In Silico Analysis of the Apolipoprotein E and the Amyloid β Peptide Interaction: Misfolding Induced by Frustration of the Salt Bridge Network

The relationship between Apolipoprotein E (ApoE) and the aggregation processes of the amyloid β (Aβ) peptide has been shown to be crucial for Alzheimer's disease (AD). The presence of the ApoE4 isoform is considered to be a contributing risk factor for AD. However, the detailed molecular properties of ApoE4 interacting with the Aβ peptide are unknown, although various mechanisms have been proposed to explain the physiological and pathological role of this relationship. Here, computer simulations have been used to investigate the process of Aβ interaction with the N-terminal domain of the human ApoE isoforms (ApoE2, ApoE3 and ApoE4). Molecular docking combined with molecular dynamics simulations have been undertaken to determine the Aβ peptide binding sites and the relative stability of binding to each of the ApoE isoforms. Our results show that from the several ApoE isoforms investigated, only ApoE4 presents a misfolded intermediate when bound to Aβ. Moreover, the initial α-helix used as the Aβ peptide model structure also becomes unstructured due to the interaction with ApoE4. These structural changes appear to be related to a rearrangement of the salt bridge network in ApoE4, for which we propose a model. It seems plausible that ApoE4 in its partially unfolded state is incapable of performing the clearance of Aβ, thereby promoting amyloid forming processes. Hence, the proposed model can be used to identify potential drug binding sites in the ApoE4-Aβ complex, where the interaction between the two molecules can be inhibited

Confab - Systematic generation of diverse low-energy conformers

<p>Abstract</p> <p>Background</p> <p>Many computational chemistry analyses require the generation of conformers, either on-the-fly, or in advance. We present Confab, an open source command-line application for the systematic generation of low-energy conformers according to a diversity criterion.</p> <p>Results</p> <p>Confab generates conformations using the 'torsion driving approach' which involves iterating systematically through a set of allowed torsion angles for each rotatable bond. Energy is assessed using the MMFF94 forcefield. Diversity is measured using the heavy-atom root-mean-square deviation (RMSD) relative to conformers already stored. We investigated the recovery of crystal structures for a dataset of 1000 ligands from the Protein Data Bank with fewer than 1 million conformations. Confab can recover 97% of the molecules to within 1.5 Å at a diversity level of 1.5 Å and an energy cutoff of 50 kcal/mol.</p> <p>Conclusions</p> <p>Confab is available from <url>http://confab.googlecode.com</url>.</p

Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction

Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represented as a machine learning problem, where neural networks are used to learn the native-like features of protein structures using a set of positive and negative training examples. A set of native protein structures provides the positive training examples, while negative training examples are simulated decoy structures obtained by reversing the sequences of native structures. Various features are extracted from the training dataset of positive and negative examples and used as inputs to the neural networks.Results: Results have shown that the best performing neural network is the one that uses input information comprising of PSI-BLAST [1] profiles of residue pairs, pairwise distance and the relative solvent accessibilities of the residues. This neural network is the best among all methods tested in discriminating the native structure from a set of decoys for all decoy datasets tested. Conclusion: This method is demonstrated to be viable, and furthermore evolutionary information is successfully used in the neural networks to improve decoy discrimination

A Simple and Effective Method for Construction of Escherichia coli Strains Proficient for Genome Engineering

Multiplex genome engineering is a standalone recombineering tool for large-scale programming and accelerated evolution of cells. However, this advanced genome engineering technique has been limited to use in selected bacterial strains. We developed a simple and effective strain-independent method for effective genome engineering in Escherichia coli. The method involves introducing a suicide plasmid carrying the l Red recombination system into the mutS gene. The suicide plasmid can be excised from the chromosome via selection in the absence of antibiotics, thus allowing transient inactivation of the mismatch repair system during genome engineering. In addition, we developed another suicide plasmid that enables integration of large DNA fragments into the lacZ genomic locus. These features enable this system to be applied in the exploitation of the benefits of genome engineering in synthetic biology, as well as the metabolic engineering of different strains of E. coli.open7

A tryptophan-rich peptide acts as a transcription activation domain

<p>Abstract</p> <p>Background</p> <p>Eukaryotic transcription activators normally consist of a sequence-specific DNA-binding domain (DBD) and a transcription activation domain (AD). While many sequence patterns and motifs have been defined for DBDs, ADs do not share easily recognizable motifs or structures.</p> <p>Results</p> <p>We report herein that the N-terminal domain of yeast valyl-tRNA synthetase can function as an AD when fused to a DNA-binding protein, LexA, and turn on reporter genes with distinct LexA-responsive promoters. The transcriptional activity was mainly attributed to a five-residue peptide, WYDWW, near the C-terminus of the N domain. Remarkably, the pentapeptide <it>per se </it>retained much of the transcriptional activity. Mutations which substituted tryptophan residues for both of the non-tryptophan residues in the pentapeptide (resulting in W₅) significantly enhanced its activity (~1.8-fold), while mutations which substituted aromatic residues with alanine residues severely impaired its activity. Accordingly, a much more active peptide, pentatryptophan (W₇), was produced, which elicited ~3-fold higher activity than that of the native pentapeptide and the N domain. Further study indicated that W₇mediates transcription activation through interacting with the general transcription factor, TFIIB.</p> <p>Conclusions</p> <p>Since W₇shares no sequence homology or features with any known transcription activators, it may represent a novel class of AD.</p

Spatial chemical distance based on atomic property fields

Similarity of compound chemical structures often leads to close pharmacological profiles, including binding to the same protein targets. The opposite, however, is not always true, as distinct chemical scaffolds can exhibit similar pharmacology as well. Therefore, relying on chemical similarity to known binders in search for novel chemicals targeting the same protein artificially narrows down the results and makes lead hopping impossible. In this study we attempt to design a compound similarity/distance measure that better captures structural aspects of their pharmacology and molecular interactions. The measure is based on our recently published method for compound spatial alignment with atomic property fields as a generalized 3D pharmacophoric potential. We optimized contributions of different atomic properties for better discrimination of compound pairs with the same pharmacology from those with different pharmacology using Partial Least Squares regression. Our proposed similarity measure was then tested for its ability to discriminate pharmacologically similar pairs from decoys on a large diverse dataset of 115 protein–ligand complexes. Compared to 2D Tanimoto and Shape Tanimoto approaches, our new approach led to improvement in the area under the receiver operating characteristic curve values in 66 and 58% of domains respectively. The improvement was particularly high for the previously problematic cases (weak performance of the 2D Tanimoto and Shape Tanimoto measures) with original AUC values below 0.8. In fact for these cases we obtained improvement in 86% of domains compare to 2D Tanimoto measure and 85% compare to Shape Tanimoto measure. The proposed spatial chemical distance measure can be used in virtual ligand screening

Whole Transcriptome Sequencing Reveals Gene Expression and Splicing Differences in Brain Regions Affected by Alzheimer's Disease

Recent studies strongly indicate that aberrations in the control of gene expression might contribute to the initiation and progression of Alzheimer's disease (AD). In particular, alternative splicing has been suggested to play a role in spontaneous cases of AD. Previous transcriptome profiling of AD models and patient samples using microarrays delivered conflicting results. This study provides, for the first time, transcriptomic analysis for distinct regions of the AD brain using RNA-Seq next-generation sequencing technology. Illumina RNA-Seq analysis was used to survey transcriptome profiles from total brain, frontal and temporal lobe of healthy and AD post-mortem tissue. We quantified gene expression levels, splicing isoforms and alternative transcript start sites. Gene Ontology term enrichment analysis revealed an overrepresentation of genes associated with a neuron's cytological structure and synapse function in AD brain samples. Analysis of the temporal lobe with the Cufflinks tool revealed that transcriptional isoforms of the apolipoprotein E gene, APOE-001, -002 and -005, are under the control of different promoters in normal and AD brain tissue. We also observed differing expression levels of APOE-001 and -002 splice variants in the AD temporal lobe. Our results indicate that alternative splicing and promoter usage of the APOE gene in AD brain tissue might reflect the progression of neurodegeneration