bioRxivMicrobiologyPreprint
Precision Discovery of Novel Inhibitors of Human Cancer Target HsMetAP1 from Vast Unexplored Metagenomic Diversity
O. W. Liu, S. Akers, G. Alvarez, S. Brown, W. Cai, Z. Charlop-Powers, K. Crispell, E.-B. Goh, W. W. Hwang, T. H. Eyles, S. Ganesh, P. Haverty, J. L. Kulp, J. L. Kulp, Z. Kurtz, A. Lubbe, M. Jamison, A. Milshteyn, P. Mokthari, S. G. Naylor, S. Oteng-Pabi, R. Overacker, A. W. Robertson, H. van Aggelen, U. Viswanathan, , D. R. Scannell
Abstract
Microbial natural products have long been a rich source of human therapeutics. While the chemical diversity encoded in the genomes of microbes is large, this modality has waned as fermentation-based discovery methods have suffered from rediscovery, inefficient scaling, and incompatibility with target-based discovery paradigms. Here, we leverage a metagenomic partitioning strategy to sequence soil microbiomes at unprecedented depth and quality. We then couple these data with target-focused, in silico search strategies and synthetic biology to discover multiple novel natural product inhibitors of human methionine aminopeptidase-1 (HsMetAP1), a validated oncology target. For one of these, metapeptin B, we demonstrate sub-micromolar potency, strong selectivity for HsMetAP1 over HsMetAP2 and elucidate structure-activity relationships. Our approach overcomes challenges of traditional natural product methods, accesses vast, untapped chemical diversity in uncultured microbes, and demonstrates computationally-enabled precision mining of modulators of human proteins.
- assay: metagenomics
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
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