Local entropy in proteins.
Аннотация
Proteins populate dynamic ensembles, yet how temperature and mutations reshape these ensembles remains poorly understood. We introduce a local entropy metric that assigns each residue a Shannon entropy based on a graph-derived map of accessible substates, providing a continuous measure of structural complexity across folded, unfolded, and intrinsically disordered states. In molecular dynamics simulations of the fast-folding gpW protein, the average local entropy exhibits a sharp transition near the melting point. Residue-specific entropy curves cluster into distinct unfolding categories and reveal that the apparent unfolding transition depends on the spatial scale used to describe amino-acid environments. We further show that local entropy captures features that differ markedly from other residue-level measures of structural fluctuations, such as the accessible volume (and the associated packing entropy), which is correlated with B-factors and primarily reflects the hydrophobic effect. In simulations of α-synuclein, an intrinsically disordered protein, local entropy varies strongly along the sequence at physiological temperature and resembles that of gpW near its melting point. Parkinson's-disease mutations in α-synuclein locally reduce entropy while also perturbing distant regions including P1, P2 and NAC segments implicated in fibril formations. These results highlight how temperature and subtle perturbations-such as single-residue changes-remodel conformational ensembles. Local entropy correlates with NMR observables and provides a generalizable framework for quantifying disorder, with broad potential applications beyond protein science.
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
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.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.