Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Docking and molecular dynamics studies of peripheral site ligand–oximes as reactivators of sarin-inhibited human acetylcholinesterase

In the present work, we performed docking and molecular dynamics simulations studies on two groups of long-tailored oximes designed as peripheral site binders of acetylcholinesterase (AChE) and potential penetrators on the blood brain barrier. Our studies permitted to determine how the tails anchor in the peripheral site of sarin-inhibited human AChE, and which aminoacids are important to their stabilization. Also the energy values obtained in the docking studies corroborated quite well with the experimental results obtained before for these oximes.     

Caspase 3 activation and PARP cleavage in lymphocytes from newborn babies of diabetic mothers with unbalanced glycaemic control

Several epidemiological studies showed that gestational diabetes mellitus is the most frequent metabolic disorder of pregnancy, the pathogenesis of which has yet to be completely clarified. The aim of this study was to investigate the presence and processing of caspase 3 (Casp3) and poly(ADP‐ribose) polymerase 1 (PARP1) in cord blood lymphocytes as markers of apoptosis in relation to glycaemic control during intrauterine life. Our results showed a specific positive correlation between the levels of active Casp3 (17–19 kDa) and the inactive form of PARP1 (89 kDa) in lymphocytes isolated from newborn babies of diabetic women with unbalanced glycaemic control, with a direct correlation between the activation of casp3 and the inactivation of PARP1, that makes lymphocytes unresponsive towards lipopolysaccharide stimulation, highlighting an altered functional response. Besides more studies are required to fully correlate the activation of the apoptotic process during the intrauterine life with the foetal health later in life, our study indicates that a cord blood lymphocyte, an easily accessible source, is informative about the activation of apoptotic stimuli in circulating cells of newborn babies in relation to the glycaemic control reached by the mother during pregnancy. Copyright © 2013 John Wiley & Sons, Ltd.     

Influence of Action-Effect Associations Acquired by Ideomotor Learning on Imitation

According to the ideomotor theory, actions are represented in terms of their perceptual effects, offering a solution for the correspondence problem of imitation (how to translate the observed action into a corresponding motor output). This effect-based coding of action is assumed to be acquired through action-effect learning. Accordingly, performing an action leads to the integration of the perceptual codes of the action effects with the motor commands that brought them about. While ideomotor theory is invoked to account for imitation, the influence of action-effect learning on imitative behavior remains unexplored. In two experiments, imitative performance was measured in a reaction time task following a phase of action-effect acquisition. During action-effect acquisition, participants freely executed a finger movement (index or little finger lifting), and then observed a similar (compatible learning) or a different (incompatible learning) movement. In Experiment 1, finger movements of left and right hands were presented as action-effects during acquisition. In Experiment 2, only right-hand finger movements were presented during action-effect acquisition and in the imitation task the observed hands were oriented orthogonally to participants’ hands in order to avoid spatial congruency effects. Experiments 1 and 2 showed that imitative performance was improved after compatible learning, compared to incompatible learning. In Experiment 2, although action-effect learning involved perception of finger movements of right hand only, imitative capabilities of right- and left-hand finger movements were equally affected. These results indicate that an observed movement stimulus processed as the effect of an action can later prime execution of that action, confirming the ideomotor approach to imitation. We further discuss these findings in relation to previous studies of action-effect learning and in the framework of current ideomotor approaches to imitation.     

Reliably Detecting Clinically Important Variants Requires Both Combined Variant Calls and Optimized Filtering Strategies

A diversity of tools is available for identification of variants from genome sequence data. Given the current complexity of incorporating external software into a genome analysis infrastructure, a tendency exists to rely on the results from a single tool alone. The quality of the output variant calls is highly variable however, depending on factors such as sequence library quality as well as the choice of short-read aligner, variant caller, and variant caller filtering strategy. Here we present a two-part study first using the high quality ‘genome in a bottle’ reference set to demonstrate the significant impact the choice of aligner, variant caller, and variant caller filtering strategy has on overall variant call quality and further how certain variant callers outperform others with increased sample contamination, an important consideration when analyzing sequenced cancer samples. This analysis confirms previous work showing that combining variant calls of multiple tools results in the best quality resultant variant set, for either specificity or sensitivity, depending on whether the intersection or union, of all variant calls is used respectively. Second, we analyze a melanoma cell line derived from a control lymphocyte sample to determine whether software choices affect the detection of clinically important melanoma risk-factor variants finding that only one of the three such variants is unanimously detected under all conditions. Finally, we describe a cogent strategy for implementing a clinical variant detection pipeline; a strategy that requires careful software selection, variant caller filtering optimizing, and combined variant calls in order to effectively minimize false negative variants. While implementing such features represents an increase in complexity and computation the results offer indisputable improvements in data quality.