DexDesign:一种基于 OSPREY 的算法,用于设计全新的 D 肽抑制剂。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Nathan Guerin, Henry Childs, Pei Zhou, Bruce R Donald
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引用次数: 0

摘要

肽识别 PDZ 结构域在人类基因组中有 270 多种独特的出现,在调节极化、信号传导和贩运途径方面发挥着核心作用。PDZ 结构域的突变会导致癌症和囊性纤维化等疾病,这使得 PDZ 结构域成为有吸引力的治疗干预靶点。D 肽抑制剂具有独特的治疗优势,包括更高的代谢稳定性和低免疫原性。在这里,我们介绍了 DexDesign,这是一种基于 OSPREY 的新型算法,用于计算设计全新的 D 肽抑制剂。DexDesign 利用了广泛适用于计算蛋白质设计的三种新技术:最小弹性集、基于 K* 的突变扫描和反丙氨酸扫描。我们应用这些技术和 DexDesign 生成了两种具有重要生物医学意义的 PDZ 结构域靶标的新型 D 肽抑制剂:CAL和MAST2。我们引入了一个分析新肽的框架--沿着复制/替换轴进行评估,并将其应用于 DexDesign 生成的 D 肽。值得注意的是,我们预测生成的多肽与其靶标的内源配体结合得更紧密,这验证了多肽作为先导抑制剂的潜力。我们还提供了免费开源计算蛋白质设计软件 OSPREY 中 DexDesign 的实现方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DexDesign: an OSPREY-based algorithm for designing de novo D-peptide inhibitors.

With over 270 unique occurrences in the human genome, peptide-recognizing PDZ domains play a central role in modulating polarization, signaling, and trafficking pathways. Mutations in PDZ domains lead to diseases such as cancer and cystic fibrosis, making PDZ domains attractive targets for therapeutic intervention. D-peptide inhibitors offer unique advantages as therapeutics, including increased metabolic stability and low immunogenicity. Here, we introduce DexDesign, a novel OSPREY-based algorithm for computationally designing de novo D-peptide inhibitors. DexDesign leverages three novel techniques that are broadly applicable to computational protein design: the Minimum Flexible Set, K*-based Mutational Scan, and Inverse Alanine Scan. We apply these techniques and DexDesign to generate novel D-peptide inhibitors of two biomedically important PDZ domain targets: CAL and MAST2. We introduce a framework for analyzing de novo peptides-evaluation along a replication/restitution axis-and apply it to the DexDesign-generated D-peptides. Notably, the peptides we generated are predicted to bind their targets tighter than their targets' endogenous ligands, validating the peptides' potential as lead inhibitors. We also provide an implementation of DexDesign in the free and open source computational protein design software OSPREY.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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