Doctor of Philosophy

dissertationAdvances in molecular dynamics (MD) simulation methodologies have enabled researchers to explore the conformational spaces of biological macromolecules more efficiently and quickly. Specifically, the development of enhanced sampling techniques has provided researchers with well-converged conformational ensembles of small macromolecules. It has been shown that converged simulations of small ribonucleic acids (RNA) such as tetranucleotides result in the population of experimentally unknown conformations, indicating RNA force field artifacts. However, although being imperfect, the current RNA force fields have also been useful in characterizing the varied interactions of ions and ligands with RNA. In this thesis, we analyze conformational ensembles of dinucleotide monophosphates generated with different force fields and water models with the aim of pinpointing force field problems. We also utilize the current force fields to demonstrate the preferential potassium binding to a buried ion-binding site in a ribosomal RNA molecule known as GTPase Associating Center (GAC) and also to elucidate an ion-dependent step in its unfolding pathway. We further show magnesium-independency of binding of a crystallographic 2-benzimidazole ligand to the Internal Ribosome Entry Site (IRES) of Hepatitis C virus (HCV), using MD simulations and docking. Our strategy is to assess simulation results with existing experimental data, and then also use simulation results to increase insight into RNA interactions and folding. These methods allow us to identify deficiencies of some current RNA force fields

A novel hybrid method of β-turn identification in protein using binary logistic regression and neural network

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins

Investigating the ion dependence of the first unfolding step of GTPase-Associating Center ribosomal RNA

<p>The interactions in the tertiary structure of a ribosomal RNA fragment in the GTPase Associating Center (<i>GAC</i>) have been experimentally studied, but the roles of the bound and diffuse cations in its folding pathway have not yet been fully elucidated. Melting experiments have shown that the temperature of the first of the two distinguishable transitions in the unfolding pathway of the <i>GAC</i> RNA can be regulated by altering the magnesium concentration, yet the physical interpretation of such ion-dependent effects on folding have not been clearly understood in spite of the availability of crystal structures that depict many <i>GAC</i> RNA–ion interactions. Here, we use umbrella sampling and molecular dynamics (MD) simulations to provide a physical description for the first transition in this unfolding pathway, with a focus on the role of a chelated magnesium ion. Our results indicate that the presence of cations mediating the local interaction of two loops stabilizes the folded state relative to the unfolded or partially folded states. Also, our findings suggest that a bridging magnesium ion between the two loops improves the stabilizing effect. This is consistent with the multistep unfolding pathway proposed for the <i>GAC</i> RNA and highlights the importance of ions in the first unfolding step. The results suggest how MD simulations can provide insight into RNA unfolding pathways as a complementary approach to experiments.</p

Consensus Conformations of Dinucleoside Monophosphates Described with Well-Converged Molecular Dynamics Simulations

Dinucleoside monophosphates (DNMPs) have been described using various experimental approaches as flexible molecules which generate ensembles populating at least a small set of different conformations in solution. However, due to limitations of each approach in its ability to delineate the ensemble of conformations, an accurate and quantitative description of certain conformational features has not been performed for all DNMPs. Here, we apply a temperature replica-exchange molecular dynamics approach to fully and quickly converge conformational distributions of all RNA DNMPs immersed in the TIP3P water model using the AMBER ff14 force field. For a selection of DNMPs, the conformational ensembles were also generated when immersed in the OPC water model using alternative AMBER and CHARMM force fields. The OPC water model and other force field choices did not introduce new conformational classes but shifted the populations among existing conformations. Except for pyrimidine–pyrimidine dinucleosides, all other DNMPs populated four major conformations (which are defined in the main text and labeled A-form, Ladder, Inverted, and Sheared), in addition to an Extended form. Pyrimidine–pyrimidines did not generate the Sheared conformation. Distinguishing features and stabilizing factors of each conformation were identified and assessed based on the known experimental interpretations. The configuration of the glycosidic bond and the nonbonding interactions of hydrogen bond acceptors with the 2′-hydroxyl group were found to play determining roles in stabilizing particular conformations which could serve as a guide for potential force field modifications to improve the accuracy. Additionally, we computed stacking free energies based on the DNMP conformational distributions and found significant discrepancies with a previous study. Our investigation determined that the AMBER force field was incorrectly implemented in the previous study. In the future, this simulation approach can be used to quickly analyze the effects of new force field modifications in shifting the conformational populations of DNMPs, and can can be further applied to foresee such effects in larger RNA motifs including tetranucleotides and tetraloops

Structural and Energetic Analysis of 2‑Aminobenzimidazole Inhibitors in Complex with the Hepatitis C Virus IRES RNA Using Molecular Dynamics Simulations

Despite the many biological functions of RNA, very few drugs have been designed or found to target RNA. Here we report the results of molecular dynamics (MD) simulations and binding energy analyses on hepatitis C virus internal ribosome entry site (IRES) RNA in complex with highly charged 2-aminobenzimidazole inhibitors. Initial coordinates were taken from NMR and crystallography studies that had yielded different binding modes. During MD simulations, the RNA–inhibitor complex is stable in the crystal conformation but not in the NMR conformation. Additionally, we found that existing and standard MD trajectory postprocessing free energy methods, such as the MM-GBSA and MM-PBSA approaches available in AMBER, seem unsuitable to properly rank the binding energies of complexes between highly charged molecules. A better correlation with the experimental data was found using a rather simple binding enthalpy calculation based on the explicitly solvated potential energies. In anticipation of further growth in the use of small molecules to target RNA, we include results addressing the impact of charge assignment on docking, the structural role of magnesium in the IRES–inhibitor complex, the entropic contribution to binding energy, and simulations of a plausible scaffold design for new inhibitors

Structural and Energetic Analysis of 2‑Aminobenzimidazole Inhibitors in Complex with the Hepatitis C Virus IRES RNA Using Molecular Dynamics Simulations

Despite the many biological functions of RNA, very few drugs have been designed or found to target RNA. Here we report the results of molecular dynamics (MD) simulations and binding energy analyses on hepatitis C virus internal ribosome entry site (IRES) RNA in complex with highly charged 2-aminobenzimidazole inhibitors. Initial coordinates were taken from NMR and crystallography studies that had yielded different binding modes. During MD simulations, the RNA–inhibitor complex is stable in the crystal conformation but not in the NMR conformation. Additionally, we found that existing and standard MD trajectory postprocessing free energy methods, such as the MM-GBSA and MM-PBSA approaches available in AMBER, seem unsuitable to properly rank the binding energies of complexes between highly charged molecules. A better correlation with the experimental data was found using a rather simple binding enthalpy calculation based on the explicitly solvated potential energies. In anticipation of further growth in the use of small molecules to target RNA, we include results addressing the impact of charge assignment on docking, the structural role of magnesium in the IRES–inhibitor complex, the entropic contribution to binding energy, and simulations of a plausible scaffold design for new inhibitors

Novel Use of Hypoxia-Inducible Polymerizable Protein to Augment Chemotherapy for Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies and is the fourth leading cause of cancer-related deaths in the United States. Unfortunately, 80–85% of patients are diagnosed with unresectable, advanced stage tumors. These tumors are incurable and result in a median survival less than approximately six months and an overall 5-year survival rate of less than 7%. Whilst chemotherapy is a critical treatment, cure is not possible without surgical resection. The poor clinical outcomes in PDAC can be partially attributed to its dense desmoplastic stroma, taking up roughly 80% of the tumor mass. The stroma surrounding the tumor disrupts the normal architecture of pancreatic tissue leading to poor vascularization, high intratumoral pressure along with hypoxia and an acidic tumor microenvironment. This complicated microenvironment presents a significant challenge for drug delivery. The current manuscript discusses a novel approach to overcome many of these various obstacles. A complex of gemcitabine (GEM) and hemoglobin S (HbS) was formulated, which self-polymerizes under hypoxic and acidic conditions. When polymerized, HbS has the potential to break the tumor stroma, decrease intratumoral pressure, and therefore improve the treatment efficacy of standard therapy. Intratumoral injection of HbS with a fluorescent small molecule surrogate for GEM into a pancreatic tumor xenograft resulted in improved dissemination of the small molecule throughout the pancreatic tumor. The self-polymerization of HbS + GEM was significantly more effective than either agent individually at decreasing tumor size in an in vivo PDAC mouse model. These findings would suggest a clinical benefit from delivering the complex of GEM and HbS via direct injection by endoscopic ultrasound (EUS). With such a treatment option, patients with locally advanced disease would have the potential to become surgical candidates, offering them a chance for cure

Computational Assessment of Potassium and Magnesium Ion Binding to a Buried Pocket in GTPase-Associating Center RNA

An experimentally well-studied model of RNA tertiary structures is a 58mer rRNA fragment, known as GTPase-associating center (GAC) RNA, in which a highly negative pocket walled by phosphate oxygen atoms is stabilized by a chelated cation. Although such deep pockets with more than one direct phosphate to ion chelation site normally include magnesium, as shown in one GAC crystal structure, another GAC crystal structure and solution experiments suggest potassium at this site. Both crystal structures also depict two magnesium ions directly bound to the phosphate groups comprising this controversial pocket. Here, we used classical molecular dynamics simulations as well as umbrella sampling to investigate the possibility of binding of potassium versus magnesium inside the pocket and to better characterize the chelation of one of the binding magnesium ions outside the pocket. The results support the preference of the pocket to accommodate potassium rather than magnesium and suggest that one of the closely binding magnesium ions can only bind at high magnesium concentrations, such as might be present during crystallization. This work illustrates the complementary utility of molecular modeling approaches with atomic-level detail in resolving discrepancies between conflicting experimental results