Until recently, the standard therapy for hepatitis C treatment has been interferon and ribavirin. Such treatment has only 50% efficacy and is not well tolerated. The emergence of new drugs has increased the treatment efficacy to 90%. Despite such an achievement, the success is limited since the virus mutates rapidly, causing the emergence of drug resistant forms. In addition, most new drugs were developed to treat genotype 1 infections. Thus, development of new potent antivirals is needed and drug discovery against hepatitis C is continued. In this thesis, a FRET-based protease assay was used to evaluate new pyrazinone based NS3 protease inhibitors that are structurally different to the newly approved and currently developing drugs. Several compounds in this series showed good potencies in the nanomolar range against NS3 proteases from genotype 1, 3, and the drug resistance variant R155K. We assume that these compounds can be further developed into drug candidates that possess activity against above mentioned enzyme variants. By using SPR technology, we analyzed interaction mechanisms and characteristics of allosteric inhibitors targeting NS5B polymerases from genotypes 1 and 3. The compounds exhibited different binding mechanisms and displayed a low affinity against NS5B from genotype 3. In order to evaluate the activity and inhibitors of the NS5B polymerase, we established an SPR based assay, which enables the monitoring of polymerization and its inhibition in real time. This assay can readily be implemented for the discovery of inhibitors targeting HCV. An SPR based fragment screening approach has also been established. A screen of a fragment library has been performed in order to identify novel scaffolds that can be used as a starting point for development of new allosteric inhibitors against NS5B polymerase. Selected fragments will be further elaborated to generate a new potent allosteric drug candidate. Alternative approaches have successfully been developed and implemented to the discovery of potential lead compounds targeting two important HCV drug targets.

Cystic fibrosis (CF) is a rare genetic disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR), an epithelial anion channel expressed in several vital organs. Absence of functional CFTR results in imbalanced osmotic equilibrium and subsequent mucus build up in the lungs-which increases the risk of infection and eventually causes death. CFTR is an ATP-binding cassette (ABC) transporter family protein composed of two transmembrane domains (TMDs), two nucleotide binding domains (NBDs), and an unstructured regulatory domain. The most prevalent patient mutation is the deletion of F508 (F508del), making F508del CFTR the primary target for current FDA approved CF therapies. However, no experimental multi-domain F508del CFTR structure has been determined and few studies have modeled F508del using multi-domain WT CFTR structures. Here, we used cryo-EM density data and Rosetta comparative modeling (RosettaCM) to compare a F508del model with published experimental data on CFTR NBD1 thermodynamics. We then apply this modeling method to generate multi-domain WT and F508del CFTR structural models. These models demonstrate the destabilizing effects of F508del on NBD1 and the NBD1/TMD interface in both the inactive and active conformation of CFTR. Furthermore, we modeled F508del/R1070W and F508del bound to the CFTR corrector VX-809. Our models reveal the stabilizing effects of VX-809 on multi-domain models of F508del CFTR and pave the way for rational design of additional drugs that target F508del CFTR for treatment of CF.

Indiana University-Purdue University Indianapolis (IUPUI) / Signal transducer and activator of transcription 3 (STAT3) is constitutively activated in malignant tumors, and its activation is associated with high histological grade and advanced cancer stage. STAT3 has been shown to play important roles in multiple aspects of cancer aggressiveness including proliferation, survival, self-renewal, migration, invasion, angiogenesis and immune response by regulating the expression of diverse downstream target genes. Thus, inhibiting STAT3 promises to be an attractive strategy for treatment of advanced tumors with metastatic potential. We firstly identified a STAT3 inhibitor, inS3-54, by targeting the DNA-binding site of STAT3 using an in-silico screening approach; however, inS3-54 was finally found not to be appropriate for further studies because of low specificity on STAT3 and poor absorption in mice. To develop an effective and specific STAT3 inhibitor, we identified 89 analogues for the structure-activity relationship analysis. By using hematopoietic progenitor cells isolated from wild-type and STAT3 conditional knockout mice, further studies showed that three analogues (A18, A26 and A69) only inhibited STAT3-dependent colony formation of hematopoietic progenitor cells, indicating a higher selectivity for STAT3 than their parental compound, inS3-54. These compounds were found to (1) inhibit STAT3-specific DNA binding activity; (2) bind to STAT3 protein; (3) suppress proliferation of cancer cells harboring aberrant STAT3 signaling; (4) inhibit migration and invasion of cancer cells and (5) inhibit STAT3-dependent expression of downstream targets by blocking the binding of STAT3 to the promoter regions of responsive genes in cells. In addition, A18 can reduce tumor growth in a mouse xenograft model of lung cancer with little effect on body weight. Taken together, we conclude that it is feasible to inhibit STAT3 by targeting its DNA-binding domain for discovery of anticancer therapeutics.