Biology subjects

Onuchic, J. N.

Publications and source records attributed to Onuchic, J. N..

At least 19 recordsLinked to original sources

bioRxiv2026

The compartmental polarization of interphase human chromosomes within the nucleus: A mechanism for transcriptional regulation of large chromosomes

The structure and dynamics of individual chromosomes are significantly modulated by their local environment within the nucleus. It has long been established that heterochromatin (B compartment loci) associates with the lamina meshwork that lines the inner nuclear envelope. However, the extent to which these interactions perturb the chromosomal organization within a territory remains unclear. Using computer simulations and published imaging data, we further characterize the interaction between chromatin and the lamina and find striking consequences of lamina-association on the chromosomal structural ensemble. We find that lamina-associating chromosomes have their compartmentalization polarized in a direction perpendicular to the nuclear surface. Further, lamina-associated chromosomes exhibit shorter average distances between euchromatin loci (A compartment) than chromosomes without lamina contact. Energy landscape analysis of our simulations reveal that the sequestration of heterochromatin to the lamina allows for euchromatin to form more spatial contacts with other segments of euchromatin. The compaction of euchromatin due to lamina-association also diminishes the mobility of these regions. These findings suggest a mechanism for bringing together euchromatic segments that are separated by large genomic distances within a chromosome, potentially to share transcriptional machinery and enhance transcription for large chromosomes, which are often found at the nuclear periphery.

biophysics↗

bioRxiv2026

Asynchronous structural rearrangements govern constriction of the human nuclear pore complex

The nuclear pore complex (NPC) is responsible for transport between the cytoplasm and nucleus. CryoET experiments have resolved multiple conformations of the pore that are dilated or constricted. Since the dilation state will impact transport properties, there is much interest in understanding the energetic factors that regulate dilation/constriction. To this end, we applied a structure-based (G[o]-like) model to study the mechanistic properties of large-scale constriction ( [~] 100[A]) in the human NPC. Even though the structures are symmetric, the simulations implicate asynchronous rear-rangements during constriction. By considering variants of the model, we further characterize the relative contributions of individual proteins to this collective process. Together, this provides an energetic/structural foundation that can guide development of precise physical approaches for studying this elusive motion.

biophysics↗

bioRxiv2026

Structural Topology-based Electrostatic Model (STEM) Reveals Ion-Coordination Exchange as a Driver of RNA Folding Dynamics

RNA is a highly charged polyelectrolyte whose folding into functional architectures depends on an ionic atmosphere that screens strong electrostatic repulsion along the phosphate backbone. Whereas monovalent ions primarily stabilize secondary structure, divalent magnesium (Mg2+) drives tertiary folding often via site-specific and adopting various dynamic coordination modes. Current RNA structure-prediction frameworks rely largely on static direct-contact information, overlooking ion-mediated interactions and the dynamic exchange between distinct coordination modes--particularly the dynamic exchange between direct (inner) and solvent-separated (outer-sphere) Mg2+-phosphate coordination that often controls RNAs conformational transition. Here, we introduce the Structural-based Electrostatic Model (STEM), a hybrid implicit-explicit framework that explicitly captures how the dynamic exchange between distinct ion-coordination modes dictates folding pathways. STEM combines explicit Mg2+ ions to resolve site-specific interactions with implicit K+ ions to describe counter-ion condensation mediated electrostatic screening through generalized Manning counter-ion condensation model, enabling computationally efficient exploration of RNA folding landscapes. The model accurately reproduces crystallographic ion-binding sites, experimental preferential ion-interaction coefficients, and Small-Angle X-ray Scattering (SAXS)-derived radii of gyration across diverse RNA systems. Applied to a 58-nt rRNA fragment, STEM reveals that folding from an intermediate to the native state is driven by a chelated Mg2+-mediated tertiary contact and captures the resulting coordination-dependent conformational breathing. By shifting the paradigm from static direct-contact descriptions to ion-mediated dynamic interactions, STEM provides a physically grounded framework for predicting dynamic ensembles of RNA structures, resolving their folding free-energy landscapes, and elucidating the mechanisms of RNA folding and function beyond native conformations across physiological salt conditions. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/734987v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@27da3borg.highwire.dtl.DTLVardef@689310org.highwire.dtl.DTLVardef@18f32f0org.highwire.dtl.DTLVardef@593184_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

A biophysical framework for accurately identifying antigen single-amino acid escape variants and corresponding variant-specific compensatory TCR sequences

The impact of single amino acid substitution on T-cell receptor (TCR) recognition is central to understanding the molecular determinants of TCR specificity and degeneracy during viral mutational escape, cancer recognition, and autoimmunity. In this study, we developed a biophysics-informed computational approach integrating experimental alanine-scan mutagenesis data from the autoimmune-associated ALWGPDPAAA peptide bound to HLA-A*02:01 together with coarse-grained structural modeling. Our approach reconstructs the energetics and structural determinants underpinning the observed loss of recognition by the diabetogenic 1E6 TCR upon single-point mutations, specifically at the critical Pro5 and Asp6 residues. Leveraging the computational models ability to incorporate multiple structural templates into binding predictions, this approach quantitatively reproduces experimentally measured affinity disruptions. Additionally, we apply our approach to identify potential compensatory interactions capable of restoring binding affinity through alternative residue interactions. This integrative computational framework contributes a strategy for inferring TCR-peptide binding energetics at the single amino acid level, guiding the rational design of peptide-based immunotherapeutics, and predicting the functional impacts of clinically relevant peptide variants.

biophysics↗

bioRxiv2024

Computational modeling of cancer cell metabolism along the catabolic-anabolic axes

Abnormal metabolism is a hallmark of cancer. Initially recognized through the observation of aerobic glycolysis in cancer nearly a century ago. Also, we now know that mitochondrial respiration is also used by cancer for progression and metastasis. However, it remains largely unclear the mechanisms by which cancer cells mix and match different metabolic modalities (oxidative/reductive) and leverage various metabolic ingredients (glucose, fatty acids, glutamine) to meet their bioenergetic and biosynthetic needs. Here, we formulate a phenotypic model for cancer metabolism by coupling master gene regulators (AMPK, HIF-1, Myc) with key metabolic substrates (glucose, fatty acid, and glutamine). The model predicts that cancer cells can acquire four metabolic phenotypes: a catabolic phenotype characterized by vigorous oxidative processes - O, an anabolic phenotype characterized by pronounced reductive activities - W, and two complementary hybrid metabolic states - one exhibiting both high catabolic and high anabolic activity - W/O, and the other relying mainly on glutamine oxidation - Q. Using this framework, we quantified gene and metabolic pathway activity respectively by developing scoring metrics based on gene expression. We validated the model-predicted gene-metabolic pathway association and the characterization of the four metabolic phenotypes by analyzing RNA-seq data of tumor samples from TCGA. Strikingly, carcinoma samples exhibiting hybrid metabolic phenotypes are often associated with the worst survival outcomes relative to other metabolic phenotypes. Our mathematical model and scoring metrics serve as a platform to quantify cancer metabolism and study how cancer cells adapt their metabolism upon perturbations, which ultimately could facilitate an effective treatment targeting cancer metabolic plasticity. Statement of significanceWe present a theoretical framework that integrates both catabolic and anabolic modes of cancer metabolism, considering the complex interplay between glucose, fatty acids, and glutamine, by coupling genetic regulation with metabolic pathways. Our work characterizes four main metabolic phenotypes in cancer - OXPHOS, glycolysis, hybrid, glutamine-dominant and demonstrates the critical role of Myc on glutamine metabolism in all four phenotypes. The characterization of metabolism can guide our evaluation of patient survival across cancer types.

systems biology↗

bioRxiv2024

Compaction-mediated segregation of partly replicated bacterial chromosome

Faithful chromosome segregation during bacterial replication requires global reorganization of the nucleoid, where Structural Maintenance of Chromosomes (SMC) complexes play a crucial role. Here we develop an energy-landscape framework that integrates data-driven pairwise interactions with coarse-grained polymer physics to infer the 3D architectural ensembles of Escherichia coli and Bacillus subtilis chromosomes throughout replication. We show that SMC-mediated long-range lengthwise compaction reshapes the nucleoid to induce a robust mid-replication transition in which the terminus relocates toward the nucleoid center and duplicated origins segregate toward opposite cell halves. SMC-deficient mutants lack this transition and instead exhibit emergent nematic-like alignment of sister chromosomes that impedes segregation. A distinctive inter-sister Hi-C signature accompanies the emergence of the nematic alignment. By systematically tuning nonspecific inter-sister adhesion, we reveal that SMC activity expands the physical regime permitting faithful segregation. This buffering protects segregation against adhesive forces intrinsic to the crowded bacterial nucleoid. Our framework provides mechanistic insight into SMC-dependent co-replication segregation across bacterial species, yielding experimentally testable predictions for imaging and sister-chromosome-resolved Hi-C.

biophysics↗

bioRxiv2023

Regulation of chromatin transcription dynamics by DNA supercoiling

Transcription has a mechanical component, as the translocation of the transcription machinery or RNA polymerase (RNAP) on DNA or chromatin is dynamically coupled to the chromatin torsion. This posits chromatin mechanics as a possible regulator of eukaryotic transcription, however, the modes and mechanisms of this regulation are elusive. Here, we first take a statistical mechanics approach to model the torsional response of topology-constrained chromatin. Our model recapitulates the experimentally observed weaker torsional rigidity of chromatin compared to bare DNA, and proposes structural transitions of nucleosomes into chirally distinct states as the driver of the contrasting torsional mechanics. Coupling chromatin mechanics with RNAP translocation in stochastic simulations, we reveal a complex interplay of DNA supercoiling and nucleosome dynamics in governing RNAP velocity. Nucleosomes play a dual role in controlling the transcription dynamics. The steric barrier aspect of nucleosomes in the gene body counteracts transcription via hindering RNAP motion, whereas the chiral transitions facilitate RNAP motion via driving a low restoring torque upon twisting the DNA. While nucleosomes with low dissociation rates are typically transcriptionally repressive, highly dynamic nucleosomes offer less of a steric barrier and enhance the transcription elongation dynamics of weakly transcribed genes via buffering DNA twist. We use the model to predict transcription-dependent levels of DNA supercoiling in segments of the budding yeast genome that are in accord with available experimental data. The model unveils a paradigm of DNA supercoiling-mediated interaction between genes and makes testable predictions that will guide experimental design.

biophysics↗

bioRxiv2023

RACER-m Leverages Structural Features for Sparse T Cell Specificity Prediction

Reliable prediction of T cell specificity against antigenic signatures is a formidable task, complicated primarily by the immense diversity of T cell receptor and antigen sequence space and the resulting limited availability of training sets for inferential models. Recent modeling efforts have demonstrated the advantage of incorporating structural information to overcome the need for extensive training sequence data, yet disentangling the heterogeneous TCR-antigen structural interface to accurately predict the MHC-allele-restricted TCR-peptide binding interactions remained challenging. Here, we present RACER-m, a coarse-grained structural template model leveraging key biophysical information from the diversity of publicly available TCR-antigen crystal structures. We find explicit inclusion of structural content substantially reduces the required number of training examples for reliable prediction of TCR-recognition specificity and sensitivity across diverse biological contexts. We demonstrate that our structural model capably identifies biophysically meaningful point-mutants that affect overall binding affinity, distinguishing its ability in predicting TCR specificity of point mutants peptides from alternative sequence-based methods. Collectively, our approach combines biophysical and inferential learning-based methods to predict TCR-peptide binding events using sparse training data. Its application is broadly applicable to studies involving both closely-related and structurally diverse TCR-peptide pairs.

biophysics↗

bioRxiv2023

Three-dimensional genome architecture persists in a 52,000-year-old woolly mammoth skin sample

Ancient DNA (aDNA) sequencing analysis typically involves alignment to a modern reference genome assembly from a related species. Since aDNA molecules are fragmentary, these alignments yield information about small-scale differences, but provide no information about larger features such as the chromosome structure of ancient species. We report the genome assembly of a female Late Pleistocene woolly mammoth (Mammuthus primigenius) with twenty-eight chromosome-length scaffolds, generated using mammoth skin preserved in permafrost for roughly 52,000 years. We began by creating a modified Hi-C protocol, dubbed PaleoHi-C, optimized for ancient samples, and using it to map chromatin contacts in a woolly mammoth. Next, we developed "reference-assisted 3D genome assembly," which begins with a reference genome assembly from a related species, and uses Hi-C and DNA-Seq data from a target species to split, order, orient, and correct sequences on the basis of their 3D proximity, yielding accurate chromosome-length scaffolds for the target species. By means of this reference-assisted 3D genome assembly, PaleoHi-C data reveals the 3D architecture of a woolly mammoth genome, including chromosome territories, compartments, domains, and loops. The active (A) and inactive (B) genome compartments in mammoth skin more closely resemble those observed in Asian elephant skin than the compartmentalization patterns seen in other Asian elephant tissues. Differences in compartmentalization between these skin samples reveal sequences whose transcription was potentially altered in mammoth. We observe a tetradic structure for the inactive X chromosome in mammoth, distinct from the bipartite architecture seen in human and mouse. Generating chromosome-length genome assemblies for two other elephantids (Asian and African elephant), we find that the overall karyotype, and this tetradic Xi structure, are conserved throughout the clade. These results illustrate that cell-type specific epigenetic information can be preserved in ancient samples, in the form of DNA geometry, and that it may be feasible to perform de novo genome assembly of some extinct species.

genomics↗

bioRxiv2023

Temporally correlated active forces drive chromosome structure and dynamics

Understanding the mechanisms governing the structure and dynamics of flexible polymers like chromosomes, especially, the signatures of motor-driven active processes is of great interest in genome biology. We study chromosomes as a coarse-grained polymer model where microscopic motor activity is captured via an additive temporally persistent noise. The active steady state is characterized by two parameters: active force, controlling the persistent-noise amplitude, and correlation time, the decay time of active noise. We find that activity drives correlated motion over long distances and a regime of dynamic compaction into a globally collapsed entangled globule. Diminished topological constraints destabilize the entangled globule, and the active segments trapped in the globule move toward the periphery, resulting in an enriched active monomer density near the periphery. We also show that heterogeneous activity leads to the segregation of the highly dynamic species from the less dynamic one, suggesting a role of activity in chromosome compartmental segregation. Adding activity to experimental-data-derived structures, we find active loci may mechanically perturb and switch compartments established via epigenetics-driven passive self-association. The key distinguishing signatures of activity are enhanced apparent diffusivity, exploration of all the dynamic regimes (sub-diffusion, effective diffusion, and super-diffusion) at various lag times, and a broadened distribution of observables like the dynamic exponents.

biophysics↗

bioRxiv2022

Spatial-temporal order-disorder transition in angiogenic NOTCH signaling controls cell fate specification

Angiogenesis is a morphogenic process resulting in the formation of new blood vessels from pre-existing ones, usually in hypoxic micro-environments. The initial steps of angiogenesis depend on robust differentiation of oligopotent endothelial cells into the Tip and Stalk phenotypic cell fates, controlled by NOTCH-dependent cell-cell communication. The dynamics of spatial patterning of this cell fate specification are only partially understood. Here, by combining a controlled experimental angiogenesis model with mathematical and computational analyses, we find that the regular spatial Tip-Stalk cell patterning can undergo an order-disorder transition at a relatively high input level of a pro-angiogenic factor VEGF. The resulting differentiation is robust but temporally unstable for most cells, with only a subset of presumptive Tip cells leading sprout extensions. We further find that sprouts form in a manner maximizing their mutual distance, consistent with a Turing-like model that may depend on local enrichment and depletion of fibronectin. Together, our data suggest that NOTCH signaling mediates a robust way of cell differentiation enabling but not instructing subsequent steps in angiogenic morphogenesis, which may require additional cues and self-organization mechanisms. This analysis can assist in further understanding of cell plasticity underlying angiogenesis and other complex morphogenic processes. Significance StatementWe investigate the spatial and temporal patterns of Tip/Stalk specification and the ensuing angiogenic sprouting by using a novel controlled micro-engineered experimental model of angiogenesis and a set of mathematical models of the spatially resolved, cell population-level VEGF-NOTCH signaling. Our analysis provides a dynamic view of the initial step of angiogenesis, revealing fluctuations in its onset, and features suggesting transitions between order and disorder in cell organization. These findings suggest how a potentially very restrictive patterning mechanism can become sensitive to a variety of environmental cues. This sensitivity can be crucial for proper vascularization of a damaged organ, and may suggest new ways of analyzing angiogenesis in the context of cancer and other pathologies. This analysis also suggests a framework for understanding of other instances of NOTCH-mediated patterning processes.

systems biology↗

bioRxiv2022

An Associative Memory Hamiltonian Model for DNA and Nucleosomes

A model for DNA and nucleosomes is introduced with the goal of studying chromosomes from a single base level all the way to higher-order chromatin structures. This model, dubbed the Widely Editable Chromatin Model (WEChroM), is able to reproduce the complex mechanics of the double helix including its bending persistence length and twisting persistence length, and their respective temperature dependence. The WEChroM Hamiltonian is composed of chain connectivity, steric interactions, and associative memory terms representing all remaining interactions leading to the structure, dynamics, and mechanical characteristics of the B-DNA. Several applications of this model are discussed to demonstrate its applicability. WEChroM is used to investigate the behavior of circular DNA in the presence of positive and negative supercoiling. We show that it recapitulates the formation of plectonemes and of structural defects that relax mechanical stress. The model spontaneously manifests an asymmetric behavior with respect to positive or negative supercoiling, similarly to what was previously observed in experiments. Additionally, we show that the associative memory Hamiltonian is also capable of reproducing the free energy of partial DNA unwrapping from nucleosomes. WEChroM can readily emulate the continuously variable mechanical properties of the 10nm fiber and, by virtue of its simplicity, allows the simulation of molecular systems large enough to study the structural ensembles of genes. WEChroM is implemented in the OpenMM simulation toolkits and is freely available for public use. Author SummaryThe structural ensembles of genes have been so far out of the reach of theoretical and computational investigations because genes are molecular complexes too big to be tackled with even the most efficient computational chemistry approaches and yet too strongly affected by heterogeneous molecular factors to be effectively modeled as a simple polymer. In this work, we develop a computationally efficient, easy-to-use, and widely editable chromatin model to study the principles of DNA folding at the gene scale. Using the framework of Associative Memory Hamiltonians, this model reproduces the structural and mechanical properties of double-stranded DNA and accounts for the effects of nucleosome-forming histone octamers and other proteins bound to DNA. Our results open the path to studying the structural and mechanical ensembles of genetic systems as large as tens of kilobases of chromatin, i.e., the size of mammalian genes.

biophysics↗

bioRxiv2022

Structural Reorganization and Relaxation Dynamics of Axially Stressed Chromosomes

Micromechanical studies of mitotic chromosomes have revealed them to be remarkably extensible objects and informed early models of mitotic chromosome organization. We use a data-driven, coarsegrained polymer modeling approach, capable of generating ensembles of chromosome structures that are quantitatively consistent with experiments, to explore the relationship between the spatial organization of individual chromosomes and their emergent mechanical properties. In particular, we investigate the mechanical properties of our model chromosomes by axially stretching them. Simulated stretching led to a linear force-extension curve for small strain, with mitotic chromosomes behaving about ten-fold stiffer than interphase chromosomes. Studying the relaxation dynamics we found that chromosomes are viscoelastic solids, with a highly liquid-like, viscous behavior in interphase that becomes solid-like in mitosis. This emergent mechanical stiffness in our model originates from lengthwise compaction, an effective potential capturing the activity of loop-extruding SMC complexes. Chromosomes denature under large strains via unraveling, which is characterized by opening of large-scale folding patterns. By quantifying the effect of mechanical perturbations on the chromosomes structural features, our model provides a nuanced understanding of in vivo mechanics of chromosomes.

biophysics↗

bioRxiv2022

Shaping the Genome via Lengthwise Compaction, Phase Separation, and Lamina Adhesion

The link between genomic structure and biological function is yet to be consolidated, it is, however, clear that physical manipulation of the genome, driven by the activity of a variety of proteins, is a crucial step. To understand the consequences of the physical forces underlying genome organization, we build a coarse-grained polymer model of the genome, featuring three fundamentally distinct classes of interactions: lengthwise compaction, i.e., compaction of chromosomes along its contour, self-adhesion among epigenetically similar genomic segments, and adhesion of chromosome segments to the nuclear envelope or lamina. We postulate that these three types of interactions sufficiently represent the concerted action of the different proteins organizing the genome architecture and show that an interplay among these interactions can recapitulate the architectural variants observed across the tree of life. The model elucidates how an interplay of forces arising from the three classes of genomic interactions can drive drastic, yet predictable, changes in the global genome architecture, and makes testable predictions. We posit that precise control over these interactions in vivo is key to the regulation of genome architecture.

biophysics↗

bioRxiv2022

Interphase chromosomes of the Aedes aegypti mosquito are liquid crystalline and can sense mechanical cues

We use data-driven physical simulations to study the three-dimensional architecture of the Aedes aegypti genome. Hi-C maps exhibit both a broad diagonal and compart-mentalization with telomeres and centromeres clustering together. Physical modeling reveals that these observations correspond to an ensemble of 3D chromosomal structures that are folded over and partially condensed. Clustering of the centromeres and telomeres near the nuclear lamina appears to be a necessary condition for the formation of the observed structures. Further analysis of the mechanical properties of the genome reveals that the chromosomes of Aedes aegypti, by virtue of their atypical structural organization, are highly sensitive to the deformation of the nuclei. This last finding provides a possible physical mechanism linking mechanical cues to gene regulation.

genomics↗

bioRxiv2021

Examining the Ensembles of Amyloid-β Monomer Variants and their Propensities to Form Fibers Using an Energy Landscape Visualization Method

The amyloid-{beta} (A{beta}) monomer, an intrinsically disordered peptide, is produced by the cleavage of the amyloid precursor protein, leading to A{beta}40 and A{beta}42 as major products. These two isoforms generate pathological aggregates, whose accumulation correlates with Alzheimers disease (AD). Experiments have shown that even though the natural abundance of A{beta}42 is smaller than that for A{beta}40, the A{beta}42 is more aggregation-prone compared to A{beta}40. Moreover, several single-point mutations are associated with early-onset forms of AD. This work analyzes coarse-grained AWSEM simulations of normal A{beta}40 and A{beta}42 monomers, along with six single-point mutations associated with early on set disease. We analyzed the simulations using the Energy Landscape Visualization Method (ELViM), a reaction coordinate-free approach suited to explore the frustrated energy landscapes of intrinsically disordered proteins. ELViM is shown to distinguish the monomer ensembles of variants that rapidly form fibers from those that do not form fibers as readily. It also delineates the amino-acid contacts characterizing each ensemble. The results shed light on the potential of ELViM to probe intrinsically disordered proteins.

biophysics↗

bioRxiv2021

Apropos of Universal Epitope Discovery for COVID-19 Vaccines: A Framework for Targeted Phage Display-Based Delivery and Integration of New Evaluation Tools

Targeted bacteriophage (phage) particles are potentially attractive yet inexpensive platforms for immunization. Herein, we describe targeted phage capsid display of an immunogenically relevant epitope of the SARS-CoV-2 Spike protein that is empirically conserved, likely due to the high mutational cost among all variants identified to date. This observation may herald an approach to developing vaccine candidates for broad-spectrum, towards universal, protection against multiple emergent variants of coronavirus that cause COVID-19.

microbiology↗

bioRxiv2021

SMOG 2 and OpenSMOG: Extending the limits of structure-based models

Applying simulations with structure-based (G[o]-like) models has proven to be an effective strategy for investigating the factors that control biomolecular dynamics. The common element of these models is that some (or all) of the intra/inter-molecular inter-actions are explicitly defined to stabilize an experimentally-determined structure. To facilitate the development and application of this broad class of models, we previously released the SMOG 2 software package. This suite allows one to easily customize and distribute structure-based (i.e. SMOG) models for any type of polymer-ligand system. Since its original release, user feedback has driven the implementation of numerous enhancements. Here, we describe recent extensions to the software and demonstrate the capabilities of the most recent version, SMOG v2.4. Changes include new tools that aid user-defined customization of force fields, as well as an interface with the OpenMM simulation libraries (OpenSMOG v1.0). To illustrate the utility of these advances, we present several applications of SMOG2 and OpenSMOG, which include systems with millions of atoms, long polymers and explicit ions. We also highlight how one can incorporate non-structure-based (e.g. AMBER-based) energetics to define a hybrid class of models. The representative applications include large-scale rearrangements of the SARS-CoV-2 Spike protein, the HIV-1 capsid in the presence of explicit ions, and crystallographic lattices of ribosomes and proteins. In summary, SMOG 2 and OpenSMOG provide robust support for researchers who seek to apply structure-based models to large and/or intricate biomolecular systems.

biophysics↗