A Computer Modeling Approach to Create an Antifungal to Improve the Treatment of

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DESCRIPTION (provided by applicant): Cryptococcal meningitis (CM) continues to be a significant cause of mortality among HIV positive individuals, and a major world-wide health concern in developing regions including Africa and Southeast Asia. The estimated mortality rate is 20% for infected HIV positive individuals in North America, despite access to good healthcare. In sub-Saharan Africa, CM causes an estimated 530,000 deaths per year among HIV positive patients compared with 350,000 for tuberculosis in the general population. For decades, Amphotericin B (AmB) has been the mainstay therapeutic for CM. However, it often fails to cure or eradicate cryptococcal infections. AmB causes severe toxicities including nephrotoxicity and leukopenia, and is not available in an oral formulation. In this proposal, we plan to use homology modeling of fungal calcineurin and newly developed chemistry to discover an oral, well tolerated fungicidal drug with low toxicity to use in the treatment of CM. Amino acid sequence changes between human and fungal proteins will be exploited to modify the immunosuppressive molecules FK506 and ascomycin to create a non-toxic, new chemical entity that targets fungal calcineurin. This new therapeutic will have the potential to be employed as a single agent or in combination with AmB or orally available triazoles to improve survival rates and compliance with treatment regimens. Our Aims are: 1. Perform computational modeling of the ternary complex of Cryptococcal neoformans calcineurin/FKBP12/FK506 to design non-toxic small molecule inhibitors of C. neoformans calcineurin. 2. Synthesize a first generation library of 30 non-immunosuppressive fungal calcineurin inhibitors using a convergent approach; successive generations will be guided by empirical data from Aim 3. 3. Screen and select compounds for antifungal activity against strains of C. neoformans and emerging cryptococcal species, pk/pd properties, and iterate library based on observed SAR.