The marionette mechanism of domain-domain communication in the antagonist, agonist, and coactivator responses of the estrogen receptor.

The human estrogen receptor α (hERα) is involved in the regulation of growth, development, and tissue homeostasis. Agonists that bind to the receptor's ligand-binding domain (LBD) lead to recruitment of coactivators and the enhancement of gene expression. In contrast, antagonists bind to the LBD and block the binding of coactivators thus decreasing gene expressions. In this work, we carry out simulations using the AWSEM (Associative memory, Water mediated, Structure and Energy Model)-Suite force field along with the 3SPN.2C force field for DNA to predict the structure of hERα and study its dynamics when binding to DNA and coactivators. Using simulations of antagonist-bound hERα and agonist-bound hERα by themselves and also along with bound DNA and coactivators, principal component analyses and free energy landscape analyses capture the pathway of domain-domain communication for agonist-bound hERα. This communication is mediated through the hinge domains that are ordinarily intrinsically disordered. These disordered segments manipulate the hinge domains much like the strings of a marionette as they twist in different ways when antagonists or agonists are bound to the ligand-binding domain.

Structural basis of DNA polymerase θ mediated DNA end joining.

DNA polymerase θ (Pol θ) plays an essential role in the microhomology-mediated end joining (MMEJ) pathway for repairing DNA double-strand breaks. However, the mechanisms by which Pol θ recognizes microhomologous DNA ends and performs low-fidelity DNA synthesis remain unclear. Here, we present cryo-electron microscope structures of the polymerase domain of Lates calcarifer Pol θ with long and short duplex DNA at up to 2.4 Šresolution. Interestingly, Pol θ binds to long and short DNA substrates similarly, with extensive interactions around the active site. Moreover, Pol θ shares a similar active site as high-fidelity A-family polymerases with its finger domain well-closed but differs in having hydrophilic residues surrounding the nascent base pair. Computational simulations and mutagenesis studies suggest that the unique insertion loops of Pol θ help to stabilize short DNA binding and assemble the active site for MMEJ repair. Taken together, our results illustrate the structural basis of Pol θ-mediated MMEJ.

Computationally exploring the mechanism of bacteriophage T7 gp4 helicase translocating along ssDNA.

Bacteriophage T7 gp4 helicase has served as a model system for understanding mechanisms of hexameric replicative helicase translocation. The mechanistic basis of how nucleoside 5'-triphosphate hydrolysis and translocation of gp4 helicase are coupled is not fully resolved. Here, we used a thermodynamically benchmarked coarse-grained protein force field, Associative memory, Water mediated, Structure and Energy Model (AWSEM), with the single-stranded DNA (ssDNA) force field 3SPN.2C to investigate gp4 translocation. We found that the adenosine 5'-triphosphate (ATP) at the subunit interface stabilizes the subunit-subunit interaction and inhibits subunit translocation. Hydrolysis of ATP to adenosine 5'-diphosphate enables the translocation of one subunit, and new ATP binding at the new subunit interface finalizes the subunit translocation. The LoopD2 and the N-terminal primase domain provide transient protein-protein and protein-DNA interactions that facilitate the large-scale subunit movement. The simulations of gp4 helicase both validate our coarse-grained protein-ssDNA force field and elucidate the molecular basis of replicative helicase translocation.

The interplay of miRNAs and ferroptosis in diseases related to iron overload.

Ferroptosis has been conceptualized as a novel cell death modality distinct from apoptosis, necroptosis, pyroptosis and autophagic cell death. The sensitivity of cellular ferroptosis is regulated at multiple layers, including polyunsaturated fatty acid metabolism, glutathione-GPX4 axis, iron homeostasis, mitochondria and other parallel pathways. In addition, microRNAs (miRNAs) have been implicated in modulating ferroptosis susceptibility through targeting different players involved in the execution or avoidance of ferroptosis. A growing body of evidence pinpoints the deregulation of miRNA-regulated ferroptosis as a critical factor in the development and progression of various pathophysiological conditions related to iron overload. The revelation of mechanisms of miRNA-dependent ferroptosis provides novel insights into the etiology of diseases and offers opportunities for therapeutic intervention. In this review, we discuss the interplay of emerging miRNA regulators and ferroptosis players under different pathological conditions, such as cancers, ischemia/reperfusion, neurodegenerative diseases, acute kidney injury and cardiomyopathy. We emphasize on the relevance of miRNA-regulated ferroptosis to disease progression and the targetability for therapeutic interventions.

Targeting ferroptosis by natural products in pathophysiological conditions.

Ferroptosis is a form of cell death that is induced by iron-mediated accumulation of lipid peroxidation. The involvement of ferroptosis in different pathophysiological conditions has offered new perspectives on potential therapeutic interventions. Natural products, which are widely recognized for their significance in drug discovery and repurposing, have shown great promise in regulating ferroptosis by targeting various ferroptosis players. In this review, we discuss the regulatory mechanisms of ferroptosis and its implications in different pathological conditions. We dissect the interactions between natural products and ferroptosis in cancer, ischemia/reperfusion, neurodegenerative diseases, acute kidney injury, liver injury, and cardiomyopathy, with an emphasis on the relevance of ferroptosis players to disease targetability.

Carbon Quantum Dot Modified Reduced Graphene Oxide Framework for Improved Alkali Metal Ion Storage Performance.

Organic materials with redox-active oxygen functional groups are of great interest as electrode materials for alkali-ion storage due to their earth-abundant constituents, structural tunability, and enhanced energy storage properties. Herein, a hybrid carbon framework consisting of reduced graphene oxide and oxygen functionalized carbon quantum dots (CQDs) is developed via the one-pot solvothermal reduction method, and a systematic study is undertaken to investigate its redox mechanism and electrochemical properties with Li-, Na-, and K-ions. Due to the incorporation of CQDs, the hybrid cathode delivers consistent improvements in charge storage performance for the alkali-ions and impressive reversible capacity (257 mAh g-1 at 50 mA g-1 ), rate capability (111 mAh g-1 at 1 A g-1 ), and cycling stability (79% retention after 10 000 cycles) with Li-ion. Furthermore, density functional theory calculations uncover the CQD structure-electrochemical reactivity trends for different alkali-ion. The results provide important insights into adopting CQD species for optimal alkali-ion storage.

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations.

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM's Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM's Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen's early Nobel prize winning experiments by using OpenMM's Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

A Mild Two-Step Synthesis of Structurally Valuable Indole-Fused Derivatives.

A mild two-step synthetic approach for the preparation of structurally valuable indolo[3',2':4,5]pyrrolo[3,2,1-kl]phenothiazines has been developed. In this work, cyclohexanone was used as the key bridge to connect the indole and phenothiazine frameworks to construct a structurally valuable indole-fused derivative. The present protocol achieved the cascade construction of multiple C-hetero bonds, affording a convenient approach access to hexacyclic-fused system that contained both indole and phenothiazine, two privileged skeletons.

AWSEM-Suite: a protein structure prediction server based on template-guided, coevolutionary-enhanced optimized folding landscapes.

The accurate and reliable prediction of the 3D structures of proteins and their assemblies remains difficult even though the number of solved structures soars and prediction techniques improve. In this study, a free and open access web server, AWSEM-Suite, whose goal is to predict monomeric protein tertiary structures from sequence is described. The model underlying the server's predictions is a coarse-grained protein force field which has its roots in neural network ideas that has been optimized using energy landscape theory. Employing physically motivated potentials and knowledge-based local structure biasing terms, the addition of homologous template and co-evolutionary restraints to AWSEM-Suite greatly improves the predictive power of pure AWSEM structure prediction. From the independent evaluation metrics released in the CASP13 experiment, AWSEM-Suite proves to be a reasonably accurate algorithm for free modeling, standing at the eighth position in the free modeling category of CASP13. The AWSEM-Suite server also features a front end with a user-friendly interface. The AWSEM-Suite server is a powerful tool for predicting monomeric protein tertiary structures that is most useful when a suitable structure template is not available. The AWSEM-Suite server is freely available at: https://awsem.rice.edu.

Forging tools for refining predicted protein structures.

Refining predicted protein structures with all-atom molecular dynamics simulations is one route to producing, entirely by computational means, structural models of proteins that rival in quality those that are determined by X-ray diffraction experiments. Slow rearrangements within the compact folded state, however, make routine refinement of predicted structures by unrestrained simulations infeasible. In this work, we draw inspiration from the fields of metallurgy and blacksmithing, where practitioners have worked out practical means of controlling equilibration by mechanically deforming their samples. We describe a two-step refinement procedure that involves identifying collective variables for mechanical deformations using a coarse-grained model and then sampling along these deformation modes in all-atom simulations. Identifying those low-frequency collective modes that change the contact map the most proves to be an effective strategy for choosing which deformations to use for sampling. The method is tested on 20 refinement targets from the CASP12 competition and is found to induce large structural rearrangements that drive the structures closer to the experimentally determined structures during relatively short all-atom simulations of 50 ns. By examining the accuracy of side-chain rotamer states in subensembles of structures that have varying degrees of similarity to the experimental structure, we identified the reorientation of aromatic side chains as a step that remains slow even when encouraging global mechanical deformations in the all-atom simulations. Reducing the side-chain rotamer isomerization barriers in the all-atom force field is found to further speed up refinement.

Exploring the folding energy landscapes of heme proteins using a hybrid AWSEM-heme model.

Heme is an active center in many proteins. Here we explore computationally the role of heme in protein folding and protein structure. We model heme proteins using a hybrid model employing the AWSEM Hamiltonian, a coarse-grained forcefield for the protein chain along with AMBER, an all-atom forcefield for the heme. We carefully designed transferable force fields that model the interactions between the protein and the heme. The types of protein-ligand interactions in the hybrid model include thioester covalent bonds, coordinated covalent bonds, hydrogen bonds, and electrostatics. We explore the influence of different types of hemes (heme b and heme c) on folding and structure prediction. Including both types of heme improves the quality of protein structure predictions. The free energy landscape shows that both types of heme can act as nucleation sites for protein folding and stabilize the protein folded state. In binding the heme, coordinated covalent bonds and thioester covalent bonds for heme c drive the heme toward the native pocket. The electrostatics also facilitates the search for the binding site.

p113 isoform encoded by CUX1 circular RNA drives tumor progression via facilitating ZRF1/BRD4 transactivation.

BACKGROUND: Metabolic reprogramming sustains tumorigenesis and aggressiveness of neuroblastoma (NB), the most common extracranial malignancy in childhood, while underlying mechanisms and therapeutic approaches still remain elusive. METHODS: Circular RNAs (circRNAs) were validated by Sanger sequencing. Co-immunoprecipitation, mass spectrometry, chromatin immunoprecipitation (ChIP) sequencing, and RNA sequencing assays were applied to explore protein interaction and target genes. Gene expression regulation was observed by ChIP, dual-luciferase reporter, real-time quantitative RT-PCR, and western blot assays. Gain- and loss-of-function studies were performed to observe the impacts of circRNA-encoded protein and its partners on the lipid metabolism, mitochondrial activity, growth, invasion, and metastasis of NB cells. RESULTS: A novel 113-amino acid protein (p113) of CUT-like homeobox 1 (CUX1) was identified in NB cells treated by serum deprivation. Further validating studies revealed that nuclear p113 was encoded by circRNA of CUX1, and promoted the lipid metabolic reprogramming, mitochondrial activity, proliferation, invasion, and metastasis of NB cells. Mechanistically, p113 interacted with Zuotin-related factor 1 (ZRF1) and bromodomain protein 4 (BRD4) to form a transcriptional regulatory complex, and mediated the transactivation of ZRF1/BRD4 in upregulating ALDH3A1, NDUFA1, and NDUFAF5 essential for conversion of fatty aldehydes into fatty acids, fatty acid ß-oxidation, and mitochondrial complex I activity. Administration of an inhibitory peptide blocking p113-ZRF1 interaction suppressed the tumorigenesis and aggressiveness of NB cells. In clinical NB cases, high expression of p113, ZRF1, or BRD4 was associated with poor survival of patients. CONCLUSIONS: These results indicate that p113 isoform encoded by CUX1 circular RNA drives tumor progression via facilitating ZRF1/BRD4 transactivation.

Structural insights into the nuclear import of the histone acetyltransferase males-absent-on-the-first by importin α1.

The histone acetyltransferase males-absent-on-the-first (MOF) acetylates the histone H4, a modification important for many biological processes, including chromatin organization, transcriptional regulation, DNA replication, recombination and repair, as well as autophagy. Depletion of MOF induces serious consequences because of the reduction of histone acetylation, such as nuclear morphological defects and cancer. Despite the critical roles of MOF in the nucleus, the structural or functional mechanisms of the nucleocytoplasmic transport of MOF remain elusive. Here, we identified novel importin α1-specific nuclear localization signals (NLSs) in the N-terminal of human MOF. The crystal structure of MOF NLSs in complex with importin α1 further revealed a unique binding mode of MOF, with two independent NLSs binding to importin α1 major and minor sites, respectively. The second NLS of MOF displays an unexpected α-helical conformation in the C-terminus, with more extensive contacts with importin α1 not limited in the minor site. Mutations of the key residues on MOF and importin α1 lead to the reduction of their interaction as well as the nuclear import of MOF, revealing an essential role of NLS2 of MOF in interacting with importin α1 minor site. Taken together, we provide structural mechanisms underlying the nucleocytoplasmic transport of MOF, which will be of great importance in understanding the functional regulation of MOF in various biological processes.

Identification of an Oleanane-Type Triterpene Hedragonic Acid as a Novel Farnesoid X Receptor Ligand with Liver Protective Effects and Anti-inflammatory Activity.

Farnesoid X receptor (FXR) and G-protein-coupled bile acid receptor 1 (GPBAR1) are two important bile acid (BA) receptors. As non-BAs drug template for GPBAR1, none of the natural oleanane-type triterpenes have been reported as FXR ligands, despite FXR and GPBAR1 having similar binding pockets for BAs. Here, we report the natural triterpene hedragonic acid that has been isolated from the stem and root of Celastrus orbiculatus Thunb. (COT) as an effective agonist for FXR. Both biochemical amplified luminescent proximity homogeneous assay and cell-based reporter assays showed that hedragonic acid regulated the transcriptional activity of FXR. Circular dichroism spectroscopy further suggested the conformational changes of FXR upon the binding of hedragonic acid. Interestingly, the crystal structure of hedragonic acid-bound FXR revealed a unique binding mode with hedragonic acid occupying a novel binding pocket different from the classic binding position. The structural comparison between hedragonic acid-bound FXR and oleanolic acid-bound GPBAR1 explained the molecular basis for the selectivity of oleanane-type triterpenes for FXR. Moreover, hedragonic acid treatment protected mice from liver injury induced by acetaminophen overdose and decreased hepatic inflammatory responses in an FXR-dependent manner, suggesting that hedragonic acid might be one of the major components of COT for its multifunctional pharmaceutical uses. In conclusion, our results provide novel structure templates for drug design based on natural triterpenes by targeting FXR and/or GPBAR1 with pharmaceutical values.

A Novel Class of Natural FXR Modulators with a Unique Mode of Selective Co-regulator Assembly.

The farnesoid X receptor (FXR) is an important target for drug discovery. Small molecules induce a conformational change in FXR that modulates its binding to co-regulators, thus resulting in distinct FXR functional profiles. However, the mechanisms for selectively recruiting co-regulators by FXR remain elusive, partly because of the lack of FXR-selective modulators. We report the identification of two natural terpenoids, tschimgine and feroline, as novel FXR modulators. Remarkably, their crystal structures uncovered a secondary binding pocket important for ligand binding. Further, tschimgine or feroline induced dynamic conformational changes in the activation function 2 (AF-2) surface, thus leading to differential co-regulator recruiting profiles, modulated by both hydrophobic and selective hydrogen-bond interactions unique to specific co-regulators. Our findings thus provide a novel structure template for optimization for FXR-selective modulators of clinical value.

Real-Time Visualization of Protein Microenvironment Changes with High Spatial Resolution in Live Cells via Site-Specific Incorporation of Rotor-Based Fluorescent Noncanonical Amino Acids.

Traditional methods, such as the use of fluorescent protein fusions and environment-sensitive fluorophores, have limitations when studying protein microenvironment changes at the finest spatial resolution. These techniques often rely on bulky proteins or tags restricted to the N- or C-terminus, which can disrupt the natural behavior of the target protein and dramatically limit the ability of their method to investigate noninvasively microenvironment effects. To overcome these challenges, we have developed an innovative strategy to visualize microenvironment changes of protein substructures in real-time by genetically incorporating environment-sensitive noncanonical amino acids (ncAAs) containing rotor-based fluorophores (RBFs) at specific positions within a protein of interest. Through computational redesign of aminoacyl-tRNA synthetase, we successfully incorporated these rotor-based ncAAs into various proteins in mammalian cells. By site-specifically placing these ncAAs in distinct regions of proteins, we detected microenvironmental changes of several different protein domains during events such as aggregation, clustering, aggregation disassembly, and cluster dissociation.

CrysFormer: Protein structure determination via Patterson maps, deep learning, and partial structure attention.

Determining the atomic-level structure of a protein has been a decades-long challenge. However, recent advances in transformers and related neural network architectures have enabled researchers to significantly improve solutions to this problem. These methods use large datasets of sequence information and corresponding known protein template structures, if available. Yet, such methods only focus on sequence information. Other available prior knowledge could also be utilized, such as constructs derived from x-ray crystallography experiments and the known structures of the most common conformations of amino acid residues, which we refer to as partial structures. To the best of our knowledge, we propose the first transformer-based model that directly utilizes experimental protein crystallographic data and partial structure information to calculate electron density maps of proteins. In particular, we use Patterson maps, which can be directly obtained from x-ray crystallography experimental data, thus bypassing the well-known crystallographic phase problem. We demonstrate that our method, CrysFormer, achieves precise predictions on two synthetic datasets of peptide fragments in crystalline forms, one with two residues per unit cell and the other with fifteen. These predictions can then be used to generate accurate atomic models using established crystallographic refinement programs.

Revealing a natural marine product as a novel agonist for retinoic acid receptors with a unique binding mode and inhibitory effects on cancer cells.

Retinoids display anti-tumour activity on various cancer cells and therefore have been used as important therapeutic agents. However, adverse side effects and RA (retinoic acid) resistance limit further development and clinical application of retinoid-based therapeutic agents. We report in the present paper the identification of a natural marine product that activates RARs (RA receptors) with a chemical structure distinct from retinoids by high-throughput compound library screening. Luffariellolide was uncovered as a novel RAR agonist by inducing co-activator binding to these receptors in vitro, further inhibiting cell growth and regulating RAR target genes in various cancer cells. Structural and molecular studies unravelled a unique binding mode of this natural ligand to RARs with an unexpected covalent modification on the RAR. Functional characterization further revealed that luffariellolide displays chemotherapeutic potentials for overcoming RA resistance in colon cancer cells, suggesting that luffariellolide may represent a unique template for designing novel non-retinoid compounds with advantages over current RA drugs.

A deep learning solution for crystallographic structure determination.

The general de novo solution of the crystallographic phase problem is difficult and only possible under certain conditions. This paper develops an initial pathway to a deep learning neural network approach for the phase problem in protein crystallography, based on a synthetic dataset of small fragments derived from a large well curated subset of solved structures in the Protein Data Bank (PDB). In particular, electron-density estimates of simple artificial systems are produced directly from corresponding Patterson maps using a convolutional neural network architecture as a proof of concept.

Functional polarization of tumor-associated macrophages dictated by metabolic reprogramming.

Macrophages are highly plastic in different tissues and can differentiate into functional subpopulations under different stimuli. Tumor-associated macrophages (TAMs) are one of the most important innate immune cells implicated in the establishment of an immunosuppressive tumor microenvironment (TME). Recent evidence pinpoints the critical role of metabolic reprogramming in dictating pro-tumorigenic functions of TAMs. Both tumor cells and macrophages undergo metabolic reprogramming to meet energy demands in the TME. Understanding the metabolic rewiring in TAMs can shed light on immune escape mechanisms and provide insights into repolarizing TAMs towards anti-tumorigenic function. Here, we discuss how metabolism impinges on the functional divergence of macrophages and its relevance to macrophage polarization in the TME.