MpUL-multi: Software for Calculation of Amyloid Fibril Mass per Unit Length from TB-TEM Images.

Structure determination for amyloid fibrils presents many challenges due to the high variability exhibited by fibrils and heterogeneous morphologies present, even in single samples. Mass per unit length (MPL) estimates can be used to differentiate amyloid fibril morphologies and provide orthogonal evidence for helical symmetry parameters determined by other methods. In addition, MPL data can provide insight on the arrangement of subunits in a fibril, especially for more complex fibrils assembled with multiple parallel copies of the asymmetric unit or multiple twisted protofilaments. By detecting only scattered electrons, which serve as a relative measure of total scattering, and therefore protein mass, dark field imaging gives an approximation of the total mass of protein present in any given length of fibril. When compared with a standard of known MPL, such as Tobacco Mosaic Virus (TMV), MPL of the fibrils in question can be determined. The program suite MpUL-multi was written for rapid semi-automated processing of TB-TEM dark field data acquired using this method. A graphical user interface allows for simple designation of fibrils and standards. A second program averages intensities from multiple TMV molecules for accurate standard determination, makes multiple measurements along a given fibril, and calculates the MPL

Prenatal Exposure to Gabapentin Alters the Development of Ventral Midbrain Dopaminergic Neurons.

Background: Gabapentin is widely prescribed as an off-label drug for the treatment of various diseases, including drug and alcohol addiction. Approximately 83-95% of the usage of gabapentin is off-label, accounting for more than 90% of its sales in the market, which indicates an alarming situation of drug abuse. Such misuse of gabapentin has serious negative consequences. The safety of the use of gabapentin in pregnant women has always been a serious issue, as gabapentin can cross placental barriers. The impact of gabapentin on brain development in the fetus is not sufficiently investigated, which poses difficulties in clinical decisions regarding prescriptions. Methods: The consequences effect of prenatal gabapentin exposure on the development of ventral midbrain dopaminergic neurons were investigated using three-dimensional neuronal cell cultures. Time-mated Swiss mice were used to isolate embryos. The ventral third of the midbrain was removed and used to enrich the dopaminergic population in 3D cell cultures that were subsequently exposed to gabapentin. The effects of gabapentin on the viability, ATP release, morphogenesis and genes expression of ventral midbrain dopaminergic neurons were investigated. Results: Gabapentin treatment at the therapeutic level interfered with the neurogenesis and morphogenesis of vmDA neurons in the fetal brain by causing changes in morphology and alterations in the expression of key developmental genes, such as Nurr1, Chl1, En1, Bdnf, Drd2, and Pitx3. The TH + total neurite length and dominant neurite length were significantly altered. We also found that gabapentin could halt the metabolic state of these neuronal cells by blocking the generation of ATP. Conclusion: Our findings clearly indicate that gabapentin hampers the morphogenesis and development of dopaminergic neurons. This implies that the use of gabapentin could lead to serious complications in child-bearing women. Therefore, caution must be exercised in clinical decisions regarding the prescription of gabapentin in pregnant women

The Influence of Prenatal Exposure to Quetiapine Fumarate on the Development of Dopaminergic Neurons in the Ventral Midbrain of Mouse Embryos.

The effects of second-generation antipsychotics on prenatal neurodevelopment, apoptotic neurodegeneration, and postnatal developmental delays have been poorly investigated. Even at standard doses, the use of quetiapine fumarate (QEPF) in pregnant women might be detrimental to fetal development. We used primary mouse embryonic neurons to evaluate the disruption of morphogenesis and differentiation of ventral midbrain (VM) neurons after exposure to QEPF. The dopaminergic VM neurons were deliberately targeted due to their roles in cognition, motor activity, and behavior. The results revealed that exposure to QEPF during early brain development decreased the effects of the dopaminergic lineage-related genes Tyrosine hydroxylase(Th), Dopamine receptor D1 (Drd1), Dopamine transporter (Dat), LIM homeobox transcription factor 1 alfa (Lmx1a), and Cell adhesion molecule L1 (Chl1), and the senescent dopaminergic gene Pituitary homeobox 3 (Pitx3). In contrast, Brain derived neurotrophic factor (Bdnf) and Nuclear receptor-related 1 (Nurr1) expressions were significantly upregulated. Interestingly, QEPF had variable effects on the development of non-dopaminergic neurons in VM. An optimal dose of QEPF (10 µM) was found to insignificantly affect the viability of neurons isolated from the VM. It also instigated a non-significant reduction in adenosine triphosphate formation in these neuronal populations. Exposure to QEPF during the early stages of brain development could also hinder the formation of VM and their structural phenotypes. These findings could aid therapeutic decision-making when prescribing 2nd generation antipsychotics in pregnant populations

De Novo Design and Experimental Characterization of Ultrashort Self-Associating Peptides

Self-association is a common phenomenon in biology and one that can have positive and negative impacts, from the construction of the architectural cytoskeleton of cells to the formation of fibrils in amyloid diseases. Understanding the nature and mechanisms of self-association is important for modulating these systems and in creating biologically-inspired materials. Here, we present a two-stage de novo peptide design framework that can generate novel self-associating peptide systems. The first stage uses a simulated multimeric template structure as input into the optimization-based Sequence Selection to generate low potential energy sequences. The second stage is a computational validation procedure that calculates Fold Specificity and/or Approximate Association Affinity (K*association) based on metrics that we have devised for multimeric systems. This framework was applied to the design of self-associating tripeptides using the known self-associating tripeptide, Ac-IVD, as a structural template. Six computationally predicted tripeptides (Ac-LVE, Ac-YYD, Ac-LLE, Ac-YLD, Ac-MYD, Ac-VIE) were chosen for experimental validation in order to illustrate the self-association outcomes predicted by the three metrics. Self-association and electron microscopy studies revealed that Ac-LLE formed bead-like microstructures, Ac-LVE and Ac-YYD formed fibrillar aggregates, Ac-VIE and Ac-MYD formed hydrogels, and Ac-YLD crystallized under ambient conditions. An X-ray crystallographic study was carried out on a single crystal of Ac-YLD, which revealed that each molecule adopts a β-strand conformation that stack together to form parallel β-sheets. As an additional validation of the approach, the hydrogel-forming sequences of Ac-MYD and Ac-VIE were shuffled. The shuffled sequences were computationally predicted to have lower K*association values and were experimentally verified to not form hydrogels. This illustrates the robustness of the framework in predicting self-associating tripeptides. We expect that this enhanced multimeric de novo peptide design framework will find future application in creating novel self-associating peptides based on unnatural amino acids, and inhibitor peptides of detrimental self-aggregating biological proteins