Exploring binding positions and backbone conformations of peptide ligands of proteins with a backbone-centred statistical energy function

IF 3 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Lu Zhang, Haiyan Liu
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Abstract

When designing peptide ligands based on the structure of a protein receptor, it can be very useful to narrow down the possible binding positions and bound conformations of the ligand without the need to choose its amino acid sequence in advance. Here, we construct and benchmark a tool for this purpose based on a recently reported statistical energy model named SCUBA (Sidechain-Unknown Backbone Arrangement) for designing protein backbones without considering specific amino acid sequences. With this tool, backbone fragments of different local conformation types are generated and optimized with SCUBA-driven stochastic simulations and simulated annealing, and then ranked and clustered to obtain representative backbone fragment poses of strong SCUBA interaction energies with the receptor. We computationally benchmarked the tool on 111 known protein-peptide complex structures. When the bound ligands are in the strand conformation, the method is able to generate backbone fragments of both low SCUBA energies and low root mean square deviations from experimental structures of peptide ligands. When the bound ligands are helices or coils, low-energy backbone fragments with binding poses similar to experimental structures have been generated for approximately 50% of benchmark cases. We have examined a number of predicted ligand-receptor complexes by atomistic molecular dynamics simulations, in which the peptide ligands have been found to stay at the predicted binding sites and to maintain their local conformations. These results suggest that promising backbone structures of peptides bound to protein receptors can be designed by identifying outstanding minima on the SCUBA-modeled backbone energy landscape.

Abstract Image

利用以骨架为中心的统计能量函数探索蛋白质肽配体的结合位置和骨架构象
在设计基于蛋白质受体结构的肽配体时,在不需要事先选择其氨基酸序列的情况下,缩小配体可能的结合位置和结合构象非常有用。在这里,我们基于最近报道的统计能量模型SCUBA (Sidechain-Unknown Backbone Arrangement)构建了一个工具并对其进行基准测试,用于设计蛋白质骨架,而不考虑特定的氨基酸序列。利用该工具,通过SCUBA驱动的随机模拟和模拟退火,生成不同局部构象类型的骨干片段,并对其进行优化,然后进行排序和聚类,得到与受体具有强SCUBA相互作用能的代表性骨干片段位姿。我们在111个已知的蛋白质-肽复合物结构上计算了该工具的基准。当结合的配体为链构象时,该方法能够生成低SCUBA能和低均方根偏差的主链片段。当结合配体为螺旋或线圈时,大约50%的基准案例产生了与实验结构相似的结合姿态的低能骨干片段。我们通过原子分子动力学模拟研究了许多预测的配体-受体复合物,其中发现肽配体停留在预测的结合位点并保持其局部构象。这些结果表明,结合蛋白受体的肽的有希望的主链结构可以通过识别scuba模型的主链能量景观上的突出最小值来设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Computer-Aided Molecular Design
Journal of Computer-Aided Molecular Design 生物-计算机:跨学科应用
CiteScore
8.00
自引率
8.60%
发文量
56
审稿时长
3 months
期刊介绍: The Journal of Computer-Aided Molecular Design provides a form for disseminating information on both the theory and the application of computer-based methods in the analysis and design of molecules. The scope of the journal encompasses papers which report new and original research and applications in the following areas: - theoretical chemistry; - computational chemistry; - computer and molecular graphics; - molecular modeling; - protein engineering; - drug design; - expert systems; - general structure-property relationships; - molecular dynamics; - chemical database development and usage.
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