Peptidomimetic Compound Library

During the last decades, a significant number of biologically active peptides have been discovered and characterized, including hormones, vasoactive peptides, and neuropeptides [1]. Owing to interaction with their membrane-bound receptors, these bioactive peptides influence cell-cell communication, participate in protein-protein interactions (PPI), cellular signaling and control a series of vital functions [2-3]. Thus, they are of great interest in the biomedical field, and the number of native and modified peptides used as therapeutics is vividly increasing [4].

Biomedical research is persistently striving for the development of new therapeutics based on peptides and proteins by introducing both structural and functional specific modifications and maintaining the features responsible for biological activity - peptidomimetics (Fig. 1). In terms of this approach, peptides and proteins are considered as tools for the discovery of other classes of compounds [5-6].

Peptidomimetics. Picture credit: Lenci, E at al., 2020 [1]

Figure 1. Classification of peptidomimetics

Peptidomimetics are organic molecules that mimic the action of a natural peptide or protein, designed to overcome points of concern linked to natural peptides and to improve other characteristics, such as enhanced receptor affinity and selectivity, potency, and good bioavailability. Hence, the design and synthesis of peptidomimetics, undoubtedly, possess  great potential in drug discovery [4].

Different synthetic strategies were developed to modulate the conformational flexibility and the peptide character of peptidomimetic compounds. Unnatural amino acids (such as beta-amino acid, alanine derivatives, etc.) and amino alcohol moieties can be introduced into peptidomimetic scaffolds. Synthetic compounds can act as peptide secondary structure mimetics (α-helix, β-turn, and β-strand) [7-11].

Life Chemicals has prepared a proprietary Peptidomimetic Screening Library of over 5,800 α-helix and β-turn mimetics selected with a ligand-based approach. This approach included various similarity analysis techniques, such as structural similarity search vs. known peptidomimetic inhibitors and scaffolds, 3D shape screening, pharmacophore screening, and complex substructure search:

  • 2D similarity analysis was performed against known peptidomimetic inhibitors and scaffolds with the Tanimoto index ≥ 0.8
  • 3D shape screening was carried out with Pharmacophore Types volume scoring against more than 1 million conformers generated from the Life Chemicals HTS Compound Collection. The screening was based on 3D structures of alpha-helices and beta-turns (type I and II), obtained with quantum mechanics calculations
  • Pharmacophore screening included pharmacophore model construction based on 3D structures of β-turns (type I and II) obtained with quantum mechanics calculations. The model contained specific exclusion volume constraint and donor/acceptor atom positions to allow hydrogen bond formation in β-turn mimetics (Fig. 2)
  • Complex substructure search involved search queries constructed on the basis of α-helix and β-turn peptidomimetic scaffolds from literature, such as various bicyclic, spiro, macrocyclic, pyrrolidine, terphenyl, oligobenzamide, anthracene, and other scaffolds (Fig. 3)

Screening compounds can be selected by cherry-picking. In addition, selection can be customized using specific parameters.

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Compound F1885-0329 aligned against pharmacophore sites. An example of a pharmacophore search based on the β-turn structure.

Figure 2. Compound F1885-0329 aligned against pharmacophore sites. An example of a pharmacophore search based on the β-turn structure.

Chemical scaffold examples used for building the search queries. 

Figure 3. Some representative scaffolds used for the construction of the search queries.


  1. Trabocch A., Guarna A. Peptidomimetics in Organic and Medicinal Chemistry: The Art of Transforming Peptides in Drugs. John Wiley & Sons, Ltd. 2014. 288p. 10.1002/9781118683033
  2. Cunningham AD, Qvit N, Mochly-Rosen D. Peptides and peptidomimetics as regulators of protein-protein interactions. Curr Opin Struct Biol. 2017;44:59-66. doi:10.1016/
  3. Mabonga L, Kappo AP. Protein-protein interaction modulators: advances, successes and remaining challenges. Biophys Rev. 2019;11(4):559-581. doi:10.1007/s12551-019-00570-x
  4. Lenci, E.; Trabocchi, A. Peptidomimetic Toolbox for Drug Discovery. Chem. Soc. Rev. 2020, 49 (11), 3262–3277.
  5. Corbière A, Vaudry H, Chan P, et al. Strategies for the Identification of Bioactive Neuropeptides in Vertebrates. Front Neurosci. 2019;13:948. doi:10.3389/fnins.2019.00948
  6. Bruno BJ, Miller GD, Lim CS. Basics and recent advances in peptide and protein drug delivery. Ther Deliv. 2013;4(11):1443-1467. doi:10.4155/tde.13.104
  7. Maryanna E. Lanning and Steven Fletcher, Multi-Facial, Non-Peptidic α-Helix Mimetics, Biology 2015, 4, 540-555; doi:10.3390/biology4030540.
  8. Andrew J. Wilson, Helix mimetics: Recent developments, Progress in Biophysics and Molecular Biology (2015), doi:10.1016/j.pbiomolbio.2015.05.001.
  9. Madura K. P. Jayatunga, Sam Thompson, Andrew D. Hamilton, a-Helix mimetics: Outwards and upwards, Bioorganic & Medicinal Chemistry Letters 24 (2014) 717–724.
  10. Maryanna Lanning & Steven Fletcher, Recapitulating the a-helix: nonpeptidic, low-molecular-weight ligands for the modulation of helix-mediated protein-protein interactions, Future Med. Chem. (2013) 5(18), 2157–2174.
  11. Landon R. Whitby, Yoshio Ando, Vincent Setola, Peter K. Vogt, Bryan L. Roth, and Dale L. Boger, Design, Synthesis, and Validation of a β-Turn Mimetic Library Targeting Protein-Protein and Peptide-Receptor Interactions. J. Am. Chem. Soc. – 2011 – Vol. 133, p. 10184–10194.
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