Brief Introduction

Fungal pathogens have a profound impact on global human health, food security, and biodiversity. Microorganisms have a remarkable capacity to evolve resistance to anti-microbial agents, threatening the efficacy of the limited arsenal of anti-microbials and becoming a dire public health crisis. This is of particular concern for fungal pathogens, which cause devastating invasive infections with treatment options limited to only three major classes of anti-fungal drugs. The limited number of anti-fungal classes available and the unacceptably high mortality rate from invasive infections make the need for new antifungals dire. Therefore, development of new, effective and affordable drugs against fungi is urgently needed.

In this study, we developed a web server called Anti-Fungi Predictor for predicting anti-fungal activity of given compounds. Anti-Fungi Predictor is free and open to all user. The web server is rapid and accurate (Accuracy > 90% and AUC > 0.95), which enables us to screen tens of millions of compounds and discover new anti-fungal agents. The web server will be applied to drug repositioning for anti-fungal therapy by screening 1836 approved drugs.