Methods of treating fungal infections, like bacterial infections, are changing due to increasing resistance to drugs, and fungal infections also play a major role in hospital-acquired infections. Researchers are using a new algorithm to look at information like known synergistic drug combinations, chemical structures and drug-target interactions to determine the best possible strategy for using existing medications to treat resistant fungal infections.
Using their "Network-based Laplacian regularized Least Square Synergistic drug combination prediction" — or NLLSS — researchers from the Chinese Academy of Sciences in Beijing were experimentally validated seven of 13 predicted antifungal synergistic drug combinations for treating Candida albicans.
"It is anticipated that NLLSS would be an important and useful resource by providing a new strategy to identify potential synergistic antifungal combinations, explore new indications of existing drugs, and provide useful insights into the underlying molecular mechanisms of synergistic drug combinations," the authors conclude.
The research is published in PLOS Computational Biology.