Combination of Neutron Scattering and Molecular Dynamics to Determine Internal Motions in Biomolecules

Abstract

The forms and frequencies of atomic dynamics on the pico- and nanosecond timescales are accessible experimentally using incoherent neutron scattering. Molecular dynamics simulations cover the same space and time domains and neutron scattering intensities can be calculated from the simulations for direct comparison with experiment. To illustrate the complementarity of neutron scattering and molecular dynamics we examine measured and simulation-derived elastic incoherent scattering profiles from myoglobin and from the crystalline alanine dipeptide. Elastic incoherent scattering gives information on the geometry of the volume accessible to the atoms in the samples. The simulation-derived dipeptide elastic scattering profiles are in reasonable accord with experiment, deviations being due to the sampling limitations in the simulations and experimental detector normalisation procedures. The simulated dynamics is decomposed, revealing characteristic profiles due to rotational diffusional and translational vibrational motions of the methyl groups. In myoglobin, for which the timescale of the simulation matches more closely that accessible to the experiment, good agreement is seen for the elastic incoherent structure factor. This indicates that the space sampled by the hydrogen atoms in the protein on the timescale <100 ps is well represented by the simulation. Part of the helix atom fluctuations can be described in terms of rigid helix motions.     

Differential expression of interferon responsive genes in rodent models of transmissible spongiform encephalopathy disease

Background

Alzheimer's disease (AD) is characterized by a decline in cognitive function and accumulation of amyloid-β peptide (Aβ) in extracellular plaques. Mutations in amyloid precursor protein (APP) and presenilins alter APP metabolism resulting in accumulation of Aβ42, a peptide essential for the formation of amyloid deposits and proposed to initiate the cascade leading to AD. However, the role of Aβ40, the more prevalent Aβ peptide secreted by cells and a major component of cerebral Aβ deposits, is less clear. In this study, virally-mediated gene transfer was used to selectively increase hippocampal levels of human Aβ42 and Aβ40 in adult Wistar rats, allowing examination of the contribution of each to the cognitive deficits and pathology seen in AD.

Results

Adeno-associated viral (AAV) vectors encoding BRI-Aβ cDNAs were generated resulting in high-level hippocampal expression and secretion of the specific encoded Aβ peptide. As a comparison the effect of AAV-mediated overexpression of APPsw was also examined. Animals were tested for development of learning and memory deficits (open field, Morris water maze, passive avoidance, novel object recognition) three months after infusion of AAV. A range of impairments was found, with the most pronounced deficits observed in animals co-injected with both AAV-BRI-Aβ40 and AAV-BRI-Aβ42. Brain tissue was analyzed by ELISA and immunohistochemistry to quantify levels of detergent soluble and insoluble Aβ peptides. BRI-Aβ42 and the combination of BRI-Aβ40+42 overexpression resulted in elevated levels of detergent-insoluble Aβ. No significant increase in detergent-insoluble Aβ was seen in the rats expressing APPsw or BRI-Aβ40. No pathological features were noted in any rats, except the AAV-BRI-Aβ42 rats which showed focal, amorphous, Thioflavin-negative Aβ42 deposits.

Conclusion

The results show that AAV-mediated gene transfer is a valuable tool to model aspects of AD pathology in vivo, and demonstrate that whilst expression of Aβ42 alone is sufficient to initiate Aβ deposition, both Aβ40 and Aβ42 may contribute to cognitive deficits.     

Purification and characterization of hexahistidine-tagged cyclohexanone monooxygenase expressed in Saccharomyces cerevisiae and Escherichia coli

Cyclohexanone monooxygenase (CMO) is a soluble flavoenzyme originally isolated from Acinetobacter spp. which carries out Baeyer-Villiger reactions with cyclic ketone substrates. In the present study we cloned the Acinetobacter CMO gene and modified it for facile purification from heterologous expression systems by incorporation of a His(6)-tag at its C-terminus. A single purification step employing metal (Ni(2+))-affinity column chromatography provided essentially homogeneous enzyme in yields of 69-72%. The properties of the purified, recombinant enzymes (rCMO) were compared with that of native CMO (nCMO) isolated from Acinetobacter cultures grown in the presence of cyclohexanone. The specific activities of His(6)-tagged rCMO and nCMO toward their index substrate, cyclohexanone, were similar and ranged from 14 to 20 micromol/min/mg. nCMO and rCMO from the Escherichia coli expression system exhibited molecular masses, determined by electrospray mass spectrometry, of 60,800 and 61,615 Da, respectively, an increase for the recombinant enzyme equivalent to the mass of the His(6)-tag. However, rCMO expressed in Saccharomyces cerevisiae consistently exhibited a mass some 50 Da larger than rCMO expressed in bacteria. Edman degradation confirmed that rCMO purified from the E. coli system and nCMO shared the same N-terminal sequence, whereas no sequence information could be obtained for rCMO expressed in yeast. Therefore, the yeast-expressed enzyme possesses an additional posttranslational modification(s), possibly acylation, at the N-terminus. Expression in E. coli is the preferred system for future site-directed mutagenesis studies and crystallization efforts.     

Efficacy of hyaluronic acid binding assay in selecting motile spermatozoa with normal morphology at high magnification

Background  

The present study aimed to evaluate the efficacy of the hyaluronic acid (HA) binding assay in the selection of motile spermatozoa with normal morphology at high magnification (8400x).     

Active-site characteristics of CYP2C19 and CYP2C9 probed with hydantoin and barbiturate inhibitors

Three series of N-3 alkyl substituted phenytoin, nirvanol, and barbiturate derivatives were synthesized and their inhibitor potencies were tested against recombinant CYP2C19 and CYP2C9 to probe the interaction of these ligands with the active sites of these enzymes. All compounds were found to be competitive inhibitors of both enzymes, although the degree of inhibitory potency was generally much greater towards CYP2C19. Inhibitor stereochemistry did not markedly influence K(i) towards CYP2C9, and log P adequately predicted inhibitor potency for this enzyme. In contrast, stereochemistry was an important factor in determining inhibitor potency towards CYP2C19. (S)-(+)-N-3-Benzylnirvanol and (R)-(-)-N-3-benzylphenobarbital emerged as the most potent and selective CYP2C19 inhibitors, with K(i) values of < 250nM--at least two orders of magnitude greater inhibitor potency than towards CYP2C9. Both inhibitors were metabolized preferentially at their C-5 phenyl substituents, indicating that CYP2C19 prefers to orient the N-3 substituents away from the active oxygen species. These features were incorporated into expanded CoMFA models for CYP2C9, and a new, validated CoMFA model for CYP2C19.     

Routes to improving the reliability of low level DNA analysis using real-time PCR

Background  

Accurate quantification of DNA using quantitative real-time PCR at low levels is increasingly important for clinical, environmental and forensic applications. At low concentration levels (here referring to under 100 target copies) DNA quantification is sensitive to losses during preparation, and suffers from appreciable valid non-detection rates for sampling reasons. This paper reports studies on a real-time quantitative PCR assay targeting a region of the human SRY gene over a concentration range of 0.5 to 1000 target copies. The effects of different sample preparation and calibration methods on quantitative accuracy were investigated.     

Improvements in protein secondary structure prediction by an enhanced neural network

Computational neural networks have recently been used to predict the mapping between protein sequence and secondary structure. They have proven adequate for determining the first-order dependence between these two sets, but have, until now, been unable to garner higher-order information that helps determine secondary structure. By adding neural network units that detect periodicities in the input sequence, we have modestly increased the secondary structure prediction accuracy. The use of tertiary structural class causes a marked increase in accuracy. The best case prediction was 79% for the class of all-alpha proteins. A scheme for employing neural networks to validate and refine structural hypotheses is proposed. The operational difficulties of applying a learning algorithm to a dataset where sequence heterogeneity is under-represented and where local and global effects are inadequately partitioned are discussed.