S2M11 for COVID-19
c19early.org
COVID-19 Treatment Clinical Evidence
COVID-19 involves the interplay of 400+ viral and host proteins and factors, providing many therapeutic targets.
c19early analyzes 6,000+ studies for 210+ treatments—over 17 million hours of research.
Only three high-profit early treatments are approved in the US.
In reality, many treatments reduce risk,
with 25 low-cost treatments approved across 163 countries.
-
Naso/
oropharyngeal treatment Effective Treatment directly to the primary source of initial infection. -
Healthy lifestyles Protective Exercise, sunlight, a healthy diet, and good sleep all reduce risk.
-
Immune support Effective Vitamins A, C, D, and zinc show reduced risk, as with other viruses.
-
Thermotherapy Effective Methods for increasing internal body temperature, enhancing immune system function.
-
Systemic agents Effective Many systemic agents reduce risk, and may be required when infection progresses.
-
High-profit systemic agents Conditional Effective, but with greater access and cost barriers.
-
Monoclonal antibodies Limited Utility Effective but rarely used—high cost, variant dependence, IV/SC admin.
-
Acetaminophen Harmful Increased risk of severe outcomes and mortality.
-
Remdesivir Harmful Increased mortality with longer followup. Increased kidney and liver injury, cardiac disorders.
S2M11 may be beneficial for
COVID-19 according to the studies below.
COVID-19 involves the interplay of 400+ viral and host proteins and factors providing many therapeutic targets.
Scientists have proposed 11,000+ potential treatments.
c19early.org analyzes
210+ treatments.
We have not reviewed S2M11 in detail.
, CoV-UniBind: a unified antibody binding database for SARS-CoV-2, Bioinformatics Advances, doi:10.1093/bioadv/vbaf328
Abstract Summary Since the emergence of SARS-CoV-2, numerous studies have investigated antibody interactions with viral variants in vitro, and several datasets have been curated to compile available protein structures and experimental measurements. However, existing data remain fragmented, limiting their utility for the development and validation of machine learning models for antibody–antigen interaction prediction. Here, we present CoV-UniBind, a unified database comprising over 75 000 entries of SARS-CoV-2 antibody–antigen sequence, binding, and structural data, integrated and standardized from three public sources and multiple peer-reviewed publications. To demonstrate its utility, we benchmarked multiple protein folding, inverse folding, and language models across tasks relevant to antibody design and vaccine development. We expect CoV-UniBind to facilitate future computational efforts in antibody and vaccine development against SARS-CoV-2. Availability and implementation The curated datasets, model scores and antibody synonyms are free to download at https://huggingface.co/datasets/InstaDeepAI/cov-unibind. Folded structures are available upon request.
, Multi-omics in COVID-19: Driving development of therapeutics and vaccines, National Science Review, doi:10.1093/nsr/nwad161
Abstract The ongoing COVID-19 pandemic caused by SARS-CoV-2 has raised global concern for public health and the economy. The development of therapeutics and vaccines to combat this virus are continuously progressing. Multi-omics approaches, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and metallomics, have helped understand the structural and molecular features of the virus, thereby assisting in the design of potential therapeutics and accelerating vaccine development for COVID-19. Here, we provide an up-to-date overview of the latest applications of multi-omics technologies in strategies addressing COVID-19, in order to provide suggestions towards the development of highly effective knowledge-based therapeutics and vaccines.