Biophysical reports · 2026
Quantifying species-specific binding affinities of transthyretin aggregation inhibitors.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Sun Xun, Dyson H Jane, Wright Peter E
Аннотация
Transthyretin (TTR) amyloidosis is one of the most common forms of systemic amyloidosis, involving deposits of pathogenic TTR aggregates in tissues and organs throughout the body. TTR aggregation is initiated by the dissociation of a native TTR tetramer into a monomeric intermediate, which subsequently misfolds and assembles into insoluble aggregates. Using an efficient 19F-NMR aggregation assay, we previously showed that designed peptide inhibitors can interact with multiple TTR species. However, quantifying species-specific binding affinities has remained difficult because the populations of these TTR species change over time and include a low-abundance monomeric intermediate. Here, we develop a quantitative method to extract species-dependent binding affinities directly from population-resolved 19F-NMR aggregation data. Using diflunisal as a model compound, we determine its binding affinities for both the tetramer and the monomeric intermediate under acidic, aggregating conditions. At acidic pH, tetramer binding becomes approximately 2-fold tighter, and monomer binding becomes 15-fold stronger, compared to neutral pH. We then apply this method to previously collected 19F-NMR aggregation data for designed peptide inhibitors. The results show that concatenating two capping peptides increases their binding affinity to both TTR tetramers and monomeric intermediates by about 2-fold, relative to the same peptides mixed separately at equal concentrations. Our method enables direct, quantitative comparison of species-dependent inhibitor binding, providing mechanistic insights useful for designing and optimizing TTR aggregation inhibitors.