A novel design strategy based on the hierarchical design of experiments (HDoE) method named focused hierarchical design of experiments (FHDoE) is presented. FHDoE combine two design layers and use focused substitutions to increase the probability of obtaining active peptides when designing libraries through a selection of compounds biased towards a lead structure. Increasing the number of peptides with measurable activity will increase the information gained and the likelihood of constructing good quantitative structure-activity relationship (QSAR) models. The utility of the novel design method is verified using two different approaches. First, a library designed with the novel FHDoE method was compared with libraries generated from classical positional scanning techniques (e.g., alanine scan) as well as with general and centered minimum analog peptide sets (MAPS) libraries by using an example found in the literature. Secondly, the same design strategies were applied to a dataset of 58 angiotensin converting enzyme (ACE) dipeptide inhibitors. QSAR models were generated from designed sublibraries and the activities of the remaining compounds were predicted. These two examples show that the use of FHDoE renders peptide libraries close in physicochemical space to the native ligand, yielding a more thorough screening of the area of interest as compared to the classical positional scans and fractional factorial design (FFD). It is also shown that an FHDoE library of six dipeptides could produce a QSAR model that better described the requisites of high activity ACE inhibitors than could QSAR models built from either a nine-dipeptide library designed with MAPS or a 58-dipeptide library.

This thesis focuses on the design and synthesis of inhibitors targeting Mycobacterium tuberculosis ribonucleotide reductase (RNR) and hepatitis C virus (HCV) NS3 protease; enzymes that have been identified as potential drug targets for the treatment of tuberculosis and hepatitis C, respectively. Small peptides have been recognized as inhibitors of these enzymes. However, the use of peptides as drugs is limited due to their unfavorable properties. These can be circumvented by the development of less peptidic molecules, often referred to as peptidomimetics. When this work was initiated, only a few inhibitors targeting M. tuberculosis RNR had been identified, whereas the HCV NS3 protease was an established drug target. Therefore, early peptidomimetic design strategies were applied to inhibitors of RNR while the NS3 protease inhibitors were subjected to modifications in a later stage of development.

It has previously been shown that peptides derived from the C-terminus of the small subunit of M. tuberculosis RNR can compete for binding to the large subunit, and thus inhibit enzyme activity. To investigate the structural requirements of these inhibitors, different series of peptides were evaluated. First, peptides from an N-terminal truncation, an alanine scan and a designed library were synthesized and evaluated to examine the importance of the individual amino acid residues. Then, a set of N-terminally Fmoc-protected peptides was evaluated, and it was found that the N-terminal group improved the affinity of the peptides even when the length of the compounds was reduced. Furthermore, potential inhibitors of less peptidic character were generated by the introduction of a benzodiazepine-based scaffold.

To further reduce the peptidic character and investigate the binding properties of HCV NS3 protease inhibitors, a series of tripeptides incorporating a β-amino acid was synthesized. Inhibition was evaluated and docking studies were performed to understand how the structural changes affected inhibitory potency. The results illustrated the importance of preserving the hydrogen bonding network and retaining electrostatic interactions in the oxyanion hole between inhibitor and protein.

Mycobacterium tuberculosis ribonucleotide reductase (RNR) is a potential target for new antitubercular drugs. Herein we describe the synthesis and evaluation of peptide inhibitors of RNR derived from the C-terminus of the small subunit of M. tuberculosis RNR. An N-terminal truncation, an alanine scan and a novel statistical molecular design (SMD) approach based on the heptapeptide Ac-Glu-Asp-Asp-Asp-Trp-Asp-Phe-OH were applied in this study. The alanine scan showed that TrP5 and Phe7 were important for inhibitory potency. A quantitative structure relationship (QSAR) model was developed based on the synthesized peptides which showed that a negative charge in positions 2, 3, and 6 is beneficial for inhibitory potency. Finally, in position 5 the model coefficients indicate that there is room for a larger side chain., as compared to Trp5.