Application of transport-based metric for continuous interpolation between cryo-EM density maps.
Application of transport-based metric for continuous interpolation between cryo-EM density maps.
复制标题
基于运输指标的应用在冷冻EM密度图之间连续插值。
DOI：
10.3934/math.2022059
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发表时间：
2022
期刊：
影响因子：
2.2
通讯作者：
Khanh Dao Duc
中科院分区：
文献类型：
--
作者：
Ecoffet, Arthur;Woollard, Geoffrey;Kushner, Artem;Poitevin, Frederic;Khanh Dao Duc
低温电子显微镜（cryo-EM）在过去几年中已广泛用于结构生物学，以收集“冻结在时间”的大分子的单个图像。由于这种技术有助于识别同一分子所采用的多种构象状态，因此它的直接产物是一组3D体积，也称为EM图。为了更深入地了解控制不同状态之间转换的可能机制，从而了解分子的作用模式，我们最近引入了一种生物信息学工具，该工具可以插值并生成连接两个给定EM图的变形轨迹。该工具基于最佳运输的最新进展，可以有效评估3D形状的Wasserstein重心。由于该方法的整体性能取决于各种关键参数，包括正则化参数的灵敏度，我们进行了各种数值实验，以证明MorphOT如何应用于不同的上下文和设置。最后，我们讨论了目前的局限性和其他最佳运输理论和固有的cryo-EM数据的构象异质性问题之间的潜在联系。
Cryogenic electron microscopy (cryo-EM) has become widely used for the past few years in structural biology, to collect single images of macromolecules “frozen in time”. As this technique facilitates the identification of multiple conformational states adopted by the same molecule, a direct product of it is a set of 3D volumes, also called EM maps. To gain more insights on the possible mechanisms that govern transitions between different states, and hence the mode of action of a molecule, we recently introduced a bioinformatic tool that interpolates and generates morphing trajectories joining two given EM maps. This tool is based on recent advances made in optimal transport, that allow efficient evaluation of Wasserstein barycenters of 3D shapes. As the overall performance of the method depends on various key parameters, including the sensitivity of the regularization parameter, we performed various numerical experiments to demonstrate how MorphOT can be applied in different contexts and settings. Finally, we discuss current limitations and further potential connections between other optimal transport theories and the conformational heterogeneity problem inherent with cryo-EM data.
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影响因子：
64.8
作者：
Nakane T;Kotecha A;Sente A;McMullan G;Masiulis S;Brown PMGE;Grigoras IT;Malinauskaite L;Malinauskas T;Miehling J;Uchański T;Yu L;Karia D;Pechnikova EV;de Jong E;Keizer J;Bischoff M;McCormack J;Tiemeijer P;Hardwick SW;Chirgadze DY;Murshudov G;Aricescu AR;Scheres SHW
通讯作者：
Scheres SHW
影响因子：
2
作者：
Heitz, Matthieu;Bonneel, Nicolas;Peyre, Gabriel
通讯作者：
Peyre, Gabriel
DOI：
10.3390/molecules25184262
发表时间：
2020-09-17
期刊：
Molecules (Basel, Switzerland)
影响因子：
--
作者：
Poitevin F;Kushner A;Li X;Dao Duc K
通讯作者：
Dao Duc K
影响因子：
6.2
作者：
Solomon, Justin;de Goes, Fernando;Guibas, Leonidas
通讯作者：
Guibas, Leonidas
影响因子：
1.7
作者：
McCann, RJ
通讯作者：
McCann, RJ