Comprehensive computational design of ordered peptide macrocycles

Hosseinzadeh, Parisa; Bhardwaj, Gaurav; Mulligan, Vikram Khipple; Shortridge, Matthew D.; Craven, Timothy W.; Pardo-Avila, Fátima; Rettie, Stephen A.; Kim, David E.; Silva, Daniel-Adriano; Ibrahim, Yehia M.; Webb, Ian K.; Cort, John R.; Adkins, Joshua N.; Varani, Gabriele; Baker, David

doi:10.1126/science.aap7577

Title: Comprehensive computational design of ordered peptide macrocycles

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Abstract

Mixed chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to-date, but there is currently no way to systematically search through the structural space spanned by such compounds for new drug candidates. Natural proteins do not provide a useful guide: peptide macrocycles lack regular secondary structures and hydrophobic cores and have different backbone torsional constraints. Hence the development of new peptide macrocycles has been approached by modifying natural products or using library selection methods; the former is limited by the small number of known structures, and the latter by the limited size and diversity accessible through library-based methods. To overcome these limitations, here we enumerate the stable structures that can be adopted by macrocyclic peptides composed of L and D amino acids. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. We synthesize and characterize by NMR twelve 7-10 residue macrocycles, 9 of which have structures very close to the design models in solution. NMR structures of three 11-14 residue bicyclic designs are also very close to the computational models. Our results provide a nearly complete coverage of themore »« less

Authors:

;

; Craven, Timothy W.; Pardo-Avila, Fátima;

;

; Cort, John R.;

; Varani, Gabriele;

Publication Date:: Thu Dec 14 00:00:00 EST 2017

Research Org.:: Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1414526

Report Number(s):: PNNL-SA-128820
Journal ID: ISSN 0036-8075; 48680

DOE Contract Number:: AC05-76RL01830

Resource Type:: Journal Article

Journal Name:: Science

Additional Journal Information:: Journal Volume: 358; Journal Issue: 6369; Journal ID: ISSN 0036-8075

Publisher:: AAAS

Country of Publication:: United States

Language:: English

Subject:: NMR; SLIM; protein folding; protein structure; Environmental Molecular Sciences Laboratory

Citation Formats


                    Hosseinzadeh, Parisa, Bhardwaj, Gaurav, Mulligan, Vikram Khipple, Shortridge, Matthew D., Craven, Timothy W., Pardo-Avila, Fátima, Rettie, Stephen A., Kim, David E., Silva, Daniel-Adriano, Ibrahim, Yehia M., Webb, Ian K., Cort, John R., Adkins, Joshua N., Varani, Gabriele, and Baker, David. Comprehensive computational design of ordered peptide macrocycles.  United States: N. p., 2017. 
        Web.  doi:10.1126/science.aap7577.

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                    Hosseinzadeh, Parisa, Bhardwaj, Gaurav, Mulligan, Vikram Khipple, Shortridge, Matthew D., Craven, Timothy W., Pardo-Avila, Fátima, Rettie, Stephen A., Kim, David E., Silva, Daniel-Adriano, Ibrahim, Yehia M., Webb, Ian K., Cort, John R., Adkins, Joshua N., Varani, Gabriele, & Baker, David. Comprehensive computational design of ordered peptide macrocycles.  United States.  https://doi.org/10.1126/science.aap7577

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                    Hosseinzadeh, Parisa, Bhardwaj, Gaurav, Mulligan, Vikram Khipple, Shortridge, Matthew D., Craven, Timothy W., Pardo-Avila, Fátima, Rettie, Stephen A., Kim, David E., Silva, Daniel-Adriano, Ibrahim, Yehia M., Webb, Ian K., Cort, John R., Adkins, Joshua N., Varani, Gabriele, and Baker, David. 2017.  
        "Comprehensive computational design of ordered peptide macrocycles".  United States.  https://doi.org/10.1126/science.aap7577.

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@article{osti_1414526,

  title        = {Comprehensive computational design of ordered peptide macrocycles},

  author       = {Hosseinzadeh, Parisa and Bhardwaj, Gaurav and Mulligan, Vikram Khipple and Shortridge, Matthew D. and Craven, Timothy W. and Pardo-Avila, Fátima and Rettie, Stephen A. and Kim, David E. and Silva, Daniel-Adriano and Ibrahim, Yehia M. and Webb, Ian K. and Cort, John R. and Adkins, Joshua N. and Varani, Gabriele and Baker, David},

  abstractNote = {Mixed chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to-date, but there is currently no way to systematically search through the structural space spanned by such compounds for new drug candidates. Natural proteins do not provide a useful guide: peptide macrocycles lack regular secondary structures and hydrophobic cores and have different backbone torsional constraints. Hence the development of new peptide macrocycles has been approached by modifying natural products or using library selection methods; the former is limited by the small number of known structures, and the latter by the limited size and diversity accessible through library-based methods. To overcome these limitations, here we enumerate the stable structures that can be adopted by macrocyclic peptides composed of L and D amino acids. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. We synthesize and characterize by NMR twelve 7-10 residue macrocycles, 9 of which have structures very close to the design models in solution. NMR structures of three 11-14 residue bicyclic designs are also very close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide based macrocycles unparalleled for other molecular systems, and vastly increase the available starting scaffolds for both rational drug design and library selection methods.},

  doi          = {10.1126/science.aap7577},

  url          = {https://www.osti.gov/biblio/1414526},
  journal      = {Science},

  issn         = {0036-8075},

  number       = 6369,

  volume       = 358,

  place        = {United States},

  year         = {Thu Dec 14 00:00:00 EST 2017},

  month        = {Thu Dec 14 00:00:00 EST 2017}

}

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