Retraction notice to “Seven misconceptions regarding volume therapy strategies--and their correction” [Br J Anaesth 103 (2009) 147–51]

NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above. ------------------------------------------------------------------------ Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-i3 and PD-i6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our de novo design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.

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A Target-Based Method for Designing Heterochiral Cyclic Peptide Binders: De Novo Inhibitors of the PD-1/PD-L1 Interaction

10.26434/chemrxiv.11663337.v2 ◽

2020 ◽

Author(s):

Salvador Guardiola ◽

Monica Varese ◽

Xavier Roig ◽

Jesús Garcia ◽

Ernest Giralt

Keyword(s):

Protein Interactions ◽

Cyclic Peptides ◽

General Framework ◽

Large Scale ◽

Cyclic Peptide ◽

De Novo ◽

Inhibitory Effect ◽

Original Text ◽

Retraction Notice ◽

Pharmaceutical Properties

NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above. ------------------------------------------------------------------------ Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-i3 and PD-i6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our de novo design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.

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Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

10.26434/chemrxiv.11663337 ◽

2020 ◽

Author(s):

Salvador Guardiola ◽

Monica Varese ◽

Xavier Roig ◽

Jesús Garcia ◽

Ernest Giralt

Keyword(s):

Protein Interactions ◽

Cyclic Peptides ◽

General Framework ◽

Large Scale ◽

De Novo ◽

Inhibitory Effect ◽

Original Text ◽

Protein Protein Interactions ◽

Retraction Notice ◽

Pharmaceutical Properties

NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above. ------------------------------------------------------------------------ Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-i3 and PD-i6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our de novo design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.

Download Full-text