A study of educational leadership preparation concerning the assistant principal : perspectives of Missouri principals and assistant principals

Abstract from short.pdf file.Dissertation supervisor: Dr. Cynthia MacGregor.Includes vita.It is unclear if the initial preparation of educational leaders, in relation to the role of assistant principals (APs), has kept pace with growing demands associated with the position. Little research exists specifically addressing the initial developmental preparation of APs. Elements of a needs assessment and program evaluation combine to build infrastructure for a conceptual framework to guide this study. A mixed method design for this study was determined to be the best method in which to provide answers concerning the proposed research questions. Participants consisted of lead and assistant principals from school districts across Missouri. Quantitative and qualitative data was analyzed for trends. Quantitative and qualitative data was compared to one another in order to attain a thorough and comprehensive examination of collected data.Includes bibliographical references (pages 149-161)

Influence of Magnesium Ions on Duplex DNA Structural, Dynamic, and Solvation Properties

Molecular dynamics (MD) simulations were performed on the DNA dodecamer comprising the EcoRI recognition site in aqueous solution. Three simulations, each of 1 ns duration, were performed that included no salt, 0.26 M Mg+2, and 0.50 M Mg2+ and 0.59 M Cl-. The simulations yielded stable structures that were intermediate to the canonical A and B conformations of DNA. Certain aspects of the MD solution structures are similar to the EcoRI dodecamer crystal structure. Interactions of the phosphates with Mg2+ occur primarily with Mg+2 fully hydrated, although direct ion−phosphate contact pairs are observed. The presence of Mg2+ leads to decreased root mean square fluctuations of the DNA phosphate backbone and the waters hydrating the DNA major groove and phosphate backbone. Calculations also indicate a small increase in hydration of the minor groove and phosphate backbone due to the presence of Mg2+. These results suggest that decreased water mobility rather than decreased hydration number is responsible for Mg2+-induced dehydration of DNA associated with decreased water activity

CHARMM Drude Polarizable Force Field for Aldopentofuranoses and Methyl-aldopentofuranosides

An empirical all-atom CHARMM polarizable force filed for aldopentofuranoses and methyl-aldopentofuranosides based on the classical Drude oscillator is presented. A single electrostatic model is developed for eight different diastereoisomers of aldopentofuranoses by optimizing the existing electrostatic and bonded parameters as transferred from ethers, alcohols, and hexopyranoses to reproduce quantum mechanical (QM) dipole moments, furanose–water interaction energies and conformational energies. Optimization of selected electrostatic and dihedral parameters was performed to generate a model for methyl-aldopentofuranosides. Accuracy of the model was tested by reproducing experimental data for crystal intramolecular geometries and lattice unit cell parameters, aqueous phase densities, and ring pucker and exocyclic rotamer populations as obtained from NMR experiments. In most cases the model is found to reproduce both QM data and experimental observables in an excellent manner, whereas for the remainder the level of agreement is in the satisfactory regimen. In aqueous phase simulations the monosaccharides have significantly enhanced dipoles as compared to the gas phase. The final model from this study is transferrable for future studies on carbohydrates and can be used with the existing CHARMM Drude polarizable force field for biomolecules

Balancing Group I Monatomic Ion–Polar Compound Interactions for Condensed Phase Simulation in the Polarizable Drude Force Field

Molecular dynamics (MD) simulations are a commonly used method for investigating molecular behavior at the atomic level. Achieving reliable MD simulation results necessitates the use of an accurate force field. In the present work, we present a protocol to enhance the quality of group 1 monatomic ions (specifically Li+, Na+, K+, Rb+, and Cs+) with respect to their interactions with common polar model compounds in biomolecules in condensed phases in the context of the Drude polarizable force field. Instead of adjusting preexisting individual parameters for ions, model compounds, and water, we employ atom-pair specific Lennard-Jones (LJ) (known as NBFIX in CHARMM) and through-space Thole dipole screening (NBTHOLE) terms to fine-tune the balance of ion–model compound, ion–water, and model compound–water interactions. This involved establishing a protocol for the optimization of NBFIX and NBTHOLE parameters targeting the difference between molecular mechanical (MM) and quantum mechanical (QM) potential energy scans (PES). It is shown that targeting PES involving complexes that include multiple model compounds and/or ions as trimers and tetramers yields parameters that produce condensed phase properties in agreement with experimental data. Validation of this protocol involved the reproduction of experimental thermodynamic benchmarks, including solvation free energies of ions in methanol and N-methylacetamide, osmotic pressures, ionic conductivities, and diffusion coefficients within the condensed phase. These results show the importance of including more complex ion–model compound complexes beyond dimers in the QM target data to account for many-body effects during parameter fitting. The presented parameters represent a significant refinement of the Drude polarizable force field, which will lead to improved accuracy for modeling ion–biomolecular interactions

Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules

Membrane permeability of drug molecules plays a significant role in the development of new therapeutic agents. Accordingly, methods to predict the passive permeability of drug candidates during a medicinal chemistry campaign offer the potential to accelerate the drug design process. In this work, we combine the physics-based site identification by ligand competitive saturation (SILCS) method and data-driven artificial intelligence (AI) to create a high-throughput predictive model for the passive permeability of druglike molecules. In this study, we present a comparative analysis of four regression models to predict membrane permeabilities of small druglike molecules; of the tested models, Random Forest was the most predictive yielding an R2 of 0.81 for the independent data set. The input feature vector used to train the developed prediction model includes absolute free energy profiles of ligands through a POPC-cholesterol bilayer based on ligand grid free energy (LGFE) profiles obtained from the SILCS approach. The use of the membrane free energy profiles from SILCS offers information on the physical forces contributing to ligand permeability, while the use of AI yields a more predictive model trained on experimental PAMPA permeability data for a collection of 229 molecules. This combination allows for rapid estimations of ligand permeability at a level of accuracy beyond currently available predictive models while offering insights into the contributions of the functional groups in the ligands to the permeability barrier, thereby offering quantitative information to facilitate rational ligand design

Conformational Sampling of Oligosaccharides Using Hamiltonian Replica Exchange with Two-Dimensional Dihedral Biasing Potentials and the Weighted Histogram Analysis Method (WHAM)

Oligosaccharides and polysaccharides exert numerous functional roles in biology through their structural diversity and conformational properties. To investigate their conformational properties using computational methods, Hamiltonian replica exchange (H-REX) combined with two-dimensional grid-based correction maps as biasing potentials (bpCMAP) significantly improves the sampling efficiency about glycosidic linkages. In the current study, we extend the application of H-REX with bpCMAP to complex saccharides and establish systematic procedures for bpCMAP construction, determination of replica distribution, and data analysis. Our main findings are that (1) the bpCMAP for each type of glycosidic linkage can be constructed from the corresponding disaccharide using gas-phase umbrella sampling simulations, (2) the replica distribution can be conveniently determined following the exact definition of the average acceptance ratio based on the assigned distribution of biasing potentials, and (3) the extracted free energy surface (or potential of mean force (PMF)) can be improved using the weighted histogram analysis method (WHAM) allowing for the inclusion of data from the excited state replicas in the calculated probability distribution. The method is applied to a branched N-glycan found on the HIV gp120 protein, and a linear N-glycan. Considering the general importance of N-glycans and the wide appreciation of the sampling problem, the present method represents an efficient procedure for the conformational sampling of complex oligo- and polysaccharides under explicit solvent conditions. More generally, the use of WHAM is anticipated to be of general utility for the calculation of PMFs from H-REX simulations in a wide range of macromolecular systems

Conformational Properties of the Deoxyribose and Ribose Moieties of Nucleic Acids: A Quantum Mechanical Study

The present work analyzes the intrinsic conformational energetics associated with the puckering of the deoxyribose and ribose sugars in nucleic acids using high-level ab initio quantum mechanical calculations. A variety of model compounds have been designed to define the minimal structural unit suitable to model the sugar moiety in nucleic acids. Results suggest that all the structural features of a nucleoside are required to model the sugar moiety of nucleic acids. Stuctures calculated at the MP2 level of theory are in close agreement with experimental structural information. In deoxyribose, the south pucker (B form of double helices) is intrinsically favored over the north pucker (A form of double helices) by ∼1.0 kcal/mol. In contrast, for ribose, with torsion ε in an RNA-like conformation, the north pucker is favored over the south pucker by ∼2.0 kcal/mol. For both the deoxyribose and ribose of nucleic acids, the lowest energy barrier between the north and south puckers is >4.0 kcal/mol. The present calculations suggest that crossing this barrier may involve a decrease in the amplitude of the furanose ring. Implications of these results with respect to nucleic acid stucture and dynamics are discussed

Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules

Membrane permeability of drug molecules plays a significant role in the development of new therapeutic agents. Accordingly, methods to predict the passive permeability of drug candidates during a medicinal chemistry campaign offer the potential to accelerate the drug design process. In this work, we combine the physics-based site identification by ligand competitive saturation (SILCS) method and data-driven artificial intelligence (AI) to create a high-throughput predictive model for the passive permeability of druglike molecules. In this study, we present a comparative analysis of four regression models to predict membrane permeabilities of small druglike molecules; of the tested models, Random Forest was the most predictive yielding an R2 of 0.81 for the independent data set. The input feature vector used to train the developed prediction model includes absolute free energy profiles of ligands through a POPC-cholesterol bilayer based on ligand grid free energy (LGFE) profiles obtained from the SILCS approach. The use of the membrane free energy profiles from SILCS offers information on the physical forces contributing to ligand permeability, while the use of AI yields a more predictive model trained on experimental PAMPA permeability data for a collection of 229 molecules. This combination allows for rapid estimations of ligand permeability at a level of accuracy beyond currently available predictive models while offering insights into the contributions of the functional groups in the ligands to the permeability barrier, thereby offering quantitative information to facilitate rational ligand design

FFParam-v2.0: A Comprehensive Tool for CHARMM Additive and Drude Polarizable Force-Field Parameter Optimization and Validation

Developing production quality CHARMM force-field (FF) parameters is a very detailed process involving a variety of calculations, many of which are specific for the molecule of interest. The first version of FFParam was developed as a standalone Python package designed for the optimization of electrostatic and bonded parameters of the CHARMM additive and polarizable Drude FFs by using quantum mechanical (QM) target data. The new version of FFParam has multiple new capabilities for FF parameter optimization and validation, with an emphasis on the ability to use condensed-phase target data in optimization. FFParam-v2 allows optimization of Lennard-Jones (LJ) parameters using potential energy scans of interactions between selected atoms in a molecule and noble gases, viz., He and Ne, and through condensed-phase calculations, from which experimental observables such as heats of vaporization and free energies of solvation may be obtained. This functionality serves as a gold standard for both optimizing parameters and validating the performance of the final parameters. A new bonded parameter optimization algorithm has been introduced to account for simultaneously optimizing multiple molecules sharing parameters. FFParam-v2 also supports the comparison of normal modes and the potential energy distribution of internal coordinates towards each normal mode obtained from QM and molecular mechanics calculations. Such comparison capability is vital to validate the balance among various bonded parameters that contribute to the complex normal modes of molecules. User interaction has been extended beyond the original graphical user interface to include command-line interface capabilities that allow for integration of FFParam in workflows, thereby facilitating the automation of parameter optimization. With these new functionalities, FFParam is a more comprehensive parameter optimization tool for both beginners and advanced users

<i>Ab Initio</i> Calculations on the Use of Helium and Neon as Probes of the van der Waals Surfaces of Molecules

Interaction energies and geometries for van der Waals (vdW) complexes from ab initio calculations must take into account limitations associated with basis set flexibility, electron correlation, and basis set superposition error (BSSE). Presented are a variety of ab initio calculations on the helium, neon, and methane homodimers and the helium−methane and neon−methane dimers. Systematic changes in polarization and diffuse functions, the treatment of electron correlation, and the influence of BSSE correction were undertaken as a function of interaction distance. Calculations on the helium and neon homodimers were compared with available empirical data. Analysis of the contribution of the BSSE correction using the function counterpoise method indicates increases in minimum energy interaction distance when BSSE corrections are included. The presence of diffuse functions minimize the magnitude of the BSSE. The present calculations lead to the selection of the MP3/6-311++G(3d,3p) without BSSE correction as an appropriate level of theory for the calculation of relative interaction energies and geometries for different orientations between either helium or neon and molecules. An exponent for an sp diffuse function on helium was determined as part of the present study