Class Of Proteins Research Articles

Matrix-Assisted Laser Desorption Ionization Time-of-Flight Mass Spectrometry Combined with Chemometrics for Protein Profiling and Classification of Boiled and Extruded Quinoa from Conventional and Organic Crops

Quinoa is an Andean crop that stands out as a high-quality protein-rich and gluten-free food. However, its increasing popularity exposes quinoa products to the potential risk of adulteration with cheaper cereals. Consequently, there is a need for novel methodologies to accurately characterize the composition of quinoa, which is influenced not only by the variety type but also by the farming and processing conditions. In this study, we present a rapid and straightforward method based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to generate global fingerprints of quinoa proteins from white quinoa varieties, which were cultivated under conventional and organic farming and processed through boiling and extrusion. The mass spectra of the different protein extracts were processed using the MALDIquant software (version 1.19.3), detecting 49 proteins (with 31 tentatively identified). Intensity values from these proteins were then considered protein fingerprints for multivariate data analysis. Our results revealed reliable partial least squares-discriminant analysis (PLS-DA) classification models for distinguishing between farming and processing conditions, and the detected proteins that were critical for differentiation. They confirm the effectiveness of tracing the agricultural origins and technological treatments of quinoa grains through protein fingerprinting by MALDI-TOF-MS and chemometrics. This untargeted approach offers promising applications in food control and the food-processing industry.

CCSer2 gates dynein activity at the cell periphery.

Cytoplasmic dynein-1 (dynein) is a microtubule-associated, minus end-directed motor that traffics hundreds of different cargos. Dynein must discriminate between cargos and traffic them at the appropriate time from the correct cellular region. How dynein's trafficking activity is regulated in time or cellular space remains poorly understood. Here, we identify CCSer2 as the first known protein to gate dynein activity in the spatial dimension. CCSer2 promotes the migration of developing zebrafish primordium cells and of cultured human cells by facilitating the trafficking of cargos that are acted on by cortically localized dynein. CCSer2 inhibits the interaction between dynein and its regulator Ndel1 exclusively at the cell periphery, resulting in localized dynein activation. Our findings suggest that the spatial specificity of dynein is achieved by the localization of proteins that disinhibit Ndel1. We propose that CCSer2 defines a broader class of proteins that activate dynein in distinct microenvironments via Ndel1 inhibition.

Elongasome core proteins and class A PBP1a display zonal, processive movement at the midcell of Streptococcus pneumoniae

Ovoid-shaped bacteria, such as Streptococcus pneumoniae (pneumococcus), have two spatially separated peptidoglycan (PG) synthase nanomachines that locate zonally to the midcell of dividing cells. The septal PG synthase bPBP2x:FtsW closes the septum of dividing pneumococcal cells, whereas the elongasome located on the outer edge of the septal annulus synthesizes peripheral PG outward. We showed previously by sm-TIRFm that the septal PG synthase moves circumferentially at midcell, driven by PG synthesis and not by FtsZ treadmilling. The pneumococcal elongasome consists of the PG synthase bPBP2b:RodA, regulators MreC, MreD, and RodZ, but not MreB, and genetically associated proteins Class A aPBP1a and muramidase MpgA. Given its zonal location separate from FtsZ, it was of considerable interest to determine the dynamics of proteins in the pneumococcal elongasome. We found that bPBP2b, RodA, and MreC move circumferentially with the same velocities and durations at midcell, driven by PG synthesis. However, outside of the midcell zone, the majority of these elongasome proteins move diffusively over the entire surface of cells. Depletion of MreC resulted in loss of circumferential movement of bPBP2b, and bPBP2b and RodA require each other for localization and circumferential movement. Notably, a fraction of aPBP1a molecules also moved circumferentially at midcell with velocities similar to those of components of the core elongasome, but for shorter durations. Other aPBP1a molecules were static at midcell or diffusing over cell bodies. Last, MpgA displayed nonprocessive, subdiffusive motion that was largely confined to the midcell region and less frequently detected over the cell body.

Deciphering the mechanism of E3 ubiquitin ligases in plant responses to abiotic and biotic stresses and perspectives on PROTACs for crop resistance.

With global climate change, it is essential to find strategies to make crops more resistant to different stresses and guarantee food security worldwide. E3 ubiquitin ligases are critical regulatory elements that are gaining importance due to their role in selecting proteins for degradation in the ubiquitin-proteasome proteolysis pathway. The role of E3 Ub ligases has been demonstrated in numerous cellular processes in plants responding to biotic and abiotic stresses. E3 Ub ligases are considered a class of proteins that are difficult to control by conventional inhibitors, as they lack a standard active site with pocket, and their biological activity is mainly due to protein-protein interactions with transient conformational changes. Proteolysis-targeted chimeras (PROTACs) are a new class of heterobifunctional molecules that have emerged in recent years as relevant alternatives for incurable human diseases like cancer because they can target recalcitrant proteins for destruction. PROTACs interact with the ubiquitin-proteasome system, principally the E3 Ub ligase in the cell, and facilitate proteasome turnover of the proteins of interest. PROTAC strategies harness the essential functions of E3 Ub ligases for proteasomal degradation of proteins involved in dysfunction. This review examines critical advances in E3 Ub ligase research in plant responses to biotic and abiotic stresses. It highlights how PROTACs can be applied to target proteins involved in plant stress response to mitigate pathogenic agents and environmental adversities.

Clathrin mediates membrane fission and budding by constricting membrane pores

Membrane budding, which underlies fundamental processes like endocytosis, intracellular trafficking, and viral infection, is thought to involve membrane coat-forming proteins, including the most observed clathrin, to form Ω-shape profiles and helix-forming proteins like dynamin to constrict Ω-profiles’ pores and thus mediate fission. Challenging this fundamental concept, we report that polymerized clathrin is required for Ω-profiles’ pore closure and that clathrin around Ω-profiles’ base/pore region mediates pore constriction/closure in neuroendocrine chromaffin cells. Mathematical modeling suggests that clathrin polymerization at Ω-profiles’ base/pore region generates forces from its intrinsically curved shape to constrict/close the pore. This new fission function may exert broader impacts than clathrin’s well-known coat-forming function during clathrin (coat)-dependent endocytosis, because it underlies not only clathrin (coat)-dependent endocytosis, but also diverse endocytic modes, including ultrafast, fast, slow, bulk, and overshoot endocytosis previously considered clathrin (coat)-independent in chromaffin cells. It mediates kiss-and-run fusion (fusion pore closure) previously considered bona fide clathrin-independent, and limits the vesicular content release rate. Furthermore, analogous to results in chromaffin cells, we found that clathrin is essential for fast and slow endocytosis at hippocampal synapses where clathrin was previously considered dispensable, suggesting clathrin in mediating synaptic vesicle endocytosis and fission. These results suggest that clathrin and likely other intrinsically curved coat proteins are a new class of fission proteins underlying vesicle budding and fusion. The half-a-century concept and studies that attribute vesicle-coat contents’ function to Ω-profile formation and classify budding as coat-protein (e.g., clathrin)-dependent or -independent may need to be re-defined and re-examined by considering clathrin’s pivotal role in pore constriction/closure.

Establishment of a circRNA-regulated E3 ubiquitin ligase signature and nomogram to predict immunotherapeutic efficacy and prognosis in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is a common type of malignant tumor where the prognosis is dismal. Circular RNA (CircRNA) is a novel RNA that regulates downstream gene transcription and translation to influence the progression of HCC. However, the regulatory relationship that exists between E3 ligases, which is a class of post-translational modifying proteins, and circRNA remains unclear.MethodsBased on the E3 ubiquitin ligase in the competitive endogenous RNA (ceRNA) network, a circRNA-regulated E3 ubiquitin ligase signature (CRE3UL) was developed. A CRE3UL signature was created using the least absolute shrinkage and selection operator (Lasso) and Cox regression analysis and merged it with clinicopathologic characteristics to generate a nomogram for prognosis prediction. The pRRophetic algorithm was utilized and immunological checkpoints were analyzed to compare the responses of patients in the high-risk group (HRG) and low-risk group (LRG) to targeted therapy and immunotherapy. Finally, experimental research will further elucidate the relationship between E3 ubiquitin ligase signature and HCC.ResultsHRG patients were found to have a worse prognosis than LRG patients. Furthermore, significant variations in prognosis were observed among different subgroups based on various clinical characteristics. The CRE3UL signature was identified as being an independent prognostic indicator. The nomogram that combined clinical characteristics and the CRE3UL signature was found to accurately predict the prognosis of HCC patients and demonstrated greater clinical utility than the current TNM staging approach. According to anticancer medication sensitivity predictions, the tumors of HRG patients were more responsive to gefitinib and nilotinib. From immune-checkpoint markers analysis, immunotherapy was identified as being more probable to assist those in the HRG.ConclusionsWe found a significant correlation between the CRE3UL signature and the tumor microenvironment, enabling precise prognosis prediction for HCC patients. Additionally, a nomogram was developed that performs well in predicting the overall survival (OS) of HCC patients. This provides valuable guidance for clinicians in devising specific personalized treatment strategies.Graphical

A rule-based protein classification approach using normalized distance-based encoding method

A rule-based protein classification approach using normalized distance-based encoding method

ACDMBI: A deep learning model based on community division and multi-source biological information fusion predicts essential proteins

Accurately identifying essential proteins is vital for drug research and disease diagnosis. Traditional centrality methods and machine learning approaches often face challenges in accurately discerning essential proteins, primarily relying on information derived from protein-protein interaction (PPI) networks. Despite attempts by some researchers to integrate biological data and PPI networks for predicting essential proteins, designing effective integration methods remains a challenge. In response to these challenges, this paper presents the ACDMBI model, specifically designed to overcome the aforementioned issues. ACDMBI is comprised of two key modules: feature extraction and classification. In terms of capturing relevant information, we draw insights from three distinct data sources. Initially, structural features of proteins are extracted from the PPI network through community division. Subsequently, these features are further optimized using Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT). Moving forward, protein features are extracted from gene expression data utilizing Bidirectional Long Short-Term Memory networks (BiLSTM) and a multi-head self-attention mechanism. Finally, protein features are derived by mapping subcellular localization data to a one-dimensional vector and processing it through fully connected layers. In the classification phase, we integrate features extracted from three different data sources, crafting a multi-layer deep neural network (DNN) for protein classification prediction. Experimental results on brewing yeast data showcase the ACDMBI model’s superior performance, with AUC reaching 0.9533 and AUPR reaching 0.9153. Ablation experiments further reveal that the effective integration of features from diverse biological information significantly boosts the model’s performance.

Comparing Multifunctional Viral and Eukaryotic Proteins for Generating Scission Necks in Membranes.

Deterministic formation of membrane scission necks by protein machinery with multiplexed functions is critical in biology. A microbial example is M2 viroporin, a proton pump from the influenza A virus that is multiplexed with membrane remodeling activity to induce budding and scission in the host membrane during viral maturation. In comparison, the dynamin family constitutes a class of eukaryotic proteins implicated in mitochondrial fission, as well as various budding and endocytosis pathways. In the case of Dnm1, the mitochondrial fission protein in yeast, the membrane remodeling activity is multiplexed with mechanoenzyme activity to create fission necks. It is not clear why these functions are combined in these scission processes, which occur in drastically different compositions and solution conditions. In general, direct experimental access to changing neck sizes induced by individual proteins or peptide fragments is challenging due to the nanoscale dimensions and influence of thermal fluctuations. Here, we use a mechanical model to estimate the size of scission necks by leveraging small-angle X-ray scattering structural data of protein-lipid systems under different conditions. The influence of interfacial tension, lipid composition, and membrane budding morphology on the size of the induced scission necks is systematically investigated using our data and molecular dynamic simulations. We find that the M2 budding protein from the influenza A virus has robust pH-dependent membrane activity that induces nanoscopic necks within the range of spontaneous hemifission for a broad range of lipid compositions. In contrast, the sizes of scission necks generated by mitochondrial fission proteins strongly depend on lipid composition, which suggests a role for mechanical constriction.

FusOn-pLM: A Fusion Oncoprotein-Specific Language Model via Focused Probabilistic Masking.

Fusion oncoproteins, a class of chimeric proteins arising from chromosomal translocations, drive and sustain various cancers, particularly those impacting children. Unfortunately, due to their intrinsically disordered nature, large size, and lack of well-defined, druggable pockets, they have been historically challenging to target therapeutically: neither small molecule-based methods nor structure-based approaches for binder design are strong options for this class of molecules. Recently, protein language models (pLMs) have demonstrated success at representing protein sequences with information-rich embeddings, enabling downstream design applications from sequence alone. However, no current pLM has been trained on fusion oncoprotein sequences and thus may not produce optimal representations for these proteins. In this work, we introduce FusOn-pLM, a novel pLM that fine-tunes the state-of-the-art ESM-2 model on fusion oncoprotein sequences. We specifically introduce a novel masked language modeling (MLM) strategy, employing a binding-site probability predictor to focus masking on key amino acid residues, thereby generating more optimal fusion oncoprotein-aware embeddings. Our model improves performance on both fusion oncoprotein-specific benchmarks and disorder prediction tasks in comparison to baseline ESM-2 representations, as well as manually-constructed biophysical embeddings, motivating downstream usage of FusOn-pLM embeddings for therapeutic design tasks targeting these fusions. We have made our model publicly available to the community at https://huggingface.co/ChatterjeeLab/FusOn-pLM.

Human dermal fibroblast-derived secretory proteins for regulating nerve restoration: A bioinformatic approach.

Human dermal fibroblasts secrete diverse proteins that regulate wound repair and tissue regeneration. In this study, dermal fibroblast-conditioned medium (DFCM) proteins potentially regulating nerve restoration were bioinformatically selected among the 337 protein lists identified by quantitative liquid chromatography-tandem mass spectrometry. Using these proteins, protein-protein interaction network analysis was conducted. In addition, the roles of DFCM proteins were reviewed according to their protein classifications. Gene Ontology protein classification categorized these 57 DFCM proteins into various classes, including protein-binding activity modulator (N=11), cytoskeletal protein (N=8), extracellular matrix protein (N=6), metabolite interconversion enzyme (N=5), chaperone (N=4), scaffold/adapter protein (N=4), calcium-binding protein (N=3), cell adhesion molecule (N=2), intercellular signal molecule (N=2), protein modifying enzyme (N=2), transfer/carrier protein (N=2), membrane traffic protein (N=1), translational protein (N=1), and unclassified proteins (N=6). Further protein-protein interaction network analysis of 57 proteins revealed significant interactions among the proteins that varied according to the settings of confidence score. Our bioinformatic analysis demonstrated that DFCM contains many secretory proteins that form significant protein-protein interaction networks crucial for regulating nerve restoration. These findings underscore DFCM proteins' critical roles in various nerve restoration stages during the wound repair process.

New promising routes in peptic ulcers: Toll-like receptors and semaphorins.

Peptic ulcers (PU) are one of the commonest yet problematic diseases found to be existing in the majority of the population. Today, drugs from a wide range of therapeutic classes are available for the management of the disease. Still, the complications of the condition are difficult to tackle and the side effect profile is quite a concern. The literature indicates that Toll-like receptors (TLRs) and Semaphorins (SEMAs) have been under study for their various pharmacological actions over the past few decades. Both these signalling pathways are found to regulate immunological and inflammatory responses. Moreover, receptors and signalling molecules from the family of TLRs and SEMAs are found to have bacterial recognition and antibacterial properties which are essential in eradicating Helicobacter pylori (H. pylori), one of the major causative agents of PU. Our understanding of SEMAs, a class of proteins involved in cell signalling, is relatively less developed compared to TLRs, another class of proteins involved in the immune response. SEMAs and TLRs play different roles in biological processes, with SEMAs primarily involved in guiding cell migration and axon guidance during development, while TLRs are responsible for recognizing pathogens and initiating an immune response. Here, in this review, we will discuss in detail the signalling cascade of TLRs and SEMAs and thereby understand its association with PU for future therapeutic targeting. The review also aims at providing an overview of the study that has been into exploring the role of these signalling pathways in the management of PU.

Chemoproteomic profiling of substrate specificity in gut microbiota-associated bile salt hydrolases.

The gut microbiome possesses numerous biochemical enzymes that biosynthesize metabolites that impact human health. Bile acids comprise a diverse collection of metabolites that have important roles in metabolism and immunity. The gut microbiota-associated enzyme that is responsible for the gateway reaction in bile acid metabolism is bile salt hydrolase (BSH), which controls the host's overall bile acid pool. Despite the critical role of these enzymes, the ability to profile their activities and substrate preferences remains challenging due to the complexity of the gut microbiota, whose metaproteome includes an immense diversity of protein classes. Using a systems biochemistry approach employing activity-based probes, we have identified gut microbiota-associated BSHs that exhibit distinct substrate preferences, revealing that different microbes contribute to the diversity of the host bile acid pool. We envision that this chemoproteomic approach will reveal how secondary bile acid metabolism controlled by BSHs contributes to the etiology of various inflammatory diseases.

Ion channel inhibition by targeted recruitment of NEDD4-2 with divalent nanobodies.

Targeted recruitment of E3 ubiquitin ligases to degrade traditionally undruggable proteins is a disruptive paradigm for developing new therapeutics. Two salient limitations are that <2% of the ~600 E3 ligases in the human genome have been exploited to produce proteolysis targeting chimeras (PROTACs), and the efficacy of the approach has not been demonstrated for a vital class of complex multi-subunit membrane proteins- ion channels. NEDD4-1 and NEDD4-2 are physiological regulators of myriad ion channels, and belong to the 28-member HECT (homologous to E6AP C-terminus) family of E3 ligases with widespread roles in cell/developmental biology and diverse diseases including various cancers, immunological and neurological disorders, and chronic pain. The potential efficacy of HECT E3 ligases for targeted protein degradation is unexplored, constrained by a lack of appropriate binders, and uncertain due to their complex regulation by layered intra-molecular and posttranslational mechanisms. Here, we identified a nanobody that binds with high affinity and specificity to a unique site on the N-lobe of the NEDD4-2 HECT domain at a location physically separate from sites critical for catalysis- the E2 binding site, the catalytic cysteine, and the ubiquitin exosite- as revealed by a 3.1 Å cryo-electron microscopy reconstruction. Recruiting endogenous NEDD4-2 to diverse ion channel proteins (KCNQ1, ENaC, and CaV2.2) using a divalent (DiVa) nanobody format strongly reduced their functional expression with minimal off-target effects as assessed by global proteomics, compared to simple NEDD4-2 overexpression. The results establish utility of a HECT E3 ligase for targeted protein downregulation, validate a class of complex multi-subunit membrane proteins as susceptible to this modality, and introduce endogenous E3 ligase recruitment with DiVa nanobodies as a general method to generate novel genetically-encoded ion channel inhibitors.

Identification of phosphorylated small ORF-encoded peptides in Hep3B cells by LC/MS/MS

Small ORF-encoded peptides (SEPs) are a class of low molecular weight proteins and peptides comprising <100 amino acids with important functions in various life activities. Although the sequence length is short, SEPs might also have post-translational modification (PTM). Phosphorylation is one of the most essential PTMs of proteins. In this work, we enriched phosphopeptides with IMAC and TiO2 materials and analyzed the phosphorylated SEPs in Hep3B cells. A total of 24 phosphorylated SEPs were identified, and 11 SEPs were coded by ncRNA. For the sequence analysis, we found that the general characteristics of phosphorylated SEPs are roughly the same as canonical proteins. Besides, two phosphorylation SEPs have the Stathmin family signature 2 motif, which can regulate the microtubule cytoskeleton. Some SEPs have domains or signal peptides, indicating their specific functions and subcellular locations. Kinase network analysis found a small number of kinases that may be a clue to the specific functions of some SEPs. However, only one-fifth of the predicted phosphorylation sites were identified by LC/MS/MS, indicating that many SEP PTMs are hidden in the dark, waiting to be uncovered and verified. This study helps expand our understanding of SEP and provides information for further SEP function investigation. SignificanceSmall ORF-encoded peptides (SEPs) are important in various life activities. Although the sequence length is short (<100AA), SEPs might also have post-translational modification (PTM). Phosphorylation is one of the most essential PTMs of proteins. We enriched phosphopeptides and analyzed the phosphorylated SEPs in Hep3B cells. That is the first time to explore the PTM of SPEs systematically. Kinase network analysis found a small number of kinases that may be a clue to the specific functions of SEPs. More SEP PTMs are hidden in the dark and waiting to be uncovered and verified. This study helps expand our understanding of SEP and provides information for further SEP function investigation.

Structure classification of the proteins from Salmonella enterica pangenome revealed novel potential pathogenicity islands

Salmonella enterica is a pathogenic bacterium known for causing severe typhoid fever in humans, making it important to study due to its potential health risks and significant impact on public health. This study provides evolutionary classification of proteins from Salmonella enterica pangenome. We classified 17,238 domains from 13,147 proteins from 79,758 Salmonella enterica strains and studied in detail domains of 272 proteins from 14 characterized Salmonella pathogenicity islands (SPIs). Among SPIs-related proteins, 90 proteins function in the secretion machinery. 41% domains of SPI proteins have no previous sequence annotation. By comparing clinical and environmental isolates, we identified 3682 proteins that are overrepresented in clinical group that we consider as potentially pathogenic. Among domains of potentially pathogenic proteins only 50% domains were annotated by sequence methods previously. Moreover, 36% (1330 out of 3682) of potentially pathogenic proteins cannot be classified into Evolutionary Classification of Protein Domains database (ECOD). Among classified domains of potentially pathogenic proteins the most populated homology groups include helix-turn-helix (HTH), Immunoglobulin-related, and P-loop domains-related. Functional analysis revealed overrepresentation of these protein in biological processes related to viral entry into host cell, antibiotic biosynthesis, DNA metabolism and conformation change, and underrepresentation in translational processes. Analysis of the potentially pathogenic proteins indicates that they form 119 clusters or novel potential pathogenicity islands (NPPIs) within the Salmonella genome, suggesting their potential contribution to the bacterium’s virulence. One of the NPPIs revealed significant overrepresentation of potentially pathogenic proteins. Overall, our analysis revealed that identified potentially pathogenic proteins are poorly studied.

Genome-Wide Identification and Expression Analysis of the High-Mobility Group B (HMGB) Gene Family in Plant Response to Abiotic Stress in Tomato.

High-mobility group B (HMGB) proteins are a class of non-histone proteins associated with eukaryotic chromatin and are known to regulate a variety of biological processes in plants. However, the functions of HMGB genes in tomato (Solanum lycopersicum) remain largely unexplored. Here, we identified 11 members of the HMGB family in tomato using BLAST. We employed genome-wide identification, gene structure analysis, domain conservation analysis, cis-acting element analysis, collinearity analysis, and qRT-PCR-based expression analysis to study these 11 genes. These genes were categorized into four groups based on their unique protein domain structures. Despite their structural diversity, all members contain the HMG-box domain, a characteristic feature of the HMG superfamily. Syntenic analysis suggested that tomato SlHMGBs have close evolutionary relationships with their homologs in other dicots. The promoter regions of SlHMGBs are enriched with numerous cis-elements related to plant growth and development, phytohormone responsiveness, and stress responsiveness. Furthermore, SlHMGB members exhibited distinct tissue-specific expression profiles, suggesting their potential roles in regulating various aspects of plant growth and development. Most SlHMGB genes respond to a variety of abiotic stresses, including salt, drought, heat, and cold. For instance, SlHMGB2 and SlHMGB4 showed positive responses to salt, drought, and cold stresses. SlHMGB1, SlHMGB3, and SlHMGB8 were involved in responses to two types of stress: SlHMGB1 responded to drought and heat, while SlHMGB3 and SlHMGB8 responded to salt and heat. SlHMGB6 and SlHMGB11 were solely regulated by drought and heat stress, respectively. Under various treatment conditions, the number of up-regulated genes significantly outnumbered the down-regulated genes, implying that the SlHMGB family may play a crucial role in mitigating abiotic stress in tomato. These findings lay a foundation for further dissecting the precise roles of SlHMGB genes.

Interpretable molecular encodings and representations for machine learning tasks

Molecular encodings and their usage in machine learning models have demonstrated significant breakthroughs in biomedical applications, particularly in the classification of peptides and proteins. To this end, we propose a new encoding method: Interpretable Carbon-based Array of Neighborhoods (iCAN). Designed to address machine learning models' need for more structured and less flexible input, it captures the neighborhoods of carbon atoms in a counting array and improves the utility of the resulting encodings for machine learning models. The iCAN method provides interpretable molecular encodings and representations, enabling the comparison of molecular neighborhoods, identification of repeating patterns, and visualization of relevance heat maps for a given data set. When reproducing a large biomedical peptide classification study, it outperforms its predecessor encoding. When extended to proteins, it outperforms a lead structure-based encoding on 71% of the data sets. Our method offers interpretable encodings that can be applied to all organic molecules, including exotic amino acids, cyclic peptides, and larger proteins, making it highly versatile across various domains and data sets. This work establishes a promising new direction for machine learning in peptide and protein classification in biomedicine and healthcare, potentially accelerating advances in drug discovery and disease diagnosis.

Epigenetics in etiopathology of hyperprolactinemia

Aim: Epigenetic alterations have been reported in patients with pituitary tumors and those on antipsychotic drugs, which are also responsible for hyperprolactinemia. This suggests a possible role of epigenetics in the etiopathology of hyperprolactinemia. Methods: The study recruited 83 hyperprolactinemia cases with prolactin &gt; 100 ng/mL and 65 controls. Global DNA methylation status was studied by MethylFlash Methylated DNA Quantification Kit and genome-wide methylation analysis (GWMA) by Infinium Methylation EPIC BeadChip 850K array. Results: Hyperprolactinemia cases showed significant global DNA hypermethylation compared to controls. Around 66.67% of hypomethylated and 12.9% of hypermethylated cases were on antipsychotics. Gene enrichment analysis of 5-cytosine-phosphate-guanine-3 (CpG) site-associated genes demonstrated significantly enriched major histocompatibility complex (MHC)-related protein classes and cellular components. Conclusions: The study suggested the role of epigenetics in the etiopathology of hyperprolactinemia.

Angiomotin family proteins in the Hippo signaling pathway.

The Motin family proteins (Motins) are a class of scaffolding proteins consisting of Angiomotin (AMOT), AMOT-like protein 1 (AMOTL1), and AMOT-like protein 2 (AMOTL2). Motins play a pivotal role in angiogenesis, tumorigenesis, and neurogenesis by modulating multiple cellular signaling pathways. Recent findings indicate that Motins are components of the Hippo pathway, a signaling cascade involved in development and cancer. This review discusses how Motins are integrated into the Hippo signaling network, as either upstream regulators or downstream effectors, to modulate cell proliferation and migration. The repression of YAP/TAZ by Motins contributes to growth inhibition, whereas subcellular localization of Motins and their interactions with actin fibers are critical in regulating cell migration. The net effect of Motins on cell proliferation and migration may contribute to their diverse biological functions.