Reliable prediction of T cell specificity against antigenic signatures is a formidable task, complicated 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 interface to accurately predict MHC-allele-restricted TCR-peptide interactions has remained challenging. Here, we present RACER-m, a coarse-grained structural model leveraging key biophysical information from the diversity of publicly available TCR-antigen crystal structures. Explicit inclusion of structural content substantially reduces the required number of training examples and maintains reliable predictions of TCR-recognition specificity and sensitivity across diverse biological contexts. Our model capably identifies biophysically meaningful point-mutant peptides that affect binding affinity, distinguishing its ability in predicting TCR specificity of point-mutants from alternative sequence-based methods. Its application is broadly applicable to studies involving both closely related and structurally diverse TCR-peptide pairs.

RNA structure and functional dynamics play fundamental roles in controlling biological systems. Molecular dynamics simulation, which can characterize interactions at an atomistic level, can advance the understanding on new drug discovery, manufacturing, and delivery mechanisms. However, it is computationally unattainable to support the development of a digital twin for enzymatic reaction network mechanism learning, and end-to-end bioprocess design and control. Thus, we create a hybrid ("mechanistic + machine learning") model characterizing the interdependence of RNA structure and functional dynamics from atomistic to macroscopic levels. To assess the proposed modeling strategy, in this paper, we consider RNA degradation which is a critical process in cellular biology that affects gene expression. The empirical study on RNA lifetime prediction demonstrates the promising performance of the proposed multi-scale bioprocess hybrid modeling strategy.

In human cells, the genomic DNA are associated with proteins to form compact chromatin structures in the nucleus. In the past decades, significant efforts have been made to obtain the three-dimensional (3D) structures of chromatin and to understand the mechanism driving the folding process of the genome, with the goal of understanding the relationship between the 3D structures and the gene regulation and expression. Recently, the advance of experimental techniques makes it possible to investigate the structural features in chromatin, such as compartmentalization and loops, at fine resolutions, which also inspired us to develop a physical model for understanding the folding mechanism of chromatin structures at comparable resolutions. Here, we introduce a theoretical model at nucleosome resolution which not only generates chromatin conformations consistent with experimental data, but also facilitates the investigation the folding mechanisms, such as loop formation as well as potential underlying regulations between different loops. In this model, every nucleosome in the chromatin is represented by a bead with the same diameter of the nucleosome while neighboring beads are connected at the distance comparable to the length of linker DNA between nucleosomes, which makes it possible to precisely compare the simulated chromatin conformations with experimentally measurable quantities. As an example, we calculate the chromatin volume concentrations from the simulated conformations, which are comparable to the experimental measures using ChromEMT. This model provides significant insights to chromatin 3D structures at fine resolutions, which also serves as a powerful tool for future investigations such as how structures affect gene regulations and expressions.

Nuclear compartments are prominent features of 3D chromatin organization, but sequencing depth limitations have impeded investigation at ultra fine-scale. CTCF loops are generally studied at a finer scale, but the impact of looping on proximal interactions remains enigmatic. Here, we critically examine nuclear compartments and CTCF loop-proximal interactions using a combination of in situ Hi-C at unparalleled depth, algorithm development, and biophysical modeling. Producing a large Hi-C map with 33 billion contacts in conjunction with an algorithm for performing principal component analysis on sparse, super massive matrices (POSSUMM), we resolve compartments to 500 bp. Our results demonstrate that essentially all active promoters and distal enhancers localize in the A compartment, even when flanking sequences do not. Furthermore, we find that the TSS and TTS of paused genes are often segregated into separate compartments. We then identify diffuse interactions that radiate from CTCF loop anchors, which correlate with strong enhancer-promoter interactions and proximal transcription. We also find that these diffuse interactions depend on CTCF's RNA binding domains. In this work, we demonstrate features of fine-scale chromatin organization consistent with a revised model in which compartments are more precise than commonly thought while CTCF loops are more protracted.

Protein synthesis by the ribosome involves a wide range of large-scale conformational rearrangements. While structural methods have provided exquisite snapshots of this machine during function, and single-molecule methods have tracked transitions between stable conformations, the kinetics is ultimately controlled by free-energy barriers. To begin to probe these barriers and identify the interactions that are characteristic of the associated transition states, we are developing and applying a range of atomic-resolution models that employ simplified energetic representations (i.e. structure-based SMOG models). While early applications of these models illustrated the relationship between tRNA structure and kinetics, newer variants have allowed for larger-scale motions and ionic effects to be studied. As an example, recent efforts have shown how entropy contributes to the dynamics of subunit rotation in the yeast ribosome, where the “small” (∼1 MDa) subunit undergoes reversible ∼10-degree rotations. Similar strategies have elucidated the influence of key ribosomal proteins during hybrid-state formation in the human mitoribosome. In addition, recently developed explicit-ion models have shown that small changes in ionic concentrations can control rate-limiting free-energy barriers during tRNA rearrangements (e.g. accommodation) on the ribosome. Together, these efforts are uncovering the intricate balance of energetic factors that control translation across the kingdoms of life.

Protein synthesis involves a complex series of large-scale conformational changes in the ribosome. While long-lived intermediate states of these processes can be characterized by experiments, computational methods can be used to identify the interactions that contribute to the rate-limiting free-energy barriers. To this end, we use a simplified energetic model to perform molecular dynamics (MD) simulations of aminoacyl-tRNA (aa-tRNA) accommodation on the ribosome. While numerous studies have probed the energetics of the early stages of accommodation, we focus on the final stage of accommodation, where the 3'-CCA tail of aa-tRNA enters the peptidyl transferase center (PTC). These simulations show how a distinct intermediate is induced by steric confinement of the tail, immediately before it completes accommodation. Multiple pathways for 3'-CCA tail accommodation can be quantitatively distinguished, where the tail enters the PTC by moving past a pocket enclosed by Helix 89, 90, and 92, or through an alternate route formed by Helix 93 and the P-site tRNA. C2573, located within Helix 90, is shown to provide the largest contribution to this late-accommodation steric barrier, such that sub-Å perturbations to this residue can alter the time scale of tail accommodation by nearly an order of magnitude. In terms of biological function, these calculations suggest how this late-stage sterically induced barrier may contribute to tRNA proofreading by the ribosome.

Proper ionic concentrations are required for the functional dynamics of RNA and ribonucleoprotein (RNP) assemblies. While experimental and computational techniques have provided many insights into the properties of chelated ions, less is known about the energetic contributions of diffuse ions to large-scale conformational rearrangements. To address this, we present a model that is designed to quantify the influence of diffuse monovalent and divalent ions on the dynamics of biomolecular assemblies. This model employs all-atom (non-H) resolution and explicit ions, where effective potentials account for hydration effects. We first show that the model accurately predicts the number of excess Mg2+ ions for prototypical RNA systems, at a level comparable to modern coarse-grained models. We then apply the model to a complete ribosome and show how the balance between diffuse Mg2+ and K+ ions can control the dynamics of tRNA molecules during translation. The model predicts differential effects of diffuse ions on the free-energy barrier associated with tRNA entry and the energy of tRNA binding to the ribosome. Together, this analysis reveals the direct impact of diffuse ions on the dynamics of an RNP assembly.

SummaryNuclear compartments segregate active from inactive chromatin, but sequencing depth limitations have impeded investigation at fine-scale. Here, we critically examine nuclear compartments using in situ Hi-C at unparalleled depth, novel algorithm development, biophysical modelling, and super-resolution microscopy. Producing the largest Hi-C map to date with 33 billion contacts in conjunction with the POSSUMM algorithm we resolve compartments to 500 bp. In contrast to coarse-resolution mapping, our results demonstrate that essentially all active promoters and distal enhancers localize in the A compartment, even when flanking sequences do not. Furthermore, we find that the TSS and TTS of paused genes are often segregated into separate compartments. These fine-scale compartments are accurately simulated by a polymer physics model of phase separation and help explain chromatin conformation patterns seen by OligoSTORM imaging. These results are consistent with a model in which phase separation creates compartments at the scale of individual DNA regulatory elements.

Applying simulations with structure-based (Gō-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.

Metal-organic frameworks (MOF) are promising media for achieving solid-state Mg2+ conduction and developing a magnesium-based battery. To this end, the chemical behavior and transport properties of an Mg(TFSI)2/DME electrolyte system inside Mg-MOF-74 were studied by density functional theory (DFT). We found that inside the MOF chemical environment, solvent and anion molecules occupy the coordinatively unsaturated open metal sites of Mg-MOF-74, while Mg2+ ions adsorb directly onto the carboxylate group of the MOF organic linker. These predicted binding geometries were further corroborated by IR spectroscopy. We computed the free energies of desolvation of Mg2+ ions inside MOF to investigate the capacity of Mg-MOF-74 thin film to act as a separator for selective Mg2+ transport. We showed that Mg-MOF-74 could facilitate partial, but not full, desolvation of Mg2+. We found that the dominant minimum-energy pathway (MEP) for Mg2+ conduction inside Mg-MOF-74 corresponds to a "solvent hopping" mechanism, with an energy barrier of 4.4 kcal/mol. The molar conductivity of Mg2+ associated with the idealized solvent hopping mechanism along the MOF one-dimensional channel was predicted to be 2.4 × 10-3 S cm-1 M-1, which is one to two orders of magnitude greater than the experimentally measured value of 1.2 × 10-4 S cm-1 M-1 (with an estimated Mg2+ concentration). We have discussed several possible factors contributing to this apparent discrepancy. The current work demonstrates the validity of the computational strategies applied and the structural models constructed for the understanding of fast and selective Mg2+ transport in Mg-MOF-74, which serves as a cornerstone for studying transport of multivalent ions in MOFs. Furthermore, it provides detailed molecular-level insights that are not yet accessible experimentally.

The ribosome is a biomolecular machine that undergoes multiple large-scale structural rearrangements during protein elongation. Here, we focus on a conformational rearrangement during translocation, known as P/E hybrid-state formation. Using a model that explicitly represents all non-hydrogen atoms, we simulated more than 120 spontaneous transitions, where the tRNA molecule is displaced between the P and E sites of the large subunit. In addition to predicting a free-energy landscape that is consistent with previous experimental observations, the simulations reveal how a six-residue gate-like region can limit P/E formation, where sub-angstrom structural perturbations lead to an order-of-magnitude change in kinetics. Thus, this precisely defined set of residues represents a novel target that may be used to control functional dynamics in bacterial ribosomes. This theoretical analysis establishes a direct relationship between ribosome structure and large-scale dynamics, and it suggests how next-generation experiments may precisely dissect the energetics of hybrid formation on the ribosome.

AbstractThe incompatibility between the anode and the cathode chemistry limits the used of Mg as an anode. This issue may be addressed by separating the anolyte and the catholyte with a membrane that only allows for Mg2+ transport. Mg‐MOF‐74 thin films were used as the separator for this purpose. It was shown to meet the needs of low‐resistance, selective Mg2+ transport. The uniform MOF thin films supported on Au substrate with thicknesses down to ca. 202 nm showed an intrinsic resistance as low as 6.4 Ω cm2, with the normalized room‐temperature ionic conductivity of ca. 3.17×10−6 S cm−1. When synthesized directly onto a porous anodized aluminum oxide (AAO) support, the resulting films were used as a standalone membrane to permit stable, low‐overpotential Mg striping and plating for over 100 cycles at a current density of 0.05 mA cm−2. The film was effective in blocking solvent molecules and counterions from crossing over for extended period of time.

Structure-based models allow milliseconds effective timescale simulations of large biomolecular assemblies. In a structure-based model, the prevalent potential energy minima are defined to correspond to native structures. Here, we have developed an all-atom structure-based model in which non-hydrogen atoms and monovalent (K+, Cl-) and divalent (Mg 2+) ions electrostatics are described explicitly. The effective potentials for ion-ion and ion-RNA interactions are constructed such that solvation is treated implicitly. To ensure correct accumulation of various ionic species near the RNA, charge-charge desolvation potential is introduced. Using an iterative refinement protocol, the effective structure-based parameters aim to reproduce the potential of mean force obtained from two-microsecond explicit-solvent simulations of model RNA structure, until the parameters converge iteratively, optimizes the weights in the effective potential. This transferable set of effective potentials for ion-ion and ion-RNA interactions are then used in structure-based models of group II introns. We study the folding of solution NMR model structure D1κζ from group IIB intron Sc.ai5γ. We determine the association sites and the residence times of the metal ions around the RNA. We study the spatial distribution of Mg2+ as a function of Mg2+ ion concentration to provideimprints into high-affinity ion-RNA interactions that can be associated with tertiary motifs. We provide insights into how diffuse ion atmosphere, outer-sphere ions, site-bound ions, and flexibility drive conformation fluctuations in biomolecular assemblies.

A generalization of the Adam-Gibbs model of relaxation in glass-forming liquids is formulated that takes into account fluctuation in the number of molecules inside the cooperative region. The configurational fraction links the excess entropy with kinetic properties described in the Adam-Gibbs model. We express the configurational fraction at the glass-transition temperature in terms of the width of the distribution of relaxation times, the nonlinearity parameter that demarcates the variations of the relaxation time with structure and temperature, the steepness index that is proportional to the slope of the logarithm of the relaxation time with respect to temperature, the excess heat capacity under constant pressure, and the number of correlated molecules or structural units. The configurational fraction in the absence of fluctuation effects is also determined for several glass-forming liquids at the glass-transition temperature.

Over the last 20 years, the application of structure-based (Gō-like) models has ranged from protein folding with coarse-grained models to all-atom representations of large-scale molecular assemblies. While there are many variants that may be employed, the common feature of these models is that some (or all) of the stabilizing energetic interactions are defined based on the knowledge of a particular experimentally obtained conformation. With the generality of this approach, there was a need for a versatile computational platform for designing and implementing this class of models. To this end, the SMOG 2 software package provides an easy-to-use interface, where the user has full control of the model parameters. This software allows the user to edit XML-formatted files in order to provide definitions of new structure-based models. SMOG 2 reads these "template" files and maps the interactions onto specific structures, which are provided in PDB format. The force field files produced by SMOG 2 may then be used to perform simulations with a variety of popular molecular dynamics suites. In this chapter, we describe some of the key features of the SMOG 2 package, while providing examples and strategies for applying these techniques to complex (often large-scale) molecular assemblies, such as the ribosome.

We unravel the internal and collective modes of a widely studied 58-nucleotide rRNA fragment in solvent using atomically detailed molecular dynamics simulations. The variation of lifetimes for water hydrogen bonds with nucleotide groups indicates heterogeneity of water dynamics on the RNA surface. The time scales of interactions of the discrete water molecules with RNA nucleotides extend from several hundred picoseconds to a few nanoseconds. We determine all of the association sites and the spatial distribution of residence times for Mg2+, K+, and water molecules in those sites. We provide insights into the population of Mg2+ and K+ ions and water molecules in the outer sphere and how their fluctuations are intricately linked with the kinetics of the 58-mer. We find that many of the long-lived Mg2+ sites identified from the simulations agree with the locations of ions in the X-ray structure. We determine the excess ion atmosphere around the rRNA and compare it with experimental data. We investigate the collective behavior of RNA, ions, and water, by performing a joint principle component analysis for the Cartesian coordinates of the RNA phosphorus atoms and for the occupation counts of the association sites. Our results indicate that the 58-mer system is a complex polymer, composed of RNA that is encased by a fluctuating network of associated counterions, co-ions, and water.

A practical strategy is proposed to facilitate the migration of holes in semiconductor (the low rate of which limits photocatalytic efficiency) by taking advantage of the Schottky barrier between p-type semiconductor and metal. A high work function is found to serve as an important selection rule for building such desirable Schottky junction between semiconductor surface facets and metal. The intrinsic charge spatial distribution has to be taken into account when selecting the facets, as it results in accumulation of photoexcited electrons and holes on certain semiconductor facets. Importantly, the facets have a high work function, the same characteristic required for the formation of Schottky junction in a p-type semiconductor-metal hybrid structure. As a result, the semiconductor crystals in the hybrid design may be better enclosed by single facets with high work function, so as to synergize the two effects: Schottky barrier versus charge spatial separation.