Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing.

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

Pushing the Limits of Characterising a Weak Halogen Bond in Solution.

Detection and characterisation of very weak, non-covalent interactions in solution is inherently challenging. Low affinity, short complex lifetime and a constant battle against entropy brings even the most sensitive spectroscopic methods to their knees. Herein we introduce a strategy for the accurate experimental description of weak chemical forces in solution. Its scope is demonstrated by the detailed geometric and thermodynamic characterisation of the weak halogen bond of a non-fluorinated aryl iodide and an ether oxygen (0.6 kJ mol-1 ). Our approach makes use of the entropic advantage of studying a weak force intramolecularly, embedded into a cooperatively folding system, and of the combined use of NOE- and RDC-based ensemble analyses to accurately describe the orientation of the donor and acceptor sites. Thermodynamic constants (ΔG, ΔH and ΔS), describing the specific interaction, were derived from variable temperature chemical shift analysis. We present a methodology for the experimental investigation of remarkably weak halogen bonds and other related weak forces in solution, paving the way for their improved understanding and strategic use in chemistry and biology.

A Quantitative Analysis of Context-Dependent Remapping of Medial Frontal Cortex Neurons and Ensembles.

UNLABELLED: The frontal cortex has been implicated in a number of cognitive and motivational processes, but understanding how individual neurons contribute to these processes is particularly challenging as they respond to a broad array of events (multiplexing) in a manner that can be dynamically modulated by the task context, i.e., adaptive coding (Duncan, 2001). Fundamental questions remain, such as how the flexibility gained through these mechanisms is balanced by the need for consistency and how the ensembles of neurons are coherently shaped by task demands. In the present study, ensembles of medial frontal cortex neurons were recorded from rats trained to perform three different operant actions either in two different sequences or two different physical environments. Single neurons exhibited diverse mixtures of responsivity to each of the three actions and these mixtures were abruptly altered by context/sequence switches. Remarkably, the overall responsivity of the population remained highly consistent both within and between context/sequences because the gains versus losses were tightly balanced across neurons and across the three actions. These data are consistent with a reallocation mixture model in which individual neurons express unique mixtures of selectivity for different actions that become reallocated as task conditions change. However, because the allocations and reallocations are so well balanced across neurons, the population maintains a low but highly consistent response to all actions. The frontal cortex may therefore balance consistency with flexibility by having ensembles respond in a fixed way to task-relevant actions while abruptly reconfiguring single neurons to encode "actions in context." SIGNIFICANCE STATEMENT: Flexible modes of behavior involve performance of similar actions in contextually relevant ways. The present study quantified the changes in how rat medial frontal cortex neurons respond to the same actions when performed in different task contexts (sequences or environments). Most neurons altered the mixture of actions they were responsive to in different contexts or sequences. Nevertheless, the responsivity profile of the ensemble remained fixed as did the ability of the ensemble to differentiate between the three actions. These mechanisms may help to contextualize the manner in which common events are represented across different situations.

Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles.

Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and other methods to improve the accuracy of the complex structure. We explain not only the merits of these methods but also their limits of application and discuss some interaction terms which are not considered in the in silico methods. In silico screening and ensemble docking are useful when one focuses on obtaining the native complex structure (the most thermodynamically stable complex). Generalized ensemble method provides a free-energy landscape, which shows the distribution of the most stable complex structure and semi-stable ones in a conformational space. Also, barriers separating those stable structures are identified. A researcher should select one of the methods according to the research aim and depending on complexity of the molecular system to be studied.

Family Environment Variables as Predictors of School Absenteeism Severity at Multiple Levels: Ensemble and Classification and Regression Tree Analysis.

School attendance problems, including school absenteeism, are common to many students worldwide, and frameworks to better understand these heterogeneous students include multiple classes or tiers of intertwined risk factors as well as interventions. Recent studies have thus examined risk factors at varying levels of absenteeism severity to demarcate distinctions among these tiers. Prior studies in this regard have focused more on demographic and academic variables and less on family environment risk factors that are endemic to this population. The present study utilized ensemble and classification and regression tree analysis to identify potential family environment risk factors among youth (i.e., children and adolescents) at different levels of school absenteeism severity (i.e., 1 + %, 3 + %, 5 + %, 10 + %). Higher levels of absenteeism were also examined on an exploratory basis. Participants included 341 youth aged 5-17 years (M = 12.2; SD = 3.3) and their families from an outpatient therapy clinic (68.3%) and community (31.7%) setting, the latter from a family court and truancy diversion program cohort. Family environment risk factors tended to be more circumscribed and informative at higher levels of absenteeism, with greater diversity at lower levels. Higher levels of absenteeism appear more closely related to lower achievement orientation, active-recreational orientation, cohesion, and expressiveness, though several nuanced results were found as well. Absenteeism severity levels of 10-15% may be associated more with qualitative changes in family functioning. These data may support a Tier 2-Tier 3 distinction in this regard and may indicate the need for specific family-based intervention goals at higher levels of absenteeism severity.

Internalizing Symptoms as Predictors of School Absenteeism Severity at Multiple Levels: Ensemble and Classification and Regression Tree Analysis.

School attendance problems are highly prevalent worldwide, leading researchers to investigate many different risk factors for this population. Of considerable controversy is how internalizing behavior problems might help to distinguish different types of youth with school attendance problems. In addition, efforts are ongoing to identify the point at which children and adolescents move from appropriate school attendance to problematic school absenteeism. The present study utilized ensemble and classification and regression tree analysis to identify potential internalizing behavior risk factors among youth at different levels of school absenteeism severity (i.e., 1+%, 3+%, 5+%, 10+%). Higher levels of absenteeism were also examined on an exploratory basis. Participants included 160 youth aged 6-19 years (M = 13.7; SD = 2.9) and their families from an outpatient therapy clinic (39.4%) and community (60.6%) setting, the latter from a family court and truancy diversion program cohort. One particular item relating to lack of enjoyment was most predictive of absenteeism severity at different levels, though not among the highest levels. Other internalizing items were also predictive of various levels of absenteeism severity, but only in a negatively endorsed fashion. Internalizing symptoms of worry and fatigue tended to be endorsed higher across less severe and more severe absenteeism severity levels. A general expectation that predictors would tend to be more homogeneous at higher than lower levels of absenteeism severity was not generally supported. The results help confirm the difficulty of conceptualizing this population based on forms of behavior but may support the need for early warning sign screening for youth at risk for school attendance problems.

Deciphering the "Fuzzy" Interaction of FG Nucleoporins and Transport Factors Using Small-Angle Neutron Scattering.

The largely intrinsically disordered phenylalanine-glycine-rich nucleoporins (FG Nups) underline a selectivity mechanism that enables the rapid translocation of transport factors (TFs) through the nuclear pore complexes (NPCs). Conflicting models of NPC transport have assumed that FG Nups undergo different conformational transitions upon interacting with TFs. To selectively characterize conformational changes in FG Nups induced by TFs we performed small-angle neutron scattering (SANS) with contrast matching. Conformational-ensembles derived from SANS data indicated an increase in the overall size of FG Nups is associated with TF interaction. Moreover, the organization of the FG motif in the interacting state is consistent with prior experimental analyses defining that FG motifs undergo conformational restriction upon interacting with TFs. These results provide structural insights into a highly dynamic interaction and illustrate how functional disorder imparts rapid and selective FG Nup-TF interactions.