Complex molecular assemblies at hand via interactive simulations

UNILIPID, a Methodology for Energetically Accurate Prediction of Protein Insertion into Implicit Membranes of Arbitrary Shape

The insertion of proteins into membranes is crucial for understanding their function in many biological processes. In this work, we present UNILIPID, a universal implicit lipid-protein description as a methodology for dealing with implicit membranes. UNILIPID is independent of the scale of representation and can be applied at the level of all atoms, coarse-grained particles down to the level of a single bead per amino acid. We provide example implementations for these scales and demonstrate the versatility of our approach by accurately reflecting the free energy of transfer for each amino acid. In addition to single membranes, we describe the analytical implementation of double membranes and show that UNILIPID is well suited for modeling at multiple scales. We generalize to membranes of arbitrary shape. With UNILIPID, we provide a methodological framework for a simple and general parameterization tuned to reproduce a selected reference hydrophobicity scale. The software we provide along with the methodological description is optimized for specific user features such as real-time response, live visual analysis, and virtual reality experiences.

Molecular Dynamics Simulations of the Proteins Regulating Synaptic Vesicle Fusion

Neuronal transmitters are packaged in synaptic vesicles (SVs) and released by the fusion of SVs with the presynaptic membrane (PM). An inflow of Ca²⁺ into the nerve terminal triggers fusion, and the SV-associated protein Synaptotagmin 1 (Syt1) serves as a Ca²⁺ sensor. In preparation for fusion, SVs become attached to the PM by the SNARE protein complex, a coiled-coil bundle that exerts the force overcoming SV-PM repulsion. A cytosolic protein Complexin (Cpx) attaches to the SNARE complex and differentially regulates the evoked and spontaneous release components. It is still debated how the dynamic interactions of Syt1, SNARE proteins and Cpx lead to fusion. This problem is confounded by heterogeneity in the conformational states of the prefusion protein-lipid complex and by the lack of tools to experimentally monitor the rapid conformational transitions of the complex, which occur at a sub-millisecond scale. However, these complications can be overcome employing molecular dynamics (MDs), a computational approach that enables simulating interactions and conformational transitions of proteins and lipids. This review discusses the use of molecular dynamics for the investigation of the pre-fusion protein-lipid complex. We discuss the dynamics of the SNARE complex between lipid bilayers, as well as the interactions of Syt1 with lipids and SNARE proteins, and Cpx regulating the assembly of the SNARE complex.

UnityMol prototype for FAIR sharing of molecular-visualization experiences: from pictures in the cloud to collaborative virtual reality exploration in immersive 3D environments

Motivated by the current COVID-19 pandemic, which has spurred a substantial flow of structural data, the use of molecular-visualization experiences to make these data sets accessible to a broad audience is described. Using a variety of technology vectors related to the cloud, 3D and virtual reality gear, how to share curated visualizations of structural biology, modeling and/or bioinformatics data sets for interactive and collaborative exploration is examined. FAIR is discussed as an overarching principle for sharing such visualizations. Four initial example scenes related to recent COVID-19 structural data are provided, together with a ready-to-use (and share) implementation in the UnityMol software.

Human Dystrophin Structural Changes upon Binding to Anionic Membrane Lipids

Scaffolding proteins play important roles in supporting the plasma membrane (sarcolemma) of muscle cells. Among them, dystrophin strengthens the sarcolemma through protein-lipid interactions, and its absence due to gene mutations leads to the severe Duchenne muscular dystrophy. Most of the dystrophin protein consists of a central domain made of 24 spectrin-like coiled-coil repeats (R). Using small angle neutron scattering (SANS) and the contrast variation technique, we specifically probed the structure of the three first consecutive repeats 1-3 (R1-3), a part of dystrophin known to physiologically interact with membrane lipids. R1-3 free in solution was compared to its structure adopted in the presence of phospholipid-based bicelles. SANS data for the protein/lipid complexes were obtained with contrast-matched bicelles under various phospholipid compositions to probe the role of electrostatic interactions. When bound to anionic bicelles, large modifications of the protein three-dimensional structure were detected, as revealed by a significant increase of the protein gyration radius from 42 ± 1 to 60 ± 4 Å. R1-3/anionic bicelle complexes were further analyzed by coarse-grained molecular dynamics simulations. From these studies, we report an all-atom model of R1-3 that highlights the opening of the R1 coiled-coil repeat when bound to the membrane lipids. This model is totally in agreement with SANS and click chemistry/mass spectrometry data. We conclude that the sarcolemma membrane anchoring that occurs during the contraction/elongation process of muscles could be ensured by this coiled-coil opening. Therefore, understanding these structural changes may help in the design of rationalized shortened dystrophins for gene therapy. Finally, our strategy opens up new possibilities for structure determination of peripheral and integral membrane proteins not compatible with different high-resolution structural methods.

Multi-scale simulations of biological systems using the OPEP coarse-grained model

Biomolecules are complex machines that are optimized by evolution to properly fulfill or contribute to a variety of biochemical tasks in the cellular environment. Computer simulations based on quantum mechanics and atomistic force fields have been proven to be a powerful microscope for obtaining valuable insights into many biological, physical, and chemical processes. Many interesting phenomena involve, however, a time scale and a number of degrees of freedom, notably if crowding is considered, that cannot be explored at an atomistic resolution. To bridge the gap between reality and simulation, many different advanced computational techniques and coarse-grained (CG) models have been developed. Here, we report some applications of the CG OPEP protein model to amyloid fibril formation, the response of catch-bond proteins to two types of fluid flow, and interactive simulations to fold peptides with well-defined 3D structures or with intrinsic disorder.

What Can Human-Guided Simulations Bring to RNA Folding?

Inspired by the recent success of scientific-discovery games for predicting protein tertiary and RNA secondary structures, we have developed an open software for coarse-grained RNA folding simulations, guided by human intuition. To determine the extent to which interactive simulations can accurately predict 3D RNA structures of increasing complexity and lengths (four RNAs with 22-47 nucleotides), an interactive experiment was conducted with 141 participants who had very little knowledge of nucleic acids systems and computer simulations, and had received only a brief description of the important forces stabilizing RNA structures. Their structures and full trajectories have been analyzed statistically and compared to standard replica exchange molecular dynamics simulations. Our analyses show that participants gain easily chemical intelligence to fold simple and nontrivial topologies, with little computer time, and this result opens the door for the use of human-guided simulations to RNA folding. Our experiment shows that interactive simulations have better chances of success when the user widely explores the conformational space. Interestingly, providing on-the-fly feedback of the root mean square deviation with respect to the experimental structure did not improve the quality of the proposed models.

Ab initio RNA folding

RNA molecules are essential cellular machines performing a wide variety of functions for which a specific three-dimensional structure is required. Over the last several years, the experimental determination of RNA structures through x-ray crystallography and NMR seems to have reached a plateau in the number of structures resolved each year, but as more and more RNA sequences are being discovered, the need for structure prediction tools to complement experimental data is strong. Theoretical approaches to RNA folding have been developed since the late nineties, when the first algorithms for secondary structure prediction appeared. Over the last 10 years a number of prediction methods for 3D structures have been developed, first based on bioinformatics and data-mining, and more recently based on a coarse-grained physical representation of the systems. In this review we are going to present the challenges of RNA structure prediction and the main ideas behind bioinformatic approaches and physics-based approaches. We will focus on the description of the more recent physics-based phenomenological models and on how they are built to include the specificity of the interactions of RNA bases, whose role is critical in folding. Through examples from different models, we will point out the strengths of physics-based approaches, which are able not only to predict equilibrium structures, but also to investigate dynamical and thermodynamical behavior, and the open challenges to include more key interactions ruling RNA folding.

MegaMol--A Prototyping Framework for Particle-Based Visualization

Visualization applications nowadays not only face increasingly larger datasets, but have to solve increasingly complex research questions. They often require more than a single algorithm and consequently a software solution will exceed the possibilities of simple research prototypes. Well-established systems intended for such complex visual analysis purposes have usually been designed for classical, mesh-based graphics approaches. For particle-based data, however, existing visualization frameworks are too generic - e.g. lacking possibilities for consistent low-level GPU optimization for high-performance graphics - and at the same time are too limited - e.g. by enforcing the use of structures suboptimal for some computations. Thus, we developed the system softwareMegaMol for visualization research on particle-based data. On the one hand, flexible data structures and functional module design allow for easy adaption to changing research questions, e.g. studying vapors in thermodynamics, solid material in physics, or complex functional macromolecules like proteins in biochemistry. Therefore, MegaMol is designed as a development framework. On the other hand, common functionality for data handling and advanced rendering implementations are available and beneficial for all applications. We present several case studies of work implemented using our system as well as a comparison to other freely available or open source systems.

The OPEP protein model: from single molecules, amyloid formation, crowding and hydrodynamics to DNA/RNA systems

The OPEP coarse-grained protein model has been applied to a wide range of applications since its first release 15 years ago. The model, which combines energetic and structural accuracy and chemical specificity, allows the study of single protein properties, DNA-RNA complexes, amyloid fibril formation and protein suspensions in a crowded environment. Here we first review the current state of the model and the most exciting applications using advanced conformational sampling methods. We then present the current limitations and a perspective on the ongoing developments.

Innovative interactive flexible docking method for multi-scale reconstruction elucidates dystrophin molecular assembly

At present, our molecular knowledge of dystrophin, the protein encoded by the DMD gene and mutated in myopathy patients, remains limited. To get around the absence of its atomic structure, we have developed an innovative interactive docking method based on the BioSpring software in combination with Small-angle X-ray Scattering (SAXS) data. BioSpring allows interactive handling of biological macromolecules thanks to an augmented Elastic Network Model (aENM) that combines the spring network with non-bonded terms between atoms or pseudo-atoms. This approach can be used for building molecular assemblies even on a desktop or a laptop computer thanks to code optimizations including parallel computing and GPU programming. By combining atomistic and coarse-grained models, the approach significantly simplifies the set-up of multi-scale scenarios. BioSpring is remarkably efficient for the preparation of numeric simulations or for the design of biomolecular models integrating qualitative experimental data restraints. The combination of this program and SAXS allowed us to propose the first high-resolution models of the filamentous central domain of dystrophin, covering repeats 11 to 17. Low-resolution interactive docking experiments driven by a potential grid enabled us to propose how dystrophin may associate with F-actin and nNOS. This information provides an insight into medically relevant discoveries to come.

Udock, the interactive docking entertainment system

Protein-protein interactions play a crucial role in biological processes. Protein docking calculations' goal is to predict, given two proteins of known structures, the associate conformation of the corresponding complex. Here, we present a new interactive protein docking system, Udock, that makes use of users' cognitive capabilities added up. In Udock, the users tackle simplified representations of protein structures and explore protein-protein interfaces' conformational space using a gamified interactive docking system with on the fly scoring. We assumed that if given appropriate tools, a naïve user's cognitive capabilities could provide relevant data for (1) the prediction of correct interfaces in binary protein complexes and (2) the identification of the experimental partner in interaction among a set of decoys. To explore this approach experimentally, we conducted a preliminary two week long playtest where the registered users could perform a cross-docking on a dataset comprising 4 binary protein complexes. The users explored almost all the surface of the proteins that were available in the dataset but favored certain regions that seemed more attractive as potential docking spots. These favored regions were located inside or nearby the experimental binding interface for 5 out of the 8 proteins in the dataset. For most of them, the best scores were obtained with the experimental partner. The alpha version of Udock is freely accessible at http://udock.fr.

A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors

With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human–computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360° atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3–4 orders of magnitude.

Fast blending scheme for molecular surface representation

Representation of molecular surfaces is a well established way to study the interaction of molecules. The state-of-the-art molecular representation is the SES model, which provides a detailed surface visualization. Nevertheless, it is computationally expensive, so the less accurate Gaussian model is traditionally preferred. We introduce a novel surface representation that resembles the SES and approaches the rendering performance of the Gaussian model. Our technique is based on the iterative blending of implicit functions and avoids any pre-computation. Additionally, we propose a GPU-based ray-casting algorithm that efficiently visualize our molecular representation. A qualitative and quantitative comparison of our model with respect to the Gaussian and SES models is presented. As showcased in the paper, our technique is a valid and appealing alternative to the Gaussian representation. This is especially relevant in all the applications where the cost of the SES is prohibitive.

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/.

Haptic-driven applications to molecular modeling: state-of-the-art and perspectives

Drug design is a creative process that combines different scientific expertise. With the development of increasingly powerful computers, disciplines such as molecular modeling and, in particular, drug design, are becoming an important component of drug discovery. However, modern software often limits the user interaction with the computer calculation, reducing the potential for researchers to use their knowledge in the design process. For this reason, interactive methodologies have been investigated in recent years. In particular, haptic-driven simulators offer the possibility for users to drive and control the modeling simulations, efficiently combining human knowledge and computational power. In this article, we will discuss the state-of-the-art and future perspectives of such methodologies.

GPU-accelerated atom and dynamic bond visualization using hyperballs: a unified algorithm for balls, sticks, and hyperboloids

Ray casting on graphics processing units (GPUs) opens new possibilities for molecular visualization. We describe the implementation and calculation of diverse molecular representations such as licorice, ball-and-stick, space-filling van der Waals spheres, and approximated solvent-accessible surfaces using GPUs. We introduce HyperBalls, an improved ball-and-stick representation replacing tubes, linking the atom spheres by hyperboloids that can smoothly connect them. This type of depiction is particularly useful to represent dynamic phenomena, such as the evolution of noncovalent bonds. It is furthermore well suited to represent coarse-grained models and spring networks. All these representations can be defined by a single general algebraic equation that is adapted for the ray-casting technique and is well suited for execution on the GPU. Using GPU capabilities, this implementation can routinely, accurately, and interactively render molecules ranging from a few atoms up to huge macromolecular assemblies with more than 500,000 particles. In simple cases, based only on spheres, we have been able to display up to two million atoms smoothly.

Direct simulation of protein-mediated vesicle fusion: lung surfactant protein B

We simulated spontaneous fusion of small unilamellar vesicles mediated by lung surfactant protein B (SP-B) using the MARTINI force field. An SP-B monomer triggers fusion events by anchoring two vesicles and facilitating the formation of a lipid bridge between the proximal leaflets. Once a lipid bridge is formed, fusion proceeds via a previously described stalk - hemifusion diaphragm - pore-opening pathway. In the absence of protein, fusion of vesicles was not observed in either unbiased simulations or upon application of a restraining potential to maintain the vesicles in close proximity. The shape of SP-B appears to enable it to bind to two vesicles at once, forcing their proximity, and to facilitate the initial transfer of lipids to form a high-energy hemifusion intermediate. Our results may provide insight into more general mechanisms of protein-mediated membrane fusion, and a possible role of SP-B in the secretory pathway and transfer of lung surfactant to the gas exchange interface.

Modeling the early stage of DNA sequence recognition within RecA nucleoprotein filaments

Homologous recombination is a fundamental process enabling the repair of double-strand breaks with a high degree of fidelity. In prokaryotes, it is carried out by RecA nucleofilaments formed on single-stranded DNA (ssDNA). These filaments incorporate genomic sequences that are homologous to the ssDNA and exchange the homologous strands. Due to the highly dynamic character of this process and its rapid propagation along the filament, the sequence recognition and strand exchange mechanism remains unknown at the structural level. The recently published structure of the RecA/DNA filament active for recombination (Chen et al., Mechanism of homologous recombination from the RecA-ssDNA/dsDNA structure, Nature 2008, 453, 489) provides a starting point for new exploration of the system. Here, we investigate the possible geometries of association of the early encounter complex between RecA/ssDNA filament and double-stranded DNA (dsDNA). Due to the huge size of the system and its dense packing, we use a reduced representation for protein and DNA together with state-of-the-art molecular modeling methods, including systematic docking and virtual reality simulations. The results indicate that it is possible for the double-stranded DNA to access the RecA-bound ssDNA while initially retaining its Watson–Crick pairing. They emphasize the importance of RecA L2 loop mobility for both recognition and strand exchange.