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In 1996, scientists discovered a connection between the gene for the human protein frataxin (FXN) and the neurodegenerative disease Friedreich’s ataxia (FRDA). Decreased FXN levels result in a variety of aberrant phenotypes including loss of activity for iron-sulfur containing enzymes, mitochondrial iron accumulation, and susceptibility to oxidative stress. These symptoms are the primary focus of current therapeutic efforts. In contrast our group is pursuing an alternate strategy of first defining FXN function at a molecular level then using this information to identify small molecule functional replacements. Recently, our group has discovered that FXN functions as an allosteric activator for the human Fe-S cluster assembly complex. The work presented here helps to further define molecular details of FXN activation and explain how FRDA missense mutants are functionally compromised. First, the FRDA missense mutants L182H and L182F were investigated. Unlike other characterized FRDA missense mutants, the L182F variant was not compromised in its ability to bind and activate the Fe-S assembly complex. The L182H variant exhibited an altered circular dichroism signature; suggesting a change in secondary structure relative to native FXN, and rapidly degraded. Together these studies suggest that L182 variants are less stable than native FXN and are likely prone to degradation in FRDA patients. Second, as a regulatory role of FXN suggests that its function is likely controlled by environmental stimuli, different maturation forms of FXN as well as post-translational modification mimics were tested as mechanisms to control FXN regulation. Here experiments were designed to test if a larger polypeptide form of FXN represents a functional form of the protein. Kinetic and analytical ultracentrifugation studies revealed a complex heterogeneous mixture of species some of which can activate the Fe-S assembly complex. A previously identified acetylation site was also tested using mutants that mimic acetylation. These mutants had little effect on the ability of FXN to bind and activate the assembly complex. Third, mutagenesis experiments were designed in which the FXN surface residues were replaced with alanine and the resulting variants were tested in binding and activity assays. These experiments revealed a localized “hot-spot” on the surface of FXN that suggests small cyclic peptide mimics might be able to replace FXN and function as FRDA therapeutics. Unexpectedly, one of the FXN variants exhibited significantly tighter binding and could have relevance for therapeutic development.

Accurate predictions of binding free energies from computer simulations are an invaluable resource for understanding biochemical processes and drug action. The primary aim of the work described in the thesis was to predict and understand ligand binding to several proteins of major pharmaceutical importance using computational methods. We report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 G-protein coupled receptor and a series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Site-directed mutagenesis, homology modelling and docking were further used to characterize agonist binding to the human neuropeptide Y2 receptor, which is important in feeding behavior and an obesity drug target.  In a separate project, homology modelling was also used for rationalization of mutagenesis data for an integron integrase involved in antibiotic resistance. Blockade of the hERG potassium channel by various drug-like compounds, potentially causing serious cardiac side effects, is a major problem in drug development. We have used a homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations are in good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships with implications for design of new compounds. Docking, scoring, molecular dynamics, and the linear interaction energy method were also used to predict binding modes and affinities for a large set of inhibitors to HIV-1 reverse transcriptase. Good agreement with experiment was found and the work provides a validation of the methodology as a powerful tool in structure-based drug design. It is also easily scalable for higher throughput of compounds.

Biochemical processes all involve associations and dissociations of chemical entities. Understanding these is of substantial importance for many modern pharmaceutical applications. In this thesis, longstanding problems with regard to ligand binding are treated with computational methods, applied to proteins of key pharmaceutical importance. Homology modeling, docking, molecular dynamics simulations and free-energy calculations are used here for quantitative characterization of ligand binding to proteins. By combining computational tools, valuable contributions have been made for pharmaceutically relevant areas: a neglected tropical disease, an ion channel anti-drug-target, and GPCR drug-targets. We report three compounds inhibiting cruzain, the main cysteine protease of the protozoa causing Chagas’ disease. The compounds were found through an extensive virtual screening study and validated with experimental enzymatic assays. The compounds inhibit the enzyme in the μM-range and are therefore valuable in further lead optimization studies. A high-resolution crystal structure of the BRICHOS domain is reported, together with molecular dynamics simulations and hydrogen-deuterium exchange mass spectrometry studies. This work revealed a plausible mechanism for how the chaperone activity of the domain may operate. Rationalization of structure-activity relationships for a set of analogous blockers of the hERG potassium channel is given. A homology model of the ion channel was used for docking compounds and molecular dynamics simulations together with the linear interaction energy method employed for calculating the binding free-energies. The three-dimensional coordinates of two GPCRs, 5HT1B and 5HT2B, were derived from homology modeling and evaluated in the GPCR Dock 2013 assessment. Our models were in good correlation with the experimental structures and all of them placed among the top quarter of all models assessed.  Finally, a computational method, based on molecular dynamics free-energy calculations, for performing alanine scanning was validated with the A2A adenosine receptor bound to either agonist or antagonist. The calculated binding free-energies were found to be in good agreement with experimental data and the method was subsequently extended to non-alanine mutations. With extensive experimental mutation data, this scheme is a valuable tool for quantitative understanding of ligand binding and can ultimately be used for structure-based drug design.