Advances in AAV capsid engineering: Integrating rational design, directed evolution and machine learning

Alan M Nisanov¹, Julio A Rivera de Jesús², David V Schaffer³

Affiliations

¹ Department of Chemistry, University of California, Berkeley, Berkeley CA 94720, USA.
² Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA; Graduate Program in Bioengineering, University of California, Berkeley, San Francisco and University of California, Berkeley, CA 94720, USA; Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA.
³ Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA. Electronic address: schaffer@berkeley.edu.

PMID: 40176349
PMCID: PMC12126824 (available on 2026-05-07)
DOI: 10.1016/j.ymthe.2025.03.056

Review

Advances in AAV capsid engineering: Integrating rational design, directed evolution and machine learning

Alan M Nisanov et al. Mol Ther. 2025.

. 2025 May 7;33(5):1937-1945.

doi: 10.1016/j.ymthe.2025.03.056. Epub 2025 Apr 1.

Authors

Alan M Nisanov¹, Julio A Rivera de Jesús², David V Schaffer³

Affiliations

¹ Department of Chemistry, University of California, Berkeley, Berkeley CA 94720, USA.
² Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA; Graduate Program in Bioengineering, University of California, Berkeley, San Francisco and University of California, Berkeley, CA 94720, USA; Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA.
³ Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA. Electronic address: schaffer@berkeley.edu.

PMID: 40176349
PMCID: PMC12126824 (available on 2026-05-07)
DOI: 10.1016/j.ymthe.2025.03.056

Abstract

Adeno-associated virus (AAV) has emerged as a highly promising vector for human gene therapy due to its favorable safety profile, versatility, and ability to transduce a wide range of tissues. However, natural AAV serotypes have shortcomings, including suboptimal transduction efficiency, pre-existing immunity, and a lack of tissue specificity, that hinder their therapeutic potential. To address these challenges, significant efforts are being applied to engineer novel AAV capsids. Rational design leverages structural insights to enhance capsid properties, directed evolution enables unbiased selection of superior variants, and machine learning accelerates discovery by computational analysis of high-throughput screening results to enable predictive algorithms. These strategies have yielded novel capsids with improved transduction efficiency, reduced immunogenicity, and enhanced tissue targeting. Future advances that continue to integrate such multi-disciplinary approaches will further drive the clinical translation of AAV-based therapies.

Keywords: AAV; NGS; directed evolution; gene therapy; high-throughput screening; machine learning; next generation sequencing; rational design.

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Conflict of interest statement

Declaration of interests We would like to declare that J.L. and D.V.S. are inventors on a number of patents related to viral vector-directed evolution and engineered AAV variants. In addition, D.V.S. is on the editorial board of Molecular Therapy. Finally, D.V.S. is on the scientific advisory board of and/or a consultant for several gene therapy companies, including Amber Bio, Axent Biosciences, Catalent, Epic Bio, GenEdit, Juvena, Radar Therapeutics, Ray Therapeutics, SonoThera, Tessera, Valitor, and Vivere. As a result, he owns equity in these companies.

References

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Advances in AAV capsid engineering: Integrating rational design, directed evolution and machine learning

Affiliations

Advances in AAV capsid engineering: Integrating rational design, directed evolution and machine learning

Authors

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Abstract

Conflict of interest statement

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