Cyclic peptides formed by disulfide bonds have been one large group of common drug candidates in drug development. Structural information of a peptide is essential to understand its interaction with its target. However, due to the high flexibility of peptides, it is difficult to sample the near-native conformations of a peptide. Here, we have developed an extended version of our MODPEP approach, named MODPEP2.0, to fast generate the conformations of cyclic peptides formed by a disulfide bond. MODPEP2.0 builds the three-dimensional (3D) structures of a cyclic peptide from scratch by assembling amino acids one by one onto the cyclic fragment based on the constructed rotamer and cyclic backbone libraries. Being tested on a data set of 193 diverse cyclic peptides, MODPEP2.0 obtained a considerable advantage in both accuracy and computational efficiency, compared with other sampling algorithms including PEP-FOLD, ETKDG, and modified ETKDG (mETKDG). MODPEP2.0 achieved a high sampling accuracy with an average C $$\alpha$$ RMSD of 2.20 Å and 1.66 Å when 10 and 100 conformations were considered, respectively, compared with 3.41 Å and 2.62 Å for PEP-FOLD, 3.44 Å and 3.16 Å for ETKDG, 3.09 Å and 2.72 Å for mETKDG. MODPEP2.0 also reproduced experimental peptide structures for 81.35% of the test cases when an ensemble of 100 conformations were considered, compared with 54.95%, 37.50% and 50.00% for PEP-FOLD, ETKDG, and mETKDG. MODPEP2.0 is computationally efficient and can generate 100 peptide conformations in one second. MODPEP2.0 will be useful in sampling cyclic peptide structures and modeling related protein-peptide interactions, facilitating the development of cyclic peptide drugs.

中文翻译：

---

由二硫键形成的环肽的高效 3D 构象异构体生成

由二硫键形成的环状肽是药物开发中一大类常见的候选药物。肽的结构信息对于了解其与靶标的相互作用至关重要。然而，由于肽的高度灵活性，很难对肽的接近天然构象进行采样。在这里，我们开发了我们的 MODPEP 方法的扩展版本，名为 MODPEP2.0，以快速生成由二硫键形成的环肽的构象。MODPEP2.0基于构建的旋转异构体和环状骨架文库，通过将氨基酸一一组装到环状片段上，从零开始构建环状肽的三维（3D）结构。正在对 193 种不同的环肽 MODPEP2 的数据集进行测试。与 PEP-FOLD、ETKDG 和修改后的 ETKDG (mETKDG) 等其他采样算法相比，0 在准确性和计算效率方面都获得了相当大的优势。当分别考虑 10 和 100 个构象时，MODPEP2.0 实现了高采样精度，平均 C $$\alpha$$ RMSD 为 2.20 Å 和 1.66 Å，而 PEP-FOLD 为 3.41 Å 和 2.62 Å，3.44 Å 和ETKDG 为 3.16 Å，mETKDG 为 3.09 Å 和 2.72 Å。当考虑 100 个构象的集合时，MODPEP2.0 还为 81.35% 的测试用例重现了实验性肽结构，而 PEP-FOLD、ETKDG 和 mETKDG 为 54.95%、37.50% 和 50.00%。MODPEP2.0 计算效率高，可以在一秒钟内生成 100 个肽构象。MODEP2。