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Updated: Oct 16, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Visualized and Quantitative Conformational Analysis of Peptidomimetics
Hajime Takashima1, Atsushi Yoshimori2, Eiji Honda1
1Research and Development Department, PRISM BioLab Co., Ltd., C21F-4110, 26-1 Muraoka-Higashi 2-chome, Fujisawa, Kanagawa 251-0012, Japan.
Abstract:
Protein-protein interactions (PPIs) are fundamentally important and challenging drug targets. Peptidomimetic molecules of various types have been developed to modulate PPIs. A particularly promising drug discovery strategy, structural peptidomimetics, was designed based on special mimicking of side-chain Cα-Cβ bonds. It is simple and versatile. Nevertheless, no quantitative method has been established to evaluate its similarity to a target peptide motif. We developed two methods that enable visual, comprehensive, and quantitative analysis of peptidomimetics: peptide conformation distribution (PCD) plot and peptidomimetic analysis (PMA) map. These methods specifically examine multiple side-chain Cα-Cβ bonds of a peptide fragment motif and their corresponding bonds (pseudo-Cα-Cβ bonds) in a mimetic molecule instead of φ and ψ angles of a single amino acid in the traditional Ramachandran plot. The PCD plot is an alignment-free method, whereas the PMA map is an alignment-based method providing distinctive and complementary analysis. Results obtained from analysis using these two methods indicate our multifacial α-helix mimetic scaffold 12 as an excellent peptidomimetic that can precisely mimic the spatial positioning of side-chain functional groups of α-helix. These methods are useful for visualized and quantified evaluation of peptidomimetics and for the rational design of new mimetic scaffolds.

