Experimental evaluation of single‐domain antibodies predicted by molecular dynamics simulations to have elevated thermal stability. (7th August 2019)

• Record Type: Journal Article
• Authors: Zabetakis, Dan; Shriver‐Lake, Lisa C.; Olson, Mark A.; Goldman, Ellen R.; Anderson, George P.
• Is Part Of: Protein science. Volume 28:Number 10(2019)
• Page Start: 1909
• Page End: 1912
• Publication Date: 2019-08-07
• Subjects: molecular dynamics simulations -- protein stabilization -- single‐domain antibody -- thermal stability; Proteins -- Periodicals; 572.6
• DOI: 10.1002/pro.3692
• Languages: English
• ISSNs: 0961-8368

Abstract

Abstract: Recently Bekker et al. [Bekker G‐J et al. Protein Sci. 2019;28:429–438.] described a computational strategy of applying molecular‐dynamics simulations to estimate the relative stabilities of single‐domain antibodies, and utilized their method to design changes with the aim of increasing the stability of a single‐domain antibody with a known crystal structure. The structure from which they generated potentially stabilizing mutations is an anti‐cholera toxin single domain antibody selected from a naïve library which has relatively low thermal stability, reflected by a melting point of 48°C. Their work was purely theoretical, so to examine their predictions, we prepared the parental and predicted stabilizing mutant single domain antibodies and examined their thermal stability, ability to refold and affinity. We found that the mutation that improved stability the most (~7°C) was one which changed an amino acid in CDR1 from an asparagine to an aspartic acid. This change unfortunately was also accompanied by a reduction in affinity. Thus, while their modeling did appear to successfully predict stabilizing mutations, introducing mutations in the binding regions is problematic. Of further interest, the mutations selected via their high temperature simulations, did improve refolding, suggesting that they were successful in stabilizing the structure at high temperatures and thereby decrease aggregation. Our result should permit them to reassess and refine their model and may one day lead to a useful in silico approach to protein stabilization.