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Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

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Similarity Analysis of Computer-Generated and Commercial Libraries for Targeted Biocompatible Coded Amino Acid

Markus Meringer¹, Gerardo M Casanola-Martin², Bakhtiyor Rasulev^2,3

¹German Aerospace Center (DLR), Department of Atmospheric Processors, Oberpfaffenhofen, 82234 Wessling, Germany.

International Journal of Molecular Sciences

|November 27, 2024

Summary

This summary is machine-generated.

We developed a new workflow to find non-natural amino acids that can be incorporated into proteins. This method efficiently identifies candidates that are compatible with biological systems and protein function.

Keywords:

Tanimoto coefficient amino acid libraries molecular fingerprint multi-dimensional scaling structural similarity

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Area of Science:

Biochemistry
Molecular Biology
Bioinformatics

Background:

Biological systems can incorporate non-natural amino acids into proteins.
Effective incorporation requires compatibility with protein function and evasion of error-checking mechanisms.
Previous methods relied on expert intuition and empirical studies, which are inefficient for large-scale screening.

Purpose of the Study:

To introduce a computational workflow for identifying biosimilar non-natural amino acids for protein incorporation.
To enable efficient screening of large libraries of real and computed amino acids.
To minimize unintended functional disturbances in proteins incorporating non-natural amino acids.

Main Methods:

Developed a workflow to search amino acid libraries for biosimilar candidates.
Applied fingerprint similarity scoring using Tanimoto coefficients.
Evaluated libraries including previously benchmarked molecules and commercial catalogs.

Main Results:

Identified candidate non-natural amino acids suitable for substitution into modern proteins.
Discovered several already-implemented amino acid substitutions.
Suggested numerous novel potential amino acid substitutions for protein engineering.

Conclusions:

The developed workflow efficiently identifies potential non-natural amino acid substitutions.
This approach expands the possibilities for protein engineering and design.
The findings facilitate the discovery of novel amino acids for coded protein synthesis.