Swarm-CG: Automatic Parametrization of Bonded Terms in MARTINI-Based Coarse-Grained Models of Simple to Complex Molecules via Fuzzy Self-Tuning Particle Swarm Optimization

We present Swarm-CG, a versatile software for the automatic iterative parametrization of bonded parameters in coarse-grained (CG) models, ideal in combination with popular CG force fields such as MARTINI. By coupling fuzzy self-tuning particle swarm optimization to Boltzmann inversion, Swarm-CG performs accurate bottom-up parametrization of bonded terms in CG models composed of up to 200 pseudo atoms within 4-24 h on standard desktop machines, using default settings. The software benefits from a user-friendly interface and two different usage modes (default and advanced). We particularly expect Swarm-CG to support and facilitate the development of new CG models for the study of complex molecular systems interesting for bio- and nanotechnology. Excellent performances are demonstrated using a benchmark of 9 molecules of diverse nature, structural complexity, and size. Swarm-CG is available with all its dependencies via the Python Package Index (PIP package: swarm-cg). Demonstration data are available at: www.github.com/GMPavanLab/SwarmCG

Cooperative Supramolecular Block Copolymerization for the Synthesis of Functional Axial Organic Heterostructures

Supramolecular block copolymerzation with optically or electronically complementary monomers provides an attractive bottom-up approach for the non-covalent synthesis of nascent axial organic heterostructures, which promises to deliver useful applications in energy conversion, optoelectronics, and catalysis. However, the synthesis of supramolecular block copolymers (BCPs) constitutes a significant challenge due to the exchange dynamics of non-covalently bound monomers and hence requires fine microstructure control. Furthermore, temporal stability of the segmented microstructure is a prerequisite to explore the applications of functional supramolecular BCPs. Herein, we report the cooperative supramolecular block copolymerization of fluorescent monomers in solution under thermodynamic control for the synthesis of axial organic heterostructures with light-harvesting properties. The fluorescent nature of the core-substituted naphthalene diimide (cNDI) monomers enables a detailed spectroscopic probing during the supramolecular block copolymerization process to unravel a nucleation-growth mechanism, similar to that of chain copolymerization for covalent block copolymers. Structured illumination microscopy (SIM) imaging of BCP chains characterizes the segmented microstructure and also allows size distribution analysis to reveal the narrow polydispersity (polydispersity index (PDI) ≈ 1.1) for the individual block segments. Spectrally resolved fluorescence microscopy on single block copolymerized organic heterostructures shows energy migration and light-harvesting across the interfaces of linearly connected segments. Molecular dynamics and metadynamics simulations provide useful mechanistic insights into the free energy of interaction between the monomers as well as into monomer exchange mechanisms and dynamics, which have a crucial impact on determining the copolymer microstructure. Our comprehensive spectroscopic, microscopic, and computational analyses provide an unambiguous structural, dynamic, and functional characterization of the supramolecular BCPs. The strategy presented here is expected to pave the way for the synthesis of multi-component organic heterostructures for various functions

Automatic Optimization of Lipid Models in the Martini Force Field Using SwarmCG.

After two decades of continued development of the Martini coarse-grained force field (CG FF), further refinment of the already rather accurate Martini lipid models has become a demanding task that could benefit from integrative data-driven methods. Automatic approaches are increasingly used in the development of accurate molecular models, but they typically make use of specifically designed interaction potentials that transfer poorly to molecular systems or conditions different than those used for model calibration. As a proof of concept, here, we employ SwarmCG, an automatic multiobjective optimization approach facilitating the development of lipid force fields, to refine specifically the bonded interaction parameters in building blocks of lipid models within the framework of the general Martini CG FF. As targets of the optimization procedure, we employ both experimental observables (top-down references: area per lipid and bilayer thickness) and all-atom molecular dynamics simulations (bottom-up reference), which respectively inform on the supra-molecular structure of the lipid bilayer systems and on their submolecular dynamics. In our training sets, we simulate at different temperatures in the liquid and gel phases up to 11 homogeneous lamellar bilayers composed of phosphatidylcholine lipids spanning various tail lengths and degrees of (un)saturation. We explore different CG representations of the molecules and evaluate improvements a posteriori using additional simulation temperatures and a portion of the phase diagram of a DOPC/DPPC mixture. Successfully optimizing up to ∼80 model parameters within still limited computational budgets, we show that this protocol allows the obtainment of improved transferable Martini lipid models. In particular, the results of this study demonstrate how a fine-tuning of the representation and parameters of the models may improve their accuracy and how automatic approaches, such as SwarmCG, may be very useful to this end. </p

Self-Sorted, Random, and Block Supramolecular Copolymers via Sequence Controlled, Multicomponent Self-Assembly

Multicomponent supramolecular copolymerization promises to construct complex nanostructures with emergent properties. However, even with two monomeric components, various possible outcomes such as self-sorted supramolecular homopolymers, a random (statistical) supramolecular copolymer, an alternate supramolecular copolymer, or a complex supramolecular block copolymer can occur, determined by their intermolecular interactions and monomer exchange dynamics and hence structural prediction is extremely challenging. Herein, we target this challenge and demonstrate unprecedented two-component sequence controlled supramolecular copolymerization by manipulating thermodynamic and kinetic routes in the pathway complexity of selfassembly of the constitutive monomers. Extensive molecular dynamics simulations provided useful mechanistic insights into the monomer exchange rates and free energy of interactions between the monomers that dictate the self-assembly pathway and sequence. The fluorescent nature of core-substituted naphthalene diimide monomers has been further utilized to characterize the three sequences via Structured Illumination Microscopy (SIM)

Game on, science - how video game technology may help biologists tackle visualization challenges.

The video games industry develops ever more advanced technologies to improve rendering, image quality, ergonomics and user experience of their creations providing very simple to use tools to design new games. In the molecular sciences, only a small number of experts with specialized know-how are able to design interactive visualization applications, typically static computer programs that cannot easily be modified. Are there lessons to be learned from video games? Could their technology help us explore new molecular graphics ideas and render graphics developments accessible to non-specialists? This approach points to an extension of open computer programs, not only providing access to the source code, but also delivering an easily modifiable and extensible scientific research tool. In this work, we will explore these questions using the Unity3D game engine to develop and prototype a biological network and molecular visualization application for subsequent use in research or education. We have compared several routines to represent spheres and links between them, using either built-in Unity3D features or our own implementation. These developments resulted in a stand-alone viewer capable of displaying molecular structures, surfaces, animated electrostatic field lines and biological networks with powerful, artistic and illustrative rendering methods. We consider this work as a proof of principle demonstrating that the functionalities of classical viewers and more advanced novel features could be implemented in substantially less time and with less development effort. Our prototype is easily modifiable and extensible and may serve others as starting point and platform for their developments. A webserver example, standalone versions for MacOS X, Linux and Windows, source code, screen shots, videos and documentation are available at the address: http://unitymol.sourceforge.net/.FlowVRNano : un laboratoire virtuel pour modéliser les systèmes moléculaires nanoscopiques en biologie et dans les matériauxAnalyse visuelle interactive pour les sciences de la vie et des matériaux capable de passer à l'échelle ex

Proteins evolve on the edge of supramolecular self-assembly

The self-association of proteins into symmetric complexes is ubiquitous in all kingdoms of life1,2,3,4,5,6. Symmetric complexes possess unique geometric and functional properties, but their internal symmetry can pose a risk. In sickle-cell disease, the symmetry of haemoglobin exacerbates the effect of a mutation, triggering assembly into harmful fibrils7. Here we examine the universality of this mechanism and its relation to protein structure geometry. We introduced point mutations solely designed to increase surface hydrophobicity among 12 distinct symmetric complexes from Escherichia coli. Notably, all responded by forming supramolecular assemblies in vitro, as well as in vivo upon heterologous expression in Saccharomyces cerevisiae. Remarkably, in four cases, micrometre-long fibrils formed in vivo in response to a single point mutation. Biophysical measurements and electron microscopy revealed that mutants self-assembled in their folded states and so were not amyloid-like. Structural examination of 73 mutants identified supramolecular assembly hot spots predictable by geometry. A subsequent structural analysis of 7,471 symmetric complexes showed that geometric hot spots were buffered chemically by hydrophilic residues, suggesting a mechanism preventing mis-assembly of these regions. Thus, point mutations can frequently trigger folded proteins to self-assemble into higher-order structures. This potential is counterbalanced by negative selection and can be exploited to design nanomaterials in living cells.</p