Pitfalls of the Martini Model

R.A. thanks The Netherlands Organisation for Scientific Research NWO (Graduate Programme Advanced Materials, No. 022.005.006) for financial support. S.T. thanks the European Commission for financial support via a Marie Skłodowska-Curie Actions Individual Fellowship (MicroMod-PSII, grant agreement 748895).The computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.publishersversionpublishe

Modelling structural properties of cyanine dye nanotubes at coarse-grained level

Self-assembly is a ubiquitous process spanning from biomolecular aggregates to nanomaterials. Even though the resulting aggregates can be studied through experimental techniques, the dynamic pathways of the process and the molecular details of the final structures are not necessarily easy to resolve. Consequently, rational design of self-assembling aggregates and their properties remains extremely challenging. At the same time, modelling the self-assembly with computational methods is not trivial, because its spatio-temporal scales are usually beyond the limits of all-atom based simulations. The use of coarse-grained (CG) models can alleviate this limitation, but usually suffers from the lack of optimised parameters for the molecular constituents. In this work, we describe the procedure of parametrizing a CG Martini model for a cyanine dye (C8S3) that self-assembles into hollow double-walled nanotubes. First, we optimised the model based on quantum mechanics calculations and all-atom reference simulations, in combination with available experimental data. Then, we conducted random self-assembly simulations, and the performance of our model was tested on preformed assemblies. Our simulations provide information on the time-dependent local arrangement of this cyanine dye, when aggregates are being formed. Furthermore, we provide guidelines for designing and optimising parameters for similar self-assembling nanomaterials

Martini 3 Coarse-Grained Force Field:Small Molecules

The recent re-parametrization of the Martini coarse-grained force field, Martini 3, improved the accuracy of the model in predicting molecular packing and interactions in molecular dynamics simulations. Here, we describe how small molecules can be accurately parametrized within the Martini 3 framework and present a database of validated small molecule models. We pay particular attention to the description of aliphatic and aromatic ring-like structures, which are ubiquitous in small molecules such as solvents and drugs or in building blocks constituting macromolecules such as proteins and synthetic polymers. In Martini 3, ring-like structures are described by models that use higher resolution coarse-grained particles (small and tiny particles). As such, the present database constitutes one of the cornerstones of the calibration of the new Martini 3 small and tiny particle sizes. The models show excellent partitioning behavior and solvent properties. Miscibility trends between different bulk phases are also captured, completing the set of thermodynamic properties considered during the parametrization. We also show how the new bead sizes allow for a good representation of molecular volume, which translates into better structural properties such as stacking distances. We further present design strategies to build Martini 3 models for small molecules of increased complexity

Associations between movement behaviours and obesity markers among preschoolers compliant and non-compliant with sleep duration:A latent profile analysis

This study identifies physical activity (PA) and sedentary behaviour (SB) clusters in preschoolers compliant (C) or non-compliant (NC) with sleep recommendations; and associates these clusters with obesity markers. PA and SB were objectively assessed (Actigraph WGT3-X) in 272 preschoolers (4.4 ± 0.7 years old). Sleep duration was parent-reported, and preschoolers were classified as C (3–4 years old: 600–780 min/day; 5 years old: 540–660 min/day) or NC with sleep recommendations. Body mass index (BMI) and waist circumference (WC) were assessed according to international protocols. Moderate to vigorous physical activity (MVPA) and light physical activity (LPA) were categorized as low/high (60 min/day or <180 min/180 min/day, respectively). SB was defined according to mean values between clusters. Latent profile analysis was performed. Associations between the observed clusters and obesity markers were determined using linear regression (RStudio; 1.3.1073). Four cluster solutions for C and NC preschoolers were identified. A negative association between C/Low MVPA cluster and BMI, and a positive association between NC/Low MVPA and BMI (β = −0.8, 95%CI = −1.6;−0.1, and β = 0.9, 95%CI = 0.1;1.7, respectively) were observed. No association was seen for SB clusters. Adequate sleep duration may have a protective role for preschoolers’ BMI, even if the children do not comply with MVPA recommendations

Building The Sugarcane Genome For Biotechnology And Identifying Evolutionary Trends

Background: Sugarcane is the source of sugar in all tropical and subtropical countries and is becoming increasingly important for bio-based fuels. However, its large (10 Gb), polyploid, complex genome has hindered genome based breeding efforts. Here we release the largest and most diverse set of sugarcane genome sequences to date, as part of an on-going initiative to provide a sugarcane genomic information resource, with the ultimate goal of producing a gold standard genome.Results: Three hundred and seventeen chiefly euchromatic BACs were sequenced. A reference set of one thousand four hundred manually-annotated protein-coding genes was generated. A small RNA collection and a RNA-seq library were used to explore expression patterns and the sRNA landscape. In the sucrose and starch metabolism pathway, 16 non-redundant enzyme-encoding genes were identified. One of the sucrose pathway genes, sucrose-6-phosphate phosphohydrolase, is duplicated in sugarcane and sorghum, but not in rice and maize. A diversity analysis of the s6pp duplication region revealed haplotype-structured sequence composition. Examination of hom(e)ologous loci indicate both sequence structural and sRNA landscape variation. 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Hypothalamic S1p/s1pr1 Axis Controls Energy Homeostasis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Sphingosine 1-phosphate receptor 1 (S1PR1) is a G-protein-coupled receptor for sphingosine-1-phosphate (S1P) that has a role in many physiological and pathophysiological processes. Here we show that the S1P/S1PR1 signalling pathway in hypothalamic neurons regulates energy homeostasis in rodents. We demonstrate that S1PR1 protein is highly enriched in hypothalamic POMC neurons of rats. Intracerebroventricular injections of the bioactive lipid, S1P, reduce food consumption and increase rat energy expenditure through persistent activation of STAT3 and the melanocortin system. Similarly, the selective disruption of hypothalamic S1PR1 increases food intake and reduces the respiratory exchange ratio. We further show that STAT3 controls S1PR1 expression in neurons via a positive feedback mechanism. Interestingly, several models of obesity and cancer anorexia display an imbalance of hypothalamic S1P/S1PR1/STAT3 axis, whereas pharmacological intervention ameliorates these phenotypes. Taken together, our data demonstrate that the neuronal S1P/S1PR1/STAT3 signalling axis plays a critical role in the control of energy homeostasis in rats.5Capes-12900-13-3; CAPES; Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Schwartz, M.W., Woods, S.C., Porte, D., Jr., Seeley, R.J., Baskin, D.G., Central nervous system control of food intake (2000) Nature, 404, pp. 661-671Munzberg, H., Huo, L., Nillni, E.A., Hollenberg, A.N., Bjorbaek, C., Role of signal transducer and activator of transcription 3 in regulation of hypothalamic proopiomelanocortin gene expression by leptin (2003) Endocrinology, 144, pp. 2121-2131Myers, M.G., Cowley, M.A., Munzberg, H., Mechanisms of leptin action and leptin resistance (2008) Annu. Rev. 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