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Karami Y, Murail S, Giribaldi J, Lefranc B, Defontaine F, Lesouhaitier O, Leprince J, de Vries S, Tufféry P. Exploring a Structural Data Mining Approach to Design Linkers for Head-to-Tail Peptide Cyclization. J Chem Inf Model 2023; 63:6436-6450. [PMID: 37827517 PMCID: PMC10599322 DOI: 10.1021/acs.jcim.3c00865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Indexed: 10/14/2023]
Abstract
Peptides have recently regained interest as therapeutic candidates, but their development remains confronted with several limitations including low bioavailability. Backbone head-to-tail cyclization, i.e., setting a covalent peptide bond linking the last amino acid with the first one, is one effective strategy of peptide-based drug design to stabilize the conformation of bioactive peptides while preserving peptide properties in terms of low toxicity, binding affinity, target selectivity, and preventing enzymatic degradation. Starting from an active peptide, it usually requires the design of a linker of a few amino acids to make it possible to cyclize the peptide, possibly preserving the conformation of the initial peptide and not affecting its activity. However, very little is known about the sequence-structure relationship requirements of designing linkers for peptide cyclization in a rational manner. Recently, we have shown that large-scale data-mining of available protein structures can lead to the precise identification of protein loop conformations, even from remote structural classes. Here, we transpose this approach to linkers, allowing head-to-tail peptide cyclization. First we show that given a linker sequence and the conformation of the linear peptide, it is possible to accurately predict the cyclized peptide conformation. Second, and more importantly, we show that it seems possible to elaborate on the information inferred from protein structures to propose effective candidate linker sequences constrained by length and amino acid composition, providing the first framework for the rational design of head-to-tail cyclization linkers. Finally, we illustrate this for two peptides using a limited set of amino-acids likely not to interfere with peptide function. For a linear peptide derived from Nrf2, the peptide cyclized starting from the experimental structure showed a 26-fold increase in the binding affinity. For urotensin II, a peptide already cyclized by a disulfide bond that exerts a broad array of biological activities, we were able, starting from models of the structure, to design a head-to-tail cyclized peptide, the first synthesized bicyclic 14-residue long urotensin II analogue, showing a retention of in vitro activity. Although preliminary, our results strongly suggest that such an approach has strong potential for cyclic peptide-based drug design.
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Affiliation(s)
- Yasaman Karami
- Université
Paris Cité, CNRS UMR 8251,
INSERM ERL U1133, 75013 Paris, France
| | - Samuel Murail
- Université
Paris Cité, CNRS UMR 8251,
INSERM ERL U1133, 75013 Paris, France
| | - Julien Giribaldi
- Institut
des Biomolécules Max Mousseron, UMR 5247, Université de Montpellier-CNRS, 34293 Montpellier, France
| | - Benjamin Lefranc
- Université
de Rouen Normandie, INSERM U1239 NorDiC, Neuroendocrine, Endocrine and Germinal Differentiation and Communication,
INSERM US51 HeRacLeS, F-76000 Rouen, France
| | - Florian Defontaine
- Université
de Rouen Normandie, UR CBSA, Research Unit
Bacterial Communication and Anti-infectious Strategies, 27000 Evreux, France
| | - Olivier Lesouhaitier
- Université
de Rouen Normandie, UR CBSA, Research Unit
Bacterial Communication and Anti-infectious Strategies, 27000 Evreux, France
| | - Jérôme Leprince
- Université
de Rouen Normandie, INSERM U1239 NorDiC, Neuroendocrine, Endocrine and Germinal Differentiation and Communication,
INSERM US51 HeRacLeS, F-76000 Rouen, France
| | - Sjoerd de Vries
- Université
Paris Cité, CNRS UMR 8251,
INSERM ERL U1133, 75013 Paris, France
| | - Pierre Tufféry
- Université
Paris Cité, CNRS UMR 8251,
INSERM ERL U1133, 75013 Paris, France
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Silva-Brea D, de Sancho D, Lopez X. Influence of metal binding on the conformational landscape of neurofilament peptides. Phys Chem Chem Phys 2023; 25:26429-26442. [PMID: 37551731 DOI: 10.1039/d3cp03179a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
Abstract
In order to understand the preferred modes of chelation in metal-binding peptides, quantum mechanical calculations can be used to compute energies, resulting in a hierarchy of binding affinities. These calculations often produce increasing stabilization energies the higher the coordination of the complex. However, as the coordination of a metal increases, the conformational freedom of the polypeptide chain is inevitably reduced, resulting in an entropic penalty. Estimating the magnitude of this penalty from the many different degrees of freedom of biomolecular systems is very challenging, and as a result this contribution to the free energy is often ignored. Here we explore this problem focusing on a family of phosphorylated neuropeptides that bind to aluminum. We find that there is a general negative correlation between both stabilization energy and entropy. Our results suggest that a subtle interplay between enthalpic and entropic forces will determine the population of the most favourable species. Additionally, we discuss the requirements for a possible "Metal Ion Hypothesis" based on our findings.
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Affiliation(s)
- David Silva-Brea
- Donostia International Physics Center (DIPC), PK 1072, 20080 Donostia San-Sebastian, Spain.
- Polimero eta Material Aurreratuak: Fisika, Kimika eta Teknologia, Kimika Fakultatea, UPV/EHU, Spain
| | - David de Sancho
- Donostia International Physics Center (DIPC), PK 1072, 20080 Donostia San-Sebastian, Spain.
- Polimero eta Material Aurreratuak: Fisika, Kimika eta Teknologia, Kimika Fakultatea, UPV/EHU, Spain
| | - Xabier Lopez
- Donostia International Physics Center (DIPC), PK 1072, 20080 Donostia San-Sebastian, Spain.
- Polimero eta Material Aurreratuak: Fisika, Kimika eta Teknologia, Kimika Fakultatea, UPV/EHU, Spain
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Watson PR, Gupta S, Hosseinzadeh P, Brown BP, Baker D, Christianson DW. Macrocyclic Octapeptide Binding and Inferences on Protein Substrate Binding to Histone Deacetylase 6. ACS Chem Biol 2023; 18:959-968. [PMID: 37027789 PMCID: PMC10130746 DOI: 10.1021/acschembio.3c00113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2023]
Abstract
Histone deacetylases (HDACs) are essential for the regulation of myriad biological processes, and their aberrant function is implicated in cancer, neurodegeneration, and other diseases. The cytosolic isozyme HDAC6 is unique among the greater family of deacetylases in that it contains two catalytic domains, CD1 and CD2. HDAC6 CD2 is responsible for tubulin deacetylase and tau deacetylase activities, inhibition of which is a key goal as new therapeutic approaches are explored. Of particular interest as HDAC inhibitors are naturally occurring cyclic tetrapeptides such as Trapoxin A or HC Toxin, or the cyclic depsipeptides Largazole and Romidepsin. Even more intriguing are larger, computationally designed macrocyclic peptide inhibitors. Here, we report the 2.0 Å resolution crystal structure of HDAC6 CD2 complexed with macrocyclic octapeptide 1. Comparison with the previously reported structure of the complex with macrocyclic octapeptide 2 reveals that a potent thiolate-zinc interaction made by the unnatural amino acid (S)-2-amino-7-sulfanylheptanoic acid contributes to nanomolar inhibitory potency for each inhibitor. Apart from this zinc-binding residue, octapeptides adopt strikingly different overall conformations and make few direct hydrogen bonds with the protein. Intermolecular interactions are dominated by water-mediated hydrogen bonds; in essence, water molecules appear to cushion the enzyme-octapeptide interface. In view of the broad specificity observed for protein substrates of HDAC6 CD2, we suggest that the binding of macrocyclic octapeptides may mimic certain features of the binding of macromolecular protein substrates.
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Affiliation(s)
- Paris R. Watson
- Roy and Diana Vagelos Laboratories, Department of Chemistry, University of Pennsylvania, 231 South 34 Street, Philadelphia, PA 19104-6323, United States
| | - Suchetana Gupta
- Department of Bioengineering, Knight Campus, University of Oregon, Eugene, OR 97403 United States
| | - Parisa Hosseinzadeh
- Department of Bioengineering, Knight Campus, University of Oregon, Eugene, OR 97403 United States
| | - Benjamin P. Brown
- Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN 37235 United States
| | - David Baker
- Department of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA 98195 United States
| | - David W. Christianson
- Roy and Diana Vagelos Laboratories, Department of Chemistry, University of Pennsylvania, 231 South 34 Street, Philadelphia, PA 19104-6323, United States
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Mortensen JC, Damjanovic J, Miao J, Hui T, Lin Y. A backbone-dependent rotamer library with high (ϕ, ψ) coverage using metadynamics simulations. Protein Sci 2022; 31:e4491. [PMID: 36327064 PMCID: PMC9679973 DOI: 10.1002/pro.4491] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 10/26/2022] [Accepted: 10/28/2022] [Indexed: 12/06/2023]
Abstract
Backbone-dependent rotamer libraries are commonly used to assign the side chain dihedral angles of amino acids when modeling protein structures. Most rotamer libraries are created by curating protein crystal structure data and using various methods to extrapolate the existing data to cover all possible backbone conformations. However, these rotamer libraries may not be suitable for modeling the structures of cyclic peptides and other constrained peptides because these molecules frequently sample backbone conformations rarely seen in the crystal structures of linear proteins. To provide backbone-dependent side chain information beyond the α-helix, β-sheet, and PPII regions, we used explicit-solvent metadynamics simulations of model dipeptides to create a new rotamer library that has high coverage in the (ϕ, ψ) space. Furthermore, this approach can be applied to build high-coverage rotamer libraries for noncanonical amino acids. The resulting Metadynamics of Dipeptides for Rotamer Distribution (MEDFORD) rotamer library predicts the side chain conformations of high-resolution protein crystal structures with similar accuracy (~80%) to a state-of-the-art rotamer library. Our ability to test the accuracy of MEDFORD at predicting the side chain dihedral angles of amino acids in noncanonical backbone conformation is restricted by the limited structural data available for cyclic peptides. For the cyclic peptide data that are currently available, MEDFORD and the state-of-the-art rotamer library perform comparably. However, the two rotamer libraries indeed make different rotamer predictions in noncanonical (ϕ, ψ) regions. For noncanonical amino acids, the MEDFORD rotamer library predicts the χ1 values with approximately 75% accuracy.
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Affiliation(s)
| | | | - Jiayuan Miao
- Department of ChemistryTufts UniversityMedfordMassachusettsUSA
| | - Tiffani Hui
- Department of ChemistryTufts UniversityMedfordMassachusettsUSA
| | - Yu‐Shan Lin
- Department of ChemistryTufts UniversityMedfordMassachusettsUSA
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Liao HJ, Tzen JTC. The Potential Role of Cyclopeptides from Pseudostellaria heterophylla, Linum usitatissimum and Drymaria diandra, and Peptides Derived from Heterophyllin B as Dipeptidyl Peptidase IV Inhibitors for the Treatment of Type 2 Diabetes: An In Silico Study. Metabolites 2022; 12:metabo12050387. [PMID: 35629891 PMCID: PMC9146144 DOI: 10.3390/metabo12050387] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/17/2022] [Accepted: 04/19/2022] [Indexed: 02/04/2023] Open
Abstract
Dipeptidyl peptidase 4 (DPP4) inhibitors can treat type 2 diabetes by slowing GLP-1 degradation to increase insulin secretion. Studies have reported that Pseudostellaria heterophylla, Linum usita-tissimum (flaxseed), and Drymaria diandra, plants rich in Caryophyllaceae-type cyclopeptides and commonly used as herbal or dietary supplements, are effective in controlling blood sugar. The active site of DPP4 is in a cavity large enough to accommodate their cyclopeptides. Molecular modeling by AutoDock Vina reveals that certain cyclopeptides in these plants have the potential for DPP4 inhibition. In particular, “Heterophyllin B” from P. heterophylla, “Cyclolinopeptide C” from flaxseed, and “Diandrine C” from D. diandra, with binding affinities of −10.4, −10.0, and −10.7 kcal/mol, are promising. Docking suggests that DPP4 inhibition may be one of the reasons why these three plants are beneficial for lowering blood sugar. Because many protein hydrolysates have shown the effect of DPP4 inhibition, a series of peptides derived from Heterophyllin B precursor “IFGGLPPP” were included in the study. It was observed that IFWPPP (−10.5 kcal/mol), IFGGWPPP (−11.4 kcal/mol), and IFGWPPP (−12.0 kcal/mol) showed good binding affinity and interaction for DPP4. Various IFGGLPPP derivatives have the potential to serve as scaffolds for the design of novel DPP4 inhibitors.
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Damjanovic J, Murphy JM, Lin YS. CATBOSS: Cluster Analysis of Trajectories Based on Segment Splitting. J Chem Inf Model 2021; 61:5066-5081. [PMID: 34608796 PMCID: PMC8549068 DOI: 10.1021/acs.jcim.1c00598] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
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Molecular dynamics
(MD) simulations are an exceedingly and increasingly
potent tool for molecular behavior prediction and analysis. However,
the enormous wealth of data generated by these simulations can be
difficult to process and render in a human-readable fashion. Cluster
analysis is a commonly used way to partition data into structurally
distinct states. We present a method that improves on the state of
the art by taking advantage of the temporal information of MD trajectories
to enable more accurate clustering at a lower memory cost. To date,
cluster analysis of MD simulations has generally treated simulation
snapshots as a mere collection of independent data points and attempted
to separate them into different clusters based on structural similarity.
This new method, cluster analysis of trajectories based on segment
splitting (CATBOSS), applies density-peak-based clustering to classify trajectory segments learned by change detection. Applying
the method to a synthetic toy model as well as four real-life data
sets–trajectories of MD simulations of alanine dipeptide and
valine dipeptide as well as two fast-folding proteins–we find
CATBOSS to be robust and highly performant, yielding natural-looking
cluster boundaries and greatly improving clustering resolution. As
the classification of points into segments emphasizes density gaps
in the data by grouping them close to the state means, CATBOSS applied
to the valine dipeptide system is even able to account for a degree
of freedom deliberately omitted from the input data set. We also demonstrate
the potential utility of CATBOSS in distinguishing metastable states
from transition segments as well as promising application to cases
where there is little or no advance knowledge of intrinsic coordinates,
making for a highly versatile analysis tool.
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Affiliation(s)
- Jovan Damjanovic
- Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States
| | - James M Murphy
- Department of Mathematics, Tufts University, Medford, Massachusetts 02155, United States
| | - Yu-Shan Lin
- Department of Chemistry, Tufts University, Medford, Massachusetts 02155, United States
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