#24 · Tools & infrastructure

Tools linking structure prediction, bioactivity data and genomes to peptide candidates

The dominant thread is computational tooling that moves from sequence, structure or genome representations toward candidate-level outputs for peptide and natural product discovery. DBAASP V4 links peptides and peptidomimetics to condition-resolved antimicrobial, antibiofilm, anticancer and cytotoxicity data for data-driven selection. Peptorama draws non-ribosomal peptide structures and compares known and BGC-predicted NRPs at the peptide level, reducing runtimes versus BGC-level comparison. A computational design study combines AlphaFold3 with Rosetta to rank millions of variants, mapping the substrate scope of ketoamide-forming HypX and PlpX. A DNA-first framework using natural-vector features and positional recurrence nominates array-associated RT loci in genomes. The items do not share a single method. What is new is infrastructure connecting structural prediction, curated bioactivity data and genome-derived candidates into outputs usable for decisions.