Here, we summarize a line of remarkably simple, theoretical research to better understand the chemical logic by which life’s standard alphabet of 20 genetically encoded amino acids evolved. The connection to the theme of this Special Issue, “Protein Structure Analysis and Prediction with Statistical Scoring Functions”, emerges from the ways in which current bioinformatics currently lacks empirical science when it comes to xenoproteins composed largely or entirely of amino acids from beyond the standard genetic code. Our intent is to present new perspectives on existing data from two different frontiers in order to suggest fresh ways in which their findings complement one another. These frontiers are origins/astrobiology research into the emergence of the standard amino acid alphabet, and empirical xenoprotein synthesis.
Exhaustive generation of molecular structures has numerous chemical and biochemical applications such as drug design, molecular database construction, exploration of alternative biochemistries, and many more. Mathematically speaking, these are graph generators with chemical constraints. In the field, the most efficient generator currently (MOLGEN) is a commercial product, limiting its use.Alternative to that, another molecular structure generator, MAYGEN, is a recent open-source tool with efficiency comparable to MOLGEN and the capacity for users to increase its performance by adding new features. One of the research fields that can benefit from this development is astrobiology; structure generators allow researchers to supplement experimental data with computational possibilities for alternative biochemistry. This protocol details one use case for structure generation in astrobiology, namely the generation and curation of alpha-amino acid libraries. Using open-source structure generators and cheminformatics tools, the practices described here can be implemented beyond astrobiology for the low-cost creation and curation of chemical structure libraries for any research question.
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