Interpretation of crystallographic and mutational studies of antifreeze proteins (AFPs) requires molecular modeling of AFPs with ice. Most models proposed so far suggested H-bonds as the major driving force of AFP-ice association. However, the bulk water offers optimal network of H-bonds and van der Waals contacts to the isolated AFP and ice suggesting that corresponding components of free energy would not decrease upon AFP-ice association. In an attempt to resolve this controversy, we Monte Carlominimized complexes of several AFPs with taking into account, in addition to nonbonded interactions and H-bonds, the hydration potential for proteins (Augspurger and Scheraga, 1996). Parameters of the hydration potential for ice were developed basing on an assumption that at the melting temperature the free energy of water-ice association is small. Simulations demonstrate that desolvation of hydrophobic groups in the AFPs upon their fitting to the grooves at the ice surface presents the major stabilizing contributions to the free energy of AFP-ice binding. Our results explain available data on structure of AFPs and their mutational analyses, in particular, a paradoxical fact that substitution of Thr residues to Val does not affect potency of Winter Flounder AFP. / Thesis / Master of Science (MS)

Mass spectrometry was used in conjunction with numerous 1-D and 2-D NMR techniques to determine the structures, devoid of stereochemistry, of five different compounds isolated from the extracts of Eunicea succinea, Eunicea tourneforti, and an unidentified species isolated from the Eunicea genus by Professor Meledath Govindan, of the University of the Virgin Islands. Three of the compounds were then identified as the known compounds eunicin, 12,13-bisepieupalmerin, and 7(S),8(S)-epoxy-1(S),11(R)-dolabella-3E,12(18) -dien-13-one by comparison of their spectroscopic data and optical rotations with those published in the literature. Optical rotations could not be measured accurately for the other two compounds because of small sample sizes; therefore, another method had to be found to elucidate the stereochemistry of these two structures. To solve this problem, molecular modeling and NOESY were employed. Comparison of the NOESY interactions to the thermodynamically available conformations of several possible stereoisomers, calculated by molecular modeling, proved to be a useful technique. One of the remaining two structures was identified as the known stereoisomer euniolide. The stereochemistry of the one remaining structure could not be assigned because sample size was not large enough to obtain a clean NOESY spectra. Finally, based on published synthetic work by Corey and Kania, the absolute stereochemistry of the dolabellane was revised to 7(R),8(R)-epoxy-1(R),11(S)- dolabella-3E,12(18)-dien-13-one. / Master of Science

Biomolecular Modeling is playing an important role in many practical applications such as biotechnology and structure-based drug design. One of the essential requirements of Biomolecular modeling is an accurate description of the solvent (water). The challenge is to make this description computationally facile that is reasonably fast, simple, robust and easy to incorporate into existing software packages. The most rigorous procedure to model the effect of aqueous solvent is to explicitly model every water molecule in the system. For many practical applications, this approach is computationally too intense, as the number of required water atoms is on average one order of magnitude larger than the number of atoms of the molecule of interest. Implicit solvent models, in which solvent molecules are represented by a continuum function, have become a popular alternative to explicit solvent methods as they are computationally more efficient. The Generalized Born (GB) implicit solvent has become quite popular due to its relative simplicity and computational efficiency. However, recent studies showed serious deficiencies of many GB variants when applied to Biomolecular Modeling such as an over- stabilization of alpha helical secondary structures and salt bridges. In this dissertation we present two new GB models aimed at computing solvation properties with a reasonable compromise between accuracy and speed. The first GB model, called NSR6, is based on a numerically surface integration over the standard molecular surface. When applied to a set of small drug-like molecules, NSR6 produced an accuracy, with respect to experiments, that is essentially at the same level as that of the expensive explicit solvent treatment. Furthermore, we developed an analytic GB model, called AR6, based on an approximation of the volume integral over the standard molecular volume. The accuracy of the AR6 model is tested relative to the numerically exact NSR6. Overall AR6 produces a good accuracy and is suitable for Molecular Dynamics simulations which is the main intended application. / Ph. D.

Better visualization of micro-level structures and processes can greatly enhance student understanding of key biological functions such as the central dogma. Previous research has demonstrated a need of introducing novel methods to increase student understanding of these concepts. The intention of this report is to show how computational modeling programs (CMPs) can be successfully used as an innovative method of teaching biology concepts that occur at a molecular level. The use of computers and web-based lessons are not new topics in secondary education studies but there is not an abundance of research related to computational modeling alone. We began by researching the many studies that have already indicated the benefits of using computers in the classroom with an emphasis on CMPs and simulations. Of these, we focused mostly on the ones that showed increased student engagement and influenced understanding of core science concepts. Based on the literature reviewed, a framework for curriculum designed around CMPs is proposed. Lastly, a model lesson is discussed to provide an example of how these professional grade tools can be employed in the classroom. This report provides a basis for the continued development of constructivist curriculum built around the use of professional grade computational tools in secondary science classrooms. / text

The results from this work are reported into two sections listed below: <br><br> Synthesis: <br><br> Following structural classes of compounds have been designed, synthesized and studied as inhibitors of pjDHFR, RTKs and tubulin: <br> 1. 2,4-Diamino-6-(substituted-arylmethyl)pyrido[2,3-d]pyrimidines <br> 2. 4-((3-Bromophenyl)linked)-6-(substituted-benzyl)-7H-pyrrolo[2,3-d]pyrimidin-2-amines<br> 3. 6-Methyl-5-((substitutedphenyl)thio)-7H-pyrrolo[2,3-d]pyrimidin-2-amines <br> A total of 35 new compounds (excluding intermediates) were synthesized, characterized and submitted for biological evaluation. Results from these studies will be presented in due course. Bulk synthesis of the potent lead compound 170 was carried out to facilitate in vivo evaluation. <br><br> Docking Studies <br><br> Docking studies were performed using LeadIT, MOE, Sybyl or Flexx for target compounds listed above and for other compounds reported by Gangjee et al. against the following targets: <br> 1. Dihydrofolate reductase: human, P. carinii, P. jirovecii (pjDHFR) and T. gondii (tgDHFR)<br> 2. Thymidylate synthase: human (hTS) and T. gondii (tgTS)<br> 3. Receptor tyrosine kinases: VEGFR2, EGFR and PDGFR-β<br> 4. Colchicine binding site of tublulin.<br> Novel homology models were generated and validated for pjDHFR, tgDHFR, tgTS, PDGFR-β and the F36C L65P pjDHFR double mutant. The tgTS homology model generated in this study and employed to design novel inhibitors shows remarkable similarity with the recently published X-ray crystal structures. Docking studies were performed to provide a molecular basis for the observed activity of target compounds against DHFR, RTKs or tubulin. Results from these studies support structure-based and ligand-based medicinal chemistry efforts in order to improve potency and/or selectivity of analogs of the docked compounds against these targets.<br> Novel topomer CoMFA models were developed for tgTS and hTS using a set of 85 bicyclic inhibitors and for RTKs using a set of 60 inhibitors reported by Gangjee et al. The resultant models could be used to explain the potency and/or selectivity differences for selected molecules for tgTS over hTS. Topomer CoMFA maps show differences in steric and/or electronic requirements among the three RTKs, and could be used, in conjuction with other medicinal chemistry approaches, to modulate the selectivity and/or potency of inhibitors with multiple RTK inhibitory potential. Drug design efforts that involve virtual library screening using these topomer CoMFA models in conjunction with traditional medicinal chemistry techniques and docking are currently underway. / Mylan School of Pharmacy and the Graduate School of Pharmaceutical Sciences; / Medicinal Chemistry / PhD; / Dissertation;

Master of Science / Department of Chemical Engineering / Keith Hohn / The study will utilize a probabilistic reaction modeling method for ring-opening reactions of epoxide. In particular, to elucidate the reaction mechanism by the methods presented, focus will be placed on the nucleophillic attack of ethylene oxide by ammonia and its anion. This focus was chosen because of the potential to gain significant advantage in computational intensity required to model the epoxy-amino macromolecular curing reactions and resulting thermochemical and physical properties of the cured resin. The method employed utilizes the combinatorial probability that 1. Two molecules will approach a transition state with sufficient energy to drive reaction 2. Any reaction will occur for a given penetration into the potential energy surface. The concept of a transition state is relaxed to allow a dynamic probability that any reaction will proceed given a position on the intrinsic reaction coordinate (IRC) rather than searching for a specific transition state of theoretical reaction probability. 3. The reaction that occurs yields a desired stable or semi-stable molecular complex This study will focus on identifying possible stable and semi-stable products and corresponding rate constants. The technique developed here is novel in that it provides an unsupervised method to identify all structures corresponding to minima on the potential energy surface. The technique provides a pragmatic and efficient approach to sample a molecular system for different reaction mechanisms and provides a relative energy requirement to achieve these mechanisms with no presupposition of the mechanism, product, or transition state. It is possible from this data to derive rate constants for a reacting system, however, the rate constant derived for the EO/NH2 molecular system yielded significantly understated reaction probabilities and therefore rate constants.

The results of three very different studies are presented. X-ray diffraction has been utilized for single-crystal structure determinations, fiber diffraction analyses, and in conjunction with molecular modeling of Cellulose IIII. Although each technique is different in its sampling, data acquisition, data treatment, and identification, the common denominator has been the use of x-rays. The single-crystal structure determination of ethylene glycol bis(tropane-3-carboxylate) is presented as an example of the use of modern single-crystal x-ray instrumentation including the use of coupled charged devices (CCDs) as detectors for accurate data collection and rapid elucidation of crystal structures. The structure determination of Cellulose IIII by x-ray diffraction and computer modeling is presented to show how the use of x-rays in weakly diffracting materials can generate a reliable structure and be a key component in model building. Finally, a study is presented in which x-ray fiber diffraction data is utilized to investigate possible correlations between the crystallite orientation, crystallinity, crystallize size and the strength properties of cotton fibers collected from various countries.

Concrete is one of the most widely used materials in the world. It is also one of the most versatile while complex materials which human have used for construction. However, an important weakness of concrete (cement-based composites) is its weak tensile properties. Therefore, over the past thirty years many studies were focused to improve its tensile properties using a variety of physical and chemical methods. One of the most successful attempts is to use polymer fibers in the structure of concrete to obtain a composite with high tensile strength and ductility.However, a thorough understanding of the mechanical behavior of fiber reinforced concrete requires the knowledge of fiber/matrix interfaces at the nanoscale. In this study, a combination of atomistic simulations and experimental techniques has been used to study the nanostructure of fiber/matrix interfaces. A new model for calcium-silicate-hydrate (C-S-H)/fiber interfaces is also proposed based on Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX) analyses. Finally, the adhesion energies between the C-S-H gel and three different polymeric fibers (polyvinyl alcohol, nylon-6 and polypropylene) were numerically studied at the atomistic level, since adhesion plays a key role in the design of ductile fiber reinforced composites. The mechanisms of adhesion as a function of the nanostructure of fiber/matrix interfaces are further studied and discussed. It is observed that the functional group in the structure of polymer macromolecule affects the adhesion energy primarily by changing the C/S ratio of the C-S-H at the interface and further by absorbing additional positive ions in the C-S-H structure. Then the mechanical response of cement paste with added polymeric fibers were studied. A correlation between adhesion energies and the load-displacement curve in split-cylinder test was found. Moreover, as there is a great interest in cellulose-based cement composites, bamboo fibers is added to the cement paste and the fiber/matrix interface and its effect on structure of C-S-H were investigated.

Les membranes biologiques jouent un rôle essentiel dans la vie cellulaire. Afin d’étudier leur comportement et leurs interactions avec des molécules, des modèles de monocouches lipidiques ont été développés. Leur compression sur balance de Langmuir permet d’obtenir une isotherme pression de surface-aire moléculaire permettant de caractériser notamment les transitions de phase et le comportement interfacial des monocouches. Seules les études de simulations de dynamique moléculaire permettent d’obtenir les propriétés structurales des lipides organisés en monocouche à l’échelle atomique. Nous avons modélisé une monocouche de 1-palmitoyl-2-oléoyl-sn-glycéro-3-phosphocholine (POPC), phospholipides majoritaires des membranes, puis réalisé une série de dynamiques moléculaires à différentes tensions de surface en utilisant GROMACS et le champ de force tout atome GAFF. Une isotherme de compression de POPC a été obtenue pour la première fois par simulation de dynamique moléculaire. L’analyse structurale des POPC a mis en évidence des variations conformationelles avec l’augmentation de la pression ainsi qu'une distribution bimodale de l’orientation des têtes polaires. L’analyse des angles dièdres a permis d’identifier les torsions responsables de cette flexibilité. Un comportement indépendant des chaînes hydrophobes a été observé et corrélé à un assemblage préférentiel des chaînes oléoyle d’une part et palmitoyle d’autre part. La connaissance des propriétés structurales et organisationnelles des monocouches de POPC est essentielle à la caractérisation des interactions mises en jeu dans la cohésion des films lipidiques et fournit une base à l’étude de leur perturbation par des molécules. / Biomembranes play an essential role in many relevant processes in cellular biology. In order to gain insight into their behaviour and interactions with molecules, models such as lipid monolayers have been developed. Monolayer compression on Langmuir trough provides surface pressure – molecular area isotherms, and allows characterisation of phase and interfacial properties of the monolayer. Such a characterisation can be completed by atomistic study of the monolayer phospholipids and molecular interactions from molecular dynamic simulations. Our work is focused on 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), a lipid comprising a saturated and an unsaturated acyl chain, major lipids in eukaryotic cell membranes. We performed MD simulations at 293 K and 300 K at different surface pressures using the all-atom general amber force field (GAFF). Simulated surface pressure-area isotherms were obtained for the first time, and a good agreement was found with experimental isotherms. Based on the structural analyses, two orientations of the head groups clearly appear. We propose that the conformational variations around the bonds connecting the phosphorus atom to the adjacent oxygen are involved in these specific orientations. Both acyl chains have distinct structural properties upon compression and suggest an independent behavior of the saturated and unsaturated chains that could be correlated with the formation of chain-type clusters observed along the simulated trajectories. Molecular insight in structural properties of POPC monolayer provides essential clues for the study of membrane-molecule interaction.

Over a billion individuals worldwide suffer from neglected diseases. This equates to approximately one-sixth of the human population. These infections are often endemic in remote tropical regions of impoverished populations where vectors can flourish and infected individuals cannot be effectively treated due to a lack of hospitals, medical equipment, drugs, and trained personnel. The few drugs that have been approved for the treatments of such illnesses are not widely used because they are riddled with inadequate implications of cost, safety, drug availability, administration, and resistance. Hence, there exists an eminent need for the design and development of improved new therapeutics. Influential world-renowned scientists in the Consortium for Parasitic Drug Development (CPDD) have preformed extensive biological testing for compounds active against parasites that cause neglected diseases. These data were acquired through several collaborations and found applicable to computational studies that examine quantitative structure-activity relationships through the development of predictive models and explore structural relationships through docking. Both of these in silico tools can contribute to an understanding of compound structural importance for specific targets. The compilation of manuscripts presented in this dissertation focus on three neglected diseases: trypanosomiasis, Chagas disease, and leishmaniasis. These diseases are caused by kinetoplastid parasites Trypanosoma brucei, Trypanosoma cruzi, and Leishmania spp., respectively. Statistically significant predictive devices were developed for the inhibition of the: (1) T. brucei P2 nucleoside transporter, (2) T. cruzi parasite at two temperatures, and (3) two species of Leishmania. From these studies compound structural importance was assessed for the targeting of each parasitic system. Since these three parasites are all from the Order Kinetoplastida and the kinetoplast DNA has been determined a viable target, compound interactions with DNA were explored to gain insight into binding modes of known and novel compounds.