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Damjanovic J, Miao J, Huang H, Lin YS. Elucidating Solution Structures of Cyclic Peptides Using Molecular Dynamics Simulations. Chem Rev 2021; 121:2292-2324. [PMID: 33426882 DOI: 10.1021/acs.chemrev.0c01087] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Protein-protein interactions are vital to biological processes, but the shape and size of their interfaces make them hard to target using small molecules. Cyclic peptides have shown promise as protein-protein interaction modulators, as they can bind protein surfaces with high affinity and specificity. Dozens of cyclic peptides are already FDA approved, and many more are in various stages of development as immunosuppressants, antibiotics, antivirals, or anticancer drugs. However, most cyclic peptide drugs so far have been natural products or derivatives thereof, with de novo design having proven challenging. A key obstacle is structural characterization: cyclic peptides frequently adopt multiple conformations in solution, which are difficult to resolve using techniques like NMR spectroscopy. The lack of solution structural information prevents a thorough understanding of cyclic peptides' sequence-structure-function relationship. Here we review recent development and application of molecular dynamics simulations with enhanced sampling to studying the solution structures of cyclic peptides. We describe novel computational methods capable of sampling cyclic peptides' conformational space and provide examples of computational studies that relate peptides' sequence and structure to biological activity. We demonstrate that molecular dynamics simulations have grown from an explanatory technique to a full-fledged tool for systematic studies at the forefront of cyclic peptide therapeutic design.
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Affiliation(s)
- Jovan Damjanovic
- Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States
| | - Jiayuan Miao
- Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States
| | - He Huang
- Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States
| | - Yu-Shan Lin
- Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States
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Reyes Romero A, Ruiz-Moreno AJ, Groves MR, Velasco-Velázquez M, Dömling A. Benchmark of Generic Shapes for Macrocycles. J Chem Inf Model 2020; 60:6298-6313. [PMID: 33270455 PMCID: PMC7768607 DOI: 10.1021/acs.jcim.0c01038] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
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Macrocycles
target proteins that are otherwise considered undruggable
because of a lack of hydrophobic cavities and the presence of extended
featureless surfaces. Increasing efforts by computational chemists
have developed effective software to overcome the restrictions of
torsional and conformational freedom that arise as a consequence of
macrocyclization. Moloc is an efficient algorithm, with an emphasis
on high interactivity, and has been constantly updated since 1986
by drug designers and crystallographers of the Roche biostructural
community. In this work, we have benchmarked the shape-guided algorithm
using a dataset of 208 macrocycles, carefully selected on the basis
of structural complexity. We have quantified the accuracy, diversity,
speed, exhaustiveness, and sampling efficiency in an automated fashion
and we compared them with four commercial (Prime, MacroModel, molecular
operating environment, and molecular dynamics) and four open-access
(experimental-torsion distance geometry with additional “basic
knowledge” alone and with Merck molecular force field minimization
or universal force field minimization, Cambridge Crystallographic
Data Centre conformer generator, and conformator) packages. With three-quarters
of the database processed below the threshold of high ring accuracy,
Moloc was identified as having the highest sampling efficiency and
exhaustiveness without producing thousands of conformations, random
ring splitting into two half-loops, and possibility to interactively
produce globular or flat conformations with diversity similar to Prime,
MacroModel, and molecular dynamics. The algorithm and the Python scripts
for full automatization of these parameters are freely available for
academic use.
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Affiliation(s)
- Atilio Reyes Romero
- Drug Design, Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, XB20, 9713 AV Groningen, The Netherlands
| | - Angel Jonathan Ruiz-Moreno
- Drug Design, Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, XB20, 9713 AV Groningen, The Netherlands.,Departamento de Farmacología y Unidad Periférica de Investigación en Biomedicina Trasnacional, Facultad de Medicina, Universidad Nacional Autónoma de México (UNAM), Av. Universidad 3000, Circuito Exterior S/N, Delegación Coyoacán, Ciudad Universitaria, 04510 Ciudad de México, Mexico.,Programa de Doctorado en Ciencias Biomédicas, UNAM, Av. Universidad 3000, Circuito Exterior S/N. Delegación Coyoacán, Ciudad Universitaria, 04510 Ciudad de México, Mexico
| | - Matthew R Groves
- Drug Design, Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, XB20, 9713 AV Groningen, The Netherlands
| | - Marco Velasco-Velázquez
- Departamento de Farmacología y Unidad Periférica de Investigación en Biomedicina Trasnacional, Facultad de Medicina, Universidad Nacional Autónoma de México (UNAM), Av. Universidad 3000, Circuito Exterior S/N, Delegación Coyoacán, Ciudad Universitaria, 04510 Ciudad de México, Mexico
| | - Alexander Dömling
- Drug Design, Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, XB20, 9713 AV Groningen, The Netherlands
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Foreman DJ, Lawler JT, Niedrauer ML, Hostetler MA, McLuckey SA. Gold(I) Cationization Promotes Ring Opening in Lysine-Containing Cyclic Peptides. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2019; 30:1914-1922. [PMID: 31250319 PMCID: PMC6812625 DOI: 10.1007/s13361-019-02247-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 05/07/2019] [Accepted: 05/07/2019] [Indexed: 06/09/2023]
Abstract
A strategy to sequence lysine-containing cyclic peptides by MSn is presented. Doubly protonated cyclic peptides ions are transformed into gold (I) cationized peptide ions via cation switching ion/ion reaction. Gold(I) cationization facilitates the oxidation of neutral lysine residues in the gas phase, weakening the adjacent amide bond. Upon activation, facile cleavage N-terminal to the oxidized lysine residue provides a site-specific ring opening pathway that converts cyclic peptides into acyclic analogs. The ensuing ion contains a cyclic imine as the new N-terminus and an oxazolone, or structural equivalent, as the new C-terminus. Product ions are formed from subsequent fragmentation events of the linearized peptide ion. Such an approach simplifies MS/MS data interpretation as a series of fragment ions with common N- and C-termini are generated. Results are presented for two cyclic peptides, sunflower trypsin inhibitor and the model cyclic peptide, β-Loop. The power of this strategy lies in the ability to generate the oxidized peptide, which is easily identified via the loss of HAuNH3 from [M + Au]+. While some competitive processes are observed, the site of ring opening can be pinpointed to the lysine residue upon MS4 enabling the unambiguous sequencing of cyclic peptides.
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Affiliation(s)
- David J Foreman
- Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, IN, 47907-2084, USA
| | - John T Lawler
- Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, IN, 47907-2084, USA
| | - Mary L Niedrauer
- Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, IN, 47907-2084, USA
| | - Matthew A Hostetler
- Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, IN, 47907-2084, USA
| | - Scott A McLuckey
- Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, IN, 47907-2084, USA.
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Cummings AE, Miao J, Slough DP, McHugh SM, Kritzer JA, Lin YS. β-Branched Amino Acids Stabilize Specific Conformations of Cyclic Hexapeptides. Biophys J 2019; 116:433-444. [PMID: 30661666 DOI: 10.1016/j.bpj.2018.12.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 11/19/2018] [Accepted: 12/13/2018] [Indexed: 01/11/2023] Open
Abstract
Cyclic peptides (CPs) are a promising class of molecules for drug development, particularly as inhibitors of protein-protein interactions. Predicting low-energy structures and global structural ensembles of individual CPs is critical for the design of bioactive molecules, but these are challenging to predict and difficult to verify experimentally. In our previous work, we used explicit-solvent molecular dynamics simulations with enhanced sampling methods to predict the global structural ensembles of cyclic hexapeptides containing different permutations of glycine, alanine, and valine. One peptide, cyclo-(VVGGVG) or P7, was predicted to be unusually well structured. In this work, we synthesized P7, along with a less well-structured control peptide, cyclo-(VVGVGG) or P6, and characterized their global structural ensembles in water using NMR spectroscopy. The NMR data revealed a structural ensemble similar to the prediction for P7 and showed that P6 was indeed much less well-structured than P7. We then simulated and experimentally characterized the global structural ensembles of several P7 analogs and discovered that β-branching at one critical position within P7 is important for overall structural stability. The simulations allowed deconvolution of thermodynamic factors that underlie this structural stabilization. Overall, the excellent correlation between simulation and experimental data indicates that our simulation platform will be a promising approach for designing well-structured CPs and also for understanding the complex interactions that control the conformations of constrained peptides and other macrocycles.
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Affiliation(s)
| | - Jiayuan Miao
- Department of Chemistry, Tufts University, Medford, Massachusetts
| | - Diana P Slough
- Department of Chemistry, Tufts University, Medford, Massachusetts
| | - Sean M McHugh
- Department of Chemistry, Tufts University, Medford, Massachusetts
| | - Joshua A Kritzer
- Department of Chemistry, Tufts University, Medford, Massachusetts.
| | - Yu-Shan Lin
- Department of Chemistry, Tufts University, Medford, Massachusetts.
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