Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond

• Published in: Journal of cheminformatics Vol. 14; no. 1; p. 26
• Main Authors: Tao, Huanyu, Wu, Qilong, Zhao, Xuejun, Lin, Peicong, Huang, Sheng-You
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 03-05-2022; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Accuracy; Algorithms; Amino acids; Bonds; Chemical bonds; Chemistry; Chemistry and Materials Science; Computational Biology/Bioinformatics; Computational efficiency; Computer applications; Computer Applications in Chemistry; Conformer generation; Cyclic peptide; Disulfide bond; Disulfide bonds; Documentation and Information in Chemistry; Drug development; Methodology; Peptide docking; Peptide modeling; Peptides; Protein structure; Sampling; Theoretical and Computational Chemistry; Peptide modeling; Cyclic peptide; Peptide docking; Disulfide bond; Conformer generation
• ISSN: 1758-2946; 1758-2946
• DOI: 10.1186/s13321-022-00605-8

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
α
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.