Exploring anti-quorum sensing and anti-virulence based strategies to fight Candida albicans infections: an in silico approach.

The complex virulence attributes of Candida albicans are an attractive target to exploit in the development of new antifungals and anti-virulence strategies to combat C. albicans infections. Particularly, quorum sensing (QS) has been reported as critical for virulence regulation in C. albicans. This work presents two knowledge networks with up-to-date information about QS regulation and experimentally tested anti-QS and anti-virulence agents for C. albicans. A semi-automatic bioinformatics workflow that combines literature mining and expert curation was used to retrieve otherwise scattered information from the scientific literature. The network representation offers an innovative and continuously updatable means for the Candida research community to query QS and virulence data systematically and in a user-friendly way. Notably, the reconstructed networks show the complexity of QS regulation and the impact that some molecules have on the inhibition of virulence mechanisms responsible for infection establishment (e.g. hyphal development) and perseverance (e.g. biofilm formation). In the future, the compiled knowledge may be used to build decision-making models that help infer new knowledge of practical significance. The knowledge networks are publicly available at https://pcquorum.org/. This Web platform enables the exploration of fungal virulence cues as well as reported inhibitors in a user-friendly fashion.