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Resistance training is used to combat skeletal muscle function decline in older adults. Few studies have been designed specific for females, resulting in very limited treatment options for skeletal muscle atrophy in aging women. Here, we analyzed the gene expression profiles of skeletal muscle samples from sedentary young women, sedentary older women, and resistance-trained older women, using microarray data from public database. A total of 45 genes that were differentially expressed during female muscle aging and reversed by resistance training were identified. Functional and pathway enrichment analysis, protein–protein interaction network analysis, and receiver operating characteristic analysis were performed to reveal the key genes and pathways involved in the effects of resistance training on female muscle aging. The collagen genes COL1A1, COL3A1, and COL4A1 were identified important regulators of female muscle aging and resistance training, by modulating multiple signaling pathways, such as PI3 kinase-Akt signaling, focal adhesions, extracellular matrix-receptor interactions, and relaxin signaling. Interestingly, the expression of CDKN1A and TP63 were increased during aging, and further upregulated by resistance training in older women, suggesting they may negatively affect resistance training outcomes. Our findings provide novel insights into the molecular mechanisms of resistance training on female muscle aging and identify potential biomarkers and targets for clinical intervention. [ABSTRACT FROM AUTHOR]

Proximity labeling (PL) via biotinylation coupled with mass spectrometry (MS) captures spatial proteomes in cells. Large-scale processing requires a workflow minimizing hands-on time and enhancing quantitative reproducibility. We introduced a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. Combining this with optimized quantitative MS based on data-independent acquisition (DIA), we increased sample throughput and improved protein identification and quantification reproducibility. We applied this pipeline to delineate subcellular proteomes across various compartments. Using the 5HT2A serotonin receptor as a model, we studied temporal changes of proximal interaction networks induced by receptor activation. In addition, we modified the pipeline for reduced sample input to accommodate CRISPR-based gene knockout, assessing dynamics of the 5HT2A network in response to perturbation of selected interactors. This PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, enhancing throughput and reproducibility of standard protocols.

Single-gene missense mutations remain challenging to interpret. Here, we deploy scalable functional screening by sequencing (SEUSS), a Perturb-seq method, to generate mutations at protein interfaces of RUNX1 and quantify their effect on activities of downstream cellular programs. We evaluate single-cell RNA profiles of 115 mutations in myelogenous leukemia cells and categorize them into three functionally distinct groups, wild-type (WT)-like, loss-of-function (LoF)-like, and hypomorphic, that we validate in orthogonal assays. LoF-like variants dominate the DNA-binding site and are recurrent in cancer; however, recurrence alone does not predict functional impact. Hypomorphic variants share characteristics with LoF-like but favor protein interactions, promoting gene expression indicative of nerve growth factor (NGF) response and cytokine recruitment of neutrophils. Accessible DNA near differentially expressed genes frequently contains RUNX1-binding motifs. Finally, we reclassify 16 variants of uncertain significance and train a classifier to predict 103 more. Our work demonstrates the potential of targeting protein interactions to better define the landscape of phenotypes reachable by missense mutations.

Photosynthesis has been using energy from sunlight to assimilate atmospheric CO2 for at least 3.5 billion years. Through evolution and natural selection, photosynthetic organisms have flourished in almost all aquatic and terrestrial environments. This is partly due to the diversity of light-harvesting complex (LHC) proteins, which facilitate photosystem assembly, efficient excitation energy transfer, and photoprotection. Structural advances have provided angstrom-level structures of many of these proteins and have expanded our understanding of the pigments, lipids, and residues that drive LHC function. In this review, we compare and contrast recently observed cryo-electron microscopy structures across photosynthetic eukaryotes to identify structural motifs that underlie various light-harvesting strategies. We discuss subtle monomer changes that result in macroscale reorganization of LHC oligomers. Additionally, we find recurring patterns across diverse LHCs that may serve as evolutionary stepping stones for functional diversification. Advancing our understanding of LHC protein-environment interactions will improve our capacity to engineer more productive crops.

The heterohexameric ATPases associated with diverse cellular activities (AAA)-ATPase Pex1/Pex6 is essential for the formation and maintenance of peroxisomes. Pex1/Pex6, similar to other AAA-ATPases, uses the energy from ATP hydrolysis to mechanically thread substrate proteins through its central pore, thereby unfolding them. In related AAA-ATPase motors, substrates are recruited through binding to the motor's N-terminal domains or N terminally bound cofactors. Here, we use structural and biochemical techniques to characterize the function of the N1 domain in Pex6 from budding yeast, Saccharomyces cerevisiae. We found that although Pex1/ΔN1-Pex6 is an active ATPase in vitro, it does not support Pex1/Pex6 function at the peroxisome in vivo. An X-ray crystal structure of the isolated Pex6 N1 domain shows that the Pex6 N1 domain shares the same fold as the N-terminal domains of PEX1, CDC48, and NSF, despite poor sequence conservation. Integrating this structure with a cryo-EM reconstruction of Pex1/Pex6, AlphaFold2 predictions, and biochemical assays shows that Pex6 N1 mediates binding to both the peroxisomal membrane tether Pex15 and an extended loop from the D2 ATPase domain of Pex1 that influences Pex1/Pex6 heterohexamer stability. Given the direct interactions with both Pex15 and the D2 ATPase domains, the Pex6 N1 domain is poised to coordinate binding of cofactors and substrates with Pex1/Pex6 ATPase activity.

Anaplastic lymphoma kinase (ALK) is a well-known oncogene involved in various malignancies such as anaplastic large cell lymphoma, lung cancer and neuroblastoma. Several substrates for fused ALK have been identified and their biological functions have been described. However, the lack of a comprehensive identification of ALK substrates limits our understanding of the biological roles of receptor ALK. Thus, this study aimed to identify novel ALK substrates and characterize their biological functions. We screened the interactors of the kinase domain of receptor ALK using proximity-dependent biotin identification and identified 43 interactors. We narrowed down the candidates by evaluating whether these interactors were downstream of ALK in a neuroblastoma cell line, NB-1. Amongst these, we identified amyloid beta precursor protein-binding family B member 1 (APBB1) as an ALK downstream molecule involved in NB-1 cell viability. Finally, we assessed the kinase-substrate relationship between ALK and APBB1 and found that ALK phosphorylated multiple tyrosine residues in APBB1 both in-cell and in-tube assays, with tyrosine 269 as a major target. In conclusion, we successfully identified a new substrate for receptor ALK. Our results may help further elucidate the molecular mechanism of ALK downstream signalling in neuroblastoma. [ABSTRACT FROM AUTHOR]

[Display omitted] • Temperature jump microscopy of live zebrafish larvae can study stress response. • Clean imaging is obtained by expressing fluorescent proteins in just a few cells. • Automated feedback and focusing mitigates temperature drift during experiments. • Hsp70 binds a client protein in vivo , while an inactive mutant does not. Biomolecular processes such as protein–protein interactions can depend strongly on cell type and even vary within a single cell type. Here we develop a microscope with a Peltier-controlled temperature stage, a laser temperature jump to induce heat stress, and an autofocusing feature to mitigate temperature drift during experiments, to study a protein–protein interaction in a selected cell type within a live organism, the zebrafish larva. As an application of the instrument, we show that there is considerable cell-to-cell variation of the heat shock protein Hsp70 binding to one of its clients, phosphoglycerate kinase in vivo. We adapt a key feature from our previous folding study, rare transformation of cells within the larva, so that individual cells can be imaged and differentiated for cell-to-cell response. Our approach can be extended to other organisms and cell types than the ones demonstrated in this work. [ABSTRACT FROM AUTHOR]

Protein-based therapeutics, including antibodies and antibody-like-proteins, have increasingly attracted attention due to their high specificity compared to small-molecular drugs. The Gγ recruitment system, one of the in vivo yeast two-hybrid systems for detecting protein–protein interactions, has been previously developed using yeast signal transduction machinery. In this study, we modified the Gγ recruitment system to screen the protein mutants that efficiently bind to the intracellular domain of the epidermal growth factor receptor L858R mutant (cytoEGFRL858R). Using the modified platform, we performed in vivo directed evolution for growth factor receptor-bound protein 2 (Grb2) and its truncated variant containing only the Src-homology 2 (SH2) domain, successfully identifying several mutants that more strongly bound to cytoEGFRL858R than their parental proteins. Some of them contained novel beneficial mutations (F108Y and Q144H) and specifically bound to the recombinant cytosolic phosphorylated EGFR in vitro , highlighting the utility of the evolutionary platform. [Display omitted] [ABSTRACT FROM AUTHOR]

A variety of variables influence food texture, two of which are gelation and emulsification. Protein interactions have an important role in influencing gelation and emulsifying properties. The utilization of plant proteins in the development of food systems is a prominent subject within the current protein transition paradigm. Plant proteins diminish gel strength compared to dairy proteins. Protein providers prefer to create their own networks rather than rely on tight ties. It may be feasible to resolve these challenges if the interactions between plant and dairy proteins are known at all sizes, from molecular to macroscopic. Therefore, the proteins and dairy proteins are the main emphasis of this review. The role of these proteins in interacting with food matrices is also discussed. Additionally, this data gives information on worldwide research trends. Finally, a glimpse into the future was discussed. [ABSTRACT FROM AUTHOR]

Microorganisms are evolving to withstand the effect of antimicrobial agents and thereby pose a global threat known as antimicrobial resistance. Resistance towards multiple drugs due to various intrinsic as well environmental factors leads to an even more dangerous drug resistance property known as multi-drug resistance (MDR). WHO has recognized MDR bacteria as a top global threat as they complicate the treatment and augment mortality and morbidity risks. Gram-negative bacteria produce beta-lactamase enzymes that can hydrolyze beta-lactam antibiotics, impacting drug susceptibility. Stenotrophomonas maltophilia, an opportunistic pathogen, exemplifies MDR due to the production of two types of beta-lactamases. The metallo-beta-lactamase (MBL) L1 produced by the bacteria is a class B1 zinc-dependent MBL that is broadly substrate-specific and is a challenge to the currently available treatment options. This study constructs and analyzes a protein-protein interaction network of L1 beta-lactamase to comprehend its role in the MDR property of the bacteria. The network encompasses 51 proteins including L1 MBL (Smlt2667) and 382 interactions, revealing key players in MDR and potential drug targets. The network analysis aids the discernment of antimicrobial gene impact on cellular function, informing drug discovery strategies. This research addresses the emerging challenge of antibiotic resistance and identifies pathways for therapeutic intervention. [ABSTRACT FROM AUTHOR]

The ubiquitin‐conjugating E2 enzymes play a central role in ubiquitin transfer. Disruptions to the ubiquitin system are implicated in multiple diseases, and as a result, molecules that modulate the activity of the ubiquitin system are of interest. E2 enzyme function relies on interactions with partner proteins, and the disruption of these is an effective way to modulate activity. Here, we report the discovery of ubiquitin variants (UbVs) that inhibit the E2 enzyme, Ube2d2 (UbcH5b). The six UbVs identified inhibit ubiquitin chain building, and the structural and biophysical characterisation of two of these demonstrate they bind to Ube2d2 with low micromolar affinity and high specificity. Both characterised UbVs bind at a site that overlaps with E1 binding, while the more inhibitory UbV has an additional binding site that blocks a critical non‐covalent ubiquitin‐binding site on the E2 enzyme. The discovery of novel protein‐based ubiquitin derivatives that inhibit protein–protein interactions is an important step towards discovering small molecules that inhibit the activity of E2 enzymes. Furthermore, the specificity of the UbVs within the Ube2d family suggests that it may be possible to develop tools to selectively inhibit highly related E2 enzymes. [ABSTRACT FROM AUTHOR]

Malaria is a potentially fatal infective illness caused due to parasites that belong to the Plasmodium genus, which are transferred to humans with the help of the stings of affected female Anopheles mosquitoes, and it persists as a serious public wellness problem worldwide. Cordia myxa is a medicinal plant that possesses various medicinal characteristics like antimicrobial, anti-inflammation, antioxidant, and antidiabetic activities, which makes it an important natural resource for the therapy of different maladies in traditional medicine. In this investigation, a certain network pharmacology method has been utilized to identify the potent active components, possible targets as well as signaling pathways present in C. myxa in relation to malaria therapy. The active compounds were submitted to molecular docking approaches to validate their successful activity against the potential targets. The study concluded that three constituents named cosmosiin, stigmastanol, robinetin, and quercetin were highly active and could regulate the expression of Interleukin 6 (IL6) and Cysteine-aspartic acid protease 3 (CASP3), which may act as a potential therapeutic target for malaria treatment. These analyses are validated by molecular dynamics simulation which reflects on the overall structural stability of the intermolecular conformation and interactions. These results can also be witnessed in simulation-based trajectories binding free energies, which concluded the significant role of electrostatic and van der Waals energies in total intermolecular interactions. Finally, we utilized machine learning to predict the anti-malarial activity of C. myxa compounds, comparing them with approved drugs. Using the Chemprop model and MAIP predictions, we assessed ten compounds, revealing their potential as lead anti-malarial agents. This study establishes a groundwork for comprehending the function of the anti-malaria action of C. myxa. [ABSTRACT FROM AUTHOR]

Ubiquitin (Ub) signals are recognized and decoded into cellular responses by Ub-receptors, proteins that tether the Ub-binding domain(s) (UBDs) with response elements. Typically, UBDs bind mono-Ub in highly dynamic and weak affinity manners, presenting challenges in identifying and characterizing their binding interfaces. Here, we report the development of a new approach to facilitate the detection of these weak interactions using split-reporter systems where two interacting proteins are proximally co-translated from a single mRNA. This proximity significantly enhances the readout signals of weak protein–protein interactions (PPIs). We harnessed this system to characterize the ultra-weak UBD and ENTH (Epsin N-terminal Homology) and discovered that the yeast Ent1-ENTH domain contains two Ub-binding patches. One is similar to a previously characterized patch on STAM1(signal-transducing adaptor molecule)-VHS (Vps27, Hrs, and STAM), and the other was predicted by AlphaFold. Using a split-CAT selection system that co-translates Ub and ENTH in combination with mutagenesis, we assessed and confirmed the existence of a novel binding patch around residue F53 on ENTH. Co-translation in the split-CAT system provides an effective tool for studying weak PPIs and offers new insights into Ub-receptor interactions. [ABSTRACT FROM AUTHOR]

Plastocyanin is a small mobile protein that facilitates electron transfer through the formation of short-lived protein–protein complexes with cytochrome bf and photosystem 1. Due to the transient nature of plastocyanin–cytochrome f complex, the lack of a long-lived tight complex makes it impossible to determine its structure by X-ray diffraction analysis. Up to today, a number of slightly different structures of such complexes have been obtained by experimental and computer methods. Now, artificial intelligence gives us the possibility to predict the structures of intermolecular complexes. In this study, we compare encounter and final complexes obtained by Brownian and molecular dynamics methods, as well as the structures predicted by AlphaFold 3, with NMR and cryo-EM data. Surprisingly, the best match for the plastocyanin electron density obtained by cryo-EM was demonstrated by an AlphaFold 3 structure. The orientation of plastocyanin in this structure almost completely coincides with its orientation obtained by molecular dynamics calculation, and, at the same time, it is different from the orientation of plastocyanin predicted on the basis of NMR data. This is even more unexpected given that only NMR structures for the plastocyanin-cytochrome f complex are available in the PDB database, which was used to train AlphaFold 3. [ABSTRACT FROM AUTHOR]

SUMMARY: Leaf size is a crucial agronomic trait directly affecting crop yield, which is mainly determined by coordinated cell proliferation, growth, and differentiation. Although endoreduplication is known to be correlated with the onset of cell differentiation and leaf size, the underlying molecular mechanisms are largely unclear. The DnaJ‐like zinc finger domain‐containing protein ORANGE (OR) was initially demonstrated to confer the massive accumulation of carotenoids in cauliflower curds. However, the cauliflower or mutant also possesses other phenotypes such as smaller curds, smaller leaves with elongated petioles, and delayed flowering. Here, we demonstrated that OR physically interacts with the transcription factor TCP7, which promotes endoreduplication by inducing the expression of the cell cycle gene CYCLIN D 1;1 (CYCD1;1). Overexpression of OR resulted in smaller rosette leaves, whereas the OR‐silencing plants had larger rosette leaves than wild‐type plants. Our microscopic observations and flow cytometry analysis revealed that the variation in leaf size was a result of different endoreduplication levels. Genetic analyses showed that OR functions antagonistically with TCP7 in regulating the endoreduplication levels in leaf cells. While the expression of OR is induced by TCP7, OR represses the transactivation activity of TCP7 by affecting its binding capability to the TCP‐binding motif in the promoter region of CYCD1;1. Through this interaction, OR negatively regulates the expression of CYCD1;1 and reduces the nuclear ploidy level in rosette leaf cells. Our findings provide new insights into the regulatory network of leaf size and also reveal a regulatory circuit controlling endoreduplication in leaf cells. Significance Statement: The zinc finger domain‐containing protein ORANGE (OR) has been reported to possess multiple functions in regulating carotenoid biosynthesis, petiole elongation, flowering, and de‐etiolation. Here, we demonstrated that, by repressing the transactivation activity of TCP7 through protein–protein interaction, OR negatively regulates the expression of the cell cycle gene CYCD1;1 and reduces the nuclear ploidy level in rosette leaf cells. [ABSTRACT FROM AUTHOR]

Mcm10 plays an essential role in the activation of replicative helicase CMG through the cell cycle-regulated interaction with the prototype MCM double hexamer in Saccharomyces cerevisiae. In this study, we reported that Mcm10 is phosphorylated by S-phase cyclin-dependent kinases (S-CDKs) at S66, which enhances Mcm10--MCM association during the S phase. S66A single mutation or even deletion of whole N-terminus (a.a. 1-128) only causes mild growth defects. Nevertheless, S66 becomes indispensable in the absence of the Mcm10 C-terminus ((a.a. 463-571), the major MCM-binding domain. Using a two-degron strategy to efficiently deplete Mcm10, we show that mcm10-S66AΔC has a severe defect in proceeding into the S phase. Notably, both lethality and S-phase deficiency can be rescued by artificially tethering mcm10-S66AΔC to MCM. These findings illustrate how the Mcm10-MCM association is regulated as a crucial event in DNA replication initiation. [ABSTRACT FROM AUTHOR]

Gynostemma pentaphyllum, a traditional Chinese medicine, is widely used to treat various diseases, but its therapeutic effects and mechanisms of action on hyperlipidemia remain unclear. This study aims to investigate the effects of Danshen leaf on hyperlipidemia through network pharmacology, molecular docking, and cellular experiments, elucidating its multifaceted mechanism of action within the LOX1‐PI3K‐AKT‐eNOS pathway. First, the active ingredients and targets of G. pentaphyllum were screened using the Traditional Chinese Medicine Systems Pharmacology database. Then, targets for hyperlipidemia were identified using the OMIM and GeneCards databases, and potential therapeutic targets for G. pentaphyllum in treating hyperlipidemia were determined. An active ingredient‐target network was constructed using Cytoscape software, and a protein–protein interaction (PPI) network was built and visualized using the STRING database and Cytoscape software. Finally, GO functional and KEGG pathway enrichment analyses were performed, and the predicted mechanisms were validated through molecular docking and cell experiments. 85 targets for G. pentaphyllum and 1556 for Hyperlipidemia were screened, with 53 common targets. Twenty‐four active ingredients of G. pentaphyllum were found to be involved in the treatment of hyperlipidemia. Key nodes such as Rhamnazin, Isofucosterol, and quercetin, and targets NCOA2, NR3C2, PGR, and PPARG showed high relevance. In the PPI network, 8 nodes, including IL6, PPARG, and VEGFA, exhibited high centrality. GO functional and KEGG pathway enrichment analyses indicated that G. pentaphyllum may treat hyperlipidemia by influencing various biological functions and pathways, such as DNA‐binding transcription factor binding, RNA polymerase II‐specific DNA‐binding transcription factor binding, and lipid and atherosclerosis. Cell experiments demonstrated that G. pentaphyllum significantly regulated the expression of key proteins in the LOX1‐PI3K‐AKT‐eNOS pathway, thereby improving hyperlipidemia. G. pentaphyllum improves hyperlipidemia by mediating the LOX1‐PI3K‐AKT‐eNOS pathway. This study provides a new theoretical basis and experimental evidence for applying G. pentaphyllum to treating hyperlipidemia. [ABSTRACT FROM AUTHOR]

Background/Objectives: The study of oxidative stress in cells and ways to prevent it attract increasing attention. Antioxidant defense of cells can be activated by releasing the transcription factor Nrf2 from a complex with Keap1, its inhibitor protein. The aim of the work was to study the effect of the modular nanotransporter (MNT) carrying an R1 anti-Keap1 monobody (MNTR1) on cell homeostasis. Methods: The murine hepatocyte AML12 cells were used for the study. The interaction of fluorescently labeled MNTR1 with Keap1 fused to hrGFP was studied using the Fluorescence-Lifetime Imaging Microscopy–Förster Resonance Energy Transfer (FLIM-FRET) technique on living AML12 cells transfected with the Keap1-hrGFP gene. The release of Nrf2 from the complex with Keap1 and its levels in the cytoplasm and nuclei of the AML12 cells were examined using a cellular thermal shift assay (CETSA) and confocal laser scanning microscopy, respectively. The effect of MNT on the formation of reactive oxygen species was studied by flow cytometry using 6-carboxy-2′,7′-dichlorodihydrofluorescein diacetate. Results: MNTR1 is able to interact with Keap1 in the cytoplasm, leading to the release of Nrf2 from the complex with Keap1 and a rapid rise in Nrf2 levels both in the cytoplasm and nuclei, ultimately causing protection of cells from the action of hydrogen peroxide. The possibility of cleavage of the monobody in endosomes leads to an increase in the observed effects. Conclusions: These findings open up a new approach to specifically modulating the interaction of intracellular proteins, as demonstrated by the example of the Keap1-Nrf2 system. [ABSTRACT FROM AUTHOR]

Context: Currently, Chagas disease represents an important public health problem affecting more than 8 million people worldwide. The vector of this disease is the Trypanosoma cruzi (Tc) parasite. Our research specifically focuses on the structure and aggregation states of the enzyme aldo-keto reductase of Tc (TcAKR) reported in this parasite. TcAKR belongs to the aldo-keto reductase (AKR) superfamily, enzymes that catalyze redox reactions involved in crucial biological processes. While most AKRs are found in monomeric forms, some have been reported to form dimeric and tetrameric structures. This is the case for some TcAKR. To better understand how TcAKR multimers form and remain stable, we conducted a comprehensive computational analysis using molecular dynamics (MD) simulations. Our approach to elucidating the aggregation states of TcAKR involved two strategies. Initially, we explored the dynamic behaviour of pre-assembled TcAKR dimers. Subsequently, we examined the self-aggregation of eight monomers. This investigation led to the identification of crucial residues that contribute to the stabilization of protein-protein interactions. It was also found that TcAKRs can form stable supramolecular assemblies, with each monomer typically surrounded by three first neighbours. These findings align with experimental reports of tetrameric or more complex supramolecular structures. Our computational studies could guide further experimental investigations aiming at drug development and assist in designing strategies to modulate aggregation. Method: Atomistic molecular dynamics simulations were carried out. The TcAKR 3D model structure was obtained by homology modelling using the Swiss Model for the TcAKR sequence (GenBank accession no. EU558869). Further, we checked the model with Alphafold2 and found a high degree of similarity between models. Several tools were used to build the dimers including CLUSPRO, GRAMM-Docking, Hdock, and Py-dock. Protein superstructures were built using the PACKMOL package. CHARMM-GUI was used to set up the simulation systems. GROMACS version 2020.5 was used to perform the simulations with the CHARMM36 force field for the protein and ions and the TIP3P model for water. Further analyses were performed using VMD, GROMACS, AMBER tools, MDLovoFit, bio3d, and in-house programs. [ABSTRACT FROM AUTHOR]

Gas vesicles (GVs) are gas-filled microbial organelles formed by unique 3-nm thick, amphipathic, force-bearing protein shells, which can withstand multiple atmospheric pressures and maintain a physically stable air bubble with megapascal surface tension. However, the molecular process of GV assembly remains elusive. To begin understanding this process, we have devised a high-throughput in vivo assay to determine the interactions of all 11 proteins in the pNL29 GV operon. Complete or partial deletions of the operon establish interdependent relationships among GV proteins during assembly. We also examine the tolerance of the GV assembly process to protein mutations and the cellular burdens caused by GV proteins. Clusters of GV protein interactions are revealed, proposing plausible protein complexes that are important for GV assembly. We anticipate our findings will set the stage for designing GVs that efficiently assemble in heterologous hosts during biomedical applications. Synopsis: Growing interest in biomedical applications for gas vesicles (GVs) demands an understanding of their structure and assembly, but little is known to date on the roles of individual gas vesicle proteins (Gvps) as assembly factors. This study utilizes modular, parallelized protein-protein interaction screening to elucidate key interactions and interdependencies of Gvps during GV assembly. Out of 66 possible Gvp-to-Gvp interactions, 28 formed a dense protein-protein interaction network. Selective inclusion of other Gvps led to gain or loss of protein-protein interactions, revealing interdependence during GV assembly. Specific subnetworks of Gvps are revealed that may be linked to different stages of GV assembly. A number of Gvps show tolerance for fusion proteins during GV assembly, unveiling a degree of plasticity with implications for GV engineering. Iburg at al develop a high-throughput in vivo screen to construct a comprehensive map of the interactions among all 11 proteins of the pNL29 gas vesicle operon. [ABSTRACT FROM AUTHOR]

Background and objectives: Breast cancer remains a significant global health concern, warranting further exploration into its genetic basis and potential therapeutic targets. This study aimed to elucidate the genetic associations of seven pivotal genes with breast cancer and discern their potential role in disease prognosis. Methods: The genes VEGFA, BRCA1, RAD51, CCNB1, CHEK1, CDK1, and XRCC4 were curated from over 30 articles. Their association with breast cancer was analyzed using both in silico and in vitro techniques. The in silico assessment involved constructing a protein-protein interaction network, accompanied by Gene Ontology and pathway enrichment analysis. Further, survival and expression analysis were conducted using Kaplan-Meier Plotter and the UALCAN database respectively. At the protein level, expression was observed using the Human Protein Atlas database. The in vitro validation involved analyzing mRNA expression levels in 10 breast cancer tissue samples. Results: The study revealed that all seven genes are significantly upregulated in breast cancer tissues compared to normal tissues, highlighting their critical role in tumor development and progression. Protein-protein interaction analysis confirmed their central involvement in vital biological processes related to breast cancer. Survival analysis showed that high expressions of these genes are associated with poorer patient prognosis, with hazard ratios indicating their potential as prognostic markers. In vitro validation further supported their overexpression in breast cancer, suggesting their importance in molecular landscape of the disease and their value as targets for therapeutic intervention. Conclusions: This study provides a profound understanding of the genetic landscape of breast cancer, emphasizing the significance of the selected seven genes in the pathology of the disease. These findings suggest potential avenues for therapeutic targeting and the advancement of personalized medicine in breast cancer treatment. [ABSTRACT FROM AUTHOR]

Lytic phages control the timepoint of host cell lysis by timing the holin-mediated release of cell wall-degrading endolysins. In phage T4, the antiholin RI inhibits the holin T, thereby preventing the early release of the T4 endolysin and lysis. The antiholin achieves lysis inhibition (LIN) in response to phage superinfections, thereby increasing the chance for lysis in an environment with a lower phage concentration. The holin T consists of a small N-terminal cytoplasmic domain, a transmembrane helix, and a periplasmic C-terminal domain. The antiholin is targeted to the periplasm by a cleavable signal peptide. Recently, the periplasmic soluble domains of the holin and the antiholin were found to form T2/RI2 tetramers in crystals. To investigate the functional relevance of this complex, we reconstituted LIN in a phage-free system, using only RI, T, and endolysin, and combined targeted mutagenesis with functional analyses. Inactivation of the RI signal peptide cleavage site did not abolish LIN, indicating that RI can function in a membrane-bound state, which argued against the tetramer. This led to analyses showing that only one of the two T/RI interfaces in the tetramer is physiologically relevant, which is also the only interaction site predicted by AlphaFold2. Some holin mutations at this interaction site prevented lysis, suggesting that the RI interaction likely acts by blocking the holin oligomerization required for hole formation. We conclude that LIN is mediated by a dimeric T/RI complex that, unlike the tetramer, can be easily formed when both partners are membrane-anchored. [ABSTRACT FROM AUTHOR]

Lys48‐linked ubiquitin chains, regulating proteasomal protein degradation, are known to include cyclized forms. This cyclization hinders recognition by many downstream proteins by occluding the Ile44‐centered patch. In contrast, the A20‐like Znf domain of ZNF216 (a ubiquitin‐binding protein, A20 Znf) is expected to bind to cyclic ubiquitin chains via constitutively solvent‐exposed surfaces. However, the underlying interaction mechanism remains unclear. Here, our ITC and NMR experiments collectively showed that cyclization did not interfere with and even slightly enhance the molecular recognition of diubiquitin by A20 Znf. This effect is explained by the cyclization‐induced repression of conformational dynamics in diubiquitin and an enlarged molecular interface in the complex. Thus, these results suggest that cyclic ubiquitin chains can be involved in regulation of ZNF216‐dependent proteasomal protein degradation. [ABSTRACT FROM AUTHOR]

The emergence of antibiotic-resistant Streptococcus pneumoniae necessitates the discovery of novel therapeutic agents. This study investigated the antimicrobial potential of green-synthesized gold nanoparticles (AuNPs) fabricated using Arthrospira platensis extract. Characterization using Fourier transform infrared spectroscopy revealed the presence of functional groups such as ketones, aldehydes, and carboxylic acids in the capping agents, suggesting their role in AuNP stabilization. Transmission electron microscopy demonstrated the formation of rod-shaped AuNPs with a mean diameter of 134.8 nm, as determined by dynamic light scattering, and a zeta potential of −27.2 mV, indicating good colloidal stability. The synthesized AuNPs exhibited potent antibacterial activity against S. pneumoniae, with a minimum inhibitory concentration (MIC) of 12 μg/mL, surpassing the efficacy of the control antibiotic, tigecycline. To elucidate the underlying mechanisms of action, an untargeted metabolomic analysis of the A. platensis extract was performed, identifying 26 potential bioactive compounds belonging to diverse chemical classes. In silico studies focused on molecular docking simulations revealed that compound 22 exhibited a strong binding affinity to S. pneumoniae topoisomerase IV, a critical enzyme for bacterial DNA replication. Molecular dynamics simulations further validated the stability of this protein–ligand complex. These findings collectively highlight the promising antimicrobial potential of A. platensis-derived AuNPs and their constituent compounds, warranting further investigation for the development of novel anti-pneumococcal therapeutics. [ABSTRACT FROM AUTHOR]

Developing a potent antiviral agent to combat Coronavirus Disease-19 (COVID-19) is of critical importance as we may be at risk of the emergence of new virus strains or another pandemic recurrence. The interaction between the SARS-CoV-2 spike protein and Angiotensin Converting Enzyme 2 (ACE2) is the main protein-protein interaction (PPI) implicated in the virus entry into the host cells. Spike-ACE2 PPI represents a major target for drug intervention. We have repurposed a previously described protein-protein interaction detection method to be utilized as a drug screening assay. The assay was standardized using Chitosan nanoparticles (CNPs) as the drug and SARS-CoV-2 spike-ACE2 interaction as the PPI model. The assay was then used to screen four natural bioactive compounds: Curcumin (Cur), Gallic acid (GA), Quercetin (Q), and Silymarin (Sil), and their cytotoxicity was evaluated in vitro. Production of the spike protein and the evaluation of its activity in comparison to a standard commercial protein was part of our work as well. Here we describe a novel simple immunofluorescent screening assay to identify potential SARS-CoV-2 inhibitors that could assess the inhibitory effect of any ligand against any PPI. [ABSTRACT FROM AUTHOR]

Heat shock factor 2 (HSF2) is a versatile transcription factor that regulates gene expression under stress conditions, during development, and in disease. Despite recent advances in characterizing HSF2‐dependent target genes, little is known about the protein networks associated with this transcription factor. In this study, we performed co‐immunoprecipitation coupled with mass spectrometry analysis to identify the HSF2 interactome in mouse testes, where HSF2 is required for normal sperm development. Endogenous HSF2 was discovered to form a complex with several adhesion‐associated proteins, a finding substantiated by mass spectrometry analysis conducted in human prostate carcinoma PC‐3 cells. Notably, this group of proteins included the focal adhesion adapter protein talin‐1 (TLN1). Through co‐immunoprecipitation and proximity ligation assays, we demonstrate the conservation of the HSF2‐TLN1 interaction from mouse to human. Additionally, employing sequence alignment analyses, we uncovered a TLN1‐binding motif in the HSF2 C terminus that binds directly to multiple regions of TLN1 in vitro. We provide evidence that the 25 C‐terminal amino acids of HSF2, fused to EGFP, are sufficient to establish a protein complex with TLN1 and modify cell–cell adhesion in human cells. Importantly, this TLN1‐binding motif is absent in the C‐terminus of a closely related HSF family member, HSF1, which does not form a complex with TLN1. These results highlight the unique molecular characteristics of HSF2 in comparison to HSF1. Taken together, our data unveil the protein partners associated with HSF2 in a physiologically relevant context and identifies TLN1 as the first adhesion‐related HSF2‐interacting partner. [ABSTRACT FROM AUTHOR]

Pathological cardiac hypertrophy is the primary cause of heart failure, yet its underlying mechanisms remain incompletely understood. Transmembrane protein 100 (TMEM100) plays a role in various disorders, such as nervous system disease, pain and tumorigenesis, but its function in pathological cardiac hypertrophy is still unknown. In this study, we observed that TMEM100 is upregulated in cardiac hypertrophy. Functional investigations have shown that adeno-associated virus 9 (AAV9) mediated-TMEM100 overexpression mice attenuates transverse aortic constriction (TAC)-induced cardiac hypertrophy, including cardiomyocyte enlargement, cardiac fibrosis, and impaired heart structure and function. We subsequently demonstrated that adenoviral TMEM100 (AdTMEM100) mitigates phenylephrine (PE)-induced cardiomyocyte hypertrophy and downregulates the expression of cardiac hypertrophic markers in vitro, whereas TMEM100 knockdown exacerbates cardiomyocyte hypertrophy. The RNA sequences of the AdTMEM100 group and control group revealed that TMEM100 was involved in oxidative stress and the MAPK signaling pathway after PE stimulation. Mechanistically, we revealed that the transmembrane domain of TMEM100 (amino acids 53–75 and 85–107) directly interacts with the C-terminal region of TAK1 (amino acids 1–300) and inhibits the phosphorylation of TAK1 and its downstream molecules JNK and p38. TAK1-binding-defective TMEM100 failed to inhibit the activation of the TAK1-JNK/p38 pathway. Finally, the application of a TAK1 inhibitor (iTAK1) revealed that TAK1 is necessary for TMEM100-mediated cardiac hypertrophy. In summary, TMEM100 protects against pathological cardiac hypertrophy through the TAK1-JNK/p38 pathway and may serve as a promising target for the treatment of cardiac hypertrophy. [ABSTRACT FROM AUTHOR]

Background: Risperidone is one of the most reliable and effective antipsychotics for schizophrenia treatment. However, the mechanism of action of risperidone is not yet fully understood. Traf2 and Nck-interacting protein kinase (TNIK), a schizophrenia susceptibility gene, is associated with risperidone treatment response. Our previous in vitro experiments confirmed that downregulated TNIK affected the effect of risperidone on downstream targets. However, the effect of downregulated TNIK on risperidone-induced molecular expression remains to be further explored. Methods: Transcriptome analysis was performed on U251 cells subjected to risperidone, TNIK siRNA, and no treatment, respectively. Compared to the notreatment group, two groups of DEGs were screened out and then intersected with the schizophrenia-related genes to screen the cross-talk genes. Those DEGs were analyzed using GO and KEGG. STRING and Cytoscape were used to construct a protein-protein interaction (PPI) network for the cross-talk gene. Results: The results showed that the parathyroid hormone synthesis, secretion, and action were significantly enriched after risperidone treatment. Downregulated TNIK could have an impact on the collagen-containing extracellular matrix, signaling receptor activator activity, and PI3K-Akt signaling pathway. Interestingly, bone mineralization function and calcium signaling pathway were enriched in the cross-talk genes. Additionally, FGFR2, FGF1, and FGFR might be the potential targets for TNIK affecting the effects of risperidone. Conclusion: The study indicated that risperidone primarily influences functions and/or pathways associated with bone metabolism, potentially contributing to the adverse effect of osteoporosis. Our study may offer a novel perspective on investigating the mechanisms underlying the adverse effects of risperidone. [ABSTRACT FROM AUTHOR]

Whole genome and exome sequencing are reporting on hundreds of thousands of missense mutations. Taking a pan-disease approach, we explored how mutations in intrinsically disordered regions (IDRs) break or generate protein interactions mediated by short linear motifs. We created a peptide-phage display library tiling ~57,000 peptides from the IDRs of the human proteome overlapping 12,301 single nucleotide variants associated with diverse phenotypes including cancer, metabolic diseases and neurological diseases. By screening 80 human proteins, we identified 366 mutation-modulated interactions, with half of the mutations diminishing binding, and half enhancing binding or creating novel interaction interfaces. The effects of the mutations were confirmed by affinity measurements. In cellular assays, the effects of motif-disruptive mutations were validated, including loss of a nuclear localisation signal in the cell division control protein CDC45 by a mutation associated with Meier-Gorlin syndrome. The study provides insights into how disease-associated mutations may perturb and rewire the motif-based interactome. Synopsis: Hundreds of mutations in the intrinsically disordered regions of the human proteome that break, diminish, enhance or create motif-based interactions are uncovered by mutational proteomic peptide-phage display. A novel peptide-phage display library that combines disease-associated amino acid changing mutations with the intrinsically disordered regions of the human proteome is described. 275 mutations associated with various diseases are reported to affect 279 motif-based protein-protein interactions. About 50% of the mutations enhance or create binding motifs, and the rest disrupt or diminish interactions. The study provides novel insights into how disease-associated mutations perturb and rewire the motif-based interactome. Hundreds of mutations in the intrinsically disordered regions of the human proteome that break, diminish, enhance or create motif-based interactions are uncovered by mutational proteomic peptide-phage display. [ABSTRACT FROM AUTHOR]

Plants are rich in tandem repeats-containing proteins. It is postulated that the occurrence of tandem repeat gene families facilitates the adaptation and survival of plants in adverse environmental conditions. This study intended to identify the tandem repeats in the transcriptome of a high potential tropical horticultural plant, roselle (Hibiscus sabdariffa L.). A total of 92,974 annotated de novo assembled transcripts were analysed using in silico approach, and 6,541 transcripts that encoded proteins containing tandem repeats with length of 20-60 amino acid residues were identified. Domain analysis revealed a total of nine tandem repeat protein families in the transcriptome of roselle, which are the Ankyrin repeats (ANK), Armadillo repeats (ARM), elongation factor-hand domain repeats (EF- hand), Huntingtin, elongation factor 3, protein phosphatase 2A, yeast kinase TOR1 repeats (HEAT), Kelch repeats (Kelch), leucine rich repeats (LRR), pentatricopeptide repeats (PPR), tetratricopeptide repeats (TPR) and WD40 repeats (WD40). Functional annotation analysis further matched 6,236 transcripts to 1,045 known proteins that contained tandem repeats including proteins implicated in plant development, protein-protein interaction, immunity and abiotic stress responses. The findings provide new insights into the occurrence of tandem repeats in the transcriptome and lay the foundation to elucidate the functional associations between tandem peptide repeats (TRs) and proteins in roselle and facilitate the identification of novel biotic and abiotic response related tandem repeats genes that may be useful in breeding improved varieties. [ABSTRACT FROM AUTHOR]

The protein–protein interaction (PPI) network of the Mediator complex is very tightly regulated and depends on different developmental and environmental cues. Here, we present an interactive platform for comparative analysis of the Mediator subunits from humans, baker's yeast Saccharomyces cerevisiae, and model plant Arabidopsis thaliana in a user‐friendly web‐interface database called MediatorWeb. MediatorWeb provides an interface to visualize and analyze the PPI network of Mediator subunits. The database facilitates downloading the untargeted and unweighted network of Mediator complex, its submodules, and individual Mediator subunits to better visualize the importance of individual Mediator subunits or their submodules. Further, MediatorWeb offers network visualization of the Mediator complex and interacting proteins that are functionally annotated. This feature provides clues to understand functions of Mediator subunits in different processes. In an additional tab, MediatorWeb provides quick access to secondary and tertiary structures, as well as residue–level contact information for Mediator subunits in each of the three model organisms. Another useful feature of MediatorWeb is detection of interologs based on orthologous analyses, which can provide clues to understand the functions of Mediator complex in less explored kingdoms. Thus, MediatorWeb and its features can help the user to understand the role of Mediator complex and its subunits in the transcription regulation of gene expression. [ABSTRACT FROM AUTHOR]

In response to various stressors, the calmodulin-binding transcription activator (CAMTA) can regulate downstream genes involved in calcium (Ca2+)/calmodulin signaling after binding to calmodulin (CAM) or calmodulin-like (CML) proteins. We previously reported seven OsCAMTA genes available throughout the rice (Oryza sativa) genome and their docking with the best probable interactors. This refined study demonstrated the evolutionary conservation of OsCAMTA motif structure and its correlation with 41 different plant species through phylogenetic tree construction along with the detailed molecular docking study focusing specifically on the calmodulin-binding domain (CaMBD) of each CAMTA protein with all available CAM/CML proteins across the rice genome. More insights regarding these were obtained from gene duplication studies through synteny analysis. Protein–protein interactions by STRING database analysis were conducted to know the involvement of OsCAMTA proteins in various development and stress-dependent pathways by identifying probable interactors. Tissue-specific expression analysis through qRT-PCR revealed that all the OsCAMTA genes except OsCAMTA7a and OsCAMTA7b were abundantly expressed in the roots of rice plants. Transcript expressions of rice CAMTAs under differential salt concentrations have depicted their participation in salt stress activity. Gene expression analysis in various temperatures indicated the most up-regulation of OsCAMTA7b, OsCAMTA4 and OsCAMTA3b at 4 ºC, 37 ºC and 42 ºC, respectively. In comparison to earlier research on OsCAMTA genes, this study is the most comprehensive fine-tuned and well-honed research conducted through tissue-specific expression study, followed by spatio-temporal expression analysis under different stresses with protein–protein interaction studies, molecular docking and prediction of microRNA to target each of the OsCAMTAs. [ABSTRACT FROM AUTHOR]

Protein phosphatase 1 (PP1) complexes have emerged as promising targets for anticancer therapies. The ability of peptides to mimic PP1-docking motifs, and so modulate interactions with regulatory factors, has enabled the creation of highly selective modulators of PP1-dependent cellular processes that promote tumor growth. The major objective of this study was to develop a novel bioactive cell-penetrating peptide (bioportide), which, by mimicking the PP1-binding motif of caveolin-1 (CAV1), would regulate PP1 activity, to hinder prostate cancer (PCa) progression. The designed bioportide, herein designated CAVPENET, and a scrambled homologue, were synthesized using microwave-assisted solid-phase methodologies and evaluated using PCa cell lines. Our findings indicate that CAVPENET successfully entered PCa cells to influence both viability and migration. This tumor suppressor activity of CAVPENET was attributed to inhibition of AKT signaling, a consequence of increased PP1γ activity. This led to the suppression of glycolytic metabolism and alteration in lipid metabolism, collectively representing the primary mechanism responsible for the anticancer properties of CAVPENET. Our results underscore the potential of the designed peptide as a novel therapy for PCa patients, setting the stage for further testing in more advanced models to fully realize its therapeutic promise. [ABSTRACT FROM AUTHOR]

The African swine fever virus (ASFV) is a large and complex DNA virus that causes a highly lethal disease in swine, for which no antiviral drugs or vaccines are currently available. Studying viral–host protein–protein interactions advances our understanding of the molecular mechanisms underlying viral replication and pathogenesis and can facilitate the discovery of antiviral therapeutics. In this study, we employed affinity tagging and purification mass spectrometry to characterize the interactome of VPS39, an important cellular factor during the early phase of ASFV replication. The interaction network of VPS39 revealed associations with mitochondrial proteins involved in membrane contact sites formation and cellular respiration. We show that the ASFV proteins CP204L and A137R target VPS39 by interacting with its clathrin heavy-chain functional domain. Furthermore, we elaborate on the potential mechanisms by which VPS39 may contribute to ASFV replication and prioritize interactions for further investigation into mitochondrial protein function in the context of ASFV infection. [ABSTRACT FROM AUTHOR]

Elevated levels of Inter-alpha-trypsin-inhibitor heavy chain 4 (ITIH4) have grabbed attention in rheumatoid arthritis (RA) pathogenesis, though its precise mechanisms remain unexplored. To elucidate these mechanisms, a comprehensive strategy employing network pharmacology and molecular docking was utilized. RA targets were sourced from the DisGeNET Database while interacting targets of ITIH4 were retrieved from the STRING and Literature databases. Venny 2.1 was used to identify overlapping genes, followed by Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) through Cytoscape 3.10.2 software, and molecular docking was performed in the ClusPro server. The study identified 18 interacting proteins of ITIH4 associated with RA, demonstrating their major involvement in the chemokine signaling pathway by enrichment analysis. Molecular docking of ITIH4 with the 18 proteins revealed that C-X-C chemokine-receptor type 4 (CXCR4), a major protein associated with chemokine signaling, has the highest binding affinity with ITIH4 with energy −1705.7 kcal/mol forming 3 Hydrogen bonds in the active site pocket of ITIH4 with His441, Arg288, Asp443 amino acids. The effect of ITIH4 on CXCR4 was analyzed via knockdown studies in rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS), demonstrating the significant downregulation of CXCR4 protein expression validated by Western blot in RA-FLS. In conclusion, it was speculated that CXCR4 might serve as a potential receptor for ITIH4 to activate the chemokine signaling, exacerbating RA pathogenesis. [ABSTRACT FROM AUTHOR]

Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due to their low variability, cost-effectiveness, and minimal invasiveness in diagnostic procedures. Machine learning (ML) methods have been applied to enhance accuracy of the biomarker discovery. However, previous ML-based studies often overlook interactions between proteins, which are crucial in complex disorders like dementia. While protein–protein interactions (PPIs) have been used in network models, these models often fail to fully capture the diverse properties of PPIs due to their local awareness. This drawback increases the chance of neglecting critical components and magnifying the impact of noisy interactions. In this study, we propose a novel graph-based ML model for dementia subtype diagnosis, the graph propagational network (GPN). By propagating the independent effect of plasma proteins on PPI network, the GPN extracts the globally interactive effects between proteins. Experimental results showed that the interactive effect between proteins yielded to further clarify the differences between dementia subtype groups and contributed to the performance improvement where the GPN outperformed existing methods by 10.4% on average. [ABSTRACT FROM AUTHOR]

Many protein–protein interactions (PPIs) affect the ways in which small molecules bind to their constituent proteins, which can impact drug efficacy and regulatory mechanisms. While recent advances have improved our ability to independently predict both PPIs and ligand–protein interactions (LPIs), a comprehensive understanding of how PPIs affect LPIs is still lacking. Here, we examined 63 pairs of ligand–protein complexes in a benchmark dataset for protein–protein docking studies and quantified six typical effects of PPIs on LPIs. A multi-chain dynamics perturbation analysis method, called mcDPA, was developed to model these effects and used to predict small-molecule binding regions in protein–protein complexes. Our results illustrated that the mcDPA can capture the impact of PPI on LPI to varying degrees, with six similar changes in its predicted ligand-binding region. The calculations showed that 52% of the examined complexes had prediction accuracy at or above 50%, and 55% of the predictions had a recall of not less than 50%. When applied to 33 FDA-approved protein–protein-complex-targeting drugs, these numbers improved to 60% and 57% for the same accuracy and recall rates, respectively. The method developed in this study may help to design drug–target interactions in complex environments, such as in the case of protein–protein interactions. [ABSTRACT FROM AUTHOR]

The physiological activities within cells are mainly regulated through protein–protein interactions (PPI). Therefore, studying protein interactions has become an essential part of researching protein function and mechanisms. Traditional biological experiments required for PPI prediction are expensive and time consuming. For this reason, many methods based on predicting PPI from protein sequences have been proposed in recent years. However, existing computational methods usually require the combination of evolutionary feature information of proteins to predict PPI docking situations. Because different relevant features of selected proteins are chosen, there may be differences in the predicted results for PPI. This article proposes a PPI prediction method based on the pretrained protein sequence model ProtBert, combined with the Bidirectional Gated Recurrent Unit (BiGRU) and attention mechanism. Only using protein sequence information and leveraging ProtBert's powerful ability to capture amino acid feature information, BiGRU is used for further feature extraction of the amino acid vectors output by ProtBert. The attention mechanism is then applied to enhance the focus on different amino acid features and improve the expression ability of protein sequence features, ultimately obtaining binary classification results for protein interactions. Experimental results show that our proposed ProtBert-BiGRU-Attention model has good predictive performance for PPI. Through relevant comparative experiments, it has been proven that our model performs well in protein binary prediction. Furthermore, through the ablation experiment of the model, different deep learning modules' contributions to the prediction have been demonstrated. [ABSTRACT FROM AUTHOR]

In the chloroplast stroma, dynamic pH changes occur from acidic to alkaline in response to fluctuating light conditions. We investigated the pH dependency of the electron transfer reaction of ferredoxin-NADP+ reductase (FNR) with ferredoxin (Fd) isoproteins, Fd1 and Fd2, which are localized in mesophyll cells and bundle sheath cells, respectively, in the leaves of C4 plant maize. The pH-dependent profile of the electron transfer activity with FNR was quite different between Fd1 and Fd2, which was mainly explained by the opposite pH dependency of the K m value of these Fds for FNR. Replacement of the amino acid residue at position of 65 (D65N) and 78 (H78A) between the two Fds conferred different effect on their pH dependency of the K m value. Double mutations of the two residues between Fd1 and Fd2 (Fd1D65N/H78A and Fd2N65D/A78H) led to the mutual exchange of the pH dependency of the electron transfer activity. This exchange was mainly explained by the changes in the pH-dependent profile of the K m values. Therefore, the differences in Asp/Asn at position 65 and His/Ala at position 78 between Fd1 and Fd2 were shown to be the major determinants for their different pH dependency in the electron transfer reaction with FNR. [ABSTRACT FROM AUTHOR]

• 1063 differentially expressed genes mainly annotated by photosynthesis, DNA replication and carbon metabolism. • 45 phytohormones, including ABA, auxin, CK, ETH, GA, JA, and SA were effective expression. • IAA-Glc, IAA-Glu, TRP, mT9G, and GA53 show the strongest correlation with ssu1, ssu2, pep1, me3 , and hsp90. • The putatively Ribosomal L 18p/L5e gene was identified. Blue and red light play a significant role in regulating transcriptional expression, phytohormone levels, and gene signal network reconstruction in the shoot apical meristem. To further elucidate the effects of red and blue light on transcriptional characteristics and phytohormone expression, and to explore signaling pathways and novel genes, we conducted comparative experiments under different light quality treatments. The results are as follows: a total of 22,327 genes were found to be effectively expressed, with a considerable number of alternative splicing events occurring concurrently. Furthermore, 1063 differentially expressed genes were identified, primarily associated with transcriptional variations resulting from the transition from blue light to red light. These differentially expressed genes are predominantly involved in KEGG annotations related to photosynthesis, DNA replication and carbon metabolism. The findings from targeted metabolism analysis reveal significant variations in 45 phytohormones, including ABA, auxin, CK, ETH, GA, JA, and SA. Correlation analysis between transcription and metabolism further indicates that IAA.Glc, IAA.Glu, TRP, mT9G, and GA53 show the strongest correlation with differentially expressed genes, with genes ssu1, ssu2, pep1, me3 , and hsp90 displaying a significant relationship. Additionally, in the protein–protein interaction network, three novel genes (LOC100286132, LOC100510780 , and LOC103653934) were identified as significant responding to the regulation of blue and red light. Following protein function analysis, the proteins were provisionally identified as ubiquitin conjugating enzyme-like, OXIDATIVE STRESS 3LIKE 2-like, and Ribosomal L 18p/L5e, respectively. Conclusively, it is depicted that the most significant impact of transitions between red light, blue light, and two light qualities lies in the transcriptional process of shot apical meristem of the C4 plant maize. This process is intricately linked to nitrogen availability, carbon dioxide assimilation capacity, and the stimulatory effects of auxin, cytokinin, and gibberellin. The expression of the putative L 18/L5e in blue and BTR light conditions may enhance transcript and synthesis capabilities of ribosome. [ABSTRACT FROM AUTHOR]

Recent studies have shown that transmembrane‐type tight junction proteins are upregulated in various cancers compared with their levels in normal tissues and are involved in cancer progression, suggesting that they are potential therapeutic targets. Here, we demonstrated the expression profile and a novel role of junctional adhesion molecule‐A (JAM‐A) in breast cancer. Immunohistochemistry of surgical specimens showed that JAM‐A was highly expressed from carcinoma in situ lesions, as in other adenocarcinomas, with higher expression in invasive carcinomas. High expression of JAM‐A contributed to malignant aspects such as lymph node metastasis and lymphatic involvement positivity. In breast cancer cells, JAM‐A expression status affects malignant potentials including proliferation and migration. Multilayered proteomics revealed that JAM‐A interacts with the amino acid transporter LAT1 in breast cancer cells. JAM‐A regulates the expression of LAT1 and interacts with it on the whole cell membrane, leading to enhanced amino acid uptake to promote tumor growth. Double high expression of JAM‐A and LAT1 predicts poor prognosis in patients with breast cancer. Of note, an antibody against an extracellular domain of JAM‐A suppressed the proliferation of breast cancer cells. Our findings indicate the possibility of JAM‐A‐targeted therapy ideally combined with LAT1‐targeted therapy as a new therapeutic strategy against breast cancer. [ABSTRACT FROM AUTHOR]

Investigations of protein–protein interactions (PPIs) are of paramount importance for comprehending cellular processes within biological systems. The bimolecular fluorescence complementation (BiFC) assay presents a convenient methodology for visualizing PPIs within live cells. While a range of fluorescent proteins have been introduced into the BiFC system, there is a growing demand for new fluorescent proteins to accommodate the expanding requirements of researchers. This study describes the introduction of Tagged blue fluorescent protein 2 (TagBFP2) into the BiFC assay to verify the interaction between two proteins, with Enhanced yellow fluorescent protein (EYFP) employed as a positive control. Both fluorescent proteins demonstrated optimal performance in this study. Compared to EYFP, the BiFC system utilizing TagBFP2 yielded a higher signal-to-noise ratio, which facilitated differentiation of the signal of PPIs from noise and enabled employment of other fluorescent proteins within the BiFC assay. Notably, the utilization of a fluorescent secondary antibody in immunofluorescence applications or the tagging of an interest protein with a fluorescent protein occupied the green or yellow channel. Overall, the present article introduces a BiFC assay that is highly straightforward, reliable, and replicable, with the ability to be completed within 1 week. This method requires neither expensive instrumentation nor technical skills of a high order. [ABSTRACT FROM AUTHOR]

The significant reduction in cassava (Manihot esculenta Crantz) yields attributed to cassava bacterial blight (CBB) constitutes an urgent matter demanding prompt attention. The current study centered on the MebHLH149 transcription factor, which is acknowledged to be reactive to CBB and exhibits augmented expression levels, as indicated by laboratory transcriptome data. Our exploration, encompassing Xanthomonas phaseoli pv. manihotis strain CHN01 (Xpm CHN01) and hormone stress, disclosed that the MebHLH149 gene interacts with the pathogen at the early stage of infection. Furthermore, the MebHLH149 gene has been discovered to be responsive to the plant hormones abscisic acid (ABA), methyl jasmonate (MeJA), and salicylic acid (SA), intimating a potential role in the signaling pathways mediated by these hormones. An analysis of the protein's subcellular localization suggested that MebHLH149 is predominantly located within the nucleus. Through virus-induced gene silencing (VIGS) in cassava, we discovered that MebHLH149-silenced plants manifested higher disease susceptibility, less ROS accumulation, and significantly larger leaf spot areas compared to control plants. The proteins MePRE5 and MePRE6, which are predicted to interact with MebHLH149, demonstrated complementary downregulation and upregulation patterns in response to silencing and overexpression of the MebHLH149 gene. This implies a potential interaction between MebHLH149 and these proteins. Both MePRE5 and MePRE6 genes are involved in the initial immune response to CBB. Notably, MebHLH149 was identified as a protein that physically interacts with MePRE5 and MePRE6. Based on these findings, it is hypothesized that the MebHLH149 gene likely functions as a positive regulator in the defense mechanisms of cassava against CBB. [ABSTRACT FROM AUTHOR]

Background: Signal transducer and activator of transcription 3 (STAT3) is a member of the cytoplasmic inducible transcription factors and plays an important role in mediating signals from cytokines, chemokines, and growth factors. We and others have found that STAT3 directly regulates pro-fibrotic signaling in the kidney. The STAT3 protein–protein interaction plays an important role in activating its transcriptional activity. It is necessary to identify these interactions to investigate their function in kidney disease. Here, we investigated the protein–protein interaction among three species to find crucial interactions that can be targeted to alleviate kidney disease. Method: In this study, we examined common protein–protein interactions leading to the activation or downregulation of STAT3 among three different species: humans (Homo sapiens), mice (Mus musculus), and rabbits (Oryctolagus cuniculus). Further, we chose to investigate the P300 and STAT3 interaction and performed studies of the activation of STAT3 using IL-6 and inhibition of the P300 by its specific inhibitor A-485 in pericytes. Next, we performed immunoprecipitation to confirm whether A-485 inhibits the binding of P300 to STAT3. Results: Using the STRING application from ExPASy, we found that six proteins, including PIAS3, JAK1, JAK2, EGFR, SRC, and EP300, showed highly confident interactions with STAT3 in humans, mice, and rabbits. We also found that IL-6 treatment increased the acetylation of STAT3 and increased histone 3 lysine acetylation (H3K27ac). Furthermore, we found that the disruption of STAT3 and P300 interaction by the P300 inhibitor A-485 decreased STAT3 acetylation and H3K27ac. Finally, we confirmed that the P300 inhibitor A-485 inhibited the binding of STAT3 with P300, which inhibited its transcriptional activity by reducing the expression of Ccnd1 (Cyclin D1). Conclusions: Targeting the P300 protein interaction with STAT3 may alleviate STAT3-mediated fibrotic signaling in humans and other species. [ABSTRACT FROM AUTHOR]

In CASP15, 87 predictors submitted around 11 000 models on 41 assembly targets. The community demonstrated exceptional performance in overall fold and interface contact predictions, achieving an impressive success rate of 90% (compared to 31% in CASP14). This remarkable accomplishment is largely due to the incorporation of DeepMind's AF2-Multimer approach into custom-built prediction pipelines. To evaluate the added value of participating methods, we compared the community models to the baseline AF2-Multimer predictor. In over 1/3 of cases, the community models were superior to the baseline predictor. The main reasons for this improved performance were the use of custom-built multiple sequence alignments, optimized AF2-Multimer sampling, and the manual assembly of AF2-Multimer-built subcomplexes. The best three groups, in order, are Zheng, Venclovas, and Wallner. Zheng and Venclovas reached a 73.2% success rate over all (41) cases, while Wallner attained 69.4% success rate over 36 cases. Nonetheless, challenges remain in predicting structures with weak evolutionary signals, such as nanobody-antigen, antibody-antigen, and viral complexes. Expectedly, modeling large complexes also remains challenging due to their high memory compute demands. In addition to the assembly category, we assessed the accuracy of modeling interdomain interfaces in the tertiary structure prediction targets. Models on seven targets featuring 17 unique interfaces were analyzed. Best predictors achieved a 76.5% success rate, with the UM-TBM group being the leader. In the interdomain category, we observed that the predictors faced challenges, as in the case of the assembly category, when the evolutionary signal for a given domain pair was weak or the structure was large. Overall, CASP15 witnessed unprecedented improvement in interface modeling, reflecting the AI revolution seen in CASP14.

Abstract Malaria is a potentially fatal infective illness caused due to parasites that belong to the Plasmodium genus, which are transferred to humans with the help of the stings of affected female Anopheles mosquitoes, and it persists as a serious public wellness problem worldwide. Cordia myxa is a medicinal plant that possesses various medicinal characteristics like antimicrobial, anti-inflammation, antioxidant, and antidiabetic activities, which makes it an important natural resource for the therapy of different maladies in traditional medicine. In this investigation, a certain network pharmacology method has been utilized to identify the potent active components, possible targets as well as signaling pathways present in C. myxa in relation to malaria therapy. The active compounds were submitted to molecular docking approaches to validate their successful activity against the potential targets. The study concluded that three constituents named cosmosiin, stigmastanol, robinetin, and quercetin were highly active and could regulate the expression of Interleukin 6 (IL6) and Cysteine-aspartic acid protease 3 (CASP3), which may act as a potential therapeutic target for malaria treatment. These analyses are validated by molecular dynamics simulation which reflects on the overall structural stability of the intermolecular conformation and interactions. These results can also be witnessed in simulation-based trajectories binding free energies, which concluded the significant role of electrostatic and van der Waals energies in total intermolecular interactions. Finally, we utilized machine learning to predict the anti-malarial activity of C. myxa compounds, comparing them with approved drugs. Using the Chemprop model and MAIP predictions, we assessed ten compounds, revealing their potential as lead anti-malarial agents. This study establishes a groundwork for comprehending the function of the anti-malaria action of C. myxa.

Understanding protein-protein interactions (PPIs) is essential because knowledge regarding PPIs helps in determining the biochemical functions of organisms. Advances made in machine learning techniques, for example, DeepFE-PPI, GcForest-PPI, and DeepPPI, have been applied to enhance PPI prediction performance. However, most methods use either handcrafted or learned features. Improving protein representation quality can significantly impact PPI model performance. This study aims to propose a deep neural network-based model, in which both handcrafted and learned features are fused to improve PPI prediction. In our method, the handcrafted features are computed by sequence descriptors, including Amino Acid Composition (AAC), Local Descriptors, Pseudo-AAC, Amphiphilic Pseudo-AAC, and Quasi-Sequence-Order. The learned features are generated by Word2vec after being trained on a large database of protein sequences. Standard evaluation methods and benchmark datasets are used to assess the proposed model. The results show that our model achieves 95.8% and 99.3% accuracy on the Saccharomyces cerevisiae and Human datasets, respectively. Additionally, the generalizability of our model is evaluated through independent tests, and our findings indicate that the proposed feature combination method correctly classifies experimentally validated interactions in eight datasets, including cross-species and PPI networks. The source code and data for this work are included at https://github.com/npxquynhdhsp/ComFeatPPI.git.

Abstract Developing a potent antiviral agent to combat Coronavirus Disease-19 (COVID-19) is of critical importance as we may be at risk of the emergence of new virus strains or another pandemic recurrence. The interaction between the SARS-CoV-2 spike protein and Angiotensin Converting Enzyme 2 (ACE2) is the main protein-protein interaction (PPI) implicated in the virus entry into the host cells. Spike-ACE2 PPI represents a major target for drug intervention. We have repurposed a previously described protein-protein interaction detection method to be utilized as a drug screening assay. The assay was standardized using Chitosan nanoparticles (CNPs) as the drug and SARS-CoV-2 spike-ACE2 interaction as the PPI model. The assay was then used to screen four natural bioactive compounds: Curcumin (Cur), Gallic acid (GA), Quercetin (Q), and Silymarin (Sil), and their cytotoxicity was evaluated in vitro. Production of the spike protein and the evaluation of its activity in comparison to a standard commercial protein was part of our work as well. Here we describe a novel simple immunofluorescent screening assay to identify potential SARS-CoV-2 inhibitors that could assess the inhibitory effect of any ligand against any PPI. Graphical Abstract

Elevated levels of Inter-alpha-trypsin-inhibitor heavy chain 4 (ITIH4) have grabbed attention in rheumatoid arthritis (RA) pathogenesis, though its precise mechanisms remain unexplored. To elucidate these mechanisms, a comprehensive strategy employing network pharmacology and molecular docking was utilized. RA targets were sourced from the DisGeNET Database while interacting targets of ITIH4 were retrieved from the STRING and Literature databases. Venny 2.1 was used to identify overlapping genes, followed by Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) through Cytoscape 3.10.2 software, and molecular docking was performed in the ClusPro server. The study identified 18 interacting proteins of ITIH4 associated with RA, demonstrating their major involvement in the chemokine signaling pathway by enrichment analysis. Molecular docking of ITIH4 with the 18 proteins revealed that C-X-C chemokine-receptor type 4 (CXCR4), a major protein associated with chemokine signaling, has the highest binding affinity with ITIH4 with energy −1705.7 kcal/mol forming 3 Hydrogen bonds in the active site pocket of ITIH4 with His441, Arg288, Asp443 amino acids. The effect of ITIH4 on CXCR4 was analyzed via knockdown studies in rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS), demonstrating the significant downregulation of CXCR4 protein expression validated by Western blot in RA-FLS. In conclusion, it was speculated that CXCR4 might serve as a potential receptor for ITIH4 to activate the chemokine signaling, exacerbating RA pathogenesis.

Abstract Pathological cardiac hypertrophy is the primary cause of heart failure, yet its underlying mechanisms remain incompletely understood. Transmembrane protein 100 (TMEM100) plays a role in various disorders, such as nervous system disease, pain and tumorigenesis, but its function in pathological cardiac hypertrophy is still unknown. In this study, we observed that TMEM100 is upregulated in cardiac hypertrophy. Functional investigations have shown that adeno-associated virus 9 (AAV9) mediated-TMEM100 overexpression mice attenuates transverse aortic constriction (TAC)-induced cardiac hypertrophy, including cardiomyocyte enlargement, cardiac fibrosis, and impaired heart structure and function. We subsequently demonstrated that adenoviral TMEM100 (AdTMEM100) mitigates phenylephrine (PE)-induced cardiomyocyte hypertrophy and downregulates the expression of cardiac hypertrophic markers in vitro, whereas TMEM100 knockdown exacerbates cardiomyocyte hypertrophy. The RNA sequences of the AdTMEM100 group and control group revealed that TMEM100 was involved in oxidative stress and the MAPK signaling pathway after PE stimulation. Mechanistically, we revealed that the transmembrane domain of TMEM100 (amino acids 53–75 and 85–107) directly interacts with the C-terminal region of TAK1 (amino acids 1–300) and inhibits the phosphorylation of TAK1 and its downstream molecules JNK and p38. TAK1-binding-defective TMEM100 failed to inhibit the activation of the TAK1-JNK/p38 pathway. Finally, the application of a TAK1 inhibitor (iTAK1) revealed that TAK1 is necessary for TMEM100-mediated cardiac hypertrophy. In summary, TMEM100 protects against pathological cardiac hypertrophy through the TAK1-JNK/p38 pathway and may serve as a promising target for the treatment of cardiac hypertrophy.