Computational inference of eIF4F complex function and structure in human cancers.

The canonical eukaryotic initiation factor 4F (eIF4F) complex, composed of eIF4G1, eIF4A1, and the cap-binding protein eIF4E, plays a crucial role in cap-dependent translation initiation in eukaryotic cells. An alternative cap-independent initiation can occur, involving only eIF4G1 and eIF4A1 through internal ribosome entry sites (IRESs). This mechanism is considered complementary to cap-dependent initiation, particularly in tumors under stress conditions. However, the selection and molecular mechanism of specific translation initiation remains poorly understood in human cancers. Thus, we analyzed gene copy number variations (CNVs) in TCGA tumor samples and found frequent amplification of genes involved in translation initiation. Copy number gains in EIF4G1 and EIF3E frequently co-occur across human cancers. Additionally, EIF4G1 expression strongly correlates with genes from cancer cell survival pathways including cell cycle and lipogenesis, in tumors with EIF4G1 amplification or duplication. Furthermore, we revealed that eIF4G1 and eIF4A1 protein levels strongly co-regulate with ribosomal subunits, eIF2, and eIF3 complexes, while eIF4E co-regulates with 4E-BP1, ubiquitination, and ESCRT proteins. Utilizing Alphafold predictions, we modeled the eIF4F structure with and without eIF4E binding. For cap-dependent initiation, our modeling reveals extensive interactions between the N-terminal eIF4E-binding domain of eIF4G1 and eIF4E. Furthermore, the eIF4G1 HEAT-2 domain positions eIF4E near the eIF4A1 N-terminal domain (NTD), resulting in the collaborative enclosure of the RNA binding cavity within eIF4A1. In contrast, during cap-independent initiation, the HEAT-2 domain directly binds the eIF4A1-NTD, leading to a stronger interaction between eIF4G1 and eIF4A1, thus closing the mRNA binding cavity without the involvement of eIF4E.

Malignant tumor cells engender second membrane-lined organelles for self-protection and tumor progression.

Cancer is a leading cause of mortality in humans, but the efficacy of current treatments for many cancers is limited, as they lack unique mechanistically defined targets. Here, we show that, upon malignant transformation, aggressive oncocells generate a second membrane exterior to their plasma membrane to form cytocapsulas (CCs) and cytocapsular tubes (CCTs), which all together constitute cytocapsular oncocells with pleotropic biological functions in cancer patient tissues in vivo. Proteomic and biochemical analyses revealed that the PMCA2 calcium pump is highly up-regulated in CCs and CCTs in malignant tumors but not in normal tissues, thus identifying a unique cancer biomarker and target for cancer therapy. Cytocapsular oncocells are universally present in solid cancers and appear in hematologic cancers in immune organs. Multi-cell malignant tumors are also enveloped by protective CC membranes. These cytocapsular tumors (CTs) generate numerous CCTs that form freeways for cancer cell metastasis to both neighboring and distant destinations. Entire cytocapsular tumor networks (CTNs) dominate physical cancer metastasis pathways in cancer patients in vivo. Later, CCTs invade micro blood vessels and release cytocapsular oncocells into the blood, providing a source of circulating tumor cells. CTNs interconnect cytocapsular tumors in primary and secondary cancer niches, creating larger cytocapsular tumor network systems (CTNSs). Primary and secondary CTNSs are in turn interconnected, forming dynamic and integrated CTNSs. Thus, interconnected cytocapsular oncocells, CTNs, and CTNSs coordinate cancer progression via the integrated cytocapsular membrane systems.

On the concept of systematization in the Kemeny-Oppenheim approach to intertheoretical reduction.

In 1956, John G. Kemeny and Paul Oppenheim proposed an approach to intertheoretical reduction as an alternative to that of Ernest Nagel. However, they neglected to provide a clear definition of its basic concept of systematization. After decades of languishing in the shadows, new interest in the KO approach is emerging. Nevertheless, there are still misunderstandings regarding this basic concept. The present paper elucidates this concept by returning to Oppenheim's hitherto little-noticed publications from the 1920s and 1930s, which Kemeny and Oppenheim obviously used as guidance in 1956. Reappraising Oppenheim's early writings delivers two significant payoffs: new clarity in understanding the concept of systematization as well as a more solid grasp of the structure of this approach as a distinctive combination of explanation and systematization.

Computational inference of eIF4F complex function and structure in human cancers.

The canonical eukaryotic initiation factor 4F (eIF4F) complex, composed of eIF4G1, eIF4A1, and the cap-binding protein eIF4E, plays a crucial role in cap-dependent translation initiation in eukaryotic cells (1). However, cap-independent initiation can occur through internal ribosomal entry sites (IRESs), involving only eIF4G1 and eIF4A1 present, which is considered to be a complementary process to cap-dependent initiation in tumors under stress conditions (2). The selection and molecular mechanism of specific translation initiation in human cancers remains poorly understood. Thus, we analyzed gene copy number variations (CNVs) in TCGA tumor samples and found frequent amplification of genes involved in translation initiation. Copy number gains in EIF4G1 and EIF3E frequently co-occur across human cancers. Additionally, EIF4G1 expression strongly correlates with genes from cancer cell survival pathways including cell cycle and lipogenesis, in tumors with EIF4G1 amplification or duplication. Furthermore, we revealed that eIF4G1 and eIF4A1 protein levels strongly co-regulate with ribosomal subunits, eIF2, and eIF3 complexes, while eIF4E co-regulates with 4E-BP1, ubiquitination, and ESCRT proteins. Using Alphafold predictions, we modeled the eIF4F structure with and without eIF4G1-eIF4E binding. The modeling for cap-dependent initiation suggests that eIF4G1 interacts with eIF4E through its N-terminal eIF4E-binding domain, bringing eIF4E near the eIF4A1 mRNA binding cavity and closing the cavity with both eIF4G1 HEAT-2 domain and eIF4E. In the cap-independent mechanism, α-helix 5 of eIF4G1 HEAT-2 domain instead directly interacts with the eIF4A1 N-terminal domain to close the mRNA binding cavity without eIF4E involvement, resulting in a stronger interaction between eIF4G1 and eIF4A1. Significance Statement: Translation initiation is primarily governed by eIF4F, employing a "cap-dependent" mechanism, but eIF4F dysregulation may lead to a "cap-independent" mechanism in stressed cancer cells. We found frequent amplification of translation initiation genes, and co-occurring copy number gains of EIF4G1 and EIF3E genes in human cancers. EIF4G1 amplification or duplication may be positively selected for its beneficial impact on the overexpression of cancer survival genes. The co-regulation of eIF4G1 and eIF4A1, distinctly from eIF4E, reveals eIF4F dysregulation favoring cap-independent initiation. Alphafold predicts changes in the eIF4F complex assembly to accommodate both initiation mechanisms. These findings have significant implications for evaluating cancer cell vulnerability to eIF4F inhibition and developing treatments that target cancer cells with dependency on the translation initiation mechanism.

NMR sample optimization and backbone assignment of a stabilized neurotensin receptor.

G protein-coupled receptors (GPCRs) are involved in a multitude of cellular signaling cascades and consequently are a prominent target for pharmaceutical drugs. In the past decades, a growing number of high-resolution structures of GPCRs has been solved, providing unprecedented insights into their mode of action. However, knowledge on the dynamical nature of GPCRs is equally important for a better functional understanding, which can be obtained by NMR spectroscopy. Here, we employed a combination of size exclusion chromatography, thermal stability measurements and 2D-NMR experiments for the NMR sample optimization of the stabilized neurotensin receptor type 1 (NTR1) variant HTGH4 bound to the agonist neurotensin. We identified the short-chain lipid di-heptanoyl-glycero-phosphocholine (DH7PC) as a promising membrane mimetic for high resolution NMR experiments and obtained a partial NMR backbone resonance assignment. However, internal membrane-incorporated parts of the protein were not visible due to lacking amide proton back-exchange. Nevertheless, NMR and hydrogen deuterium exchange (HDX) mass spectrometry experiments could be used to probe structural changes at the orthosteric ligand binding site in the agonist and antagonist bound states. To enhance amide proton exchange we partially unfolded HTGH4 and observed additional NMR signals in the transmembrane region. However, this procedure led to a higher sample heterogeneity, suggesting that other strategies need to be applied to obtain high-quality NMR spectra of the entire protein. In summary, the herein reported NMR characterization is an essential step toward a more complete resonance assignment of NTR1 and for probing its structural and dynamical features in different functional states.

Challenges for chemistry in Ukraine after the war: Ukrainian science requires rebuilding and support.

The unprovoked Russian invasion has created considerable challenges for Ukrainian science. In this article, we discuss actions needed to support and rebuild Ukrainian science and educational systems. The proposed actions take into account past Ukrainian scientific achievements including developments in organic chemistry.

NIN-like protein 7 transcription factor is a plant nitrate sensor.

Nitrate is an essential nutrient and signaling molecule for plant growth. Plants sense intracellular nitrate to adjust their metabolic and growth responses. Here we identify the primary nitrate sensor in plants. We found that mutation of all seven Arabidopsis NIN-like protein (NLP) transcription factors abolished plants' primary nitrate responses and developmental programs. Analyses of NIN-NLP7 chimeras and nitrate binding revealed that NLP7 is derepressed upon nitrate perception via its amino terminus. A genetically encoded fluorescent split biosensor, mCitrine-NLP7, enabled visualization of single-cell nitrate dynamics in planta. The nitrate sensor domain of NLP7 resembles the bacterial nitrate sensor NreA. Substitutions of conserved residues in the ligand-binding pocket impaired the ability of nitrate-triggered NLP7 to control transcription, transport, metabolism, development, and biomass. We propose that NLP7 represents a nitrate sensor in land plants.

High fidelity sampling schedules for NMR spectra of high dynamic range.

The ability to reconstruct non-uniformly sampled (NUS) NMR spectra has mostly been accepted. Still a concern is lingering regarding artifacts from sampling non-uniformly. As experienced, some sampling schedules yield better results than others. Finding a useful schedule is relatively trivial for a low dynamic range spectrum and a conservative sparsity, but not so when the dynamic range is large and/or when extreme sparsity is used. High dynamic range is typically found in NOESY and spectra of metabolites, where quantification of peak heights is desired at high fidelity. Extreme sparsity is desired when high throughput is a goal. In all cases, selecting a poor sampling schedule can create unnecessary artifacts. Effectively, it is important to select a sampling schedule that provides a signal-to-artifact apex ratio (SAAR) value in par or better than the signal-to-noise ratio (SNR) value. Notably, by signal-to-artifact apex ratio we consider reconstruction fidelity as the apex intensity likeness, i.e., as the true signal to the tallest artifact. We show that the quality of reconstruction depends on the particular sampling schedule. We evaluate the reconstruction quality in the frequency domain following a matched Lorentz-to-Gauss transform plus common apodization and Fourier Transform. As the Lorentz-to-Gauss transform improves resolution and reduces ridges we include this when defining the Signal-to-Artifact Apex Ratio (SAAR) metric. This metric measures the ratio of simulated reconstructed peak height to the tallest artifact of reconstruction in a spectrum without noise. Once a NUS schedule is found with an optimal SAAR it will be satisfactory for all spectra recorded with the same parameter set. Tables with good seed values are provided in the supplement.

Protocol to analyze dysregulation of the eIF4F complex in human cancers using R software and large public datasets.

Understanding dysregulation of the eukaryotic initiation factor 4F (eIF4F) complex across tumor types is critical to cancer treatment development. We present a protocol and accompanying R package "eIF4F.analysis". We describe analysis of copy number status, gene abundance and stoichiometry, survival probability, expression covariation, correlating genes, mRNA/protein correlation, and protein co-expression. Using publicly available large multi-omics data, eIF4F.analysis permits computationally derived and statistically powerful inferences regarding initiation factor regulation in human cancers and clinical relevance of protein interactions within the eIF4F complex. For complete details on the use and execution of this protocol, please refer to Wu and Wagner (2021).1.

Deep computational analysis details dysregulation of eukaryotic translation initiation complex eIF4F in human cancers.

eIF4F plays diverse roles in human cancers, which complicate the development of an overarching understanding of its functional and regulatory impacts across tumor types. Typically, eIF4F drives initiation from the mRNA 5' end (cap) and is composed of eIF4G1, eIF4A1, and cap-binding eIF4E. Cap-independent initiation is possible without eIF4E, from internal ribosomal entry sites (IRESs). By analyzing large public datasets, we found that cancers selectively overexpress EIF4G1 more than EIF4E. That expression imbalance supports EIF4G1 as a prognostic indicator in patients with cancer. It also attenuates "housekeeping" pathways that are usually regulated in a tissue-specific manner via cap-dependent initiation in healthy tissues and reinforce regulation of cancer-preferred pathways in cap-independent contexts. Cap-independent initiation is mechanistically attributable to eIF4G1 hyperphosphorylation that promotes binding to eIF4A1 and reduced eIF4E availability. Collectively, these findings reveal a novel model of dysregulated eIF4F function and highlight the clinical relevance of cap-(in)dependent initiation in cancer.

VirtualFlow Ants-Ultra-Large Virtual Screenings with Artificial Intelligence Driven Docking Algorithm Based on Ant Colony Optimization.

The docking program PLANTS, which is based on ant colony optimization (ACO) algorithm, has many advanced features for molecular docking. Among them are multiple scoring functions, the possibility to model explicit displaceable water molecules, and the inclusion of experimental constraints. Here, we add support of PLANTS to VirtualFlow (VirtualFlow Ants), which adds a valuable method for primary virtual screenings and rescoring procedures. Furthermore, we have added support of ligand libraries in the MOL2 format, as well as on the fly conversion of ligand libraries which are in the PDBQT format to the MOL2 format to endow VirtualFlow Ants with an increased flexibility regarding the ligand libraries. The on the fly conversion is carried out with Open Babel and the program SPORES. We applied VirtualFlow Ants to a test system involving KEAP1 on the Google Cloud up to 128,000 CPUs, and the observed scaling behavior is approximately linear. Furthermore, we have adjusted several central docking parameters of PLANTS (such as the speed parameter or the number of ants) and screened 10 million compounds for each of the 10 resulting docking scenarios. We analyzed their docking scores and average docking times, which are key factors in virtual screenings. The possibility of carrying out ultra-large virtual screening with PLANTS via VirtualFlow Ants opens new avenues in computational drug discovery.

A general chemical crosslinking strategy for structural analyses of weakly interacting proteins applied to preTCR-pMHC complexes.

T lymphocytes discriminate between healthy and infected or cancerous cells via T-cell receptor-mediated recognition of peptides bound and presented by cell-surface-expressed major histocompatibility complex molecules (MHCs). Pre-T-cell receptors (preTCRs) on thymocytes foster development of αßT lymphocytes through their ß chain interaction with MHC displaying self-peptides on thymic epithelia. The specific binding of a preTCR with a peptide-MHC complex (pMHC) has been identified previously as forming a weak affinity complex with a distinct interface from that of mature αßTCR. However, a lack of appropriate tools has limited prior efforts to investigate this unique interface. Here we designed a small-scale linkage screening protocol using bismaleimide linkers for determining residue-specific distance constraints between transiently interacting protein pairs in solution. Employing linkage distance restraint-guided molecular modeling, we report the oriented solution docking geometry of a preTCRß-pMHC interaction. The linkage model of preTCRß-pMHC complex was independently verified with paramagnetic pseudocontact chemical shift (PCS) NMR of the unlinked protein mixtures. Using linkage screens, we show that the preTCR binds with differing affinities to peptides presented by MHC in solution. Moreover, the C-terminal peptide segment is a key determinant in preTCR-pMHC recognition. We also describe the process for future large-scale production and purification of the linked constructs for NMR, X-ray crystallography, and single-molecule electron microscopy studies.

A biphenyl inhibitor of eIF4E targeting an internal binding site enables the design of cell-permeable PROTAC-degraders.

The eukaryotic translation initiation factor 4E (eIF4E) is the master regulator of cap-dependent protein synthesis. Overexpression of eIF4E is implicated in diseases such as cancer, where dysregulation of oncogenic protein translation is frequently observed. eIF4E has been an attractive target for cancer treatment. Here we report a high-resolution X-ray crystal structure of eIF4E in complex with a novel inhibitor (i4EG-BiP) that targets an internal binding site, in contrast to the previously described inhibitor, 4EGI-1, which binds to the surface. We demonstrate that i4EG-BiP is able to displace the scaffold protein eIF4G and inhibit the proliferation of cancer cells. We provide insights into how i4EG-BiP is able to inhibit cap-dependent translation by increasing the eIF4E-4E-BP1 interaction while diminishing the interaction of eIF4E with eIF4G. Leveraging structural details, we designed proteolysis targeted chimeras (PROTACs) derived from 4EGI-1 and i4EG-BiP and characterized these on biochemical and cellular levels. We were able to design PROTACs capable of binding eIF4E and successfully engaging Cereblon, which targets proteins for proteolysis. However, these initial PROTACs did not successfully stimulate degradation of eIF4E, possibly due to competitive effects from 4E-BP1 binding. Our results highlight challenges of targeted proteasomal degradation of eIF4E that must be addressed by future efforts.

Structural basis of the dynamic human CEACAM1 monomer-dimer equilibrium.

Human (h) carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) function depends upon IgV-mediated homodimerization or heterodimerization with host ligands, including hCEACAM5, hTIM-3, PD-1, and a variety of microbial pathogens. However, there is little structural information available on how hCEACAM1 transitions between monomeric and dimeric states which in the latter case is critical for initiating hCEACAM1 activities. We therefore mutated residues within the hCEACAM1 IgV GFCC' face including V39, I91, N97, and E99 and examined hCEACAM1 IgV monomer-homodimer exchange using differential scanning fluorimetry, multi-angle light scattering, X-ray crystallography and/or nuclear magnetic resonance. From these studies, we describe hCEACAM1 homodimeric, monomeric and transition states at atomic resolution and its conformational behavior in solution through NMR assignment of the wildtype (WT) hCEACAM1 IgV dimer and N97A mutant monomer. These studies reveal the flexibility of the GFCC' face and its important role in governing the formation of hCEACAM1 dimers and selective heterodimers.

Cryo-EM structure of an activated GPCR-G protein complex in lipid nanodiscs.

G-protein-coupled receptors (GPCRs) are the largest superfamily of transmembrane proteins and the targets of over 30% of currently marketed pharmaceuticals. Although several structures have been solved for GPCR-G protein complexes, few are in a lipid membrane environment. Here, we report cryo-EM structures of complexes of neurotensin, neurotensin receptor 1 and Gαi1ß1γ1 in two conformational states, resolved to resolutions of 4.1 and 4.2 Å. The structures, determined in a lipid bilayer without any stabilizing antibodies or nanobodies, reveal an extended network of protein-protein interactions at the GPCR-G protein interface as compared to structures obtained in detergent micelles. The findings show that the lipid membrane modulates the structure and dynamics of complex formation and provide a molecular explanation for the stronger interaction between GPCRs and G proteins in lipid bilayers. We propose an allosteric mechanism for GDP release, providing new insights into the activation of G proteins for downstream signaling.

A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening.

The unparalleled global effort to combat the continuing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic over the last year has resulted in promising prophylactic measures. However, a need still exists for cheap, effective therapeutics, and targeting multiple points in the viral life cycle could help tackle the current, as well as future, coronaviruses. Here, we leverage our recently developed, ultra-large-scale in silico screening platform, VirtualFlow, to search for inhibitors that target SARS-CoV-2. In this unprecedented structure-based virtual campaign, we screened roughly 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets. In addition to targeting the active sites of viral enzymes, we also targeted critical auxiliary sites such as functionally important protein-protein interactions.

NUScon: a community-driven platform for quantitative evaluation of nonuniform sampling in NMR.

Although the concepts of nonuniform sampling (NUS​​​​​​​) and non-Fourier spectral reconstruction in multidimensional NMR began to emerge 4 decades ago , it is only relatively recently that NUS has become more commonplace. Advantages of NUS include the ability to tailor experiments to reduce data collection time and to improve spectral quality, whether through detection of closely spaced peaks (i.e., "resolution") or peaks of weak intensity (i.e., "sensitivity"). Wider adoption of these methods is the result of improvements in computational performance, a growing abundance and flexibility of software, support from NMR spectrometer vendors, and the increased data sampling demands imposed by higher magnetic fields. However, the identification of best practices still remains a significant and unmet challenge. Unlike the discrete Fourier transform, non-Fourier methods used to reconstruct spectra from NUS data are nonlinear, depend on the complexity and nature of the signals, and lack quantitative or formal theory describing their performance. Seemingly subtle algorithmic differences may lead to significant variabilities in spectral qualities and artifacts. A community-based critical assessment of NUS challenge problems has been initiated, called the "Nonuniform Sampling Contest" (NUScon), with the objective of determining best practices for processing and analyzing NUS experiments. We address this objective by constructing challenges from NMR experiments that we inject with synthetic signals, and we process these challenges using workflows submitted by the community. In the initial rounds of NUScon our aim is to establish objective criteria for evaluating the quality of spectral reconstructions. We present here a software package for performing the quantitative analyses, and we present the results from the first two rounds of NUScon. We discuss the challenges that remain and present a roadmap for continued community-driven development with the ultimate aim of providing best practices in this rapidly evolving field. The NUScon software package and all data from evaluating the challenge problems are hosted on the NMRbox platform.

Pre-T cell receptors topologically sample self-ligands during thymocyte ß-selection.

Self-discrimination, a critical but ill-defined molecular process programmed during thymocyte development, requires myriad pre-T cell receptors (preTCRs) and αßTCRs. Using x-ray crystallography, we show how a preTCR applies the concave ß-sheet surface of its single variable domain (Vß) to "horizontally" grab the protruding MHC α2-helix. By contrast, αßTCRs purpose all six complementarity-determining region (CDR) loops of their paired VαVß module to recognize peptides bound to major histocompatibility complex molecules (pMHCs) in "vertical" head-to-head binding. The preTCR topological fit ensures that CDR3ß reaches the peptide's featured C-terminal segment for pMHC sampling, establishing the subsequent αßTCR canonical docking mode. "Horizontal" docking precludes germline CDR1ß- and CDR2ß-MHC binding to broaden ß-chain repertoire diversification before αßTCR-mediated selection refinement. Thus, one subunit successively attunes the recognition logic of related multicomponent receptors.

Allosterically Coupled Multisite Binding of Testosterone to Human Serum Albumin.

Human serum albumin (HSA) acts as a carrier for testosterone, other sex hormones, fatty acids, and drugs. However, the dynamics of testosterone's binding to HSA and the structure of its binding sites remain incompletely understood. Here, we characterize the dynamics of testosterone's binding to HSA and the stoichiometry and structural location of the binding sites using 2-dimensional nuclear magnetic resonance (2D NMR), fluorescence spectroscopy, 4,4'-dianilino-1,1'-binaphthyl-5,5'-disulfonic acid dipotassium salt partitioning, and equilibrium dialysis, complemented by molecular modeling. 2D NMR studies showed that testosterone competitively displaced 18-[13C]-oleic acid from at least 3 known fatty acid binding sites on HSA that also bind many drugs. Binding isotherms of testosterone's binding to HSA generated using fluorescence spectroscopy and equilibrium dialysis were nonlinear and the apparent dissociation constant varied with different concentrations of testosterone and HSA. The binding isotherms neither conformed to a linear binding model with 1:1 stoichiometry nor to 2 independent binding sites; the binding isotherms were most consistent with 2 or more allosterically coupled binding sites. Molecular dynamics studies revealed that testosterone's binding to fatty acid binding site 3 on HSA was associated with conformational changes at site 6, indicating that residues in in these 2 distinct binding sites are allosterically coupled. There are multiple, allosterically coupled binding sites for testosterone on HSA. Testosterone shares these binding sites on HSA with free fatty acids, which could displace testosterone from HSA under various physiological states or disease conditions, affecting its bioavailability.