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Towards a theory of protein adsorption

机译:迈向蛋白质吸附理论

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摘要

Predicting protein adsorption from solution to a surface is a perennial problem in biomedicine and related fields. Despite constant attention in the literature, it is not currently possible to predict quantitatively the amount of adsorbed protein given environment, protein and surface parameters. In previous work, we presented the Biomolecular Adsorption Database, an online collection of protein adsorption data collected from the literature, and more recently a program and set of algorithms for computing physico-chemical descriptors on protein surfaces. In this paper, we present a purely empirical approach to predicting protein adsorption using a linearly piecewise model with breakpoint. This model makes use of the previously developed surface property algorithms to describe the protein. We fitted and validated this model using the Biomolecular Adsorption Database. This model is capable of accounting for over 90% of the variance in the data, despite the fact that the adsorption data spans over three orders of magnitude. This represents a significant improvement over previous predictive modelling results.
机译:在生物医学和相关领域中,预测蛋白质从溶液到表面的吸附是一个长期存在的问题。尽管在文献中一直受到关注,但在给定的环境,蛋白质和表面参数的情况下,目前尚无法定量地预测吸附蛋白质的量。在以前的工作中,我们介绍了生物分子吸附数据库,从文献中收集的蛋白质吸附数据的在线收集,以及最近提供的用于计算蛋白质表面物理化学描述符的程序和算法集。在本文中,我们提出了使用具有断点的线性分段模型预测蛋白质吸附的纯粹经验方法。该模型利用先前开发的表面特性算法来描述蛋白质。我们使用生物分子吸附数据库拟合并验证了该模型。尽管吸附数据跨越三个数量级,但该模型仍能够解决数据变化的90%以上。这代表了对先前预测建模结果的重大改进。

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