Exploratory AI-Assisted In Silico Evidence That Bacterial Signaling Molecules May Occupy a Drug-Like Pharmacokinetic Space: A Preliminary Comparative Cheminformatics Analysis and Candidate Identification
Abstract
The hypothesis that antibiotics evolved from or co-opted bacterial intercellular signaling molecules predicts that signaling-active compounds should exhibit physicochemical properties favorable for drug development. We explored this prediction through a comparative cheminformatics analysis of 74 bacterial signaling molecules — comprising 48 small-molecule diffusible signals, 17 peptide autoinducers and intracellular messengers, and 9 antibiotics with documented signaling activity — against 71 randomly selected drug-like molecules. Small-molecule signaling molecules showed significantly higher Lipinski Rule-of-5 compliance than random drugs (95.8% vs. 73.2%; Odds Ratio = 8.40, 95% CI: 1.86–38.1, p = 0.001; Bonferroni-adjusted p = 0.009), while peptide autoinducers and intracellular messengers showed near-zero compliance (5.9%), confirming that the enrichment is specific to small-molecule diffusible signals. Predicted membrane permeability was over 2-fold higher for small-molecule signals (72.9% vs. 32.4% classified as “Good”), and enrichment was observed across six of seven drug-likeness filters (Enrichment Factors 1.12–1.31). We identified 10 signaling-active molecules with favorable profiles whose direct antibiotic activity has not been systematically tested; six are free of PAINS alerts. This analysis was conducted with substantial AI assistance, molecular properties were compiled from databases rather than computed de novo, and results require independent verification…
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