ArticleThe journal of physical chemistry. B2018
Computational Analysis for the Rational Design of Anti-Amyloid Beta (Aβ) Antibodies.
Article in The journal of physical chemistry. B, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Recent Developments in Free Energy Calculations for Drug Discovery.Frontiers in molecular biosciences · 2021Review
- Molecular interactions between monoclonal oligomer-specific antibody 5E3 and its amyloid beta cognates.PloS one · 2020Article
- Robustness and Efficiency of Poisson-Boltzmann Modeling on Graphics Processing Units.Journal of chemical information and modeling · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder that lacks effective treatment options. Anti-amyloid beta (Aβ) antibodies are the leading drug candidates to treat AD, but the results of clinical trials have been disappointing. Introducing rational mutations into anti-Aβ antibodies to increase their effectiveness is a way forward, but the path to take is unclear. In this study, we demonstrate the use of computational fragment-based docking and MMPBSA binding free energy calculations in the analysis of anti-Aβ antibodies for rational drug design efforts. Our fragment-based docking method successfully predicts the emergence of the common EFRH epitope. MD simulations coupled with MMPBSA binding free energy calculations are used to analyze scenarios described in prior studies, and we computationally introduce rational mutations into PFA1 to predict mutations that can improve its binding affinity toward the pE3-Aβ
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Registered trials
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