Heat Shock Protein 90 (HSP90) as a Universal Target in Rhizopus Strains: Overcoming Antifungal Resistance through Bioinformatics

In an attempt to solve the problem of antifungal resistance in the Rhizopus species, which contributes to the severity of mucormycosis, the study was conducted to target the Heat Shock Protein 90 (HSP90). The main aim was to develop a new de novo protein inhibitor that was specific to the fungal HSP90 but not to the human counterpart, reducing off-target toxicity, and overcoming the limitations of the current therapies.

A bioinformatics approach was adopted. The strategy involved determining the conserved domains of the HSP90 protein of different strains of Rhizopus through multiple sequence alignment. The ten possible de novo protein inhibitors were then generated using a deep learning model on the basis of the consensus sequence of this conserved region. The stability and binding affinity of these inhibitors were measured through molecular dynamics simulations and protein-protein molecular docking to the fungal and human HSP90 structures.

The analysis led to the identification of an inhibitor of lead de novo, Gen7, which exhibited improved binding and specificity. Molecular docking revealed that Gen7 had much higher affinity and interacted extensively with Rhizopus stolonifer HSP90 (12 hydrogen bonds, 4 salt bridges) than with human HSP90 (5 hydrogen bonds, 3 salt bridges). This fungal selectivity was later confirmed by subsequent molecular dynamics simulations. The Gen7-R. stolonifer complex was highly stable with an RMSD of about 4-5 A, whereas the Gen7-human complex was very unstable with a variation of RMSD of up to 15 A.

The results indicate that deep learning and bioinformatics have the potential to be used in designing highly selective therapeutic agents. This will address the serious problem of off-target toxicity that has hampered the clinical development of earlier HSP90 inhibitors, offering a feasible solution to developing more effective and safer antifungal agents.

This study successfully designed and computationally validated Gen7, a novel de novo inhibitor that selectively targets HSP90 in Rhizopus species. The research provides strong proof of concept for a new class of targeted antifungal agents, offering a promising avenue for developing innovative treatments against drug-resistant fungal infections like mucormycosis.