C002 for COVID-19

C002 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 C002 in detail.
Bhasin et al., 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.
Feng et al., One Thousand SARS-CoV-2 Antibody Structures Reveal Convergent Binding and Near-Universal Immune Escape, bioRxiv, doi:10.1101/2025.08.07.669152
Since the emergence of SARS-CoV-2, understanding how antibodies recognize and adapt to viral evolution has been central to vaccine and therapeutic developments. To date, over 1,100 SARS-CoV-2 antibody structures, 16% of all known antibody-antigen complexes, have been resolved, marking the largest structural biology effort towards a single pathogen. Here, we present a comprehensive analysis of this landmark dataset to investigate the principles of antibody recognition and immune escape. Human immunoglobulins (IgGs) and camelid single-chain antibodies dominate the dataset, collectively mapping 99% of the receptor-binding domain surface. Despite remarkable sequence and conformational diversity, antibodies exhibit striking convergence in their paratope structures, revealing evolutionary constraints in epitope selection. Structural and functional analyses reveal near-universal immune escape of antibodies, including all clinical monoclonals, by advanced variants such as KP3.1.1. On average, over one-third of antibody epitope residues are mutated. These findings support pervasive immune escape, underscoring the need to effectively leverage multi-epitope targeting strategies to achieve durable immunity.
Guo et al., 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.