Computational Prediction of Cyclic Peptide Structural Ensembles and Application to the Design of Keap1 Binders-Reference-Cited by-同舟云学术

Computational Prediction of Cyclic Peptide Structural Ensembles and Application to the Design of Keap1 Binders

Published:2023-11-02 Issue:21 Volume:63 Page:6925-6937
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Fonseca Lopez Francini¹,Miao Jiayuan¹^ORCID,Damjanovic Jovan¹^ORCID,Bischof Luca²³,Braun Michael B.²³,Ling Yingjie¹,Hartmann Marcus D.²³^ORCID,Lin Yu-Shan¹^ORCID,Kritzer Joshua A.¹^ORCID

Affiliation:

1. Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States

2. Department of Protein Evolution, Max Planck Institute for Biology, 72076 Tübingen, Germany

3. Interfaculty Institute of Biochemistry, Tübingen University, 72076 Tübingen, Germany

Funder

National Institute of General Medical Sciences

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c01337

Reference74 articles.

1. Cyclic peptide therapeutics: past, present and future

2. DrugBank 5.0: a major update to the DrugBank database for 2018

3. A gold mine for drug discovery: Strategies to develop cyclic peptides into therapies

4. Construction and screening of vast libraries of natural product-like macrocyclic peptides using in vitro display technologies

5. Accurate de novo design of membrane-traversing macrocycles

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