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Folding Then Binding vs Folding Through Binding in Macrocyclic Peptide Inhibitors of Human Pancreatic α-Amylase.

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Goldbach L, Vermeulen BJA, Caner S, Liu M, Tysoe C, van Gijzel L, Yoshisada R, Trellet M, van Ingen H, Brayer GD, Bonvin AMJJ, Jongkees SAK
OpenAccess logo ACS Chem Biol 14 1751-1759 (2019)
Cited: 15 times
EuropePMC logo PMID: 31241898

Abstract

De novo macrocyclic peptides, derived using selection technologies such as phage and mRNA display, present unique and unexpected solutions to challenging biological problems. This is due in part to their unusual folds, which are able to present side chains in ways not available to canonical structures such as α-helices and β-sheets. Despite much recent interest in these molecules, their folding and binding behavior remains poorly characterized. In this work, we present cocrystallization, docking, and solution NMR structures of three de novo macrocyclic peptides that all bind as competitive inhibitors with single-digit nanomolar Ki to the active site of human pancreatic α-amylase. We show that a short stably folded motif in one of these is nucleated by internal hydrophobic interactions in an otherwise dynamic conformation in solution. Comparison of the solution structures with a target-bound structure from docking indicates that stabilization of the bound conformation is provided through interactions with the target protein after binding. These three structures also reveal a surprising functional convergence to present a motif of a single arginine sandwiched between two aromatic residues in the interactions of the peptide with the key catalytic residues of the enzyme, despite little to no other structural homology. Our results suggest that intramolecular hydrophobic interactions are important for priming binding of small macrocyclic peptides to their target and that high rigidity is not necessary for high affinity.

Articles - 5u3a mentioned but not cited (10)

  1. Enhancing glycan stability via site-selective fluorination: modulating substrate orientation by molecular design. Axer A, Jumde RP, Adam S, Faust A, Schäfers M, Fobker M, Koehnke J, Hirsch AKH, Gilmour R. Chem Sci 12 1286-1294 (2020)
  2. Folding Then Binding vs Folding Through Binding in Macrocyclic Peptide Inhibitors of Human Pancreatic α-Amylase. Goldbach L, Vermeulen BJA, Caner S, Liu M, Tysoe C, van Gijzel L, Yoshisada R, Trellet M, van Ingen H, Brayer GD, Bonvin AMJJ, Jongkees SAK. ACS Chem Biol 14 1751-1759 (2019)
  3. Identification of Phenolic Compounds from Nettle as New Candidate Inhibitors of Main Enzymes Responsible on Type-II Diabetes. Salim B, Said G, Kambouche N, Kress S. Curr Drug Discov Technol 17 197-202 (2020)
  4. Succinimide Derivatives as Antioxidant Anticholinesterases, Anti-α-Amylase, and Anti-α-Glucosidase: In Vitro and In Silico Approaches. Alshehri OM, Mahnashi MH, Sadiq A, Zafar R, Jan MS, Ullah F, Alshehri MA, Alshamrani S, Hassan EE. Evid Based Complement Alternat Med 2022 6726438 (2022)
  5. Cu/TEMPO catalyzed dehydrogenative 1,3-dipolar cycloaddition in the synthesis of spirooxindoles as potential antidiabetic agents. Teja C, Babu SN, Noor A, Daniel JA, Devi SA, Nawaz Khan FR. RSC Adv 10 12262-12271 (2020)
  6. Antidiabetic Properties of Hydroalcoholic Leaf and Stem Extract of Levisticum officinale: An implication for α-amylase Inhibitory Activity of Extract Ingredients through Molecular Docking. Ghaedi N, Pouraboli I, Askari N. Iran J Pharm Res 19 231-250 (2020)
  7. Screening chemical inhibitors for alpha-amylase from leaves extracts of Murraya koenigii (Linn.) and Aegle marmelos L. Sangilimuthu AY, Sivaraman T, Chandrasekaran R, Sundaram KM, Ekambaram G. J Complement Integr Med 18 51-57 (2020)
  8. Secondary Metabolite Profiling, Antioxidant, Antidiabetic and Neuroprotective Activity of Cestrum nocturnum (Night Scented-Jasmine): Use of In Vitro and In Silico Approach in Determining the Potential Bioactive Compound. Ahmad S, Alrouji M, Alhajlah S, Alomeir O, Pandey RP, Ashraf MS, Ahmad S, Khan S. Plants (Basel) 12 1206 (2023)
  9. The oxygen-oxygen distance of water in crystallographic data sets. Palese LL. Data Brief 28 105076 (2020)
  10. Virtual Screening Technology for Two Novel Peptides in Soybean as Inhibitors of α-Amylase and α-Glucosidase. Tang X, Chen X, Wang H, Yang J, Li L, Zhu J, Liu Y. Foods 12 4387 (2023)


Reviews citing this publication (1)

  1. Peptide Folding and Binding Probed by Systematic Non-canonical Mutagenesis. Rogers JM. Front Mol Biosci 7 100 (2020)

Articles citing this publication (4)

  1. Cyclic peptides can engage a single binding pocket through highly divergent modes. Patel K, Walport LJ, Walshe JL, Solomon PD, Low JKK, Tran DH, Mouradian KS, Silva APG, Wilkinson-White L, Norman A, Franck C, Matthews JM, Guss JM, Payne RJ, Passioura T, Suga H, Mackay JP. Proc Natl Acad Sci U S A 117 26728-26738 (2020)
  2. The role of NMR in leveraging dynamics and entropy in drug design. Dubey A, Takeuchi K, Reibarkh M, Arthanari H. J Biomol NMR 74 479-498 (2020)
  3. AAp-MSMD: Amino Acid Preference Mapping on Protein-Protein Interaction Surfaces Using Mixed-Solvent Molecular Dynamics. Kudo G, Yanagisawa K, Yoshino R, Hirokawa T. J Chem Inf Model 63 7768-7777 (2023)
  4. Cyclization and Docking Protocol for Cyclic Peptide-Protein Modeling Using HADDOCK2.4. Charitou V, van Keulen SC, Bonvin AMJJ. J Chem Theory Comput 18 4027-4040 (2022)


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