T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics

Ratio and proportion: mapping the conceptual field

Ratio and proportion are central to the middle school mathematics curriculum, but the full scope and extent of this topic is not described in detail in most state curriculum standards. In this thesis, numerous textbooks from the past one hundred years are sampled, along with several state‟s standards and the Louisiana state comprehensive curriculum. These sources are used to develop a more defined map of ratio and proportion as a conceptual field and a structured collection of problems. Proportional reasoning involves three phases: 1) the comparison of two magnitudes, expressed as ratio or rate, 2) the comparison of two ratios, called a proportion, and 3) the expression of proportional relationships as functions. As we follow this progression, proportional reasoning tasks change accordingly, through ratios, rates, missing-value proportions, similarity situations, and ultimately functions that express proportionality

Molecular dynamics simulations of complex systems including HIV-1 protease

Advances in supercomputer architectures have resulted in a situation where many scienti�fic codes are used on systems whose performance characteristics di�ffer considerably from the platform they were developed and optimised for. This is particularly apparent in the realm of Grid computing, where new technologies such as MPIg allow researchers to connect geographically disparate resources together into virtual parallel machines. Finding ways to exploit these new resources efficiently is necessary both to extract the maximum bene�fit from them, and to provide the enticing possibility of enabling new science. In this thesis, an existing general purpose molecular dynamics code (LAMMPS) is extended to allow it to perform more efficiently in a geographically distributed Grid environment showing considerable performance gains as a result. The technique of replica exchange molecular dynamics is discussed along with its applicability to the Grid model and its bene�fits with respect to increasing sampling of configurational space. The dynamics of two sub-structures of the HIV-1 protease (known as the flaps) are investigated using replica exchange molecular dynamics in LAMMPS showing considerable movement that would have been difficult to investigate by traditional methods. To complement this, a study was carried out investigating the use of computational tools to calculate binding affinity between HIV-1 protease mutants and the drug lopinavir in comparison with results derived experimentally by other research groups. The results demonstrate some promise for computational methods in helping to determine the most eff�ective course of treatment for patients in the future

Rapid, Accurate, Precise and Reproducible Binding Affinity Calculations using Ensembles of Molecular Dynamics Simulations

The accurate prediction of the binding affinities of ligands to proteins is a major goal in drug discovery and personalised medicine. The use of in silico methods to predict binding affinities has been largely confined to academic research until recently, primarily due to the lack of their reproducibility, as well as unaffordably longer time to solution. In this thesis, I mainly describe the ensemble based molecular dynamics approaches, ESMACS and TIES, that provide a route to reliable predictions of free energies meeting the requirements of speed, accuracy, precision and reliability. The performance of both these methods when applied to a diverse set of protein targets and ligands is reported. The results are in very good agreement with experimental data while the methods are repeatable by construction. Statistical uncertainties of the order of 0.5 kcal/mol or less are achieved. These methods have been further extended to incorporate enhanced sampling techniques based on replica exchange (also known as parallel tempering) to handle situations where conformational sampling is difficult using standard molecular dynamics. A critical assessment of free energy estimators like MBAR has been made for their application in binding affinity prediction. The methodologies described are shown to have a positive impact in the drug design process in the pharmaceutical domain as well as in personalised medicine, with concomitant potential major industrial and societal impact. Finally, our automated workflow, comprising the Binding Affinity Calculator (BAC) together with the FabSim are described. These tools and services help us complete the entire execution in 8 hours or less, depending on the high performance architecture and hardware available

Amyloid Fibril Nucleation In Reverse Micelles

The 40-residue amyloid beta protein (Abeta) is the unstructured cleavage product of a common membrane protein that is produced in large quantities, but normally cleared from the brain before it exerts any apparent toxicity. Under some conditions, however, it undergoes a conformational change and aggregates into fibrils. These fibrils then coalesce into amyloid plaques, which are the pathognomonic brain lesions of Alzheimer‘s disease. The plaques are centers of active oxidative stress and neuronal death, so the conditions under which fibrils form is of high interest. When Abeta is encapsulated in a reverse micelle, its infrared spectrum indicates that it spontaneously adopts a fibril-like structure, which is remarkable because only one Abeta strand is present in each reverse micelle. That observation suggests that some aspect of the reverse micelle environment such as crowding, dehydration, proximity to a membrane, or high ionic strength may induce Abeta to nucleate amyloid fibril formation. Therefore, an understanding of the factors that induce Abeta to adopt fibril-like structure in reverse micelles may reveal what causes amyloid fibrils to form in Alzheimer\u27s disease. Molecular dynamics simulations of Abeta in reverse micelles have been performed to identify and understand these factors. Results indicate that Abeta side chains penetrate the reverse micelle surface, anchoring the peptide in the membrane. Other interactions between peptide and membrane stabilize intrachain hydrogen bond formation and secondary structure. These interactions may be important factors in the formation of amyloid fibrils and the pathogenesis of Alzheimer‘s disease

National Educators' Workshop: Update 95. Standard Experiments in Engineering Materials Science and Technology

This document contains a collection of experiments presented and demonstrated at the National Educators' Workshop: Update 95. The experiments related to the nature and properties of engineering materials and provided information to assist in teaching about materials in the education community