In silico pathway-based subtractive proteomics for identifying novel drug targets in Candida albicans with structure-guided drug repurposing of aspartate-semialdehyde dehydrogenase inhibitors.

CONTEXT: Candida albicans is the most common cause of candidemia and is classified as a high-priority pathogen due to its increasing prevalence among fragilised and hospital-based patients. In this study, the subtractive proteomics approach identified 12 key targets involved in vital pathways that play a crucial role in metabolism and regulation, supporting fungal growth, maintaining balance, and enabling pathogenicity. These pathways are essential for the pathogen's survival and virulence, highlighting them as potential targets for treatments against C. albicans infections. Notably, aspartate-semialdehyde dehydrogenase (ASADH) plays a role in cell wall construction, stress-associated dormancy, and the production of virulence-associated components, which are critical aspects of C. albicans infections. The structure-guided virtual screening identified five potent hits: Acarbose, Iotrolan, Iodixanol, Nystatin, and Ferric derisomaltose, which exhibit better affinity, ranging from -12.25 to -11.90 kcal/mol with CaASADH and exhibits stable binding during 500 ns MD simulations, highlighting their potential as lead compounds for anti-C. albicans drug development.

METHODS: Subtractive proteomics pipeline was performed in a standalone Linux environment, and the three-stage Schrödinger's Glide docking algorithm was used for molecular docking studies. All MD simulations were conducted using GROMACS for 500 ns, and the conformational dynamic stability was examined using RMSD, RMSF, Rg, SASA, PCA, CD-HIT, BLASTp, DrugBank, BlastKOALA, screening, SiteMap, LigPrep, SwissParam, MMPBSA, and CHARMM36 force field.