Computational maturation of a single-domain antibody against Aβ42 aggregation. Issue 41 (7th October 2021)

• Record Type: Journal Article
• Authors: Lin, Jiacheng; Figazzolo, Chiara; Metrick, Michael A.; Sormanni, Pietro; Vendruscolo, Michele
• Is Part Of: Chemical science. Volume 12:Issue 41(2021)
• Page Start: 13940
• Page End: 13948
• Publication Date: 2021-10-07
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/d1sc03898b
• Languages: English
• ISSNs: 2041-6520

Abstract

Abstract : A computational maturation method enables the generation of an antibody variant with over 200-fold increased potency against the primary nucleation process in Aβ42 aggregation. Abstract : The expansion of structural databases and the increase in computing power are enabling approaches for antibody discovery based on computational design. It has already been shown that it is possible to use this approach to generate antibodies for specific epitopes on challenging targets. Here we describe an application of this procedure for antibody maturation through the computational design of mutational variants of increased potency. We illustrate this procedure in the case of a single-domain antibody targeting an epitope in the N-terminal region of Aβ42, a peptide whose aggregation is closely associated with Alzheimer's disease. We show that this approach enables the generation of an antibody variant with over 200-fold increased potency against the primary nucleation process in Aβ42 aggregation. Our results thus demonstrate that potentiated antibody variants can be obtained by computational maturation.