Mex-3 RNA binding family member A (MEX3A)/circMPP6 complex promotes colorectal cancer progression by inhibiting autophagy.

RNA-binding proteins (RBPs)-RNA networks have contributed to cancer development. Circular RNAs (circRNAs) are considered as protein recruiters; nevertheless, the patterns of circRNA-protein interactions in colorectal cancer (CRC) are still lacking. Processing bodies (PBs) formed through liquid-liquid phase separation (LLPS) are membrane-less organelles (MLOs) consisting of RBPs and RNA. Previous evidence suggests a connection between PBs dynamics and cancer progression. Despite the increasingly acknowledged crucial role of RBPs and RNA in the accumulation and maintenance of MLOs, there remains a lack of specific research on the interactions between PBs-related RBPs and circRNAs in CRC. Herein, we identify that MEX-3 RNA binding family member A (MEX3A), frequently upregulated in CRC tissues, predicts poorer patient survival. Elevated MEX3A accelerates malignance and inhibits autophagy of CRC cells. Importantly, MEX3A undergoes intrinsically disordered regions (IDRs)-dependent LLPS in the cytoplasm. Specifically, circMPP6 acts as a scaffold to facilitate the interaction between MEX3A and PBs proteins. The MEX3A/circMPP6 complex modulates PBs dynamic and promotes UPF-mediated phosphodiesterase 5A (PDE5A) mRNA degradation, consequently leading to the aggressive properties of CRC cells. Clinically, CRC patients exhibiting high MEX3A expression and low PDE5A expression have the poorest overall survival. Our findings reveal a collaboration between MEX3A and circMPP6 in the regulation of mRNA decay through triggering the PBs aggregation, which provides prognostic markers and/or therapeutic targets for CRC.

Considerations Around Structure-Based Drug Discovery for KRAS Using DOCK.

Molecular docking is a popular computational tool in drug discovery. Leveraging structural information, docking software predicts binding poses of small molecules to cavities on the surfaces of proteins. Virtual screening for ligand discovery is a useful application of docking software. In this chapter, using the enigmatic KRAS protein as an example system, we endeavor to teach the reader about best practices for performing molecular docking with UCSF DOCK. We discuss methods for virtual screening and docking molecules on KRAS. We present the following six points to optimize our docking setup for prosecuting a virtual screen: protein structure choice, pocket selection, optimization of the scoring function, modification of sampling spheres and sampling procedures, choosing an appropriate portion of chemical space to dock, and the choice of which top scoring molecules to pick for purchase.

1D and 2D NMR for KRAS:Ligand Binding.

Fragment-based screening by ligand-observed 1D NMR and binding interface mapping by protein-observed 2D NMR are popular methods used in drug discovery. These methods allow researchers to detect compound binding over a wide range of affinities and offer a simultaneous assessment of solubility, purity, and chemical formula accuracy of the target compounds and the 15N-labeled protein when examined by 1D and 2D NMR, respectively. These methods can be applied for screening fragment binding to the active (GMPPNP-bound) and inactive (GDP-bound) states of oncogenic KRAS mutants.

Luminescence-Based Techniques for KRAS Thermal Stability Monitoring.

Various biochemical methods have been introduced to detect and characterize KRAS activity and interactions, from which the vast majority is based on luminescence detection in its varying forms. Among these methods, thermal stability assays, using luminophore-conjugated proteins or external environment sensing dyes, are widely used. In this chapter, we describe methods enabling KRAS stability monitoring in vitro, with an emphasis on ligand-induced stability. This chapter focuses mainly on luminescence-based techniques utilizing external dye molecules and fluorescence detection.

Profiling Complex RAS-Effector Interactions Using NMR Spectroscopy.

Knowledge of how effectors interact with RAS GTPases is key to understanding how these switch-like proteins function in cells. Effectors bind specifically to GTP-loaded RAS using RAS association (RA) or RAS binding domains (RBDs) that show wide-ranging affinities and thermodynamic characteristics. Both normal development and RAS-induced tumorigenesis depend on multiple distinct effector proteins that are frequently co-expressed and co-localized, suggesting an antagonistic nature to signaling whereby multiple proteins compete for a limited pool of activated GTPase. NMR spectroscopy offers a powerful approach to multiplex effectors and/or regulatory enzymes and quantifies their interaction with RAS, expanding our biophysical and systems-level understanding of RAS signaling in a more integrated and physiologically relevant setting. Here we describe a method to directly quantitate GTPase binding to competing effectors, using wild-type KRAS complex with ARAF and PLCε1 as a model. Unlabeled RBD/RA domains are added simultaneously to isotopically labeled RAS, and peak intensities at chemical shifts characteristic of individually bound domains provide quantitation. Similar competition-based assays can be run with small molecule interactors, GEF/GAP domains, or regulatory enzymes that drive posttranslational modifications. Such efforts bring in vitro interaction experiments in line with more complex cellular environments.

Duodenocolic fistula healing by pentadecapeptide BPC 157 in rats. A cytoprotection viewpoint.

Using duodenocolic fistula in rats, this study attempts to highlight the particular cytoprotection aspects of the healing of fistulas and therapy potential of the stable gastric pentadecapeptide BPC 157, a cytoprotection mediator (i.e. upgrading minor vessels to induce healing at both fistula's sides). Upon duodenocolic fistula creation (two 'perforated' lesions put together) (assessed at 3, 6, 9, 12, and 15 min), BPC 157, given locally at the fistula, or intragastrically (10 µg/kg, 10 ng/kg), rapidly induces vessel 'recruitment', 'running' toward the defect, simultaneously at duodenum and colon, providing numerous collaterals and branching. The mRNA expression studies done at that time provided strongly elevated (nitric oxide synthase 2) and decreased (cyclooxygenase-2, vascular endothelial growth factor A, nitric oxide synthase (NOS)-1, NOS-3, nuclear factor-kappa-B-activating protein) gene expression. As therapy, rats with duodenocolic fistulas, received BPC 157 10 µg/kg, 10 ng/kg, per-orally, in drinking water till sacrifice, or alternatively, intraperitoneally, first application at 30 min after surgery, last at 24 h before sacrifice, at day 1, 3, 7, 14, 21, and 28. Controls exhibited both defects persisting, continuous fistula leakage, diarrhea, continuous weight loss, advanced adhesion formation and intestinal obstruction. Contrary, all BPC 157-treated rats have closed both defects, duodenal and colonic, no fistula leakage (finally, maximal instilled volume corresponds to healthy rats), no cachexia, the same weight as before surgery, no diarrhea, markedly less adhesion formation and intestinal passage obstruction. Thus, BPC 157 regimens resolve the duodenal/colon lesions and duodenocolic fistulas in rats, and rapid vessels recovery appears as the essential point in the implementation of the cytoprotection concept in the fistula therapy.

Enhancing missense variant pathogenicity prediction with protein language models using VariPred.

Computational approaches for predicting the pathogenicity of genetic variants have advanced in recent years. These methods enable researchers to determine the possible clinical impact of rare and novel variants. Historically these prediction methods used hand-crafted features based on structural, evolutionary, or physiochemical properties of the variant. In this study we propose a novel framework that leverages the power of pre-trained protein language models to predict variant pathogenicity. We show that our approach VariPred (Variant impact Predictor) outperforms current state-of-the-art methods by using an end-to-end model that only requires the protein sequence as input. Using one of the best-performing protein language models (ESM-1b), we establish a robust classifier that requires no calculation of structural features or multiple sequence alignments. We compare the performance of VariPred with other representative models including 3Cnet, Polyphen-2, REVEL, MetaLR, FATHMM and ESM variant. VariPred performs as well as, or in most cases better than these other predictors using six variant impact prediction benchmarks despite requiring only sequence data and no pre-processing of the data.

Perspective: The complex relationship between charge, mobility, and gas-phase protein structure.

Ion mobility spectrometry coupled to mass spectrometry (IMS/MS) is a widely used tool for biomolecular separations and structural elucidation. The application of IMS/MS has resulted in exciting developments in structural proteomics and genomics. This perspective gives a brief background of the field, addresses some of the important issues in making structural measurements, and introduces complementary techniques.

The MBO2/FAP58 heterodimer stabilizes assembly of inner arm dynein b and reveals axoneme asymmetries involved in ciliary waveform.

Cilia generate three-dimensional waveforms required for cell motility and transport of fluid, mucus, and particles over the cell surface. This movement is driven by multiple dynein motors attached to nine outer doublet microtubules that form the axoneme. The outer and inner arm dyneins are organized into 96-nm repeats tandemly arrayed along the length of the doublets. Motility is regulated in part by projections from the two central pair microtubules that contact radial spokes located near the base of the inner dynein arms in each repeat. Although much is known about the structures and protein complexes within the axoneme, many questions remain about the regulatory mechanisms that allow the cilia to modify their waveforms in response to internal or external stimuli. Here, we used Chlamydomonas mbo (move backwards only) mutants with altered waveforms to identify at least two conserved proteins, MBO2/CCDC146 and FAP58/CCDC147, that form part of a L-shaped structure that varies between doublet microtubules. Comparative proteomics identified additional missing proteins that are altered in other motility mutants, revealing overlapping protein defects. Cryo-electron tomography and epitope tagging revealed that the L-shaped, MBO2/FAP58 structure interconnects inner dynein arms with multiple regulatory complexes, consistent with its function in modifying the ciliary waveform.

The GFPT2-O-GlcNAcylation-YBX1 axis promotes IL-18 secretion to regulate the tumor immune microenvironment in pancreatic cancer.

The immunosuppressive microenvironment caused by several intrinsic and extrinsic mechanism has brought great challenges to the immunotherapy of pancreatic cancer. We identified GFPT2, the key enzyme in hexosamine biosynthesis pathway (HBP), as an immune-related prognostic gene in pancreatic cancer using transcriptome sequencing and further confirmed that GFPT2 promoted macrophage M2 polarization and malignant phenotype of pancreatic cancer. HBP is a glucose metabolism pathway leading to the generation of uridine diphosphate N-acetylglucosamine (UDP-GlcNAc), which is further utilized for protein O-GlcNAcylation. We confirmed GFPT2-mediated O-GlcNAcylation played an important role in regulating immune microenvironment. Through cellular proteomics, we identified IL-18 as a key downstream of GFPT2 in regulating the immune microenvironment. Through CO-IP and protein mass spectrum, we confirmed that YBX1 was O-GlcNAcylated and nuclear translocated by GFPT2-mediated O-GlcNAcylation. Then, YBX1 functioned as a transcription factor to promote IL-18 transcription. Our study elucidated the relationship between the metabolic pathway of HBP in cancer cells and the immune microenvironment, which might provide some insights into the combination therapy of HBP vulnerability and immunotherapy in pancreatic cancer.

sOCP: a framework predicting smORF coding potential based on TIS and in-frame features and effectively applied in the human genome.

Small open reading frames (smORFs) have been acknowledged to play various roles on essential biological pathways and affect human beings from diabetes to tumorigenesis. Predicting smORFs in silico is quite a prerequisite for processing the omics data. Here, we proposed the smORF-coding-potential-predicting framework, sOCP, which provides functions to construct a model for predicting novel smORFs in some species. The sOCP model constructed in human was based on in-frame features and the nucleotide bias around the start codon, and the small feature subset was proved to be competent enough and avoid overfitting problems for complicated models. It showed more advanced prediction metrics than previous methods and could correlate closely with experimental evidence in a heterogeneous dataset. The model was applied to Rattus norvegicus and exhibited satisfactory performance. We then scanned smORFs with ATG and non-ATG start codons from the human genome and generated a database containing about a million novel smORFs with coding potential. Around 72 000 smORFs are located on the lncRNA regions of the genome. The smORF-encoded peptides may be involved in biological pathways rare for canonical proteins, including glucocorticoid catabolic process and the prokaryotic defense system. Our work provides a model and database for human smORF investigation and a convenient tool for further smORF prediction in other species.

Chitin-mediated blockade of chitinase-like proteins reduces tumor immunosuppression, inhibits lymphatic metastasis and enhances anti-PD-1 efficacy in complementary TNBC models.

BACKGROUND: Chitinase-like proteins (CLPs) play a key role in immunosuppression under inflammatory conditions such as cancer. CLPs are enzymatically inactive and become neutralized upon binding of their natural ligand chitin, potentially reducing CLP-driven immunosuppression. We investigated the efficacy of chitin treatment in the context of triple-negative breast cancer (TNBC) using complementary mouse models. We also evaluated the immunomodulatory influence of chitin on immune checkpoint blockade (ICB) and compared its efficacy as general CLP blocker with blockade of a single CLP, i.e. chitinase 3-like 1 (CHI3L1). METHODS: Female BALB/c mice were intraductally injected with luciferase-expressing 4T1 or 66cl4 cells and systemically treated with chitin in combination with or without anti-programmed death (PD)-1 ICB. For single CLP blockade, tumor-bearing mice were treated with anti-CHI3L1 antibodies. Metastatic progression was monitored through bioluminescence imaging. Immune cell changes in primary tumors and lymphoid organs (i.e. axillary lymph nodes and spleen) were investigated through flow cytometry, immunohistochemistry, cytokine profiling and RNA-sequencing. CHI3L1-stimulated RAW264.7 macrophages were subjected to 2D lymphatic endothelial cell adhesion and 3D lymphatic integration in vitro assays for studying macrophage-mediated lymphatic remodeling. RESULTS: Chitin significantly reduced primary tumor progression in the 4T1-based model by decreasing the high production of CLPs that originate from tumor-associated neutrophils (TANs) and Stat3 signaling, prominently affecting the CHI3L1 and CHI3L3 primary tumor levels. It reduced immunosuppressive cell types and increased anti-tumorigenic T-cells in primary tumors as well as axillary lymph nodes. Chitin also significantly reduced CHI3L3 primary tumor levels and immunosuppression in the 66cl4-based model. Compared to anti-CHI3L1, chitin enhanced primary tumor growth reduction and anti-tumorigenicity. Both treatments equally inhibited lymphatic adhesion and integration of macrophages, thereby hampering lymphatic tumor cell spreading. Upon ICB combination therapy, chitin alleviated anti-PD-1 resistance in both TNBC models, providing a significant add-on reduction in primary tumor and lung metastatic growth compared to chitin monotherapy. These add-on effects occurred through additional increase in CD8α+ T-cell infiltration and activation in primary tumor and lymphoid organs. CONCLUSIONS: Chitin, as a general CLP blocker, reduces CLP production, enhances anti-tumor immunity as well as ICB responses, supporting its potential clinical relevance in immunosuppressed TNBC patients.

Thermodynamic and molecular dynamic insights into how fusion influences peptide-tag recognition of an antibody.

To understand the effect of protein fusion on the recognition of a peptide-tag by an antibody, we fused a CCR5-derived peptide-tag (pep1) to GFP and investigated its recognition by an anti-pep1 antibody, 4B08. First, to characterize the thermodynamic properties associated with the pep1-4B08 binding, isothermal titration calorimetry experiments were conducted. It was found that pep1 fused to the C-terminus of GFP (GFP-CT) enhanced the enthalpic gain by 2.1 kcal mol-1 and the entropic loss only by 0.9 kcal mol-1, resulting in an 8-fold increase in the binding affinity compared to the unfused pep1. On the other hand, pep1 fused to the N-terminus of GFP (GFP-NT) enhanced the enthalpic gain by 3.0 kcal mol-1 and the entropic loss by 3.2 kcal mol-1, leading to no significant enhancement of the binding affinity. To gain deeper insights, molecular dynamics simulations of GFP-NT, GFP-CT, and pep1 were performed. The results showed that the location of the fusion point sensitively affects the interaction energy, the solvent accessible surface area, and the fluctuation of pep1 in the unbound state, which explains the difference in the experimental thermodynamic properties.

Assessing Weak Anion Binding to Small Peptides.

Since Hofmeister's seminal studies in the late 19th century, it has been known that salts and buffers can drastically affect the properties of peptides and proteins. These Hofmeister effects can be conceived of in terms of three distinct phenomena/mechanisms: water-salt interactions that indirectly induce the salting-out of a protein by water sequestration by the salt, and direct salt-protein interactions that can either salt-in or salt-out the protein. Unfortunately, direct salt-protein interactions responsible for Hofmeister effects are weak and difficult to quantify. As such, they are frequently construed of as being nonspecific. Nevertheless, there has been considerable effort to better specify these interactions. Here, we use pentapeptides to demonstrate the utility of the H-dimension of nuclear magnetic resonance (NMR) spectroscopy to assess anion binding using N-H signal shifts. We qualify binding using these, demonstrating the upfield shifts induced by anion association and revealing how they are much larger than the corresponding downfield shifts induced by magnetic susceptibility and other ionic strength change effects. We also qualify binding in terms of how the pattern of signal shifts changes with point mutations. In general, we find that the observed upfield shifts are small compared with those induced by anion binding to amide-based hosts, and MD simulations suggest that this is so. Thus, charge-diffuse anions associate mostly with the nonpolar regions of the peptide rather than directly interacting with the amide N-H groups. These findings reveal the utility of 1H NMR spectroscopy for qualifying affinity to peptides─even when affinity constants are very low─and serve as a benchmark for using NMR spectroscopy to study anion binding to more complex systems.

DrugMGR: a deep bioactive molecule binding method to identify compounds targeting proteins.

MOTIVATION: Understanding the intermolecular interactions of ligand-target pairs is key to guiding the optimization of drug research on cancers, which can greatly mitigate overburden workloads for wet labs. Several improved computational methods have been introduced and exhibit promising performance for these identification tasks, but some pitfalls restrict their practical applications: (i) first, existing methods do not sufficiently consider how multigranular molecule representations influence interaction patterns between proteins and compounds; and (ii) second, existing methods seldom explicitly model the binding sites when an interaction occurs to enable better prediction and interpretation, which may lead to unexpected obstacles to biological researchers. RESULTS: To address these issues, we here present DrugMGR, a deep multigranular drug representation model capable of predicting binding affinities and regions for each ligand-target pair. We conduct consistent experiments on three benchmark datasets using existing methods and introduce a new specific dataset to better validate the prediction of binding sites. For practical application, target-specific compound identification tasks are also carried out to validate the capability of real-world compound screen. Moreover, the visualization of some practical interaction scenarios provides interpretable insights from the results of the predictions. The proposed DrugMGR achieves excellent overall performance in these datasets, exhibiting its advantages and merits against state-of-the-art methods. Thus, the downstream task of DrugMGR can be fine-tuned for identifying the potential compounds that target proteins for clinical treatment. AVAILABILITY AND IMPLEMENTATION: https://github.com/lixiaokun2020/DrugMGR.

Maturation and Conformational Switching of a De Novo Designed Phase-Separating Polypeptide.

Cellular compartments formed by biomolecular condensation are widespread features of cell biology. These organelle-like assemblies compartmentalize macromolecules dynamically within the crowded intracellular environment. However, the intermolecular interactions that produce condensed droplets may also create arrested states and potentially pathological assemblies such as fibers, aggregates, and gels through droplet maturation. Protein liquid-liquid phase separation is a metastable process, so maturation may be an intrinsic property of phase-separating proteins, where nucleation of different phases or states arises in supersaturated condensates. Here, we describe the formation of both phase-separated droplets and proteinaceous fibers driven by a de novo designed polypeptide. We characterize the formation of supramolecular fibers in vitro and in bacterial cells. We show that client proteins can be targeted to the fibers in cells using a droplet-forming construct. Finally, we explore the interplay between phase separation and fiber formation of the de novo polypeptide, showing that the droplets mature with a post-translational switch to largely ß conformations, analogous to models of pathological phase separation.

Novel genetic variant in hereditary spastic paraparesis.

A man in his 30s was referred to neurology with right-sided paraesthesia, tremors, chest pain and lower urinary tract and erectile dysfunction. He had a medical history of left acetabular dysplasia, and subjective memory impairment, the latter being in the context of depression and chronic pain with opioid use. There was no notable family history. On examination, he had a spastic paraparesis. Imaging revealed atrophy of the thoracic spine. Lumbar puncture demonstrated a raised protein but other constituents were normal, including no presence of oligoclonal bands. Genetic testing revealed a novel heterozygous likely pathogenic SPAST variant c. 1643A>T p.(Asp548Val), confirming the diagnosis of hereditary spastic paraparesis. Symptomatic treatment with physiotherapy and antispasmodic therapy was initiated. This is the first study reporting a patient with this SPAST variant. Ensembl variant effect predictor was used, with the application of computational variant prediction tools providing support that the variant we have identified is likely deleterious and damaging. Our variant CADD score was high, indicating that our identified variant was a highly deleterious substitution.

Transmucosal Delivery of Peptides and Proteins Through Nanofibers: Current Status and Emerging Developments.

Advancements in recombinant DNA technology have made proteins and peptides available for diagnostic and therapeutic applications, but their effectiveness when taken orally leads to poor patient compliance, requiring clinical administration. Among the alternative routes, transmucosal delivery has the advantage of being noninvasive and bypassing hepato-gastrointestinal clearance. Various mucosal routes-buccal, nasal, pulmonary, rectal, and vaginal-have been explored for delivering these macromolecules. Nanofibers, due to their unique properties like high surface-area-to-volume ratio, mechanical strength, and improved encapsulation efficiency, serve as promising carriers for proteins and peptides. These nanofibers can be tailored for quick dissolution, controlled release, enhanced encapsulation, targeted delivery, and improved bioavailability, offering superior pharmaceutical and pharmacokinetic performance compared to conventional methods. This leads to reduced dosages, fewer side effects, and enhanced patient compliance. Hence, nanofibers hold tremendous potential for protein/peptide delivery, especially through mucosal routes. This review focuses on the therapeutic application of proteins and peptides, challenges faced in their conventional delivery, techniques for fabricating different types of nanofibers and, various nanofiber-based dosage forms, and factors influencing nanofiber generation. Insights pertaining to the precise selection of materials used for fabricating nanofibers and regulatory aspects have been covered. Case studies wherein the use of specific protein/peptide-loaded nanofibers and delivered via oral/vaginal/nasal mucosa for diagnostic/therapeutic use and related preclinical and clinical studies conducted have been included in this review.

Molecular docking and molecular dynamics simulation decoding molecular mechanism of EDCs binding to hERRγ.

CONTEXT: Human estrogen-related receptor γ (hERRγ) is a key protein involved in various endocrines and metabolic signaling. Numerous environmental endocrine-disrupting chemicals (EDCs) can impact related physiological activities through receptor signaling pathways. Focused on hERRγ with 4-isopropylphenol, bisphenol-F (BPF), and BP(2,2)(Un) complexes, we executed molecular docking and multiple molecular dynamics (MD) simulations along with molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) and solvation interaction energy (SIE) calculation to study the detailed dynamical structural characteristics and interactions between them. Molecular docking showed that hydrogen bonds and hydrophobic interactions were the prime interactions to keep the stability of BPF-hERRγ and hERRγ-BP(2,2)(Un) complexes. Through MD simulations, we observed that all complexes reach equilibrium during the initial 50 ns of simulation, but these three EDCs lead to local structure changes in hERRγ. Energy results further identified key residues L268, V313, L345, and F435 around the binding pockets through CH-π, π-π, and hydrogen bonds interactions play an important stabilizing role in the recognition with EDCs. And most noticeable of all, hydrophobic methoxide groups in BP(2,2)(Un) is useful for decreasing the binding ability between EDCs and hERRγ. These results may contribute to evaluate latent diseases associated with EDCs exposure at the micro level and find potential substitutes. METHOD: Autodock4.2 was used to conduct the molecular docking, sietraj program was performed to calculate the energy, and VMD software was used to visualize the structure. Amber18 was conducted to perform the MD simulation and other analyses.

Beyond self­eating: Emerging autophagy­independent functions for the autophagy molecules in cancer (Review).

Autophagy is a conserved catabolic process that controls organelle quality, removes misfolded or abnormally aggregated proteins and is part of the defense mechanisms against intracellular pathogens. Autophagy contributes to the suppression of tumor initiation by promoting genome stability, cellular integrity, redox balance and proteostasis. On the other hand, once a tumor is established, autophagy can support cancer cell survival and promote epithelial­to­mesenchymal transition. A growing number of molecules involved in autophagy have been identified. In addition to their key canonical activity, several of these molecules, such as ATG5, ATG12 and Beclin­1, also exert autophagy­independent functions in a variety of biological processes. The present review aimed to summarize autophagy­independent functions of molecules of the autophagy machinery and how the activity of these molecules can influence signaling pathways that are deregulated in cancer progression.