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 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.

Explicit ion modeling predicts physicochemical interactions for chromatin organization.

Molecular mechanisms that dictate chromatin organization in vivo are under active investigation, and the extent to which intrinsic interactions contribute to this process remains debatable. A central quantity for evaluating their contribution is the strength of nucleosome-nucleosome binding, which previous experiments have estimated to range from 2 to 14 kBT. We introduce an explicit ion model to dramatically enhance the accuracy of residue-level coarse-grained modeling approaches across a wide range of ionic concentrations. This model allows for de novo predictions of chromatin organization and remains computationally efficient, enabling large-scale conformational sampling for free energy calculations. It reproduces the energetics of protein-DNA binding and unwinding of single nucleosomal DNA, and resolves the differential impact of mono- and divalent ions on chromatin conformations. Moreover, we showed that the model can reconcile various experiments on quantifying nucleosomal interactions, providing an explanation for the large discrepancy between existing estimations. We predict the interaction strength at physiological conditions to be 9 kBT, a value that is nonetheless sensitive to DNA linker length and the presence of linker histones. Our study strongly supports the contribution of physicochemical interactions to the phase behavior of chromatin aggregates and chromatin organization inside the nucleus.

Residue coevolution and mutational landscape for OmpR and NarL response regulator subfamilies.

DNA-binding response regulators (DBRRs) are a broad class of proteins that operate in tandem with their partner kinase proteins to form two-component signal transduction systems in bacteria. Typical DBRRs are composed of two domains where the conserved N-terminal domain accepts transduced signals and the evolutionarily diverse C-terminal domain binds to DNA. These domains are assumed to be functionally independent, and hence recombination of the two domains should yield novel DBRRs of arbitrary input/output response, which can be used as biosensors. This idea has been proved to be successful in some cases; yet, the error rate is not trivial. Improvement of the success rate of this technique requires a deeper understanding of the linker-domain and inter-domain residue interactions, which have not yet been thoroughly examined. Here, we studied residue coevolution of DBRRs of the two main subfamilies (OmpR and NarL) using large collections of bacterial amino acid sequences to extensively investigate the evolutionary signatures of linker-domain and inter-domain residue interactions. Coevolutionary analysis uncovered evolutionarily selected linker-domain and inter-domain residue interactions of known experimental structures, as well as previously unknown inter-domain residue interactions. We examined the possibility of these inter-domain residue interactions as contacts that stabilize an inactive conformation of the DBRR where DNA binding is inhibited for both subfamilies. The newly gained insights on linker-domain/inter-domain residue interactions and shared inactivation mechanisms improve the understanding of the functional mechanism of DBRRs, providing clues to efficiently create functional DBRR-based biosensors. Additionally, we show the feasibility of applying coevolutionary landscape models to predict the functionality of domain-swapped DBRR proteins. The presented result demonstrates that sequence information can be used to filter out bioengineered DBRR proteins that are predicted to be nonfunctional due to a high negative predictive value.

ß­adrenergic receptor activation promotes the proliferation of HepG2 cells via the ERK1/2/CREB pathways.

Primary liver cancer is one of the most frequently diagnosed malignant tumors seen in clinics, and typically exhibits aggressive invasive behaviors, a poor prognosis, and is associated with high mortality rates. Long-term stress exposure causes norepinephrine (NE) release and activates the ß-Adrenergic receptor (ß-AR), which in turn exacerbates the occurrence and development of different types of cancers; however, the molecular mechanisms of ß-AR in liver cancer are not fully understood. In the present study, reverse transcription (RT)-PCR and RT-quantitative PCR showed that ß-AR expression was upregulated in human liver cancer cells (HepG2) compared with normal liver cells (LO2). Moreover, NE treatment promoted the growth of HepG2 cells, which could be blocked by propranolol, a ß-AR antagonist. Notably, NE had no significant effect on the migration and epithelial-mesenchymal transition in HepG2 cells. Further experiments revealed that NE increased the phosphorylation levels of the extracellular signal-regulated kinase 1/2 (ERK1/2) and cyclic adenosine monophosphate response element-binding protein (CREB), while inhibition of ERK1/2 and CREB activation significantly blocked NE-induced cell proliferation. In summary, the findings of the present study suggested that ß-adrenergic receptor activation promoted the proliferation of HepG2 cells through ERK1/2/CREB signaling pathways.

Cucurbitacin E inhibits the proliferation of glioblastoma cells via FAK/AKT/GSK3ß pathway.

Glioblastoma (GBM) is the most common primary intracranial tumor in the brain with high growth rate and high mortality rate. Cucurbitacin E (CUE), a tetracyclic triterpene compound derived from species of the genus Cucurbita, has been demonstrated to display significant antitumor effects on various malignancies. In the present study, the effects of CUE on GBM and its underlying molecular mechanisms were explored. The data revealed that CUE inhibited the proliferation of the GBM cell lines U87­MG and U251­MG in a dose­ and time­dependent manner. Mechanistically, CUE reduced the phosphorylation of focal adhesion kinase (FAK), protein kinase B (AKT), and glycogen synthase kinase­3ß (GSK3ß) at both basal and epidermal growth factor (EGF)­induced levels. Moreover, CUE inhibited the proliferation of U87­MG and U251­MG cells by blocking EGF­induced phosphorylation of the FAK, AKT and GSK3ß. Subsequently, CUE reduced the expression of cyclinD1 and cyclinB1. Collectively, these results indicated that CUE inhibited the proliferation of U87­MG and U251­MG cells by suppressing the FAK/AKT/GSK3ß signaling pathway, which also suggested that CUE has potential application in treating GBM.

Explicit Ion Modeling Predicts Physicochemical Interactions for Chromatin Organization.

Molecular mechanisms that dictate chromatin organization in vivo are under active investigation, and the extent to which intrinsic interactions contribute to this process remains debatable. A central quantity for evaluating their contribution is the strength of nucleosome-nucleosome binding, which previous experiments have estimated to range from 2 to 14 kBT. We introduce an explicit ion model to dramatically enhance the accuracy of residue-level coarse-grained modeling approaches across a wide range of ionic concentrations. This model allows for de novo predictions of chromatin organization and remains computationally efficient, enabling large-scale conformational sampling for free energy calculations. It reproduces the energetics of protein-DNA binding and unwinding of single nucleosomal DNA, and resolves the differential impact of mono and divalent ions on chromatin conformations. Moreover, we showed that the model can reconcile various experiments on quantifying nucleosomal interactions, providing an explanation for the large discrepancy between existing estimations. We predict the interaction strength at physiological conditions to be 9 kBT, a value that is nonetheless sensitive to DNA linker length and the presence of linker histones. Our study strongly supports the contribution of physicochemical interactions to the phase behavior of chromatin aggregates and chromatin organization inside the nucleus.

Harmine exerts anxiolytic effects by regulating neuroinflammation and neuronal plasticity in the basolateral amygdala.

Increasing evidence indicates that an altered immune system is closely linked to the pathophysiology of anxiety disorders, and inhibition of neuroinflammation may represent an effective therapeutic strategy to treat anxiety disorders. Harmine, a beta-carboline alkaloid in various medicinal plants, has been widely reported to display anti-inflammatory and potentially anxiolytic effects. However, the exact underlying mechanisms are not fully understood. Our recent study has demonstrated that dysregulation of neuroplasticity in the basolateral amygdala (BLA) contributes to the pathological processes of inflammation-related anxiety. In this study, using a mouse model of anxiety challenged with Escherichia coli lipopolysaccharide (LPS), we found that harmine alleviated LPS-induced anxiety-like behaviors in mice. Mechanistically, harmine significantly prevented LPS-induced neuroinflammation by suppressing the expression of pro-inflammatory cytokines including IL-1ß and TNF-α. Meanwhile, ex vivo whole-cell slice electrophysiology combined with optogenetics showed that LPS-induced increase of medial prefrontal cortex (mPFC)-driven excitatory but not inhibitory synaptic transmission onto BLA projection neurons, thereby alleviating LPS-induced shift of excitatory/inhibitory balance towards excitation. In addition, harmine attenuated the increased intrinsic neuronal excitability of BLA PNs by reducing the medium after-hyperpolarization. In conclusion, our findings provide new evidence that harmine may exert its anxiolytic effect by downregulating LPS-induced neuroinflammation and restoring the changes in neuronal plasticity in BLA PNs.

Contact map dependence of a T-cell receptor binding repertoire.

The T-cell arm of the adaptive immune system provides the host protection against unknown pathogens by discriminating between host and foreign material. This discriminatory capability is achieved by the creation of a repertoire of cells each carrying a T-cell receptor (TCR) specific to non-self-antigens displayed as peptides bound to the major histocompatibility complex (pMHC). The understanding of the dynamics of the adaptive immune system at a repertoire level is complex, due to both the nuanced interaction of a TCR-pMHC pair and to the number of different possible TCR-pMHC pairings, making computationally exact solutions currently unfeasible. To gain some insight into this problem, we study an affinity-based model for TCR-pMHC binding in which a crystal structure is used to generate a distance-based contact map that weights the pairwise amino acid interactions. We find that the TCR-pMHC binding energy distribution strongly depends both on the number of contacts and the repeat structure allowed by the topology of the contact map of choice; this in turn influences T-cell recognition probability during negative selection, with higher variances leading to higher survival probabilities. In addition, we quantify the degree to which neoantigens with mutations in sites with higher contacts are recognized at a higher rate.

Chromatin fiber breaks into clutches under tension and crowding.

The arrangement of nucleosomes inside chromatin is of extensive interest. While in vitro experiments have revealed the formation of 30 nm fibers, most in vivo studies have failed to confirm their presence in cell nuclei. To reconcile the diverging experimental findings, we characterized chromatin organization using a residue-level coarse-grained model. The computed force-extension curve matches well with measurements from single-molecule experiments. Notably, we found that a dodeca-nucleosome in the two-helix zigzag conformation breaks into structures with nucleosome clutches and a mix of trimers and tetramers under tension. Such unfolded configurations can also be stabilized through trans interactions with other chromatin chains. Our study suggests that unfolding from chromatin fibers could contribute to the irregularity of in vivo chromatin configurations. We further revealed that chromatin segments with fibril or clutch structures engaged in distinct binding modes and discussed the implications of these inter-chain interactions for a potential sol-gel phase transition.

Ligand-induced transmembrane conformational coupling in monomeric EGFR.

Single pass cell surface receptors regulate cellular processes by transmitting ligand-encoded signals across the plasma membrane via changes to their extracellular and intracellular conformations. This transmembrane signaling is generally initiated by ligand binding to the receptors in their monomeric form. While subsequent receptor-receptor interactions are established as key aspects of transmembrane signaling, the contribution of monomeric receptors has been challenging to isolate due to the complexity and ligand-dependence of these interactions. By combining membrane nanodiscs produced with cell-free expression, single-molecule Förster Resonance Energy Transfer measurements, and molecular dynamics simulations, we report that ligand binding induces intracellular conformational changes within monomeric, full-length epidermal growth factor receptor (EGFR). Our observations establish the existence of extracellular/intracellular conformational coupling within a single receptor molecule. We implicate a series of electrostatic interactions in the conformational coupling and find the coupling is inhibited by targeted therapeutics and mutations that also inhibit phosphorylation in cells. Collectively, these results introduce a facile mechanism to link the extracellular and intracellular regions through the single transmembrane helix of monomeric EGFR, and raise the possibility that intramolecular transmembrane conformational changes upon ligand binding are common to single-pass membrane proteins.

LncRNA ASB16-AS1 drives proliferation, migration, and invasion of colorectal cancer cells through regulating miR-185-5p/TEAD1 axis.

As a common malignant tumor, colorectal cancer (CRC) has a high incidence. Recent investigations have suggested that although great improvement has been achieved in the survival rate of early-stage CRC patients, the overall survival rate remains low. Mounting reports have proved that lncRNAs take part in the development of various cancers and possess the regulatory functions in cancers. For example, ASB16 antisense RNA 1 (ASB16-AS1) is a poorly researched novel lncRNA whose specific functions in CRC are still unknown. In our research, we discovered that ASB16-AS1 was with high expression in CRC cells. In addition, ASB16-AS1 silencing restrained the proliferation, migration, invasion, and stemness while accelerating cell apoptosis of CRC cells. Mechanism experiments were applied to explore the regulatory mechanism of ASB16-AS1. It turned out that miR-185-5p could interact with ASB16-AS1 and inhibited the progression of CRC cells. TEAD1 (TEA domain transcription factor1) - a major effector of the Hippo signaling was proved to serve as the target of miR-185-5p and promote CRC development. In short, ASB16-AS1 drove the progression of CRC through the regulation of miR-185-5p/TEAD1 axis.

Multiscale modeling of genome organization with maximum entropy optimization.

Three-dimensional (3D) organization of the human genome plays an essential role in all DNA-templated processes, including gene transcription, gene regulation, and DNA replication. Computational modeling can be an effective way of building high-resolution genome structures and improving our understanding of these molecular processes. However, it faces significant challenges as the human genome consists of over 6 × 109 base pairs, a system size that exceeds the capacity of traditional modeling approaches. In this perspective, we review the progress that has been made in modeling the human genome. Coarse-grained models parameterized to reproduce experimental data via the maximum entropy optimization algorithm serve as effective means to study genome organization at various length scales. They have provided insight into the principles of whole-genome organization and enabled de novo predictions of chromosome structures from epigenetic modifications. Applications of these models at a near-atomistic resolution further revealed physicochemical interactions that drive the phase separation of disordered proteins and dictate chromatin stability in situ. We conclude with an outlook on the opportunities and challenges in studying chromosome dynamics.

Cooperative DNA looping by PRC2 complexes.

Polycomb repressive complex 2 (PRC2) is an essential protein complex that silences gene expression via post-translational modifications of chromatin. This paper combined homology modeling, atomistic and coarse-grained molecular dynamics simulations, and single-molecule force spectroscopy experiments to characterize both its full-length structure and PRC2-DNA interactions. Using free energy calculations with a newly parameterized protein-DNA force field, we studied a total of three potential PRC2 conformations and their impact on DNA binding and bending. Consistent with cryo-EM studies, we found that EZH2, a core subunit of PRC2, provides the primary interface for DNA binding, and its curved surface can induce DNA bending. Our simulations also predicted the C2 domain of the SUZ12 subunit to contact DNA. Multiple PRC2 complexes bind with DNA cooperatively via allosteric communication through the DNA, leading to a hairpin-like looped configuration. Single-molecule experiments support PRC2-mediated DNA looping and the role of AEBP2 in regulating such loop formation. The impact of AEBP2 can be partly understood from its association with the C2 domain, blocking C2 from DNA binding. Our study suggests that accessory proteins may regulate the genomic location of PRC2 by interfering with its DNA interactions.

Exploring Energy Landscapes of Intrinsically Disordered Proteins: Insights into Functional Mechanisms.

Intrinsically disordered proteins (IDPs) lack a rigid three-dimensional structure and populate a polymorphic ensemble of conformations. Because of the lack of a reference conformation, their energy landscape representation in terms of reaction coordinates presents a daunting challenge. Here, our newly developed energy landscape visualization method (ELViM), a reaction coordinate-free approach, shows its prime application to explore frustrated energy landscapes of an intrinsically disordered protein, prostate-associated gene 4 (PAGE4). PAGE4 is a transcriptional coactivator that potentiates the oncogene c-Jun. Two kinases, namely, HIPK1 and CLK2, phosphorylate PAGE4, generating variants phosphorylated at different serine/threonine residues (HIPK1-PAGE4 and CLK2-PAGE4, respectively) with opposing functions. While HIPK1-PAGE4 predominantly phosphorylates Thr51 and potentiates c-Jun, CLK2-PAGE4 hyperphosphorylates PAGE4 and attenuates transactivation. To understand the underlying mechanisms of conformational diversity among different phosphoforms, we have analyzed their atomistic trajectories simulated using AWSEM forcefield, and the energy landscapes were elucidated using ELViM. This method allows us to identify and compare the population distributions of different conformational ensembles of PAGE4 phosphoforms using the same effective phase space. The results reveal a predominant conformational ensemble with an extended C-terminal segment of WT PAGE4, which exposes a functional residue Thr51, implying its potential of undertaking a fly-casting mechanism while binding to its cognate partner. In contrast, for HIPK1-PAGE4, a compact conformational ensemble enhances its population sequestering phosphorylated-Thr51. This clearly explains the experimentally observed weaker affinity of HIPK1-PAGE4 for c-Jun. ELViM appears as a powerful tool, especially to analyze the highly frustrated energy landscape representation of IDPs where appropriate reaction coordinates are hard to apprehend.

Stability and folding pathways of tetra-nucleosome from six-dimensional free energy surface.

The three-dimensional organization of chromatin is expected to play critical roles in regulating genome functions. High-resolution characterization of its structure and dynamics could improve our understanding of gene regulation mechanisms but has remained challenging. Using a near-atomistic model that preserves the chemical specificity of protein-DNA interactions at residue and base-pair resolution, we studied the stability and folding pathways of a tetra-nucleosome. Dynamical simulations performed with an advanced sampling technique uncovered multiple pathways that connect open chromatin configurations with the zigzag crystal structure. Intermediate states along the simulated folding pathways resemble chromatin configurations reported from in situ experiments. We further determined a six-dimensional free energy surface as a function of the inter-nucleosome distances via a deep learning approach. The zigzag structure can indeed be seen as the global minimum of the surface. However, it is not favored by a significant amount relative to the partially unfolded, in situ configurations. Chemical perturbations such as histone H4 tail acetylation and thermal fluctuations can further tilt the energetic balance to stabilize intermediate states. Our study provides insight into the connection between various reported chromatin configurations and has implications on the in situ relevance of the 30 nm fiber.

Rapid Assessment of T-Cell Receptor Specificity of the Immune Repertoire.

Accurate assessment of TCR-antigen specificity at the whole immune repertoire level lies at the heart of improved cancer immunotherapy, but predictive models capable of high-throughput assessment of TCR-peptide pairs are lacking. Recent advances in deep sequencing and crystallography have enriched the data available for studying TCR-p-MHC systems. Here, we introduce a pairwise energy model, RACER, for rapid assessment of TCR-peptide affinity at the immune repertoire level. RACER applies supervised machine learning to efficiently and accurately resolve strong TCR-peptide binding pairs from weak ones. The trained parameters further enable a physical interpretation of interacting patterns encoded in each specific TCR-p-MHC system. When applied to simulate thymic selection of an MHC-restricted T-cell repertoire, RACER accurately estimates recognition rates for tumor-associated neoantigens and foreign peptides, thus demonstrating its utility in helping address the large computational challenge of reliably identifying the properties of tumor antigen-specific T-cells at the level of an individual patient's immune repertoire.

Single-molecule and in silico dissection of the interaction between Polycomb repressive complex 2 and chromatin.

Polycomb repressive complex 2 (PRC2) installs and spreads repressive histone methylation marks on eukaryotic chromosomes. Because of the key roles that PRC2 plays in development and disease, how this epigenetic machinery interacts with DNA and nucleosomes is of major interest. Nonetheless, the mechanism by which PRC2 engages with native-like chromatin remains incompletely understood. In this work, we employ single-molecule force spectroscopy and molecular dynamics simulations to dissect the behavior of PRC2 on polynucleosome arrays. Our results reveal an unexpectedly diverse repertoire of PRC2 binding configurations on chromatin. Besides reproducing known binding modes in which PRC2 interacts with bare DNA, mononucleosomes, and adjacent nucleosome pairs, our data also provide direct evidence that PRC2 can bridge pairs of distal nucleosomes. In particular, the "1-3" bridging mode, in which PRC2 engages two nucleosomes separated by one spacer nucleosome, is a preferred low-energy configuration. Moreover, we show that the distribution and stability of different PRC2-chromatin interaction modes are modulated by accessory subunits, oncogenic histone mutations, and the methylation state of chromatin. Overall, these findings have implications for the mechanism by which PRC2 spreads histone modifications and compacts chromatin. The experimental and computational platforms developed here provide a framework for understanding the molecular basis of epigenetic maintenance mediated by Polycomb-group proteins.

Molecular-replacement phasing using predicted protein structures from AWSEM-Suite.

The phase problem in X-ray crystallography arises from the fact that only the intensities, and not the phases, of the diffracting electromagnetic waves are measured directly. Molecular replacement can often estimate the relative phases of reflections starting with those derived from a template structure, which is usually a previously solved structure of a similar protein. The key factor in the success of molecular replacement is finding a good template structure. When no good solved template exists, predicted structures based partially on templates can sometimes be used to generate models for molecular replacement, thereby extending the lower bound of structural and sequence similarity required for successful structure determination. Here, the effectiveness is examined of structures predicted by a state-of-the-art prediction algorithm, the Associative memory, Water-mediated, Structure and Energy Model Suite (AWSEM-Suite), which has been shown to perform well in predicting protein structures in CASP13 when there is no significant sequence similarity to a solved protein or only very low sequence similarity to known templates. The performance of AWSEM-Suite structures in molecular replacement is discussed and the results show that AWSEM-Suite performs well in providing useful phase information, often performing better than I-TASSER-MR and the previous algorithm AWSEM-Template.

Protein Structure Refinement Guided by Atomic Packing Frustration Analysis.

Recent advances in machine learning, bioinformatics, and the understanding of the folding problem have enabled efficient predictions of protein structures with moderate accuracy, even for targets where there is little information from templates. All-atom molecular dynamics simulations provide a route to refine such predicted structures, but unguided atomistic simulations, even when lengthy in time, often fail to eliminate incorrect structural features that would prevent the structure from becoming more energetically favorable owing to the necessity of making large scale motions and to overcoming energy barriers for side chain repacking. In this study, we show that localizing packing frustration at atomic resolution by examining the statistics of the energetic changes that occur when the local environment of a site is changed allows one to identify the most likely locations of incorrect contacts. The global statistics of atomic resolution frustration in structures that have been predicted using various algorithms provide strong indicators of structural quality when tested over a database of 20 targets from previous CASP experiments. Residues that are more correctly located turn out to be more minimally frustrated than more poorly positioned sites. These observations provide a diagnosis of both global and local quality of predicted structures and thus can be used as guidance in all-atom refinement simulations of the 20 targets. Refinement simulations guided by atomic packing frustration turn out to be quite efficient and significantly improve the quality of the structures.

Enhancing intracellular accumulation and target engagement of PROTACs with reversible covalent chemistry.

Current efforts in the proteolysis targeting chimera (PROTAC) field mostly focus on choosing an appropriate E3 ligase for the target protein, improving the binding affinities towards the target protein and the E3 ligase, and optimizing the PROTAC linker. However, due to the large molecular weights of PROTACs, their cellular uptake remains an issue. Through comparing how different warhead chemistry, reversible noncovalent (RNC), reversible covalent (RC), and irreversible covalent (IRC) binders, affects the degradation of Bruton's Tyrosine Kinase (BTK), we serendipitously discover that cyano-acrylamide-based reversible covalent chemistry can significantly enhance the intracellular accumulation and target engagement of PROTACs and develop RC-1 as a reversible covalent BTK PROTAC with a high target occupancy as its corresponding kinase inhibitor and effectiveness as a dual functional inhibitor and degrader, a different mechanism-of-action for PROTACs. Importantly, this reversible covalent strategy is generalizable to improve other PROTACs, opening a path to enhance PROTAC efficacy.