A Quantum Chemical Deep-Dive into the π-π Interactions of 3-Methylindole and Its Halogenated Derivatives-Towards an Improved Ligand Design and Tryptophan Stacking

Overview

Journal Pharmaceuticals (Basel)

Publisher MDPI

Specialty Chemistry

Date 2022 Aug 26

PMID 36015083

Authors

Ruben Van Lommel

Tom Bettens

Thomas M A Barlow

Jolien Bertouille

Steven Ballet

Frank De Proft

Affiliations

Soon will be listed here.

Abstract

Non-covalent π-π stacking interactions often play a key role in the stability of the secondary and tertiary structures of peptides and proteins, respectively, and can be a means of ensuring the binding of ligands within protein and enzyme binding sites. It is generally accepted that minor structural changes to the aromatic ring, such as substitution, can have a large influence on these interactions. Nevertheless, a thorough understanding of underpinning phenomena guiding these key interactions is still limited. This is especially true for larger aromatic structures. To expand upon this knowledge, elaborate ab initio calculations were performed to investigate the effect of halogenation on the stability of 3-methylindole stacking. 3-Methylindole served as a representation of the tryptophan side chain, and is a frequently used motif in drug design and development. Moreover, an expression is derived that is able to accurately predict the interaction stability of stacked halogenated 3-methylindole dimers as well as halogenated toluene dimers, based on monomer level calculated DFT descriptors. We aim for this expression to provide the field with a straightforward and reliable method to assess the effect of halogenation on the π-π stacking interactions between aromatic scaffolds.

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References

McGaughey G, Gagne M, Rappe A . pi-Stacking interactions. Alive and well in proteins. J Biol Chem. 1998; 273(25):15458-63. DOI: 10.1074/jbc.273.25.15458. View

Chadha N, Silakari O . Indoles as therapeutics of interest in medicinal chemistry: Bird's eye view. Eur J Med Chem. 2017; 134:159-184. DOI: 10.1016/j.ejmech.2017.04.003. View

Sun X, Soini T, Poater J, Hamlin T, Bickelhaupt F . PyFrag 2019-Automating the exploration and analysis of reaction mechanisms. J Comput Chem. 2019; 40(25):2227-2233. PMC: 6771738. DOI: 10.1002/jcc.25871. View

Kumar K, Woo S, Siu T, Cortopassi W, Duarte F, Paton R . Cation-π interactions in protein-ligand binding: theory and data-mining reveal different roles for lysine and arginine. Chem Sci. 2018; 9(10):2655-2665. PMC: 5903419. DOI: 10.1039/c7sc04905f. View

Vitaku E, Smith D, Njardarson J . Analysis of the structural diversity, substitution patterns, and frequency of nitrogen heterocycles among U.S. FDA approved pharmaceuticals. J Med Chem. 2014; 57(24):10257-74. DOI: 10.1021/jm501100b. View

Wheeler S, Houk K . Integration Grid Errors for Meta-GGA-Predicted Reaction Energies: Origin of Grid Errors for the M06 Suite of Functionals. J Chem Theory Comput. 2010; 6(2):395-404. PMC: 2840268. DOI: 10.1021/ct900639j. View

Wheeler S . Local nature of substituent effects in stacking interactions. J Am Chem Soc. 2011; 133(26):10262-74. DOI: 10.1021/ja202932e. View

Asensio J, Arda A, Canada F, Jimenez-Barbero J . Carbohydrate-aromatic interactions. Acc Chem Res. 2012; 46(4):946-54. DOI: 10.1021/ar300024d. View

Schneider H . Interactions in supramolecular complexes involving arenes: experimental studies. Acc Chem Res. 2012; 46(4):1010-9. DOI: 10.1021/ar3000579. View

10.

Bootsma A, Wheeler S . Converting SMILES to Stacking Interaction Energies. J Chem Inf Model. 2019; 59(8):3413-3421. DOI: 10.1021/acs.jcim.9b00379. View

11.

Guvench O, Brooks 3rd C . Tryptophan side chain electrostatic interactions determine edge-to-face vs parallel-displaced tryptophan side chain geometries in the designed beta-hairpin "trpzip2". J Am Chem Soc. 2005; 127(13):4668-74. DOI: 10.1021/ja043492e. View

12.

Bootsma A, Wheeler S . Tuning Stacking Interactions between Asp-Arg Salt Bridges and Heterocyclic Drug Fragments. J Chem Inf Model. 2018; 59(1):149-158. DOI: 10.1021/acs.jcim.8b00563. View

13.

van Lenthe E, Baerends E . Optimized Slater-type basis sets for the elements 1-118. J Comput Chem. 2003; 24(9):1142-56. DOI: 10.1002/jcc.10255. View

14.

Samanta U, Pal D, Chakrabarti P . Environment of tryptophan side chains in proteins. Proteins. 2000; 38(3):288-300. View

15.

Bootsma A, Doney A, Wheeler S . Predicting the Strength of Stacking Interactions between Heterocycles and Aromatic Amino Acid Side Chains. J Am Chem Soc. 2019; 141(28):11027-11035. DOI: 10.1021/jacs.9b00936. View

16.

Tozer D, De Proft F . Computation of the hardness and the problem of negative electron affinities in density functional theory. J Phys Chem A. 2006; 109(39):8923-9. DOI: 10.1021/jp053504y. View

17.

Waters M . Aromatic interactions in peptides: impact on structure and function. Biopolymers. 2004; 76(5):435-45. DOI: 10.1002/bip.20144. View

18.

Vermeeren P, van der Lubbe S, Fonseca Guerra C, Bickelhaupt F, Hamlin T . Understanding chemical reactivity using the activation strain model. Nat Protoc. 2020; 15(2):649-667. DOI: 10.1038/s41596-019-0265-0. View

19.

Jonasson P, Aronsson G, Carlsson U, Jonsson B . Tertiary structure formation at specific tryptophan side chains in the refolding of human carbonic anhydrase II. Biochemistry. 1997; 36(17):5142-8. DOI: 10.1021/bi961882a. View

20.

Trinquier G, Sanejouand Y . Which effective property of amino acids is best preserved by the genetic code?. Protein Eng. 1998; 11(3):153-69. DOI: 10.1093/protein/11.3.153. View