Fungal pathogens pose a global threat to human health, with Candida albicans among the leading killers. Systematic analysis of essential genes provides a powerful strategy to discover potential antifungal targets. Here, we build a machine learning model to generate genome-wide gene essentiality predictions for C. albicans and expand the largest functional genomics resource in this pathogen (the GRACE collection) by 866 genes. Using this model and chemogenomic analyses, we define the function of three uncharacterized essential genes with roles in kinetochore function, mitochondrial integrity, and translation, and identify the glutaminyl-tRNA synthetase Gln4 as the target of N-pyrimidinyl-β-thiophenylacrylamide (NP-BTA), an antifungal compound.

The essential eukaryotic chaperone Hsp90 regulates the form and function of diverse client proteins, many of which govern thermotolerance, virulence, and drug resistance in fungal species. However, use of Hsp90 inhibitors as antifungal therapeutics has been precluded by human host toxicities and suppression of immune responses. We recently described resorcylate aminopyrazoles (RAPs) as the first class of Hsp90 inhibitors capable of discriminating between fungal (Cryptococcus neoformans, Candida albicans) and human isoforms of Hsp90 in biochemical assays. Here, we report an iterative structure−property optimization toward RAPs capable of inhibiting C. neoformans growth in culture. In addition, we report the first X-ray crystal structures of C. neoformans Hsp90 nucleotide binding domain (NBD), as the apoprotein and in complexes with the non-species-selective Hsp90 inhibitor NVP-AUY922 and three RAPs revealing unique ligand-induced conformational rearrangements, which reaffirm the hypothesis that intrinsic differences in protein flexibility can confer selective inhibition of fungal versus human Hsp90 isoforms.

Invasive fungal infections have escalated from a rare curiosity to a major cause of human mortality around the globe. This is in part due to a scarcity in the number of antifungal drugs available to combat mycotic disease, making the discovery of novel bioactive compounds and determining their mode of action of utmost importance. The development and application of chemical genomic assays using the model yeast Saccharomyces cerevisiae has provided powerful methods to identify the mechanism of action of diverse molecules in a living cell. Furthermore, complementary assays are continually being developed in fungal pathogens, most notably Candida albicans and Cryptococcus neoformans, to elucidate compound mechanism of action directly in the pathogen of interest. Collectively, the suite of chemical genetic assays that have been developed in multiple fungal species enables the identification of candidate drug target genes, as well as genes involved in buffering drug target pathways, and genes involved in general cellular responses to small molecules. In this review, we examine current yeast chemical genomic assays and highlight how such resources provide powerful tools that can be utilized to bolster the antifungal pipeline.

Pathogenic fungi represent a serious but underacknowledged threat to human health. The treatment and management of these infections relies heavily on the use of azole antifungals, a class of molecules that contain a five-membered nitrogen-containing ring and inhibit the biosynthesis of the key membrane sterol ergosterol.

Candida albicans is the leading cause of systemic candidiasis. Effective treatment is threatened by a dearth of antifungal options and the emergence of resistance. Thus, there is an urgent need to identify novel therapeutic targets to expand our antifungal armamentarium. A promising approach is the discovery of essential genes, as most antimicrobials target essential bioprocesses. Despite detailed characterization of gene essentiality in Saccharomyces cerevisiae,defining essential targets in the pathogen of interest is necessary due to the high level of divergence between these organisms. Thus, using a machine learning algorithm we generated a comprehensive prediction of all genes essential in C. albicans. We leveraged our essentiality predictions with high-throughput screening and chemogenomic datasets to assign the mechanism of action of a previously uncharacterized compound. We identified T-035897 as a molecule with potent bioactivity against C. albicans. Prior chemogenomic profiling in S. cerevisiae suggested that T-035897 targets the glutaminyl tRNA synthetase Gln4, whose homolog in C. albicans was predicted and verified to be required for viability. To confirm the mechanism of T-035897 in C. albicans, we performed haploinsufficiency profiling,which supported Gln4as the target. In parallel, selection of resistant mutants and targeted sequencing uncovered substitutions in the Gln4 catalytic domain. Moreover, T-035897 inhibited translation in afluorescence-based reporter assay. Finally, T-035897 selectively abrogated fungal cell growth in a co-culture model with mammalian cells. Thus, we highlight the power of leveraging essentiality datasets in order to characterize compounds with potent antifungal activity in an effort to unveil novel therapeutic strategies.