Identification of Antifungal Targets Based on Computer Modeling

Abstract

Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host–pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools.

Integrative functional genomics decodes herpes simplex virus 1

“…To reveal the potential function or functional motifs of predicted protein sequences, we used sequence comparison, domain composition, structure prediction and motif searches [62][63][64] . Sequence comparisons exploited Blast searches iteratively 65 and identified catalytic as well as regulatory domains including predictions by the conserved domain database 66 .…”

Integrative functional genomics decodes herpes simplex virus 1

“…Analysis of the predicted protein sequences to reveal function and functional motifs used sequence comparison, domain composition, structure prediction and motif searches as described previously [61][62][63] .…”

Identification of Salicylic Acid Mechanism against Leaf Blight Disease in Oryza sativa by SR-FTIR Microspectroscopic and Docking Studies

“…Secondary structure analysis of developed PR1b from Oryza sativa predicted that there is an expected similarity in the abundance of α-helix, β-sheet, and other secondary conformations of the structural β-sheet relative proportions of the model PR1b [ 47 , 48 , 49 , 50 ]. To be more specific, PROCHECK and verify 3D checked out and verified a very simple and accurate model that correctly predicted the final structure [ 51 , 52 ]. Because there was a difference in the RMS deviation of this structure from the template structure, as well as a difference after MD simulations, our predicted form can be used safely for docking [ 53 , 54 , 55 , 56 ].…”

“…Protein coordinates from the templates were assigned to the sequence using spatial requirements. ClustalX [ 50 , 51 , 52 , 53 , 54 ] uses the default parameters to align the reference structures to the target sequences.…”