Abstract

Candida albicans (CA) has been identified as the major opportunistic pathogen in immunosuppressed patients. Most of currently available drugs are either highly toxic or becoming ineffective against resistant strains. An approach to overcome this burden relies on azole derivatives with increased potency and selectivity. Aiming at shedding some light on structural and chemical features that are important for the antifungal activity of azole derivatives, classical 2D QSAR and hologram QSAR (HQSAR) studies were performed for a diverse set of 52 bifonazole derivatives with antifungal activity. Topological descriptors, employed in Classical QSAR studies, resulted in models with low correlation (r² = 0.38, q² = 0.27) and lack of predictive power (r²pred = -0.6). On the other hand molecular holograms afforded HQSAR models with good correlation coefficients (r² = 0.92, q² = 0.65) and good predictive ability (r²pred = 0.79).

Highlights

  • During the past two decades, the incidence of invasive and systemic fungal infections has increased dramatically

  • The data set used for the QSAR studies contains 52 derivatives of bifonazole with antifungal activity that were selected from the literature.[17,18]

  • Classical QSAR and hologram QSAR (HQSAR) models were derived for a series of bifonazole derivatives with antifungal activity (Table 1)

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Summary

Introduction

During the past two decades, the incidence of invasive and systemic fungal infections has increased dramatically. The data set used for the QSAR studies contains 52 derivatives of bifonazole with antifungal activity that were selected from the literature.[17,18] The biological property of this dataset is reported as MIC values, which is the antifungal concentration required to substantially

Results
Conclusion

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