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<p>Ion permeation through voltage gated sodium channels is modulated by many drugs and toxins. However, the atomistic mechanisms of action of most these ligands are poorly understood. This study focuses on three compounds: a steroidal alkaloid batrachotoxin (BTX), a pyrethroid insecticide deltamethrin, and an alkylamide insecticide BTG 502, which bind to distinct but allosterically coupled receptor sites. BTX belongs to the class of the sodium channel agonists (activators), which cause persistent channel activation by inhibiting channel inactivation. Traditionally, BTX is believed to bind at the channel-lipid interface and allosterically modulate ion permeation through the channel. However, in the last decade, amino acid residues that affect BTX action have been found in the pore-facing inner helices of all four domains, suggesting that BTX binds in the channel pore (Tikhonov and Zhorov, <em>FEBS Letters</em> 2005). An alkylamide insecticide BTG 502 reduces sodium currents and antagonizes the action of BTX on cockroach sodium channels, suggesting that it also binds inside the pore. Conversely, pyrethroids bind at the lipid-exposed cavity formed by a short intracellular linker-helix IIS4-S5 and transmembrane helices IIS5 and IIIS6.</p> <p>In this study we first developed a new method of electrostatic-energy calculations, a new protocol of ligand docking, and tested this methodology on 60 ligand-protein complexes of known structure (Garden and Zhorov 2010). We then applied this methodology to rationalize effects of various mutations in the domain III inner helix of the cockroach sodium channel BgNav1.1 on the action of BTX, BTG 502 and deltamethrin. Our collaborators, Dr. Ke Dong et al. from Michigan State University, mutated all residues in the pore-lining helix of domain III (IIIS6) and found several new BTX and BTG 502 sensing residues. Using these data along with other published data on BTX- and deltamethrin-sensing residues as distance constrains, we docked BTX, BTG 502 and deltamethrin in a Kv1.2-based homology model of the open BgNav1.1 channel. We arrived at models, which are consistent with all currently available data on the action of the ligands. In the BTX-binding model, the toxin adopts a “horseshoe” conformation and binds in the channel pore with the horseshoe plane normal to the pore axis. In this binding mode BTX allows would allow ion permeation through the hydrophilic inner face of the horseshoe, and resist the activation-gate closure. Various BTX moieties interact with known BTX sensing residues. In particular, the tertiary ammonium group of BTX is engaged in cation-p interactions with the newly discovered BTX-sensing residue Phe³ⁱ¹⁶. In the BTG 502-binding model, the ligand wraps around IIIS6 making direct contacts with all known BTG 502-sending residues, including buried residues on the IIIS6 helix side, which does not face the pore. Deltamethrin binds within the cavity formed by the linker-helix IIS4-S5, the outer helix IIS5, and the inner helix IIIS6 at the interface between domains II and III, similar to the pyrethroid-binding mode predicted by others (O'Reilly, Khambay et al. 2006). Our study revealed a unique mode of action of BTX in which the agonists enables the ion permeation by forming a “channel within a channel”. We also found that the BTG 502 receptor site overlaps with receptors for BTX and deltamethrin, which are located in different parts of the channel.</p> / Doctor of Philosophy (PhD)

Analysis of genome sequences is enabling identification of numerous novel characteristics that provide valuable means for genetic and biochemical studies. Of these characteristics, Conserved Signature Indels (CSIs) in proteins which are specific for a given group of organisms have proven particularly useful for evolutionary and biochemical studies. My research work focused on using comparative genomics techniques to identify a large number of CSIs which are distinctive characteristics of fungi and other important groups of organisms. These CSIs were utilized to understand the evolutionary relationships among different proteins (species), and also regarding their structural features and functional significance. Based on multiple CSIs that I have identified for the PIP4K/PIP5K family of proteins, different isozymes of these proteins and also their subfamilies can now be reliably distinguished in molecular terms. Further, the species distribution of CSIs in the PIP4K/PIP5K proteins and phylogenetic analyses of these protein sequences, my work provides important insights into the evolutionary history of this protein family. The functional significance of one of the CSI in the PIP5K proteins, specific for the Saccharomycetaceae family of fungi, was also investigated. The results from structural analysis and molecular dynamics (MD) simulation studies show that this 8 aa CSI plays an important role in facilitating the binding of fungal PIP5K protein to the membrane surface. In other work, we identified multiple highly-specific CSIs in the phosphoketolase (PK) proteins, which clearly distinguish the bifunctional form of PK found in bifidobacteria from its homologs (monofunctional) found in other organisms. Structural analyses and docking studies with these proteins indicate that the CSIs in bifidobacterial PK, which are located on the subunit interface, play a role in the formation/stabilization of the protein dimer. We have also identified 2 large CSIs in SecA proteins that are uniquely found in thermophilic species from two different phyla of bacteria. Detailed bioinformatics analyses on one of these CSIs show that a number of residues from this CSI, through their interaction with a conserved network of water molecules, play a role in stabilizing the binding of ADP/ATP to the SecA protein at high temperature. My work also involved developing an integrated software pipeline for homology modeling of proteins and analyzing the location of CSIs in protein structures. Overall, my thesis work establishes the usefulness of CSIs in protein sequences as valuable means for genetic, biochemical, structural and evolutionary studies. / Dissertation / Doctor of Philosophy (PhD)

In humans, mammals, and perhaps all vertebrates, sphingolipids exist as a family of cellular signaling molecules and have been shown to be involved in a wide range of biological processes ranging from proliferation to apoptosis. As such, sphingolipid signaling has garnered the attention of numerous researchers as an attractive candidate for pharmacological manipulation. The synthetic pathway of one prominent sphingolipid, sphingosine 1-phosphate (S1P), has been implicated in a variety of disease states such as cancer, sickle cell disease, multiple sclerosis, and renal fibrosis. Formation of S1P is facilitated from the ATP dependent phosphorylation of sphingosine (Sph) through its generative enzyme's sphingosine kinase 1 and 2 (SphK1 and SphK2). Inhibition of SphK1 and SphK2 results in the manipulation of S1P levels, which has been shown to be therapeutic in various animal models of disease. While there are multiple examples of potent SphK1-selective and dual SphK1/2 inhibitors, SphK2-selective inhibitors are scarce. Herein, we describe the design, synthesis and biological testing of SphK2-selective inhibitors. We first describe the discovery that introducing a trifluoromethyl group onto the internal aryl ring of our inhibitor scaffold led to superior selectivity and potency towards SphK2. We demonstrate that the trifluoromethyl moiety is interacting with a previously unknown side cavity in the substrate binding site of SphK2 that is unique and could be exploited in the design of SphK2-selective inhibitors. The synthesis of 21 derivatives with various substituents spanning off the internal aryl ring was completed, therefore characterizing the preferred size and chemical nature of moieties positioned in that portion of the binding site. This work led to the development of the most potent SphK2-selective inhibitor known at the time. We then describe the transformation of our SphK2-selective inhibitors into an orally bioavailable drug. We explain how the guanidine functionality on our inhibitor scaffold hinders our compounds from being orally bioavailable. Consequently, a library of 24 derivatives with various modifications to the guanidine functionality was synthesized and evaluated for improved orally bioavailability. Highlighted in this work is the development of the most potent SphK2-selective inhibitor currently known 3.14 (SLS1081832), which displays a hSphK2 Ki of 82 nM and 122-fold selectivity for SphK2. Chemical modification and in vivo assessment of 3.14 (SLS1081832) prodrugs was explored. / Doctor of Philosophy / In humans, sphingosine 1-phosphate (S1P) is a signaling molecule that is generated through an ATP dependent reaction of sphingosine (Sph) via sphingosine kinase 1 and 2 (SphK1 and SphK2). Furthermore, S1P has been shown to be implicated in various diseases such as cancer, sickle cell disease, multiple sclerosis, and renal fibrosis. Inhibition of SphK1 and SphK2 has been shown to be therapeutic towards the symptoms of these diseases. Therefore, in order to alleviate these disorders, the concentrations of S1P must be controlled through pharmacological inhibition of SphK1 and SphK2. There are multiple reported examples of potent SphK1-selective and dual SphK1/2 inhibitors; however, SphK2-selective inhibitors are scarce. This work describes the synthesis and biological assessment of 21 compounds for their effectiveness in selectively targeting and inhibiting SphK2. The work led to the discovery of a previously unrecognized side cavity in the binding pocket of SphK2 that enhances inhibitor potency and selectivity towards SphK2. Furthermore, studies characterizing the preferred size and chemical nature of moieties positioned in that portion of the binding site led to the development of the most potent SphK2- selective inhibitor known at the time. Building on this work, we next focused on the transformation of our SphK2-selective inhibitors into a drug that could be administered orally. We describe the synthesis of 24 compounds with various modifications to one portion of our scaffold and their effect on improved orally bioavailability. This work led to the development of the most potent SphK2-selective inhibitor currently known 3.14 (SLS1081832).

A variety of diseases including Alzheimer's disease, asthma, cancer, fibrosis, multiple sclerosis, and sickle cell disease have been associated with elevated levels of sphingosine-1-phosphate (S1P). S1P, a pleiotropic lipid mediator involved in a broad range of cellular processes, is synthesized solely by the phosphorylation of sphingosine (Sph) and is catalyzed by the two isoforms of sphingosine kinase (SphK1 and SphK2). Therefore, SphKs are a potential therapeutic target; however, the physiological role of SphK2 is still emerging. In order to determine the role of SphK2 in vivo, more potent and selective small molecule inhibitors of SphK2, as well as dual inhibitors are necessary. Herein, explorations and advancements on the second generation SphK2 selective inhibitor SLR080811 are disclosed. Investigations into the lipophilic tail region of the hSphK2 inhibitor SLR080811 are detailed. This investigation highlights the dependency of SphK2 selectivity and potency on overall compound length. More importantly, this study identified the internal aryl ring of SLR080811 as a key pharmacophore of the scaffold. To further probe the significance of the aromatic region, the phenyl ring was replaced by a 2,6-naphthyl ether skeleton. Investigations into the tail region of this scaffold are described in detail. Key discoveries from this structure-activity relationship study include SLC5111312 (hSphK2 Ki = 0.90 μM, dual hSphK inhibitor), SLC5091592 (hSphK2 Ki = 1.02 μM, > 20-fold hSphK2 selective) and SLC5121591 (hSphK2 Ki = 0.61 μM, >16-fold hSphK2 selective). Molecular modeling studies with hSphK2 indicate that the extended aromatic group is able to participate in π-π stacking interactions with Phe548. In silico docking studies indicate that a guanidine hydrogen bond to Asp211 is key for SphK2 selectivity, and incorporation of a 3'-hydroxyl group on the pyrrolidine ring increases hydrogen bonding to Asp308, thereby increasing SphK1 potency and reducing selectivity. Additionally, biological studies employing SLC5111312 have helped to further elucidate the role of SphK2, suggesting that SphK2 has a catalytic role in the regulation of blood S1P levels. The shape of the hSphK2 binding pocket was probed by introducing an indole moiety in place of the naphthyl ring and varying its substitution pattern. One key discovery from this study is SLC5101465 (hSphK2 Ki = 0.09 μM, > 111 fold SphK2 selective), which has a 1,5-indole substitution pattern with an N-nonyl "tail". Molecular docking simulations highlight the importance of rotatable bonds and a relatively linear orientation between the "head group" and "tail group" to maintain essential hydrogen bond interactions to Asp residues with the guanidine moiety while minimizing steric interactions in the middle of the binding pocket. Expanding upon the 1,5-indole scaffold of SLC5101465, a series of aryl tail derivatives are examined. This study confirms the necessity of electron withdrawing groups located at the end of the inhibitor scaffold to optimize binding in the tail region of the SphK2 binding pocket. / Ph. D.

Active docking in modular robotic systems has received a lot of interest recently as it allows small versatile robotic systems to coalesce and achieve the structural benefits of larger robotic systems. This feature enables reconfigurable modular robotic systems to bridge the gap between small agile systems and larger robotic systems. The proposed self-reconfigurable mobile robot design exhibits dual mobility using a tracked drive for longitudinal locomotion and wheeled drive for lateral locomotion. The two degrees of freedom (DOF) docking interface referred to as GHEFT (Genderless, High strength, Efficient, Fail-Safe, high misalignment Tolerant) allows for an efficient docking while tolerating misalignments in 6-DOF. In addition, motion along the vertical axis is also achieved via an additional translational DOF, allowing for toggling between tracked and wheeled locomotion modes by lowering and raising the wheeled assembly. This thesis also presents a visual-based onboard Hybrid Target Tracking algorithm to detect and follow a target robot leading to autonomous docking between the modules. As a result of this proposed approach, the tracked features are then used to bring the robots in sufficient proximity for the docking procedure using Image Based Visual Servoing (IBVS) control. Experimental results to validate the robustness of the proposed tracking method, as well as the reliability of the autonomous docking procedure, are also presented in this thesis. / Master of Science / Active docking in modular robotic systems has received a lot of interest recently as it allows small versatile robotic systems to coalesce and achieve the structural benefits of larger robotic systems. This feature enables reconfigurable modular robotic systems to bridge the gap between small agile systems and larger robotic systems. Such robots can prove useful in environments that are either too dangerous or inaccessible to humans. Therefore, in this research, several specific hardware and software development aspects related to self-reconfigurable mobile robots are proposed. In terms of hardware development, a robotic module was designed that is symmetrically invertible and exhibits dual mobility using a tracked drive for longitudinal locomotion and wheeled drive for lateral locomotion. Such interchangeable mobility is important when the robot operates in a constrained workspace. The mobile robot also has integrated two degrees of freedom (DOF) docking mechanisms referred to as GHEFT (Genderless, High strength, Efficient, Fail-Safe, high misalignment Tolerant). The docking interface allows for an efficient docking while tolerating misalignments in 6-DOF. In addition, motion along the vertical axis is also performed via an additional translational DOF, allowing for lowering and raising the wheeled assembly. The robot is equipped with sensors to provide positional feedback of the joints relative to the target robot. In terms of software development, a visual-based onboard Hybrid Target Tracking algorithm for high-speed consistent tracking iv of colored targets is also presented in this work. The proposed technique is used to detect and follow a colored target attached to the target robot leading to autonomous docking between the modules using Image Based Visual Servoing (IBVS). Experimental results to validate the robustness of the proposed tracking approach, as well as the reliability of the autonomous docking procedure, are also presented in the thesis. The thesis is concluded with discussions about future research in both structured and unstructured terrains.

The less-than-truckload (LTL) industry is highly competitive, with recent average profit margins less than 3%. LTL shipments are routed through a network of service centers and hubs. The performance of the entire LTL distribution network is highly dependent on the speed and accuracy of the hub operations. The focus of this research effort is to improve hub operations in order to reduce costs and increase service performance levels. Specifically, new approaches are investigated for assigning trailers to dock doors and sequencing the unloading of shipments at hubs. This thesis reviews current industry practices and available research literature on hub operations. Solution approaches for the trailer-to-door assignment and freight sequencing problems are presented along with case study results. The main performance measures are bottleneck time, total labor time, and total travel distance. For the trailer-to-door assignment problem, also referred to as the hub layout problem, the three approaches investigated are the original approach, a semi-permanent approach, and a dynamic approach. For the freight sequencing problem, the five approaches evaluated are trailer-at-a-time, trailer-at-a-time with offloading, nearest neighbor within a group, nearest neighbor within a shared group, and nearest neighbor. The approaches are implemented in C++ and analyzed using data from a regional LTL carrier. The case study results indicate that the dynamic layout performs significantly better than the original and semi-permanent layout for total distance, total labor time, and bottleneck time. For total distance and total labor time, the dynamic layout with nearest neighbor sequencing is the preferred approach. For bottleneck time, the dynamic layout with trailer-at-a-time with offloading performs best, while the nearest neighbor sequencing approach performs almost as well. In general, the case study results indicate that a dynamic layout with either a trailer-at-a-time with offloading approach or a nearest neighbor approach offers the largest potential for improvement. The assumptions and results of the hub layout and freight sequencing approaches are further evaluated using a simulation model. The simulation model indicates that a dynamic layout with nearest neighbor sequencing offers the largest potential for improvement in a more realistic environment with probabilistic and dynamic events. The simulation results also indicate that the trailer-at-a-time with offloading approach may need to be modified to account for more realistic dock conditions. In summary, the approaches explored in this research offer significant opportunity to improve hub operations through reducing bottleneck time, total labor time, and total travel distance. / Master of Science

Kinases are involved in a multitude of signaling pathways, such as cellular growth, proliferation, and apoptosis, and have been discovered to be important in numerous diseases including cancer, Alzheimer's disease, cardiovascular health, rheumatoid arthritis, and fibrosis. Due to the involvement in a wide variety of disease types, kinases have been studied for exploitation and use as targets for therapeutics. There are many limitations with developing kinase target therapeutics due to the high similarity of kinase active site composition, making the utilization of new techniques to determine kinase exploitability for therapeutic design with high specificity essential for the advancement of novel drug strategies. In silico approaches have become increasingly prevalent for providing useful insight into protein structure-function relationships, offering new information to researchers about drug discovery strategies. This work utilizes streamlined computational techniques on an atomistic level to aid in the identification of orthologue and isoform exploitability, identifying new features to be utilized for future inhibitor design. By exploring two separate kinases and kinase targeting domains, we found that orthologues and isoforms contain distinct features, likely responsible for their biological roles, which can be utilized and exploited for selective drug development. In this work, we identified new exploitable features between kinase orthologues for treatment in Human African Trypanosomiasis and structural morphology differences between two kinase isoforms that can potentially be exploited for cancer therapeutic design. / Master of Science in Life Sciences / Numerous diseases such as cancer, Alzheimer's disease, cardiovascular disease, rheumatoid arthritis, and fibrosis have been attributed to different cell growth and survival pathways. Many of these pathways are controlled by a class of enzymes called kinases. Kinases are involved in almost every metabolic pathway in human cells and can act as molecular switches to turn on and off disease progression. Due to the involvement of these kinases' in a wide variety of disease types, kinases have been continually studied for the development of new drugs. Developing effective drugs for kinases requires an extensive understanding of the structural characteristics due to the high structural similarity across all kinases. In silico, or computational, techniques are useful strategies for drug development practices, offering new information into protein structure-function relationships, which in turn can be utilized in drug discovery advancements. Utilizing computational methods to explore structural features can help identify specific protein structural features, thus providing new strategies for protein specific inhibitor design. In this work, we identified new exploitable features between kinase orthologues for treatment in Human African Trypanosomiasis and structural morphology differences between two kinase isoforms that can potentially be exploited for cancer therapeutic design.

Peroxisome proliferator-activated receptor γ (PPARγ) is associated with a wide range of diseases, including type 2 diabetes mellitus (T2D). Thiazolidinediones (TZDs) are agonists of PPARγ which have an insulin sensitizing effect, and are therefore used as a treatment for T2D. However, TZDs cause negative side effects in patients, such as weight gain, edema, and increased risk of bone fracture. Partial agonists could be an alternative to TZD-based drugs with fewer side effects. However, there is a lack of understanding of the types of PPARγ partial agonists and how they differ from full agonists. In silico techniques, like virtual screening, molecular docking, and pharmacophore modeling, allow us to determine and characterize markers of varying levels of agonism. An extensive search of the RCSB Protein Data Bank found 62 structures of PPARγ resolved with partial agonists. Cross-docking was performed and found that two PDB structures, 3TY0 and 5TWO, would be effective as receptor structures for virtual screening. By clustering known partial agonists by common pharmacophore features, we found several distinct groups of partial agonists. Interaction and pharmacophore models were created for each group of partial agonists. Virtual screening of FDA-approved compounds showed that the models were able to predict potential partial agonists of PPARγ. This study provides additional insight into the different binding modes of partial agonists of PPARγ and their characteristics. These models can be used to assist drug discovery efforts for intelligently designing novel therapeutics for T2D which have fewer negative side effects. / Master of Science in Life Sciences / The peroxisome proliferator-activated receptor γ (PPARγ) protein is associated with a wide range of diseases, including type 2 diabetes mellitus (T2D). Thiazolidinediones (TZDs) are compounds that activate PPARγ, and increase insulin sensitivity in patients with T2D. However, TZDs cause negative side effects in patients, such as weight gain, increased fluid retention, and increased risk of bone fracture. Partial agonists could be an alternative to TZD-based drugs with fewer side effects. However, there is a lack of understanding of the types of PPARγ partial agonists and how they differ from full agonists. Computational techniques allow us to investigate common features between known partial agonists. An extensive search of the RCSB Protein Data Bank found 62 structures of PPARγ which contained partial agonists. Each known partial agonist was docked into twelve complete PPARγ structures, and it was found that two structure models would be effective as receptor structures for virtual screening. A set of known partial agonists were grouped based on common chemical features, and three distinct groups of partial agonists were found. Binding criteria for each of these three groups were developed. A library of FDA-approved compounds was screened using the criteria for binding to identify potential novel partial agonists. Three potential novel partial agonists were found in the screening. This study provides additional insight into how different compounds activate PPARγ. These methods can be used to assist drug discovery efforts for intelligently designing novel therapeutics for T2D which have fewer negative side effects.

Metastasis is a major cause of cancer-related deaths and there is a great need for therapies aimed at preventing the spread of cancer, for which lysyl oxidase (LOX), an amino oxidase, plays a crucial role. The general aim of the thesis project was to screen and validate compounds with LOX inhibitory activities. To achieve this goal, we built a pharmacophore model of LOX inhibitors (LOXi) and screened a database of over 4400 compounds with known anti-tumoral activity in cell assays, the Biolab’s database. Top hits from the pharmacophore screening were docked to a LOX crystal structure to assess interactions between predicted inhibitors and the enzyme, and the methodology was implemented using MOE (Molecular Operating Environment) software. The pharmacophore model here developed had 5 features and produced an enrichment factor of 20 in our refinement stage. Biolab’s database screening resulted in the discovery of 344 hits. We docked the top 100 hits against a crystal structure of LOX and the results from the top 10 compounds, ranked by their interaction energy, were further analyzed. Using computer simulation software like MOE, increases the chances of finding a true inhibitor of LOX as compared to random testing of potential inhibitors, thus saving time and resources. / Metastaser är en viktig orsak till cancerrelaterade dödsfall och det finns ett stort behov av behandlingar som syftar till att förhindra spridning av cancer, där lysyloxidas (LOX), ett aminooxidas, spelar en avgörande roll. Det allmänna syftet med avhandlingsprojektet var att screena och validera föreningar med LOX-hämmande aktiviteter genom att konstruera en farmakofilmodell av LOX-hämmare (LOXi) för att screena en databas med föreningar med känd anti-tumoral aktivitet, Biolabs databas. De bästa träffarna från farmakoforscreeningen dockades till en LOX-kristallstruktur för att bedöma interaktioner mellan förutsedda hämmare och enzymet. Metoden implementerades med hjälp av programvaran MOE (Molecular Operating Environment). Den farmakospormodell som utvecklades här hade 5 funktioner och gav en anrikningsfaktor på 20 i vårt förfiningssteg. Biolabs databasscreening resulterade i upptäckten av 344 träffar. Vi dockade de 100 bästa träffarna mot en kristallstruktur av LOX och resultaten från de 10 bästa föreningarna, rangordnade efter deras interaktionsenergi, analyserades ytterligare. Genom att använda datorsimuleringsprogram som MOE ökar chansen att hitta en verklig hämmare av LOX jämfört med slumpmässiga tester av potentiella hämmare, vilket sparar tid och resurser.