Нейросекреторная активность супраоптического ядра переднего гипоталамуса кроликов под действием транскутанной электростимуляции зрительного анализатора

На 8 кролях породи Метелик вивчали вплив непрямої черезшкірної електростимуляції зорового аналізатора на нейросекреторну активність магноцелюлярних клітин супраоптичного ядра переднього гіпоталамусу. На мікропрепаратах інтактних тварин переважали нейрони II морфофункціонального типу, що перебувають у стадії синтезу нейросекрету. Показано, що за дії электростимуляції спостерігається перерозподіл головних морфо-функціональних типів нейронів. Відзначено збільшення змісту клітин I й III типів, відповідно у стадіях спокою після виведення секрету й накопичення, що вказує на активацію процесів звільнення нейросекрету і його акумуляції. Виразність реакції нервової тканини однакова при силі стимулюючого струму 100 мкА й 300 мкА.The influence of indirect through-skin electrostimulation (different doses) of the optical analyser on neurosecretory activity of anterior hypothalamus magnocellular nucleus was stading during chronic experiment. The stady was carried out on rabbits. Five morphological types of neurons was exposed in the supraoptical nucleus of control animal groop: I type- phase of rest after neurosecrets leading, II- phase of synthesis, III- phase of accumulation, IV - leading phase, V - phase of degerneration, but neurons of II types was prevalenced (51%). The indirect electrostimulation of the optical analyser provokes quantitative changes of keeping same neurons types. The number of I and III types neurons increases (on 20% and 7%) . The kind of changes is indicative of electrostimulation activation influense on neurosecrets leading and accumulation. Expression of nervous tissue reaction was identical under different doses (100 mkA and 300 mkA) of afferent electrostimulation

An overview of data‐driven HADDOCK strategies in CAPRI rounds 38-45

Our information-driven docking approach HADDOCK has demonstrated a sustained performance since the start of its participation to CAPRI. This is due, in part, to its ability to integrate data into the modeling process, and to the robustness of its scoring function. We participated in CAPRI both as server and manual predictors. In CAPRI rounds 38-45, we have used various strategies depending on the available information. These ranged from imposing restraints to a few residues identified from literature as being important for the interaction, to binding pockets identified from homologous complexes or template-based refinement/CA-CA restraint-guided docking from identified templates. When relevant, symmetry restraints were used to limit the conformational sampling. We also tested for a large decamer target a new implementation of the MARTINI coarse-grained force field in HADDOCK. Overall, we obtained acceptable or better predictions for 13 and 11 server and manual submissions, respectively, out of the 22 interfaces. Our server performance (acceptable or higher-quality models when considering the top 10) was better (59%) than the manual (50%) one, in which we typically experiment with various combinations of protocols and data sources. Again, our simple scoring function based on a linear combination of intermolecular van der Waals and electrostatic energies and an empirical desolvation term demonstrated a good performance in the scoring experiment with a 63% success rate across all 22 interfaces. An analysis of model quality indicates that, while we are consistently performing well in generating acceptable models, there is room for improvement for generating/identifying higher quality models

Binding hotspots of BAZ2B bromodomain: Histone interaction revealed by solution NMR driven docking.

Bromodomains are epigenetic reader domains, which have come under increasing scrutiny both from academic and pharmaceutical research groups. Effective targeting of the BAZ2B bromodomain by small molecule inhibitors has been recently reported, but no structural information is yet available on the interaction with its natural binding partner, acetylated histone H3K14ac. We have assigned the BAZ2B bromodomain and studied its interaction with H3K14ac acetylated peptides by NMR spectroscopy using both chemical shift perturbation (CSP) data and clean chemical exchange (CLEANEX-PM) NMR experiments. The latter was used to characterize water molecules known to play an important role in mediating interactions. Besides the anticipated Kac binding site, we consistently found the bromodomain BC loop as hotspots for the interaction. This information was used to create a data-driven model for the complex using HADDOCK. Our findings provide both structure and dynamics characterization that will be useful in the quest for potent and selective inhibitors to probe the function of the BAZ2B bromodomain.This is the final published version of the article. It has been published by the American Chemical Society in Biochemistry. The article can be accessed on their website here: http://pubs.acs.org/doi/abs/10.1021/bi500909d. It is freely available under a CC BY licence

West-Life: A Virtual Research Environment for structural biology

The West-Life project (https://about.west-life.eu/)is a Horizon 2020 project funded by the European Commission to provide data processing and data management services for the international community of structural biologists, and in particular to support integrative experimental approaches within the field of structural biology. It has developed enhancements to existing web services for structure solution and analysis, created new pipelines to link these services into more complex higher-level workflows, and added new data management facilities. Through this work it has striven to make the benefits of European e-Infrastructures more accessible to life-science researchers in general and structural biologists in particular

A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 A° interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ,75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking

A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 A° interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ,75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking

Navigation guidée par le contenu pour l'exploration moléculaire.

International audienceno abstrac

Content and task based navigation for structural biology in 3D environments

International audienceno abstrac

Interactive Visual Analytics of Molecular Data in Immersive Environments via a Semantic Definition of the Content and the Context

International audienceno abstrac