Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Proc Natl Acad Sci U S A. 2024 Aug 6;121(32):e2403324121. doi: 10.1073/pnas.2403324121. Epub 2024 Jul 25.
Proteins play a key role in biological electron transport, but the structure-function relationships governing the electronic properties of peptides are not fully understood. Despite recent progress, understanding the link between peptide conformational flexibility, hierarchical structures, and electron transport pathways has been challenging. Here, we use single-molecule experiments, molecular dynamics (MD) simulations, nonequilibrium Green's function-density functional theory (NEGF-DFT), and unsupervised machine learning to understand the role of secondary structure on electron transport in peptides. Our results reveal a two-state molecular conductance behavior for peptides across several different amino acid sequences. MD simulations and Gaussian mixture modeling are used to show that this two-state molecular conductance behavior arises due to the conformational flexibility of peptide backbones, with a high-conductance state arising due to a more defined secondary structure (beta turn or 3 helices) and a low-conductance state occurring for extended peptide structures. These results highlight the importance of helical conformations on electron transport in peptides. Conformer selection for the peptide structures is rationalized using principal component analysis of intramolecular hydrogen bonding distances along peptide backbones. Molecular conformations from MD simulations are used to model charge transport in NEGF-DFT calculations, and the results are in reasonable qualitative agreement with experiments. Projected density of states calculations and molecular orbital visualizations are further used to understand the role of amino acid side chains on transport. Overall, our results show that secondary structure plays a key role in electron transport in peptides, which provides broad avenues for understanding the electronic properties of proteins.
蛋白质在生物电子传递中起着关键作用,但控制肽电子性质的结构-功能关系尚未完全了解。尽管最近取得了进展,但理解肽构象灵活性、层次结构和电子传输途径之间的联系一直具有挑战性。在这里,我们使用单分子实验、分子动力学(MD)模拟、非平衡格林函数-密度泛函理论(NEGF-DFT)和无监督机器学习来理解二级结构对肽中电子传输的作用。我们的结果揭示了几种不同氨基酸序列的肽的两态分子电导行为。MD 模拟和高斯混合建模用于表明这种两态分子电导行为是由于肽骨架的构象灵活性引起的,高电导状态是由于更确定的二级结构(β转角或 3 螺旋)引起的,低电导状态是由于扩展的肽结构引起的。这些结果强调了螺旋构象对肽中电子传输的重要性。使用沿肽骨架的分子内氢键距离的主成分分析来合理化肽结构的构象选择。从 MD 模拟中得到的分子构象用于 NEGF-DFT 计算中的电荷传输建模,结果与实验结果具有合理的定性一致性。投影态密度计算和分子轨道可视化进一步用于理解氨基酸侧链对传输的作用。总的来说,我们的结果表明,二级结构在肽中的电子传输中起着关键作用,这为理解蛋白质的电子性质提供了广泛的途径。