Early-stage human islet amyloid polypeptide aggregation: Mechanisms behind dimer formation.

Amyloid aggregates of human islet amyloid polypeptide (hIAPP or human amylin) have long been implicated in the development of type II diabetes. While hIAPP is known to aggregate into amyloid fibrils, it is the early-stage prefibrillar species that have been proposed to be cytotoxic. A detailed picture of the early-stage aggregation process and relevant intermediates would be valuable in the development of effective therapeutics. Here, we use atomistic molecular dynamics simulations with a combination of enhanced sampling methods to examine the formation of the hIAPP dimer in water. Bias-exchange metadynamics calculations reveal relative conformational stabilities of the hIAPP dimer. Finite temperature string method calculations identify pathways for dimer formation, along with relevant free energy barriers and intermediate structures. We show that the initial stages of dimerization involve crossing a substantial free energy barrier to form an intermediate structure exhibiting transient ß-sheet character, before proceeding to form an entropically stabilized dimer structure.

Membrane Permeation versus Amyloidogenicity: A Multitechnique Study of Islet Amyloid Polypeptide Interaction with Model Membranes.

Islet amyloid polypeptide (IAPP) is responsible for cell depletion in the pancreatic islets of Langherans, and for multiple pathological consequences encountered by patients suffering from type 2 Diabetes Mellitus. We have examined the amyloidogenicity and cytotoxic mechanisms of this peptide by investigating model-membrane permeation and structural effects of fragments of the human IAPP and several rat IAPP mutants. In vitro experiments and molecular dynamics simulations reveal distinct physical segregation, membrane permeation, and amyloid aggregation processes that are mediated by two separate regions of the peptide. These observations suggest a "detergent-like" mechanism, where lipids are extracted from the bilayer by the N-terminus of IAPP, and integrated into amyloid aggregates. The amyloidogenic aggregation would kinetically compete with the process of membrane permeation and, therefore, inhibit it. This hypothesis represents a new perspective on the mechanism underlying the membrane disruption by amyloid peptides, and could influence the development of new therapeutic strategies.

Structural motif of polyglutamine amyloid fibrils discerned with mixed-isotope infrared spectroscopy.

Polyglutamine (polyQ) sequences are found in a variety of proteins, and mutational expansion of the polyQ tract is associated with many neurodegenerative diseases. We study the amyloid fibril structure and aggregation kinetics of K2Q24K2W, a model polyQ sequence. Two structures have been proposed for amyloid fibrils formed by polyQ peptides. By forming fibrils composed of both (12)C and (13)C monomers, made possible by protein expression in Escherichia coli, we can restrict vibrational delocalization to measure 2D IR spectra of individual monomers within the fibrils. The spectra are consistent with a ß-turn structure in which each monomer forms an antiparallel hairpin and donates two strands to a single ß-sheet. Calculated spectra from atomistic molecular-dynamics simulations of the two proposed structures confirm the assignment. No spectroscopically distinct intermediates are observed in rapid-scan 2D IR kinetics measurements, suggesting that aggregation is highly cooperative. Although 2D IR spectroscopy has advantages over linear techniques, the isotope-mixing strategy will also be useful with standard Fourier transform IR spectroscopy.

An Analysis of Biomolecular Force Fields for Simulations of Polyglutamine in Solution.

Polyglutamine (polyQ) peptides are a useful model system for biophysical studies of protein folding and aggregation, both for their intriguing aggregation properties and their own relevance to human disease. The genetic expansion of a polyQ tract triggers the formation of amyloid aggregates associated with nine neurodegenerative diseases. Several clearly identifiable and separable factors, notably the length of the polyQ tract, influence the mechanism of aggregation, its associated kinetics, and the ensemble of structures formed. Atomistic simulations are well positioned to answer open questions regarding the thermodynamics and kinetics of polyQ folding and aggregation. The additional, explicit representation of water permits deeper investigation of the role of solvent dynamics, and it permits a direct comparison of simulation results with infrared spectroscopy experiments. The generation of meaningful simulation results hinges on satisfying two essential criteria: achieving sufficient conformational sampling to draw statistically valid conclusions, and accurately reproducing the intermolecular forces that govern system structure and dynamics. In this work, we examine the ability of 12 biomolecular force fields to reproduce the properties of a simple, 30-residue polyQ peptide (Q30) in explicit water. In addition to secondary and tertiary structure, we consider generic structural properties of polymers that provide additional dimensions for analysis of the highly degenerate disordered states of the molecule. We find that the 12 force fields produce a wide range of predictions. We identify AMBER ff99SB, AMBER ff99SB*, and OPLS-AA/L to be most suitable for studies of polyQ folding and aggregation.

Sculpting bespoke mountains: Determining free energies with basis expansions.

The intriguing behavior of a wide variety of physical systems, ranging from amorphous solids or glasses to proteins, is a direct manifestation of underlying free energy landscapes riddled with local minima separated by large barriers. Exploring such landscapes has arguably become one of statistical physics's great challenges. A new method is proposed here for uniform sampling of rugged free energy surfaces. The method, which relies on special Green's functions to approximate the Dirac delta function, improves significantly on existing simulation techniques by providing a boundary-agnostic approach that is capable of mapping complex features in multidimensional free energy surfaces. The usefulness of the proposed approach is established in the context of a simple model glass former and model proteins, demonstrating improved convergence and accuracy over existing methods.

Ribosome kinetics and aa-tRNA competition determine rate and fidelity of peptide synthesis.

It is generally accepted that the translation rate depends on the availability of cognate aa-tRNAs. In this study it is shown that the key factor that determines translation rate is the competition between near-cognate and cognate aa-tRNAs. The transport mechanism in the cytoplasm is diffusion, thus the competition between cognate, near-cognate and non-cognate aa-tRNAs to bind to the ribosome is a stochastic process. Two competition measures are introduced; C(i) and R(i) (i=1, 64) are quotients of the arrival frequencies of near-cognates vs. cognates and non-cognates vs. cognates, respectively. Furthermore, the reaction rates of bound cognates differ from those of bound near-cognates. If a near-cognate aa-tRNA binds to the A site of the ribosome, it may be rejected at the anti-codon recognition step or proofreading step or it may be accepted. Regardless of its fate, the near-cognates and non-cognates have caused delays of varying duration to the observed rate of translation. Rate constants have been measured at a temperature of 20 degrees C by (Gromadski, K.B., Rodnina, M.V., 2004. Kinetic determinants of high-fidelity tRNA discrimination on the ribosome. Mol. Cell 13, 191-200). These rate constants have been re-evaluated at 37 degrees C, using experimental data at 24.5 degrees C and 37 degrees C (Varenne, S., et al., 1984. Translation in a non-uniform process: effect of tRNA availability on the rate of elongation of nascent polypeptide chains. J. Mol. Biol. 180, 549-576). The key results of the study are: (i) the average time (at 37 degrees C) to add an amino acid, as defined by the ith codon, to the nascent peptide chain is: tau(i)=9.06+1.445x[10.48C(i)+0.5R(i)] (in ms); (ii) the misreading frequency is directly proportional to the near-cognate competition, E(i)=0.0009C(i); (iii) the competition from near-cognates, and not the availability of cognate aa-tRNAs, is the most important factor that determines the translation rate - the four codons with highest near-cognate competition (in the case of E. coli) are [GCC]>[CGG]>[AGG]>[GGA], which overlap only partially with the rarest codons: [AGG]<[CCA]<[GCC]<[CAC]; (iv) based on the kinetic rates at 37 degrees C, the average time to insert a cognate amino acid is 9.06ms and the average delay to process a near-cognate aa-tRNA is 10.45ms and (vii) the model also provides estimates of the vacancy times of the A site of the ribosome - an important factor in frameshifting.

A model of tuberculosis transmission and intervention strategies in an urban residential area.

The model herein aims to explore the dynamics of the spread of tuberculosis (TB) in an informal settlement or township. The population is divided into households of various sizes and also based on commuting status. The model dynamics distinguishes between three distinct social patterns: the exposure of commuters during travel, random diurnal interaction and familial exposure at night. Following the general SLIR models, the population is further segmented into susceptible (S), exposed/latently infected (L), active/infectious (I), and recovered (R) individuals. During the daytime, commuters travel on public transport, while non-commuters randomly interact in the community to mimic chance encounters with infectious persons. At night, each family interacts and sleeps together in the home. The risk of exposure to TB is based on the proximity, duration, and frequency of encounters with infectious persons. The model is applied to a hypothetical population to explore the effects of different intervention strategies including vaccination, wearing of masks during the commute, prophylactic treatment of latent infections and more effective case-finding and treatment. The most important findings of the model are: (1) members of larger families are responsible for more disease transmissions than those from smaller families, (2) daily commutes on public transport provide ideal conditions for transmission of the disease, (3) improved diagnosis and treatment has the greatest impact on the spread of the disease, and (4) detecting TB at the first clinic visit, when patients are still smear negative, is key.