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Brigita Urbanc

Publications and source records attributed to Brigita Urbanc.

7 recordsLinked to original sources

Ab initio discrete molecular dynamics approach to protein folding and aggregation.

Understanding the toxicity of amyloidogenic protein aggregates and designing therapeutic approaches require the knowledge of their structure at atomic resolution. Although solid-state NMR, X-ray diffraction, and other experimental techniques are capable of discerning the protein fibrillar structure, determining the structures of early aggregates, called oligomers, is a challenging experimental task. Computational studies by all-atom molecular dynamics, which provides a complete description of a protein in the solvent, are typically limited to study folding of smaller protein or aggregation of a small number of short protein fragments. We review an efficient ab initio computer simulation approach to protein folding and aggregation using discrete molecular dynamics (DMD) in combination with several coarse-grained protein models and implicit solvent. This approach involves different complexity levels in both the protein model and the interparticle interactions. Starting from the simplest protein model with minimal interactions, and gradually increasing its complexity, while guided by in vitro findings, we can systematically select the key features of the protein model and interactions that drive protein folding and aggregation. Because the method used in this DMD approach does not require any knowledge of the native or any other state of the protein, it can be applied to study degenerative disorders associated with protein misfolding and aberrant protein aggregation. The choice of the coarse-grained model depends on the complexity of the protein and specific questions to be addressed, which are mostly suggested by in vitro findings. Thus, we illustrate our approach on amyloid beta-protein (Abeta) associated with Alzheimer's disease (AD). Despite the simplifications introduced in the DMD approach, the predicted Abeta conformations are in agreement with existing experimental data. The in silico findings also provide further insights into the structure and dynamics of Abeta folding and oligomer formation that are amenable to in vitro testing.

Amyloid beta-Peptides↗

Elucidating amyloid beta-protein folding and assembly: A multidisciplinary approach.

Oligomeric, neurotoxic amyloid protein assemblies are thought to be causative agents in Alzheimer's and other neurodegenerative diseases. Development of oligomer-specific therapeutic agents requires a mechanistic understanding of the oligomerization process. This is a daunting task because amyloidogenic protein oligomers often are metastable and comprise structurally heterogeneous populations in equilibrium with monomers and fibrils. A single methodological approach cannot elucidate the entire protein assembly process. An integrated multidisciplinary program is required. We discuss here the synergistic application of in hydro, in vacuo, and in silico methods to the study of the amyloid beta-protein, the key pathogenetic agent in Alzheimer's disease.

Amino Acid Sequence↗

Computer simulations of Alzheimer's amyloid beta-protein folding and assembly.

Pathological folding and aggregation of the amyloid beta-protein (Abeta) are widely perceived as central to understanding Alzheimer's disease (AD) at the molecular level. Experimental approaches to study Abeta self-assembly are limited, because most relevant aggregates are quasi-stable and inhomogeneous. In contrast, simulations can provide significant insights into the problem, including specific sites in the molecule that would be attractive for drug targeting and details of the assembly pathways leading to the production of toxic assemblies. Here we review computer simulation approaches to understanding the structural biology of Abeta. We discuss the ways in which these simulations help guide experimental work, and in turn, how experimental results guide the development of theoretical and simulation approaches that may be of general utility in understanding pathologic protein folding and assembly.

Alzheimer Disease↗

Solvent and mutation effects on the nucleation of amyloid beta-protein folding.

Experimental evidence suggests that the folding and aggregation of the amyloid beta-protein (Abeta) into oligomers is a key pathogenetic event in Alzheimer's disease. Inhibiting the pathologic folding and oligomerization of Abeta could be effective in the prevention and treatment of Alzheimer's disease. Here, using all-atom molecular dynamics simulations in explicit solvent, we probe the initial stages of folding of a decapeptide segment of Abeta, Abeta(21-30), shown experimentally to nucleate the folding process. In addition, we examine the folding of a homologous decapeptide containing an amino acid substitution linked to hereditary cerebral hemorrhage with amyloidosis-Dutch type, [Gln-22]Abeta(21-30). We find that: (i) when the decapeptide is in water, hydrophobic interactions and transient salt bridges between Lys-28 and either Glu-22 or Asp-23 are important in the formation of a loop in the Val-24-Lys-28 region of the wild-type decapeptide; (ii) in the presence of salt ions, salt bridges play a more prominent role in the stabilization of the loop; (iii) in water with a reduced density, the decapeptide forms a helix, indicating the sensitivity of folding to different aqueous environments; and (iv) the "Dutch" peptide in water, in contrast to the wild-type peptide, fails to form a long-lived Val-24-Lys-28 loop, suggesting that loop stability is a critical factor in determining whether Abeta folds into pathologic structures.

Amyloid beta-Peptides↗

Folding events in the 21-30 region of amyloid beta-protein (Abeta) studied in silico.

Oligomeric assemblies of the amyloid beta-protein (Abeta) have been implicated in the pathogenesis of Alzheimer's disease as a primary source of neurotoxicity. Recent in vitro studies have suggested that a 10-residue segment, Ala-21-Ala-30, forms a turn-like structure that nucleates the folding of the full-length Abeta. To gain a mechanistic insight, we simulated Abeta(21-30) folding by using a discrete molecular dynamics algorithm and a united-atom model incorporating implicit solvent and a variable electrostatic interaction strength (EIS). We found that Abeta(21-30) folds into a loop-like conformation driven by an effective hydrophobic attraction between Val-24 and the butyl portion of the Lys-28 side chain. At medium EIS [1.5 kcal/mol (1 cal = 4.18 J)], unfolded conformations almost disappear, in agreement with experimental observations. Under optimal conditions for folding, Glu-22 and Asp-23 form transient electrostatic interactions (EI) with Lys-28 that stabilize the loop conformations. Glu-22-Lys-28 is the most favored interaction. High EIS, as it occurs in the interior of proteins and aggregates, destabilizes the packing of Val-24 and Lys-28. Analysis of the unpacked structures reveals strong EI with predominance of the Asp-23-Lys-28 interaction, in agreement with studies of molecular modeling of full-length Abeta fibrils. The binary nature of the EI involving Lys-28 provides a mechanistic explanation for the linkage of amino acid substitutions at Glu-22 with Alzheimer's disease and cerebral amyloid angiopathy. Substitutions may alter the frequency of Glu-22 or Asp-23 involvement in contact formation and affect the stability of the folding nucleus formed in the Abeta(21-30) region.

Algorithms↗

A statistically based density map method for identification and quantification of regional differences in microcolumnarity in the monkey brain.

We present a statistical density map method derived from condensed matter physics to quantify microcolumns, the fundamental computational unit of the cerebral cortex. This method provides measures for microcolumnar strength, width, spacing, length, and periodicity. We applied this method to Nissl-stained 30 microm thick frozen sections from areas 46, TE, and TL of rhesus monkey brains, areas that differ visually in microcolumnarity and are associated with different cognitive functions. Our results indicate that microcolumns in these areas are similar in width, spacing, and periodicity, but are stronger (possess a higher neuronal density) in area TE, as compared to areas TL and 46. We modeled the effect of section orientation on microcolumnar spacing and demonstrated that this method provides an adequate estimate of spacing. We also modeled disruption of microcolumnarity by performing simulations that randomly displace neurons and demonstrated that displacements of only one neuronal diameter effectively eliminate microcolumnar organization. These results indicate that our density map method is sensitive enough to detect and quantify subtle differences in microcolumnar organization that may occur in the context of development, aging, and neuropathology, as well as between areas and species.

Animals↗

Age-related reduction in microcolumnar structure in area 46 of the rhesus monkey correlates with behavioral decline.

Many age-related declines in cognitive function are attributed to the prefrontal cortex, area 46 being especially critical. Yet in normal aging, studies indicate that neurons are not lost in area 46, suggesting that impairments result from more subtle processes. One cortical feature that is functionally important, but that has not been examined in normal aging because of a lack of efficient quantitative methods, is the vertical arrangement of neurons into microcolumns, a fundamental computational unit of the cortex. By using a density-map method derived from condensed-matter physics, we quantified microcolumns in area 46 of seven young and seven aged rhesus monkeys that had been cognitively tested. This analysis demonstrated that there is no age-related reduction in total neuronal density or in microcolumn width, length, or periodicity. There was, however, a statistically significant decrease in the strength of microcolumns, indicating microcolumnar disorganization. This reduction in strength was significantly correlated with age-related cognitive decline on tests of spatial working memory and recognition memory independent of the effect of age. Modeling demonstrated that random neuron displacements of approximately 30% of a neuronal diameter (<3 mum) produced the observed reduction in strength. Hence, it is possible that, with changes in dendrites and myelinated axons, subtle displacements of neurons occur that alter microcolumnar structure and correlate with age-induced dysfunction. Therefore, quantitative measurement of microcolumnar structure may provide a sensitive morphological method to assay microcolumnar function in aging and other conditions.

Aging↗