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对一大类蛋白质和RNA进行热点识别,揭示了分子识别的统一原理。

Hot-spot identification on a broad class of proteins and RNA suggest unifying principles of molecular recognition.

作者信息

Kulp John L, Cloudsdale Ian S, Kulp John L, Guarnieri Frank

机构信息

Conifer Point Pharmaceuticals, Doylestown, Pennsylvania, United States of America.

Department of Chemistry, Baruch S. Blumberg Institute, Doylestown, Pennsylvania, United States of America.

出版信息

PLoS One. 2017 Aug 24;12(8):e0183327. doi: 10.1371/journal.pone.0183327. eCollection 2017.

Abstract

Chemically diverse fragments tend to collectively bind at localized sites on proteins, which is a cornerstone of fragment-based techniques. A central question is how general are these strategies for predicting a wide variety of molecular interactions such as small molecule-protein, protein-protein and protein-nucleic acid for both experimental and computational methods. To address this issue, we recently proposed three governing principles, (1) accurate prediction of fragment-macromolecule binding free energy, (2) accurate prediction of water-macromolecule binding free energy, and (3) locating sites on a macromolecule that have high affinity for a diversity of fragments and low affinity for water. To test the generality of these concepts we used the computational technique of Simulated Annealing of Chemical Potential to design one small fragment to break the RecA-RecA protein-protein interaction and three fragments that inhibit peptide-deformylase via water-mediated multi-body interactions. Experiments confirm the predictions that 6-hydroxydopamine potently inhibits RecA and that PDF inhibition quantitatively tracks the water-mediated binding predictions. Additionally, the principles correctly predict the essential bound waters in HIV Protease, the surprisingly extensive binding site of elastase, the pinpoint location of electron transfer in dihydrofolate reductase, the HIV TAT-TAR protein-RNA interactions, and the MDM2-MDM4 differential binding to p53. The experimental confirmations of highly non-obvious predictions combined with the precise characterization of a broad range of known phenomena lend strong support to the generality of fragment-based methods for characterizing molecular recognition.

摘要

化学性质多样的片段倾向于在蛋白质上的局部位点共同结合,这是基于片段技术的基石。一个核心问题是,对于实验方法和计算方法而言,这些预测各种分子相互作用(如小分子 - 蛋白质、蛋白质 - 蛋白质和蛋白质 - 核酸相互作用)的策略有多普遍。为了解决这个问题,我们最近提出了三个指导原则:(1)准确预测片段 - 大分子结合自由能;(2)准确预测水 - 大分子结合自由能;(3)定位大分子上对多种片段具有高亲和力且对水具有低亲和力的位点。为了测试这些概念的普遍性,我们使用化学势模拟退火的计算技术设计了一个小片段来破坏RecA - RecA蛋白质 - 蛋白质相互作用,并设计了三个通过水介导的多体相互作用抑制肽脱甲酰基酶的片段。实验证实了以下预测:6 - 羟基多巴胺能有效抑制RecA,并且肽脱甲酰基酶抑制作用定量跟踪水介导的结合预测。此外,这些原则正确地预测了HIV蛋白酶中必需的结合水、弹性蛋白酶令人惊讶的广泛结合位点、二氢叶酸还原酶中电子转移的精确位置、HIV TAT - TAR蛋白质 - RNA相互作用以及MDM2 - MDM4与p53的差异结合。对高度不明显预测的实验证实,再加上对广泛已知现象的精确表征,有力地支持了基于片段的分子识别表征方法的普遍性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2c8/5570288/2ec69323b1e5/pone.0183327.g001.jpg

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