ArticleScience advances2024
Optimal trade-off control in machine learning-based library design, with application to adeno-associated virus (AAV) for gene therapy.
Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Artificial intelligence in biologic drug discovery: A review of methodological evolution and therapeutic applications.Acta pharmaceutica Sinica. B · 2026Review
- Directed evolution of novel AAV capsids for enhanced delivery to mouse and human Schwann cells.Molecular therapy. Nucleic acids · 2026Article
- Machine learning-driven optimization of specific, compact, and efficient base editors via single-round diversification.Nucleic acids research · 2026Article
- Intrinsic dataset features drive mutational effect prediction by protein language models.bioRxiv : the preprint server for biology · 2026Article
- Site-Specific Chemical Conjugation of Recombinant Proteins onto the AAV Capsid.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Gene Therapy for Inherited Retinal Disease: Current Strategies, Personalized Medicine, and Future Implications-A Comprehensive Review.Journal of personalized medicine · 2025Review
- Exploring AAV-Mediated Gene Therapy for Inner Ear Diseases: from Preclinical Success to Clinical Potential.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Engineering Targeted Gene Delivery Systems for Primary Hereditary Skeletal Myopathies: Current Strategies and Future Perspectives.Biomedicines · 2025Review
- Enhancement of CRISPR-Cas12a system through universal circular RNA design.Cell reports methods · 2025Article
- Common AAV gene therapy vectors show nonselective transduction ofMolecular therapy. Methods & clinical development · 2025Article
- Revolution of AAV in Drug Discovery: From Delivery System to Clinical Application.Journal of medical virology · 2025Review
- Engineering CAR-T Therapeutics for Enhanced Solid Tumor Targeting.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Optimized AAV capsids for basal ganglia diseases show robust potency and distribution.Nature communications · 2025Article
- Advances in AAV capsid engineering: Integrating rational design, directed evolution and machine learning.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Review
- Adeno-associated viral vector targeted evolution for neurofibromatosis gene delivery.Trends in molecular medicine · 2025Review
- AAVolve: Concatenated long-read deep sequencing enables whole capsid tracking during shuffled AAV library selection.Molecular therapy. Methods & clinical development · 2024Article
- Multimodal evaluation of network activity and optogenetic interventions in human hippocampal slices.Nature neuroscience · 2024Article
- The AAV2.7m8 capsid packages a higher degree of heterogeneous vector genomes than AAV2.Gene therapy · 2024Article
- Systematic multi-trait AAV capsid engineering for efficient gene delivery.Nature communications · 2024Article
- Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering.Nature communications · 2024Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Adeno-associated viruses (AAVs) hold tremendous promise as delivery vectors for gene therapies. AAVs have been successfully engineered-for instance, for more efficient and/or cell-specific delivery to numerous tissues-by creating large, diverse starting libraries and selecting for desired properties. However, these starting libraries often contain a high proportion of variants unable to assemble or package their genomes, a prerequisite for any gene delivery goal. Here, we present and showcase a machine learning (ML) method for designing AAV peptide insertion libraries that achieve fivefold higher packaging fitness than the standard NNK library with negligible reduction in diversity. To demonstrate our ML-designed library's utility for downstream engineering goals, we show that it yields approximately 10-fold more successful variants than the NNK library after selection for infection of human brain tissue, leading to a promising glial-specific variant. Moreover, our design approach can be applied to other types of libraries for AAV and beyond.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.