From Atoms to Cells: Using Mesoscale Landscapes to Construct Visual Narratives

A comprehensive review on structural insights through molecular visualization: tools, applications, and limitations

CONTEXT

Biomolecules serve as intrinsic repositories of information related to function, binding interactions, molecular motion, and structural conformations. With the rapid accumulation of structural data from fields such as structural biology and cheminformatics, the ability to visualize biomolecular architecture has become essential for researchers in biology, pharmacology, and related disciplines. Molecular visualization represents a foundational step in accessing and interpreting this data, enabling its application in diverse scientific and therapeutic contexts. Recent advancements in computational algorithms and web-based visualization platforms have provided powerful resources for structural biologists, chemists, and crystallographers, facilitating efficient analysis and reproducibility of experimental outcomes. This review offers a comprehensive overview of contemporary molecular visualization tools, emphasizing their practical applications. Particular attention is given to PyMOL and NGL Viewer, with detailed guidance for their implementation in visualizing proteins, DNA, protein-ligand complexes, protein-protein interactions, protein-DNA assemblies, and small molecule ligands. Challenges frequently encountered in structural biology and cheminformatics, such as the identification of lead compounds for therapeutic development, are also addressed. Molecular dynamics simulations, including binding free energy calculations, are discussed as cost- and time-effective strategies to enhance drug discovery pipelines. In response to the increasing complexity of data-driven research, this review aims to serve as a valuable resource for professionals seeking efficient, reliable visualization tools to support structure-based research and drug design.

METHODS

This review article provides a comprehensive comparative analysis of biomolecular visualization features integrated into standalone and web-based molecular visualization tools. PyMOL (standalone) and NGL (web-based) were systematically employed to visualize proteins, ligands, protein-ligand complexes, protein-protein complexes, and protein-DNA complexes. The methodological framework outlined in this study establishes standardized guidelines for the effective utilization of molecular visualization tools, offering valuable insights for structural biologists and researchers engaged in molecular modeling and structural analysis.

An Improved 21st Century Judicial System with Environmental Science Expertise is Needed for Resolving Interstate Water Conflicts

As stresses on groundwater resources increase due to growing population and climate change, water litigation, such as the recently decided Mississippi (MS) vs Tennessee (TN) lawsuit, will become more common. In the United States, lawsuits between states can be heard only by the Supreme Court of the United States (SCOTUS). These lawsuits are expensive and lengthy, often requiring highly specialized technical expertise. In the MS vs TN case, the Court unanimously held that an interstate aquifer is subject to equitable apportionment. Although this appears to be a sound resolution, a careful examination of the SCOTUS hearing transcript revealed that the Justices had several egregious misconceptions about the groundwater system. These misconceptions arose in part due to the failure of technical experts to communicate groundwater concepts in understandable terms and in part due to the Justices' lack of expertise in groundwater science. To address these issues, we first explore methods for improving scientific communication in courtrooms. Second, we propose ideas for reforming the legal system and provide compelling arguments for using the lower courts to hear such cases. We also explore the possibility of creating specialized federal water courts to resolve water disputes.

A Concise Review of Biomolecule Visualization

The structural characteristics of biomolecules are a major focus in the field of structural biology. Molecular visualization plays a crucial role in displaying structural information in an intuitive manner, aiding in the understanding of molecular properties. This paper provides a comprehensive overview of core concepts, key techniques, and tools in molecular visualization. Additionally, it presents the latest research findings to uncover emerging trends and highlights the challenges and potential directions for the development of the field.

A brief history of visualizing membrane systems in molecular dynamics simulations

Understanding lipid dynamics and function, from the level of single, isolated molecules to large assemblies, is more than ever an intensive area of research. The interactions of lipids with other molecules, particularly membrane proteins, are now extensively studied. With advances in the development of force fields for molecular dynamics simulations (MD) and increases in computational resources, the creation of realistic and complex membrane systems is now common. In this perspective, we will review four decades of the history of molecular dynamics simulations applied to membranes and lipids through the prism of molecular graphics.

Mesoscience in cell biology and cancer research

Mesoscale characteristics and their interdimensional correlation are the focus of contemporary interdisciplinary research. Mesoscience is a discipline that has the potential to radically update the existing knowledge structure, which differs from the conventional unit-scale and system-scale research models, revealing a previously untouchable area for scientific research. Integrative biology research aims to dissect the complex problems of life systems by conducting comprehensive research and integrating various disciplines from all biological levels of the living organism. However, the mesoscientific issues between different research units are neglected and challenging. Mesoscale research in biology requires the integration of research theories and methods from other disciplines (mathematics, physics, engineering, and even visual imaging) to investigate theoretical and frontier questions of biological processes through experiments, computations, and modeling. We reviewed  integrative paradigms and methods for the biological mesoscale problems (focusing on oncology research) and prospected the potential of their multiple dimensions and upcoming challenges. We expect to establish an interactive and collaborative theoretical platform for further expanding the depth and width of our understanding on the nature of biology.

Study of trioleoylglycerol two-layer and adiposome cross-section mimicking four-layer systems through atomic-level simulations

Adiposomes are artificially prepared lipid droplet (LD)-mimetic structures, which, unlike LDs, do not harbor proteins. The dynamics of interaction between triacylglycerols (TAGs), drug molecule, and phospholipids in adiposomes is currently not well-established. Trioleoylglycerol (TOG) molecule was divided into three parts: two oleoyl tails and one 2-monooleoylglycerol (MOG). Forcefield parameters for two oleoyl tails were adopted from the AMBER18 repository while that of the MOG forcefield was taken from the literature. Charge correction was performed on the MOG forcefield before its utilization. After charge correction, the resulting TOG molecule had zero charge. TOG bilayer (2L) and tetralayer (4L) systems were prepared and simulated. TOG bilayer (2L) systems-modeled from two different initial conformations, the TOG3 conformation and the TOG2:1 conformation-showed that TOG2:1 conformation was more prevailing irrespective of the starting conformation and was subsequently used in further simulations. The hydrated TOG 2L system showed TOG-water solution solubility of 0.051 mol L-1 which is near experimental values. This validated the correct parameterization of the TOG molecule. The simulations of 4L systems showed stable membrane behaviors toward the end of simulations. It was also observed that in the 4L system, the TOG molecules showed the formation of micelles with the drug molecule. Almost six TOGs remained continuously in contact with the drug molecule throughout the simulation. The availability of charge-corrected TOG parameterization is expected to equip future studies with a framework for molecular dynamics simulations of adiposomes and/or LDs at the atomic level.

Integrative illustration of a JCVI-syn3A minimal cell

Data from genomics, proteomics, structural biology and cryo-electron microscopy are integrated into a structural illustration of a cross section through an entire JCVI-syn3.0 minimal cell. The illustration is designed with several goals: to inspire excitement in science, to depict the underlying scientific results accurately, and to be feasible in traditional media. Design choices to achieve these goals include reduction of visual complexity with simplified representations, use of orthographic projection to retain scale relationships, and an approach to color that highlights functional compartments of the cell. Given that this simple cell provides an attractive laboratory for exploring the central processes needed for life, several functional narratives are included in the illustration, including division of the cell and the first depiction of an entire cellular proteome. The illustration lays the foundation for 3D molecular modeling of this cell.

Building Structural Models of a Whole Mycoplasma Cell

Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations.

PDB-101: Educational resources supporting molecular explorations through biology and medicine

The Protein Data Bank (PDB) archive is a rich source of information in the form of atomic-level three-dimensional (3D) structures of biomolecules experimentally determined using macromolecular crystallography, nuclear magnetic resonance (NMR) spectroscopy, and electron microscopy (3DEM). Originally established in 1971 as a resource for protein crystallographers to freely exchange data, today PDB data drive research and education across scientific disciplines. In 2011, the online portal PDB-101 was launched to support teachers, students, and the general public in PDB archive exploration (pdb101.rcsb.org). Maintained by the Research Collaboratory for Structural Bioinformatics PDB, PDB-101 aims to help train the next generation of PDB users and to promote the overall importance of structural biology and protein science to nonexperts. Regularly published features include the highly popular Molecule of the Month series, 3D model activities, molecular animation videos, and educational curricula. Materials are organized into various categories (Health and Disease, Molecules of Life, Biotech and Nanotech, and Structures and Structure Determination) and searchable by keyword. A biennial health focus frames new resource creation and provides topics for annual video challenges for high school students. Web analytics document that PDB-101 materials relating to fundamental topics (e.g., hemoglobin, catalase) are highly accessed year-on-year. In addition, PDB-101 materials created in response to topical health matters (e.g., Zika, measles, coronavirus) are well received. PDB-101 shows how learning about the diverse shapes and functions of PDB structures promotes understanding of all aspects of biology, from the central dogma of biology to health and disease to biological energy.

Bayesian metamodeling of complex biological systems across varying representations

Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide and conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are 1) converted to a standardized statistical representation relying on probabilistic graphical models, 2) coupled by modeling their mutual relations with the physical world, and 3) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we provide a proof-of-principle metamodel of glucose-stimulated insulin secretion by human pancreatic β-cells. The input models include a coarse-grained spatiotemporal simulation of insulin vesicle trafficking, docking, and exocytosis; a molecular network model of glucose-stimulated insulin secretion signaling; a network model of insulin metabolism; a structural model of glucagon-like peptide-1 receptor activation; a linear model of a pancreatic cell population; and ordinary differential equations for systemic postprandial insulin response. Metamodeling benefits from decentralized computing, while often producing a more accurate, precise, and complete model that contextualizes input models as well as resolves conflicting information. We anticipate Bayesian metamodeling will facilitate collaborative science by providing a framework for sharing expertise, resources, data, and models, as exemplified by the Pancreatic β-Cell Consortium.

Nanoscape, a data-driven 3D real-time interactive virtual cell environment

Our understanding of cellular and structural biology has reached unprecedented levels of detail, and computer visualisation techniques can be used to create three-dimensional (3D) representations of cells and their environment that are useful in both teaching and research. However, extracting and integrating the relevant scientific data, and then presenting them in an effective way, can pose substantial computational and aesthetic challenges. Here we report how computer artists, experts in computer graphics and cell biologists have collaborated to produce a tool called Nanoscape that allows users to explore and interact with 3D representations of cells and their environment that are both scientifically accurate and visually appealing. We believe that using Nanoscape as an immersive learning application will lead to an improved understanding of the complexities of cellular scales, densities and interactions compared with traditional learning modalities.

An updated toolkit for exploring bacterial cell wall structure and dynamics

The bacterial cell wall is made primarily from peptidoglycan, a complex biomolecule which forms a bag-like exoskeleton that envelops the cell. As it is unique to bacteria and typically essential for their growth and survival, it represents one of the most successful targets for antibiotics. Although peptidoglycan has been studied intensively for over 50 years, the past decade has seen major steps in our understanding of this molecule because of the advent of new analytical and imaging methods. Here, we outline the most recent developments in tools that have helped to elucidate peptidoglycan structure and dynamics.

Strong intracellular signal inactivation produces sharper and more robust signaling from cell membrane to nucleus

For a chemical signal to propagate across a cell, it must navigate a tortuous environment involving a variety of organelle barriers. In this work we study mathematical models for a basic chemical signal, the arrival times at the nuclear membrane of proteins that are activated at the cell membrane and diffuse throughout the cytosol. Organelle surfaces within human B cells are reconstructed from soft X-ray tomographic images, and modeled as reflecting barriers to the molecules’ diffusion. We show that signal inactivation sharpens signals, reducing variability in the arrival time at the nuclear membrane. Inactivation can also compensate for an observed slowdown in signal propagation induced by the presence of organelle barriers, leading to arrival times at the nuclear membrane that are comparable to models in which the cytosol is treated as an open, empty region. In the limit of strong signal inactivation this is achieved by filtering out molecules that traverse non-geodesic paths.

The inside of cells is a complex spatial environment, filled with organelles, filaments and proteins. It is an open question how cell signaling pathways function robustly in the presence of such spatial heterogeneity. In this work we study how organelle barriers influence the most basic of chemical signals; the diffusive propagation of an activated protein from the cell membrane to nucleus. Three-dimensional B cell organelle and membrane geometries reconstructed from soft X-ray tomographic images are used in building mathematical models of the signal propagation process. Our models demonstrate that organelle barriers significantly increase the time required for a diffusing protein to traverse from the cell membrane to nucleus when compared to a cell with an empty cytosolic space. We also show that signal inactivation, a fundamental component of all signaling pathways, can provide robustness in the signal arrival time in two ways. Increasing rates of signal inactivation reduce variability in the arrival time, while also dramatically reducing the degree to which organelle barriers increase the arrival time (in comparison to a cell with an empty cytosol).

Challenges in protein docking

Current developments in protein docking aim at improvement of applicability, accuracy and utility of modeling macromolecular complexes. The challenges include the need for greater emphasis on protein docking to molecules of different types, proper accounting for conformational flexibility upon binding, new promising methodologies based on residue co-evolution and deep learning, affinity prediction, and further development of fully automated docking servers. Importantly, new developments increasingly focus on realistic modeling of protein interactions in vivo, including crowded environment inside a cell, which involves multiple transient encounters, and propagating the system in time. This opinion paper offers the author's perspective on these challenges in structural modeling of protein interactions and the future of protein docking.

Art and Science of the Cellular Mesoscale

Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models.

Scale Trotter: Illustrative Visual Travels Across Negative Scales

We present ScaleTrotter, a conceptual framework for an interactive, multi-scale visualization of biological mesoscale data and, specifically, genome data. ScaleTrotter allows viewers to smoothly transition from the nucleus of a cell to the atomistic composition of the DNA, while bridging several orders of magnitude in scale. The challenges in creating an interactive visualization of genome data are fundamentally different in several ways from those in other domains like astronomy that require a multi-scale representation as well. First, genome data has intertwined scale levels-the DNA is an extremely long, connected molecule that manifests itself at all scale levels. Second, elements of the DNA do not disappear as one zooms out-instead the scale levels at which they are observed group these elements differently. Third, we have detailed information and thus geometry for the entire dataset and for all scale levels, posing a challenge for interactive visual exploration. Finally, the conceptual scale levels for genome data are close in scale space, requiring us to find ways to visually embed a smaller scale into a coarser one. We address these challenges by creating a new multi-scale visualization concept. We use a scale-dependent camera model that controls the visual embedding of the scales into their respective parents, the rendering of a subset of the scale hierarchy, and the location, size, and scope of the view. In traversing the scales, ScaleTrotter is roaming between 2D and 3D visual representations that are depicted in integrated visuals. We discuss, specifically, how this form of multi-scale visualization follows from the specific characteristics of the genome data and describe its implementation. Finally, we discuss the implications of our work to the general illustrative depiction of multi-scale data.

Analogies in 3D molecular visualisations: development of a cell biology animation 'How cells move - a new interpretation of old data'

Cell biology and imaging technology have vastly improved over the past decades, enabling scientists to dissect the inner workings of a cell. In addition to technical limits on spatial and temporal resolution, which obscure the picture at the molecular level, the sheer density and complexity of information impede clear understanding. 3D molecular visualisation has therefore blossomed as a way to translate molecular data in a more tangible form. Whilst the molecular machinery involved in cell locomotion has been extensively studied, existing narratives describing how cells generate the forces that drive movement remain unclear. Polymerisation of a protein called actin is clearly essential. The general belief in the cell migration field is that actin polymerisation's main role is to push the leading edge of the cell forwards, while the rest of the cell follows passively. The cell migration & chemotaxis group at the CRUK Beatson Institute propose an alternative hypothesis, in which actin filaments constitute cables. Motor proteins pull on these cables, causing them to behave like the treads of a tank and drive cell movement. This article describes the development of a 3D animation that uses analogical reasoning to contrast the 'tank' hypothesis for cell locomotion with the current dogma.

Multi-Scale Procedural Animations of Microtubule Dynamics Based on Measured Data

Biologists often use computer graphics to visualize structures, which due to physical limitations are not possible to image with a microscope. One example for such structures are microtubules, which are present in every eukaryotic cell. They are part of the cytoskeleton maintaining the shape of the cell and playing a key role in the cell division. In this paper, we propose a scientifically-accurate multi-scale procedural model of microtubule dynamics as a novel application scenario for procedural animation, which can generate visualizations of their overall shape, molecular structure, as well as animations of the dynamic behaviour of their growth and disassembly. The model is spanning from tens of micrometers down to atomic resolution. All the aspects of the model are driven by scientific data. The advantage over a traditional, manual animation approach is that when the underlying data change, for instance due to new evidence, the model can be recreated immediately. The procedural animation concept is presented in its generic form, with several novel extensions, facilitating an easy translation to other domains with emergent multi-scale behavior.

Integrative Modeling and Visualization of Exosomes

Information from proteomics, microscopy, and structural biology are integrated to create structural models of exosomes, small vesicles released from cells. Three visualization methods are employed and compared: 2D painting of a cross section using traditional media, manual creation of a cross section using the mesoscale 2.5D digital painting software cellPAINT, and generation of a 3D atomic model using the mesoscale modeling program cellPACK.

Molecular Graphics: Bridging Structural Biologists and Computer Scientists

Visualization of molecular structures is one of the most common tasks carried out by structural biologists, typically using software, such as Chimera, COOT, PyMOL, or VMD. In this Perspective article, we outline how past developments in computer graphics and data visualization have expanded the understanding of biomolecular function, and we summarize recent advances that promise to further transform structural biology. We also highlight how progress in molecular graphics has been impeded by communication barriers between two communities: the computer scientists driving these advances, and the structural and computational biologists who stand to benefit. By pointing to canonical papers and explaining technical progress underlying new graphical developments in simple terms, we aim to improve communication between these communities; this, in turn, would help shape future developments in molecular graphics.

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.

Communicating Genome Architecture: Biovisualization of the Genome, from Data Analysis and Hypothesis Generation to Communication and Learning

Genome discoveries at the core of biology are made by visual description and exploration of the cell, from microscopic sketches and biochemical mapping to computational analysis and spatial modeling. We outline the experimental and visualization techniques that have been developed recently which capture the three-dimensional interactions regulating how genes are expressed. We detail the challenges faced in integration of the data to portray the components and organization and their dynamic landscape. The goal is more than a single data-driven representation as interactive visualization for de novo research is paramount to decipher insights on genome organization in space.