Frustration and Direct-Coupling Analyses to Predict Formation and Function of Adeno-Associated Virus.
Journal
Biophysical journal
ISSN: 1542-0086
Titre abrégé: Biophys J
Pays: United States
ID NLM: 0370626
Informations de publication
Date de publication:
02 02 2021
02 02 2021
Historique:
received:
06
07
2020
revised:
08
11
2020
accepted:
08
12
2020
pubmed:
29
12
2020
medline:
15
5
2021
entrez:
28
12
2020
Statut:
ppublish
Résumé
Adeno-associated virus (AAV) is a promising gene therapy vector because of its efficient gene delivery and relatively mild immunogenicity. To improve delivery target specificity, researchers use combinatorial and rational library design strategies to generate novel AAV capsid variants. These approaches frequently propose high proportions of nonforming or noninfective capsid protein sequences that reduce the effective depth of synthesized vector DNA libraries, thereby raising the discovery cost of novel vectors. We evaluated two computational techniques for their ability to estimate the impact of residue mutations on AAV capsid protein-protein interactions and thus predict changes in vector fitness, reasoning that these approaches might inform the design of functionally enriched AAV libraries and accelerate therapeutic candidate identification. The Frustratometer computes an energy function derived from the energy landscape theory of protein folding. Direct-coupling analysis (DCA) is a statistical framework that captures residue coevolution within proteins. We applied the Frustratometer to select candidate protein residues predicted to favor assembled or disassembled capsid states, then predicted mutation effects at these sites using the Frustratometer and DCA. Capsid mutants were experimentally assessed for changes in virus formation, stability, and transduction ability. The Frustratometer-based metric showed a counterintuitive correlation with viral stability, whereas a DCA-derived metric was highly correlated with virus transduction ability in the small population of residues studied. Our results suggest that coevolutionary models may be able to elucidate complex capsid residue-residue interaction networks essential for viral function, but further study is needed to understand the relationship between protein energy simulations and viral capsid metastability.
Identifiants
pubmed: 33359833
pii: S0006-3495(20)33223-9
doi: 10.1016/j.bpj.2020.12.018
pmc: PMC7895998
pii:
doi:
Substances chimiques
Capsid Proteins
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
489-503Subventions
Organisme : NIGMS NIH HHS
ID : R35 GM133631
Pays : United States
Informations de copyright
Copyright © 2020 Biophysical Society. Published by Elsevier Inc. All rights reserved.
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