Molecular dynamics conformational search of six cyclic peptides used in the template assembled synthetic protein approach for protein de novo design

Biopolymers ◽  
1992 ◽  
Vol 32 (10) ◽  
pp. 1283-1310 ◽  
Author(s):  
Rainer Floegel ◽  
Manfred Mutter
Keyword(s):  
Molecular Dynamics ◽  
Cyclic Peptides ◽  
De Novo ◽  
De Novo Design ◽  
Conformational Search ◽  
Synthetic Protein

Assessing protein conformational sampling and structural stability via de novo design and molecular dynamics simulations

Biopolymers ◽  
2015 ◽  
Vol 103 (6) ◽  
pp. 351-361 ◽  
Author(s):  
Keila C. Cunha ◽  
Victor H. Rusu ◽  
Isabelle F. T. Viana ◽  
Ernesto T. A. Marques ◽  
Rafael Dhalia ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Structural Stability ◽  
De Novo ◽  
De Novo Design ◽  
Conformational Sampling ◽  
Dynamics Simulations

scholarly journals Target-templated de novo design of macrocyclic d-/l-peptides: discovery of drug-like inhibitors of PD-1

2021 ◽  
Vol 12 (14) ◽  
pp. 5164-5170
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Macarena Sánchez-Navarro ◽  
Jesús García ◽  
...  
Keyword(s):  
Specific Surface ◽  
Protein Interactions ◽  
In Silico ◽  
Cyclic Peptides ◽  
De Novo ◽  
De Novo Design ◽  
Target Protein ◽  
Surface Patch ◽  
Protein Protein Interactions

In silico design of heterochiral cyclic peptides that bind to a specific surface patch on the target protein (PD-1, in this case) and disrupt protein–protein interactions.

Structure-based de novo design, molecular docking and molecular dynamics of primaquine analogues acting as quinone reductase II inhibitors

2015 ◽  
Vol 62 ◽  
pp. 235-244 ◽  
Author(s):  
Erika Murce ◽  
Teobaldo Ricardo Cuya-Guizado ◽  
Helmut Isaac Padilla-Chavarria ◽  
Tanos Celmar Costa França ◽  
Andre Silva Pimentel
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
De Novo ◽  
De Novo Design ◽  
Quinone Reductase

scholarly journals Anchor extension: a structure-guided approach to design cyclic peptides targeting enzyme active sites

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Parisa Hosseinzadeh ◽  
Paris R. Watson ◽  
Timothy W. Craven ◽  
Xinting Li ◽  
Stephen Rettie ◽  
...  
Keyword(s):  
Histone Deacetylases ◽  
Cyclic Peptides ◽  
Active Sites ◽  
De Novo ◽  
Computational Design ◽  
De Novo Design ◽  
Recent Success ◽  
Protein Interfaces ◽  
Canonical Amino Acid ◽  
Hdac6 Inhibitor

AbstractDespite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational “anchor extension” methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC50 values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain.

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

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

<p>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.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>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-<i>i</i>3 and PD-<i>i</i>6) 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 <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

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

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

<p>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.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>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-<i>i</i>3 and PD-<i>i</i>6) 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 <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

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

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

<p>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.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>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-<i>i</i>3 and PD-<i>i</i>6) 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 <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

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