Allosteric Control of a Plant Receptor Kinase through S-Glutathionylation

Growing evidence supports the importance of protein S-glutathionylation as a regulatory post-translational modification with functional consequences for proteins. Discoveries of redox-state-dependent protein kinase S-glutathionylation have fueled discussion of redox-sensitive signaling. Following previously published experimental evidence for S-glutathionylation induced deactivation of the Arabidopsis thaliana kinase BRASSINOSTEROID INSENSITIVE 1-ASSOCIATED RECEPTOR-LIKE KINASE 1 (BAK1), we investigated the consequences of S-glutathionylation on the equilibrium conformational ensemble of BAK1 using all-atom molecular dynamics simulations. We found that glutathionylation of C408 allosterically destabilizes the active-like state of BAK1 and stabilizes an inactive conformation known to recur in protein kinases. Glutathionylation of C408 also has structural consequences throughout the BAK1 kinase domain, whereas glutathionylation of C353 in the N-lobe and C374 near the ATP-binding site have few notable effects on BAK1 compared with the unmodified protein. Our results suggest an allosteric mechanism for inhibition of BAK1 by C408 S-glutathionylation, and more generally, support the notion of protein kinase S-glutathionylation as a means of redox signaling in plant cells.

Redundant and regulatory roles for Toll-like receptors in Leishmania infection

Toll-like receptors (TLRs) are germline-encoded, non-clonal innate immune receptors, which are often the first receptors to recognize the molecular patterns on pathogens. Therefore, the immune response initiated by TLRs has far-reaching consequences on the outcome of an infection. As soon as the cell surface TLRs and other receptors recognize a pathogen, the pathogen is phagocytosed. Inclusion of TLRs in the phagosome results in quicker phagosomal maturation and stronger adaptive immune response, as TLRs influence co-stimulatory molecule expression and determinant selection by major histocompatibility complex (MHC) class II and MHC class I for cross-presentation. The signals delivered by the TCR-peptide-MHC complex and co-stimulatory molecules are indispensable for optimal T cell activation. In addition, the cytokines induced by TLRs can skew the differentiation of activated T cells to different effector T cell subsets. However, the potential of TLRs to influence adaptive immune response into different patterns is severely restricted by multiple factors: gross specificity for the molecular patterns, lack of receptor rearrangements, sharing of limited number of adaptors that assemble signalling complexes and redundancy in ligand recognition. These features of apparent redundancy and regulation in the functioning of TLRs characterize them as important and probable contributory factors in the resistance or susceptibility to an infection.

Enhanced unbiased sampling of protein dynamics using evolutionary coupling information

One of the major challenges in atomistic simulations of proteins is efficient sampling of pathways associated with rare conformational transitions. Recent developments in statistical methods for computation of direct evolutionary couplings between amino acids within and across polypeptide chains have allowed for inference of native residue contacts, informing accurate prediction of protein folds and multimeric structures. In this study, we assess the use of distances between evolutionarily coupled residues as natural choices for reaction coordinates which can be incorporated into Markov state model-based adaptive sampling schemes and potentially used to predict not only functional conformations but also pathways of conformational change, protein folding, and protein-protein association. We demonstrate the utility of evolutionary couplings in sampling and predicting activation pathways of the β 2-adrenergic receptor (β 2-AR), folding of the FiP35 WW domain, and dimerization of the E. coli molybdopterin synthase subunits. We find that the time required for β 2-AR activation and folding of the WW domain are greatly diminished using evolutionary couplings-guided adaptive sampling. Additionally, we were able to identify putative molybdopterin synthase association pathways and near-crystal structure complexes from protein-protein association simulations.

Dynamic-template-directed multiscale assembly for large-area coating of highly-aligned conjugated polymer thin films

Solution processable semiconducting polymers have been under intense investigations due to their diverse applications from printed electronics to biomedical devices. However, controlling the macromolecular assembly across length scales during solution coating remains a key challenge, largely due to the disparity in timescales of polymer assembly and high-throughput printing/coating. Herein we propose the concept of dynamic templating to expedite polymer nucleation and the ensuing assembly process, inspired by biomineralization templates capable of surface reconfiguration. Molecular dynamic simulations reveal that surface reconfigurability is key to promoting template–polymer interactions, thereby lowering polymer nucleation barrier. Employing ionic-liquid-based dynamic template during meniscus-guided coating results in highly aligned, highly crystalline donor–acceptor polymer thin films over large area (>1 cm²) and promoted charge transport along both the polymer backbone and the π–π stacking direction in field-effect transistors. We further demonstrate that the charge transport anisotropy can be reversed by tuning the degree of polymer backbone alignment.

Controlling macromolecular assembly across length scales during solution coating of semiconducting polymers is still a challenge. Here the authors show a biomineralization inspired dynamic templating method that expedites polymer nucleation and assembly which allows for surface reconfiguration.

Markov State Models and tICA Reveal a Nonnative Folding Nucleus in Simulations of NuG2

After reanalyzing simulations of NuG2-a designed mutant of protein G-generated by Lindorff-Larsen et al. with time structure-based independent components analysis and Markov state models as well as performing 1.5 ms of additional sampling on Folding@home, we found an intermediate with a register-shift in one of the β-sheets that was visited along a minor folding pathway. The minor folding pathway was initiated by the register-shifted sheet, which is composed of solely nonnative contacts, suggesting that for some peptides, nonnative contacts can lead to productive folding events. To confirm this experimentally, we suggest a mutational strategy for stabilizing the register shift, as well as an infrared experiment that could observe the nonnative folding nucleus.

Molecular dynamics simulations reveal the conformational dynamics of Arabidopsis thaliana BRI1 and BAK1 receptor-like kinases

The structural motifs responsible for activation and regulation of eukaryotic protein kinases in animals have been studied extensively in recent years, and a coherent picture of their activation mechanisms has begun to emerge. In contrast, non-animal eukaryotic protein kinases are not as well understood from a structural perspective, representing a large knowledge gap. To this end, we investigated the conformational dynamics of two key Arabidopsis thaliana receptor-like kinases, brassinosteroid-insensitive 1 (BRI1) and BRI1-associated kinase 1 (BAK1), through extensive molecular dynamics simulations of their fully phosphorylated kinase domains. Molecular dynamics simulations calculate the motion of each atom in a protein based on classical approximations of interatomic forces, giving researchers insight into protein function at unparalleled spatial and temporal resolutions. We found that in an otherwise "active" BAK1 the αC helix is highly disordered, a hallmark of deactivation, whereas the BRI1 αC helix is moderately disordered and displays swinging behavior similar to numerous animal kinases. An analysis of all known sequences in the A. thaliana kinome found that αC helix disorder may be a common feature of plant kinases.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Pupillometric Assessment of Cholinergic Functioning in People with Alzheimer Disease: A Study from India

Background

Diagnosis of Alzheimer disease is mainly clinical, based on longitudinal history and clinical criteria due to lack of specific biochemical tests and neuroimaging studies. Deficient central cholinergic activity of AD pathology is said to be reflected as decreased peripheral cholinergic activity. Assessing peripheral cholinergic function with pupillometer for diagnostic and prognostic purpose may be beneficial, as it may be a non-invasive, acceptable, and easily administered diagnostic tool if proven so.

Method

This is a single point case control pilot study with sample size of 45 (25 AD patient and 20 controls). CAMDEX-R based interview, HMSE, and DSM-IV criteria were used for detailed assessment and diagnosis. The pupillometric parameters (Horizontal and vertical diameters of pupil) were measured by Oasis Colvard pupillometer (SKU-0401A) under three conditions namely after 5 minute of dark adaptation in dark room (PD-5min-DA i.e. Baseline PD); after 5 minutes (PD-5min-T) and 15 minutes (PD-15min-T) of instillation of 2–3 drops of 1.0% Tropicamide.

Results

There was no difference in baseline pupil diameter (horizontal + vertical) of AD patients and age matched healthy controls. 1% tropicamide induced significant increment in pupil diameters from baseline to after 5 (‘PD-5min-T’) and 15 minutes (‘PD-15min-T’) of its instillation in both AD patients and age matched healthy controls. But tropicamide induced increment in pupil diameters were approximately equal in cases and controls.

Conclusion

The study did not find the role of 1% tropicamide induced pupillary hypersensitivity in AD patients for diagnostic purpose.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

Application of Hidden Markov Models in Biomolecular Simulations

Hidden Markov models (HMMs) provide a framework to analyze large trajectories of biomolecular simulation datasets. HMMs decompose the conformational space of a biological molecule into finite number of states that interconvert among each other with certain rates. HMMs simplify long timescale trajectories for human comprehension, and allow comparison of simulations with experimental data. In this chapter, we provide an overview of building HMMs for analyzing bimolecular simulation datasets. We demonstrate the procedure for building a Hidden Markov model for Met-enkephalin peptide simulation dataset and compare the timescales of the process.

Pricing policy for declining demand using item preservation technology

We have designed an inventory model for seasonal products in which deterioration can be controlled by item preservation technology investment. Demand for the product is considered price sensitive and decreases linearly. This study has shown that the profit is a concave function of optimal selling price, replenishment time and preservation cost parameter. We simultaneously determined the optimal selling price of the product, the replenishment cycle and the cost of item preservation technology. Additionally, this study has shown that there exists an optimal selling price and optimal preservation investment to maximize the profit for every business set-up. Finally, the model is illustrated by numerical examples and sensitive analysis of the optimal solution with respect to major parameters.

Transition path theory analysis of c-Src kinase activation

Nonreceptor tyrosine kinases of the Src family are large multidomain allosteric proteins that are crucial to cellular signaling pathways. In a previous study, we generated a Markov state model (MSM) to simulate the activation of c-Src catalytic domain, used as a prototypical tyrosine kinase. The long-time kinetics of transition predicted by the MSM was in agreement with experimental observations. In the present study, we apply the framework of transition path theory (TPT) to the previously constructed MSM to characterize the main features of the activation pathway. The analysis indicates that the activating transition, in which the activation loop first opens up followed by an inward rotation of the αC-helix, takes place via a dense set of intermediate microstates distributed within a fairly broad "transition tube" in a multidimensional conformational subspace connecting the two end-point conformations. Multiple microstates with negligible equilibrium probabilities carry a large transition flux associated with the activating transition, which explains why extensive conformational sampling is necessary to accurately determine the kinetics of activation. Our results suggest that the combination of MSM with TPT provides an effective framework to represent conformational transitions in complex biomolecular systems.

Conserve Water: A Method for the Analysis of Solvent in Molecular Dynamics

Molecular dynamics with explicit solvent is favored for its ability to more correctly simulate aqueous biological processes and has become routine thanks to increasingly powerful computational resources. However, analysis techniques including Markov state models (MSMs) ignore solvent atoms and focus solely on solute coordinates despite solvent being implicated in myriad biological phenomena. We present a unified framework called "solvent-shells featurization" for including solvent degrees of freedom in analysis and show that this method produces better models. We apply this method to simulations of dewetting in the two-domain protein BphC to generate a predictive MSM and identify functional water molecules. Furthermore, the proposed methodology could be easily extended for building MSMs of any systems with indistinguishable components.

Conformational heterogeneity of the calmodulin binding interface

Calmodulin (CaM) is a ubiquitous Ca(2+) sensor and a crucial signalling hub in many pathways aberrantly activated in disease. However, the mechanistic basis of its ability to bind diverse signalling molecules including G-protein-coupled receptors, ion channels and kinases remains poorly understood. Here we harness the high resolution of molecular dynamics simulations and the analytical power of Markov state models to dissect the molecular underpinnings of CaM binding diversity. Our computational model indicates that in the absence of Ca(2+), sub-states in the folded ensemble of CaM's C-terminal domain present chemically and sterically distinct topologies that may facilitate conformational selection. Furthermore, we find that local unfolding is off-pathway for the exchange process relevant for peptide binding, in contrast to prior hypotheses that unfolding might account for binding diversity. Finally, our model predicts a novel binding interface that is well-populated in the Ca(2+)-bound regime and, thus, a candidate for pharmacological intervention.

Post-traumatic cervical spondyloptosis: A rare entity with multiple management options

Post-traumatic cervical spondyloptosis is a rare condition associated with high energy injuries, and to our knowledge only case reports are available. There are no universally accepted treatment paradigms for these cases and management is individualised according to the case and surgeon preference. We retrospectively analysed our management and clinical outcomes of this condition. From January 2007 to August 2014 we treated eight patients with cervical spondyloptosis at our institute. Only two patients had no neurological deficits; all the remaining patients had partial cord injury. Seven were treated surgically with preoperative traction followed by anterior cervical discectomy and fusion with fixation in three patients, and combined anterior and posterior fusion and fixation in four. Depending on the presence of anterior compression by a disc an anterior first or posterior first approach was advocated. All four combined anterior and posterior fusion and fixation patients needed to be turned more than once (540°). There was no neurological deterioration in any of the patients, as they either improved or remained stable neurologically. Post-traumatic cervical spondyloptosis is a challenging entity to manage. Surgery can be done safely with good clinical and radiological outcome and needs to be tailored to the individual patient.

Complex pathways in folding of protein G explored by simulation and experiment

The B1 domain of protein G has been a classic model system of folding for decades, the subject of numerous experimental and computational studies. Most of the experimental work has focused on whether the protein folds via an intermediate, but the evidence is mostly limited to relatively slow kinetic observations with a few structural probes. In this work we observe folding on the submillisecond timescale with microfluidic mixers using a variety of probes including tryptophan fluorescence, circular dichroism, and photochemical oxidation. We find that each probe yields different kinetics and compare these observations with a Markov State Model constructed from large-scale molecular dynamics simulations and find a complex network of states that yield different kinetics for different observables. We conclude that there are many folding pathways before the final folding step and that these paths do not have large free energy barriers.