processing model trained using viral protein sequence data was able to predict promising targets for vaccines against HIV, influenza and coronaviruses.
Researchers show that genomic tracking can be used to trace individual virus transmission lineages and could therefore be adopted for future pandemics.
Researchers suggest that identifying new treatments for autoimmune diseases requires studying the immune system AND target tissues together.
A new analysis suggests SARS-CoV-2-specific antibodies remain relatively stable for eight months and Spike protein-specific memory B cells increase in number over time.
A new study reveals that the healing process following a brain injury could initiate the growth of glioblastoma cancers.
A new study suggests that inflammation and blood vessel damage may be the primary causes of neurological symptoms in COVID-19 patients, instead of the virus infecting the brain.
According to researchers, an interaction between host microRNA and SARS-CoV-2 could be responsible for the range of disease severities.
Scientists have created a prognostic classification model which uses biomarkers to help predict an individual’s risk of developing severe COVID-19 symptoms.
The study found five key genetic differences when they compared sequences from severe COVID-19 patients to healthy individuals.