ArticlePharmaceuticals (Basel, Switzerland)2022
Rethinking Protein Drug Design with Highly Accurate Structure Prediction of Anti-CRISPR Proteins.
Article in Pharmaceuticals (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- From CASP13 to the Nobel Prize: DeepMind's AlphaFold Journey in Revolutionizing Protein Structure Prediction and Beyond.Current protein & peptide science · 2026Review
- Targeting multidrug-resistant bacteria with genetic-information-free protein-only phages.bioRxiv : the preprint server for biology · 2025Article
- AlphaFold 3: an unprecedent opportunity for fundamental research and drug development.Precision clinical medicine · 2025Review
- Self-assembling T7 phage syringes with modular genomes for targeted delivery of penicillin against β-lactam-resistant Escherichia coli.BMC biotechnology · 2025Article
- Review
- AcrDB update: Predicted 3D structures of anti-CRISPRs in human gut viromes.Protein science : a publication of the Protein Society · 2025Article
- FoldX force field revisited, an improved version.Bioinformatics (Oxford, England) · 2025Article
- Exploring pangenomic diversity and CRISPR-Cas evasion potential in jumbo phages: a comparative genomics study.Microbiology spectrum · 2024Article
- A pangenome analysis of ESKAPE bacteriophages: the underrepresentation may impact machine learning models.Frontiers in molecular biosciences · 2024Article
- CRISPR-Cas-Docker: web-based in silico docking and machine learning-based classification of crRNAs with Cas proteins.BMC bioinformatics · 2023Article
- AlphaFold2 and its applications in the fields of biology and medicine.Signal transduction and targeted therapy · 2023Review
- Three Innovations of Next-Generation Antibiotics: Evolvability, Specificity, and Non-Immunogenicity.Antibiotics (Basel, Switzerland) · 2023Review
- Deep learning in CRISPR-Cas systems: a review of recent studies.Frontiers in bioengineering and biotechnology · 2023Review
- In silico optimization of RNA-protein interactions for CRISPR-Cas13-based antimicrobials.Biology direct · 2022Article
- AlphaFold, Artificial Intelligence (AI), and Allostery.The journal of physical chemistry. B · 2022Review
- Investigating the Genomic Background of CRISPR-Cas Genomes for CRISPR-Based Antimicrobials.Evolutionary bioinformatics online · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein therapeutics play an important role in controlling the functions and activities of disease-causing proteins in modern medicine. Despite protein therapeutics having several advantages over traditional small-molecule therapeutics, further development has been hindered by drug complexity and delivery issues. However, recent progress in deep learning-based protein structure prediction approaches, such as AlphaFold2, opens new opportunities to exploit the complexity of these macro-biomolecules for highly specialised design to inhibit, regulate or even manipulate specific disease-causing proteins. Anti-CRISPR proteins are small proteins from bacteriophages that counter-defend against the prokaryotic adaptive immunity of CRISPR-Cas systems. They are unique examples of natural protein therapeutics that have been optimized by the host-parasite evolutionary arms race to inhibit a wide variety of host proteins. Here, we show that these anti-CRISPR proteins display diverse inhibition mechanisms through accurate structural prediction and functional analysis. We find that these phage-derived proteins are extremely distinct in structure, some of which have no homologues in the current protein structure domain. Furthermore, we find a novel family of anti-CRISPR proteins which are structurally similar to the recently discovered mechanism of manipulating host proteins through enzymatic activity, rather than through direct inference. Using highly accurate structure prediction, we present a wide variety of protein-manipulating strategies of anti-CRISPR proteins for future protein drug design.
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