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

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-nati...

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Autores principales: Tao, Huanyu, Wu, Qilong, Zhao, Xuejun, Lin, Peicong, Huang, Sheng-You
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066754/
https://www.ncbi.nlm.nih.gov/pubmed/35505401
http://dx.doi.org/10.1186/s13321-022-00605-8
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author Tao, Huanyu
Wu, Qilong
Zhao, Xuejun
Lin, Peicong
Huang, Sheng-You
author_facet Tao, Huanyu
Wu, Qilong
Zhao, Xuejun
Lin, Peicong
Huang, Sheng-You
author_sort Tao, Huanyu
collection PubMed
description 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[Formula: see text] 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13321-022-00605-8.
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spelling pubmed-90667542022-05-04 Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond Tao, Huanyu Wu, Qilong Zhao, Xuejun Lin, Peicong Huang, Sheng-You J Cheminform Methodology 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[Formula: see text] 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13321-022-00605-8. Springer International Publishing 2022-05-03 /pmc/articles/PMC9066754/ /pubmed/35505401 http://dx.doi.org/10.1186/s13321-022-00605-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology
Tao, Huanyu
Wu, Qilong
Zhao, Xuejun
Lin, Peicong
Huang, Sheng-You
Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond
title Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond
title_full Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond
title_fullStr Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond
title_full_unstemmed Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond
title_short Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond
title_sort efficient 3d conformer generation of cyclic peptides formed by a disulfide bond
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066754/
https://www.ncbi.nlm.nih.gov/pubmed/35505401
http://dx.doi.org/10.1186/s13321-022-00605-8
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