UniProt: the universal protein knowledgebase in 2021

Unraveling the potential of uninvestigated thermoalkaliphilic lipases by molecular docking and molecular dynamic simulation: an in silico characterization study

Thermoalkaliphilic lipase enzymes are mostly favored for use in the detergent industry. While there has been considerable research on Geobacillus lipases, a significant portion of these enzymes remains unexplored or undocumented in the scientific literature. This work performed in silico phylogeny, sequence alignment, structural and enzyme-substrate interaction analyses of the five thermoalkaliphilic lipases belonging to different Geobacillus species (Geobacillus stearothermophilus lipase = GsLip, Geobacillus sp. B4113_201601 lipase = Gb4Lip, Geobacillus kaustophilus HTA426 lipase = GkLip, Geobacillus sp. SP22 lipase = GspLip, Geobacillus sp. NTU 03 lipase = GntLip). For this purpose, unreviewed enzyme sequences of five Geobacillus thermoalkaliphilic lipases were analyzed at sequence and phylogeny levels. 3D homology enzyme models were built, validated, and investigated by different bioinformatics tools. The ligand interactions screening using seven para-nitrophenyl (pNP) esters and enzyme-ligand interactions were analyzed on Gb4Lip:pNP-C12 and BTL2:pNP-C12 by MD simulation. Biophysicochemical characteristic analysis showed that Gb4Lip had a theoretical T m value of above 65 ºC, and a higher aliphatic index indicating greater thermal stability. Sequence alignment showed a hydrophilic threonine in the α6 helix of Gb4Lip, indicating high enzymatic activity. A normalized temperature factor B (B'-factor) analysis showed that the lid domains of five lipases significantly possessed lower B'-factor values, compared to G. thermocatenulatus lipase 2 (BTL2), indicating that they had higher rigidity. Molecular docking results indicated that the five lipases had the highest binding affinity toward pNP-C12. The RMSF investigation revealed that the thermostability of Gb4Lip is influenced by specific molecular elements: D202-S203 within the αB region of the lid domain, and E274-Q275 within the b3 strand, as well as W278 in the b3-b4 loop, and H282 in the b4 strand of the Ca2+-binding region. MD simulation analysis showed that catalytic residue S114 and at least one oxyanion hole residue (F17 and/or Q114) in Gb4Lip frequently formed hydrogen bonds with the pNP-C12 ligand at 343 K and 348 K throughout the simulation process, indicating that Gb4Lip might catalyze relatively long-chain ligand pNP-C12 with high performance. In conclusion, Gb4Lip might be a more suitable candidate as the detergent additive. In addition, this investigation can offer valuable perspectives on Family I.5 lipases such as Gb4Lip for future exploration in the field of protein engineering.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04023-5.

Overlap in oncogenic and pro-inflammatory pathways associated with areca nut and nicotine exposure

Background

Betel nut/areca nut/Areca catechu is one of the most commonly used psychoactive substance, and is also a major preventable cause of cancer. Unlike other psychoactive substances, such as nicotine, the mechanisms underlying addiction to areca nuts and related oncogenesis remain elusive. Recent reports suggest a possible overlap in the mechanisms of action of nicotine and areca nuts in the human body. Thus, this study aimed to investigate the interactome of human proteins associated with areca nut exposure and the intricate similarities and differences in the effects of the two psychoactive substances on humans.

Methods

A list of proteins associated with areca nut use was obtained from the available literature using terms from Medical Subject Headings (MeSH). Protein-protein interaction (PPI) networks and functional enrichment were analyzed. The results obtained for both psychoactive substances were compared.

Results

Given the limited number of common proteins (36/226, 16%) in the two sets, a substantial overlap (612/1176 nodes, 52%) was observed in the PPI networks, as well as in Gene Ontology. Areca nuts mainly affect signaling pathways through three hub proteins (alpha serine/threonine-protein kinase, tumor protein 53, and interleukin-6), which are common to both psychoactive substances, as well as two unique hub proteins (epidermal growth factor receptor and master regulator of cell cycle entry and proliferative metabolism). Areca nut-related proteins are associated with unique pathways, such as extracellular matrix organization, lipid storage, and metabolism, which are not found in nicotine-associated proteins.

Conclusions

Areca nuts affect regulatory mechanisms, leading to systemic toxicity and oncogenesis. Areca nuts also affect unique pathways that can be studied as potential markers of exposure, as well as targets for anticancer therapeutic agents.

Repurposing phytochemicals of Citrullus colocynthis against maltase-glucoamylase using molecular docking, MMGBSA, MD simulation and linear regression to identify potential anti-diabetic compounds

Diabetes is a common lifestyle disorder found in populations of different age groups. Maltase-glucoamylase catalyses the release of the glucose molecule in the final enzymatic reaction of starch digestion; therefore, inhibition of maltase-glucoamylase is one of the approaches in the development of therapeutics for diabetes. Citrullus colocynthis is commonly recommended in Ayurveda for the treatment of diabetes. The current study applied a structure-based drug design approach to repurpose the phytochemicals of Citrullus colocynthis to identify potential inhibitors for maltase-glucoamylase. 70 phytochemicals of Citrullus colocynthis were screened against maltase-glucoamylase and top 5 molecules 8-p-hydroxybenzylisovitexin, isoorientin, cucurbitacin B, cucurbitacin E, and cucurbitacin I with significant binding energy of -10 kcal/mol, -9.9 kcal/mol, -9.6 kcal/mol, -9.2 kcal/mol, and -7.7 kcal/mol were identified. Furthermore, MMGBSA, pharmacokinetics properties and toxicity prediction were performed on the five identified molecules and top 3 molecules were selected for molecular dynamics (MD) simulation. It was observed from the structural flexibility and dynamic behaviour of the systems that conformational changes were noticed in the complexes as compared to its native state, which suggests that the 3 molecules, namely 8-p-hydroxybenzylisovitexin, isoorientin, and cucurbitacin I of Citrullus colocynthis may act as inhibitors for maltase-glucoamylase.Communicated by Ramaswamy H. Sarma.

Characterization of the transcriptional effects of the plastic additive dibutyl phthalate alone and in combination with microplastic on the green-lipped mussel Perna canaliculus

The presence and persistence of microplastics (MPs) in diverse aquatic environments are of global concern. Microplastics can impact marine organisms via direct physical interaction and the release of potentially harmful chemical additives incorporated into the plastic. These chemicals are physically bound to the plastic matrix and can leach out. The hazards associated with chemical additives to exposed organisms is not well characterized. We investigated the hazards of plastic additives leaching from plastic. We used the common plasticizer dibutyl phthalate (DBP) as a chemical additive proxy and the New Zealand green-lipped mussel (Perna canaliculus) as a model. We used early-adult P. canaliculus exposed to combinations of virgin and DBP-spiked polyvinyl chloride (PVC), MPs, and DBP alone for 7 days. Whole transcriptome sequencing (RNA-seq) was conducted to assess whether leaching of DBP from MPs poses a hazard. The differences between groups were evaluated using pairwise permutational multivariate analysis of variance (PERMANOVA), and all treatments were significantly different from controls. In addition, a significant difference was seen between DBP and PVC MP treatment. Transcriptome analysis revealed that mussels exposed to DBP alone had the most differentially expressed genes (914), followed by PVC MP + DBP (448), and PVC MP (250). Gene ontology functional analysis revealed that the most enriched pathway types were in cellular metabolism, immune response, and endocrine disruption. Microplastic treatments enriched numerous pathways related to cellular metabolism and immune response. The combined exposure of PVC MP + DBP appears to cause combined effects, suggesting that DBP is bioavailable to the exposed mussels in the PVC MP + DBP treatment. Our results support the hypothesis that chemical additives are potentially an important driver of MP toxicity. Environ Toxicol Chem 2024;43:1604-1614. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

MicroProteinDB: A database to provide knowledge on sequences, structures and function of ncRNA-derived microproteins

Omics-based technologies have revolutionized our comprehension of microproteins encoded by ncRNAs, revealing their abundant presence and pivotal roles within complex functional landscapes. Here, we developed MicroProteinDB (http://bio-bigdata.hrbmu.edu.cn/MicroProteinDB), which offers and visualizes the extensive knowledge to aid retrieval and analysis of computationally predicted and experimentally validated microproteins originating from various ncRNA types. Employing prediction algorithms grounded in diverse deep learning approaches, MicroProteinDB comprehensively documents the fundamental physicochemical properties, secondary and tertiary structures, interactions with functional proteins, family domains, and inter-species conservation of microproteins. With five major analytical modules, it will serve as a valuable knowledge for investigating ncRNA-derived microproteins.

A hidden proteome encoded by circRNAs in human placentas: Implications for uncovering preeclampsia pathogenesis

BACKGROUND

CircRNA-encoded proteins (CEPs) are emerging as new players in health and disease, and function as baits for the common partners of their cognate linear-spliced RNA encoded proteins (LEPs). However, their prevalence across human tissues and biological roles remain largely unexplored. The placenta is an ideal model for identifying CEPs due to its considerable protein diversity that is required to sustain fetal development during pregnancy. The aim of this study was to evaluate circRNA translation in the human placenta, and the potential roles of the CEPs in placental development and dysfunction.

METHODS

Multiomics approaches, including RNA sequencing, ribosome profiling, and LC-MS/MS analysis, were utilised to identify novel translational events of circRNAs in human placentas. Bioinformatics methods and the protein bait hypothesis were employed to evaluate the roles of these newly discovered CEPs in placentation and associated disorders. The pathogenic role of a recently identified CEP circPRKCB119aa in preeclampsia was investigated through qRT-PCR, Western blotting, immunofluorescence imaging and phenotypic analyses.

RESULTS

We found that 528 placental circRNAs bound to ribosomes with active translational elongation, and 139 were translated to proteins. The CEPs showed considerable structural homology with their cognate LEPs, but are more stable, hydrophobic and have a lower molecular-weight than the latter, all of which are conducive to their function as baits. On this basis, CEPs are deduced to be closely involved in placental function. Furthermore, we focused on a novel CEP circPRKCB119aa, and illuminated its pathogenic role in preeclampsia; it enhanced trophoblast autophagy by acting as a bait to inhibit phosphorylation of the cognate linear isoform PKCβ.

CONCLUSIONS

We discovered a hidden circRNA-encoded proteome in the human placenta, which offers new insights into the mechanisms underlying placental development, as well as placental disorders such as preeclampsia. Key points A hidden circRNA-encoded proteome in the human placenta was extensively identified and systematically characterised. The circRNA-encoded proteins (CEPs) are potentially related to placental development and associated disorders. A novel conserved CEP circPRKCB119aa enhanced trophoblast autophagy by inhibiting phosphorylation of its cognate linear-spliced isoform protein kinase C (PKC) β in preeclampsia.

Cannabinoid CB2 receptor orthologues; in vitro function and perspectives for preclinical to clinical translation

Cannabinoid CB2 receptor agonists are in development as therapeutic agents, including for immune modulation and pain relief. Despite promising results in rodent preclinical studies, efficacy in human clinical trials has been marginal to date. Fundamental differences in ligand engagement and signalling responses between the human CB2 receptor and preclinical model species orthologues may contribute to mismatches in functional outcomes. This is a tangible possibility for the CB2 receptor in that there is a relatively large degree of primary amino acid sequence divergence between human and rodent. Here, we summarise CB2 receptor gene and protein structure, assess comparative molecular pharmacology between CB2 receptor orthologues, and review the current status of preclinical to clinical translation for drugs targeted at the CB2 receptor, focusing on comparisons between human, mouse and rat receptors. We hope that raising wider awareness of, and proposing strategies to address, this additional challenge in drug development will assist in ongoing efforts toward successful therapeutic translation of drugs targeted at the CB2 receptor. LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein-Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc.

Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene

Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson's disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein's biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments.Communicated by Ramaswamy H. Sarma.

Comparative analysis of the antimicrobial resistance and virulence traits in ESBL-producing-Klebsiella pneumoniae ST307 strains colonizing the gastrointestinal tract and causing a fatal bloodstream infection in a leukemia patient

Klebsiella pneumoniae is an opportunistic pathogen that can colonize the gastrointestinal tract (GIT) of humans. The mechanisms underlying the successful translocation of this pathogen to cause extra-intestinal infections remain unknown, although virulence and antimicrobial resistance traits likely play significant roles in the establishment of infections. We investigated K. pneumoniae strains isolated from GIT colonization (strains Kp_FZcol-1, Kp_FZcol-2 and Kp_FZcro-1) and from a fatal bloodstream infection (strain Kp_HM-1) in a leukemia patient. All strains belonged to ST307, carried a transferable IncF plasmid containing the blaCTX-M-15 gene (pKPN3-307 TypeA-like plasmid) and showed a multidrug-resistance phenotype. Phylogenetic analysis demonstrated that Kp_HM-1 was more closely related to Kp_FZcro-1 than to the other colonizing strains. The Kp_FZcol-2 genome showed 81 % coverage with the Kp_HM-1 246,730 bp plasmid (pKp_HM-1), lacking most of its putative virulence genes. Searching public genomes with similar coverage, we observed the occurrence of this deletion in K. pneumoniae ST307 strains recovered from human colonization and infection in different countries. Our findings suggest that strains lacking the putative virulence genes found in the pKPN3-307 TypeA plasmid are still able to colonize and infect humans, highlighting the need to further investigate the role of these genes for the adaptation of K. pneumoniae ST307 in distinct human body sites.

Deciphering nutritional stress responses via knowledge-enriched transcriptomics for microbial engineering

Understanding diverse bacterial nutritional requirements and responses is foundational in microbial research and biotechnology. In this study, we employed knowledge-enriched transcriptomic analytics to decipher complex stress responses of Vibrio natriegens to supplied nutrients, aiming to enhance microbial engineering efforts. We computed 64 independently modulated gene sets that comprise a quantitative basis for transcriptome dynamics across a comprehensive transcriptomics dataset containing a broad array of nutrient conditions. Our approach led to the i) identification of novel transporter systems for diverse substrates, ii) a detailed understanding of how trace elements affect metabolism and growth, and iii) extensive characterization of nutrient-induced stress responses, including osmotic stress, low glycolytic flux, proteostasis, and altered protein expression. By clarifying the relationship between the acetate-associated regulon and glycolytic flux status of various nutrients, we have showcased its vital role in directing optimal carbon source selection. Our findings offer deep insights into the transcriptional landscape of bacterial nutrition and underscore its significance in tailoring strain engineering strategies, thereby facilitating the development of more efficient and robust microbial systems for biotechnological applications.

Proteomes of plasmodium knowlesi early and late ring-stage parasites and infected host erythrocytes

The emerging malaria parasite Plasmodium knowlesi threatens the goal of worldwide malaria elimination due to its zoonotic spread in Southeast Asia. After brief ex-vivo culture we used 2D LC/MS/MS to examine the early and late ring stages of infected Macaca mulatta red blood cells harboring P. knowlesi. The M. mulatta clathrin heavy chain and T-cell and macrophage inhibitor ERMAP were overexpressed in the early ring stage; glutaredoxin 3 was overexpressed in the late ring stage; GO term differential enrichments included response to oxidative stress and the cortical cytoskeleton in the early ring stage. P. knowlesi clathrin heavy chain and 60S acidic ribosomal protein P2 were overexpressed in the late ring stage; GO term differential enrichments included vacuoles in the early ring stage, ribosomes and translation in the late ring stage, and Golgi- and COPI-coated vesicles, proteasomes, nucleosomes, vacuoles, ion-, peptide-, protein-, nucleocytoplasmic- and RNA-transport, antioxidant activity and glycolysis in both stages. SIGNIFICANCE: Due to its zoonotic spread, cases of the emerging human pathogen Plasmodium knowlesi in southeast Asia, and particularly in Malaysia, threaten regional and worldwide goals for malaria elimination. Infection by this parasite can be fatal to humans, and can be associated with significant morbidity. Due to zoonotic transmission from large macaque reservoirs that are untreatable by drugs, and outdoor biting mosquito vectors that negate use of preventive measures such as bed nets, its containment remains a challenge. Its biology remains incompletely understood. Thus we examine the expressed proteome of the early and late ex-vivo cultured ring stages, the first intraerythrocyte developmental stages after infection of host rhesus macaque erythrocytes. We used GO term enrichment strategies and differential protein expression to compare early and late ring stages. The early ring stage is characterized by the enrichment of P. knowlesi vacuoles, and overexpression of the M. mulatta clathrin heavy chain, important for clathrin-coated pits and vesicles, and clathrin-mediated endocytosis. The M. mulatta protein ERMAP was also overexpressed in the early ring stage, suggesting a potential role in early ring stage inhibition of T-cells and macrophages responding to P. knowlesi infection of reticulocytes. This could allow expansion of the host P. knowlesi cellular niche, allowing parasite adaptation to invasion of a wider age range of RBCs than the preferred young RBCs or reticulocytes, resulting in proliferation and increased pathogenesis in infected humans. Other GO terms differentially enriched in the early ring stage include the M. mulatta cortical cytoskeleton and response to oxidative stress. The late ring stage is characterized by overexpression of the P. knowlesi clathrin heavy chain. Combined with late ring stage GO term enrichment of Golgi-associated and coated vesicles, and enrichment of COPI-coated vesicles in both stages, this suggests the importance to P. knowlesi biology of clathrin-mediated endocytosis. P. knowlesi ribosomes and translation were also differentially enriched in the late ring stage. With expression of a variety of heat shock proteins, these results suggest production of folded parasite proteins is increasing by the late ring stage. M. mulatta endocytosis was differentially enriched in the late ring stage, as were clathrin-coated vesicles and endocytic vesicles. This suggests that M. mulatta clathrin-based endocytosis, perhaps in infected reticulocytes rather than mature RBC, may be an important process in the late ring stage. Additional ring stage biology from enriched GO terms includes M. mulatta proteasomes, protein folding and the chaperonin-containing T complex, actin and cortical actin cytoskeletons. P knowlesi biology also includes proteasomes, as well as nucleosomes, antioxidant activity, a variety of transport processes, glycolysis, vacuoles and protein folding. Mature RBCs have lost internal organelles, suggesting infection here may involve immature reticulocytes still retaining organelles. P. knowlesi parasite proteasomes and translational machinery may be ring stage drug targets for known selective inhibitors of these processes in other Plasmodium species. To our knowledge this is the first examination of more than one timepoint within the ring stage. Our results expand knowledge of both host and parasite proteins, pathways and organelles underlying P. knowlesi ring stage biology.

Discrete Correlate Summation Clustering of a Dopamine-Angiotensin Network

We present a model of directed investigation of KEGG pathway analysis, beginning with discrete correlate summation (DCS) clustering of Swiss-Prot sets. Dopamine and angiotensin related proteins define the boundary for pathway analyses upon a network of proteins also associated with a compositely defined matrix of Swiss-Prot keywords to provide a framework for their biological indices (Figure 1).

Distinct microbial nitrogen cycling processes in the deepest part of the ocean

The Mariana Trench (MT) is the deepest part of the ocean on Earth. Previous studies have described the microbial community structures and functional potential in the seawater and surface sediment of MT. Still, the metabolic features and adaptation strategies of the microorganisms involved in nitrogen cycling processes are poorly understood. In this study, comparative metagenomic approaches were used to study microbial nitrogen cycling in three MT habitats, including hadal seawater [9,600-10,500 m below sea level (mbsl)], surface sediments [0-46 cm below seafloor (cmbsf) at a water depth between 7,143 and 8,638 mbsl], and deep sediments (200-306 cmbsf at a water depth of 8,300 mbsl). We identified five new nitrite-oxidizing bacteria (NOB) lineages that had adapted to the oligotrophic MT slope sediment, via their CO2 fixation capability through the reductive tricarboxylic acid (rTCA) or Calvin-Benson-Bassham (CBB) cycle; an anammox bacterium might perform aerobic respiration and utilize sedimentary carbohydrates for energy generation because it contains genes encoding type A cytochrome c oxidase and complete glycolysis pathway. In seawater, abundant alkane-oxidizing Ketobacter species can fix inert N2 released from other denitrifying and/or anammox bacteria. This study further expands our understanding of microbial life in the largely unexplored deepest part of the ocean.

IMPORTANCE

The metabolic features and adaptation strategies of the nitrogen cycling microorganisms in the deepest part of the ocean are largely unknown. This study revealed that anammox bacteria might perform aerobic respiration in response to nutrient limitation or O2 fluctuations in the Mariana Trench sediments. Meanwhile, an abundant alkane-oxidizing Ketobacter species could fix N2 in hadal seawater. This study provides new insights into the roles of hadal microorganisms in global nitrogen biogeochemical cycles. It substantially expands our understanding of the microbial life in the largely unexplored deepest part of the ocean.

Comparative proteomic profiling of the ovine and human PBMC inflammatory response

Understanding the cellular and molecular mechanisms of inflammation requires robust animal models. Sheep are commonly used in immune-related studies, yet the validity of sheep as animal models for immune and inflammatory diseases remains to be established. This cross-species comparative study analyzed the in vitro inflammatory response of ovine (oPBMCs) and human PBMCs (hPBMCs) using mass spectrometry, profiling the proteome of the secretome and whole cell lysate. Of the entire cell lysate proteome (oPBMCs: 4217, hPBMCs: 4574 proteins) 47.8% and in the secretome proteome (oPBMCs: 1913, hPBMCs: 1375 proteins) 32.8% were orthologous between species, among them 32 orthologous CD antigens, indicating the presence of six immune cell subsets. Following inflammatory stimulation, 71 proteins in oPBMCs and 176 in hPBMCs showed differential abundance, with only 7 overlapping. Network and Gene Ontology analyses identified 16 shared inflammatory-related terms and 17 canonical pathways with similar activation/inhibition patterns in both species, demonstrating significant conservation in specific immune and inflammatory responses. However, ovine PMBCs also contained a unique WC1+γδ T-cell subset, not detected in hPBMCs. Furthermore, differences in the activation/inhibition trends of seven canonical pathways and the sets of DAPs between sheep and humans, emphasize the need to consider interspecies differences in translational studies and inflammation research.

Integration of background knowledge for automatic detection of inconsistencies in gene ontology annotation

MOTIVATION

Biological background knowledge plays an important role in the manual quality assurance (QA) of biological database records. One such QA task is the detection of inconsistencies in literature-based Gene Ontology Annotation (GOA). This manual verification ensures the accuracy of the GO annotations based on a comprehensive review of the literature used as evidence, Gene Ontology (GO) terms, and annotated genes in GOA records. While automatic approaches for the detection of semantic inconsistencies in GOA have been developed, they operate within predetermined contexts, lacking the ability to leverage broader evidence, especially relevant domain-specific background knowledge. This paper investigates various types of background knowledge that could improve the detection of prevalent inconsistencies in GOA. In addition, the paper proposes several approaches to integrate background knowledge into the automatic GOA inconsistency detection process.

RESULTS

We have extended a previously developed GOA inconsistency dataset with several kinds of GOA-related background knowledge, including GeneRIF statements, biological concepts mentioned within evidence texts, GO hierarchy and existing GO annotations of the specific gene. We have proposed several effective approaches to integrate background knowledge as part of the automatic GOA inconsistency detection process. The proposed approaches can improve automatic detection of self-consistency and several of the most prevalent types of inconsistencies.

This is the first study to explore the advantages of utilizing background knowledge and to propose a practical approach to incorporate knowledge in automatic GOA inconsistency detection. We establish a new benchmark for performance on this task. Our methods may be applicable to various tasks that involve incorporating biological background knowledge.

AVAILABILITY AND IMPLEMENTATION

https://github.com/jiyuc/de-inconsistency.

Angelicin: A leading culprit involved in fructus Psoraleae liver injury via inhibition of VKORC1

ETHNOPHARMACOLOGICAL RELEVANCE

The adverse effects of Fructus Psoraleae (FP), especially liver injury, have attracted wide attention in recent years.

AIM OF THE STUDY

To establish a system to explore potential hepatotoxic targets and the chief culprit of liver injury based on clinical experience, network pharmacological method, molecular docking, and in vitro and in vivo experiments.

MATERIALS AND METHODS

Clinical applications and adverse reactions to FP were obtained from public literatures. Components absorbed in the blood were selected as candidates to search for potential active targets (PATs) of FP. Subsequently, potential pharmacological core targets (PPCTs) were screened through the "drug targets-disease targets" network. Non-drug active targets (NPATs) were obtained by subtracting the PPCTs from the PATs. The potential hepatotoxic targets (PHTs) of FP were the intersection targets obtained from Venn analysis using NPATs, hepatotoxic targets, and adverse drug reaction (ADR) targets provided by the databases. Then, potential hepatotoxic components and targets were obtained using the "NPATS-component" network relationship. Molecular docking and in vitro and in vivo hepatotoxicity experiments were performed to verify the targets and related components.

RESULTS

Overall, 234 NPATs were acquired from our analysis, and 6 targets were identified as PHTs. Results from molecular docking and in vitro and in vivo experiments showed that angelicin is the leading cause of liver injury in FP, and VKORC1 plays an important role.

CONCLUSION

The results indicate that six targets, especially VKORC1, are associated with the PHTs of FP, and angelicin is the leading culprit involved in FP liver injury via inhibition of VKORC1.

Assembly and Genome Annotation of Different Strains of Apple Fruit Moth Virus (Cydia pomonella granulovirus)

Cydia pomonella granulovirus is a natural pathogen for Cydia pomonella that is used as a biocontrol agent of insect populations. The study of granulovirus virulence is of particular interest since the development of resistance in natural populations of C. pomonella has been observed during the long-term use of the Mexican isolate CpGV. In our study, we present the genomes of 18 CpGV strains endemic to southern Russia and from Kazakhstan, as well as a strain included in the commercial preparation "Madex Twin", which were sequenced and analyzed. We performed comparative genomic analysis using several tools. From comparisons at the level of genes and protein products that are involved in the infection process of virosis, synonymous and missense substitution variants have been identified. The average nucleotide identity has demonstrated a high similarity with other granulovirus genomes of different geographic origins. Whole-genome alignment of the 18 genomes relative to the reference revealed regions of low similarity. Analysis of gene repertoire variation has shown that BZR GV 4, BZR GV 6, and BZR GV L-7 strains have been the closest in gene content to the commercial "Madex Twin" strain. We have confirmed two deletions using read depth coverage data in regions lacking genes shown by homology analysis for granuloviruses BZR GV L-4 and BZR GV L-6; however, they are not related to the known genes causing viral pathogenicity. Thus, we have isolated novel CpGV strains and analyzed their potential as strains producing highly effective bioinsecticides against C. pomonella.

Next-generation Drosophila protein interactome map and its functional implications

We describe a next-generation Drosophila protein interaction map-"DPIM2"-established from affinity purification-mass spectrometry of 5,805 baits, covering the largest fraction of the Drosophila proteome. The network contains 32,668 interactions among 3,644 proteins, organized into 632 clusters representing putative functional modules. Our analysis expands the pool of known protein interactions in Drosophila, provides annotation for poorly studied genes, and postulates previously undescribed protein interaction relationships. The predictive power and functional relevance of this network are probed through the lens of the Notch signaling pathway, and we find that newly identified members of complexes that include known Notch modifiers can also modulate Notch signaling. DPIM2 allows direct comparisons with a recently published human protein interaction network, defining the existence of functional interactions conserved across species. Thus, DPIM2 defines a valuable resource for predicting protein co-complex memberships and functional associations as well as generates functional hypotheses regarding specific protein interactions.

mitoPADdb: A database of mitochondrial proteins associated with diseases

Mitochondrial protein/gene mutations and expression variations contribute to the pathogenesis of various diseases, such as neurodegenerative and metabolic diseases. Detailed studies on mitochondrial protein-encoding (MPE) genes across diseases can provide clues for novel therapeutic strategies. Here, we collected, compiled, and manually curated the MPE gene mutation and expression variations data and their association with diseases in a single platform named mitoPADdb. The database contains 810 genes with 18,356 mutations and 1284 qualitative expression variations associated with 1793 diseases, grouped into 15 categories. It allows users to perform a comparative quantitative gene expression analysis for 317 transcriptomic studies across disease categories. Further, it provides information on MPE genes-associated molecular pathways. The mitoPADdb is a valuable resource for investigating mitochondrial dysfunction-related diseases. It can be accessed via http://bicresources.jcbose.ac.in/ssaha4/mitopaddb/index.html.

iNP_ESM: Neuropeptide Identification Based on Evolutionary Scale Modeling and Unified Representation Embedding Features

Neuropeptides are biomolecules with crucial physiological functions. Accurate identification of neuropeptides is essential for understanding nervous system regulatory mechanisms. However, traditional analysis methods are expensive and laborious, and the development of effective machine learning models continues to be a subject of current research. Hence, in this research, we constructed an SVM-based machine learning neuropeptide predictor, iNP_ESM, by integrating protein language models Evolutionary Scale Modeling (ESM) and Unified Representation (UniRep) for the first time. Our model utilized feature fusion and feature selection strategies to improve prediction accuracy during optimization. In addition, we validated the effectiveness of the optimization strategy with UMAP (Uniform Manifold Approximation and Projection) visualization. iNP_ESM outperforms existing models on a variety of machine learning evaluation metrics, with an accuracy of up to 0.937 in cross-validation and 0.928 in independent testing, demonstrating optimal neuropeptide recognition capabilities. We anticipate improved neuropeptide data in the future, and we believe that the iNP_ESM model will have broader applications in the research and clinical treatment of neurological diseases.

Coordinated Regulation of Renal Glucose Reabsorption and Gluconeogenesis by mTORC2 and Potassium

Background

The kidney proximal tubule is uniquely responsible for reabsorption of filtered glucose and gluconeogenesis (GNG). Insulin stimulates glucose transport and suppresses GNG in the proximal tubule, however, the signaling mechanisms and coordinated regulation of these processes remain poorly understood. The kinase complex mTORC2 is critical for regulation of growth, metabolism, solute transport, and electrolyte homeostasis in response to a wide array of inputs. Here we examined its role in the regulation of renal glucose reabsorption and GNG.

Methods

Rictor, an essential component of mTORC2, was knocked out using the Pax8-LC1 system to generate inducible tubule specific Rictor knockout (TRKO) mice. These animals were subjected to fasting, refeeding, and variation in dietary K + . Metabolic parameters including glucose homeostasis and renal function were assessed in balance cages. Kidneys and livers were also harvested for molecular analysis of gluconeogenic enzymes, mTORC2-regulated targets, and plasma membrane glucose transporters.

Results

On a normal chow diet, TRKO mice had marked glycosuria despite indistinguishable blood glucose relative to WT controls. Kidney plasma membrane showed lower SGLT2 and SGLT1 in the fed state, supporting reduced renal glucose reabsorption. Additional metabolic testing provided evidence for renal insulin resistance with elevated fasting insulin, impaired pyruvate tolerance, elevated hemoglobin A1c, and increased renal gluconeogenic enzymes in the fasted and fed states. These effects were correlated with reduced downstream phosphorylation of Akt and the transcription factor FOXO4, identifying a novel role of FOXO4 in the kidney. Interestingly, high dietary K + prevented glycosuria and excessive GNG in TRKO mice, despite persistent reduction in mTORC2 substrate phosphorylation.

Conclusion

Renal tubule mTORC2 is critical for coordinated regulation of sodium-glucose cotransport by SGLT2 and SGLT1 as well as renal GNG. Dietary K + promotes glucose reabsorption and suppresses GNG independently of insulin signaling and mTORC2, potentially providing an alternative signaling mechanism in states of insulin resistance.

SIGNIFICANCE STATEMENT

The kidney contributes to regulation of blood glucose through reabsorption of filtered glucose and gluconeogenesis. This study shows that mTORC2 and dietary potassium coordinate the regulation of sodium-glucose cotransport and glucose production in the kidney via independent mechanisms. New insights into the regulation of these processes in the kidney offer promising implications for diabetes mellitus management and treatment.

Chemical Composition of Commercial Cannabis

Cannabis is widely used for medicinal and recreational purposes. As a result, there is increased interest in its chemical components and their physiological effects. However, current information on cannabis chemistry is often outdated or scattered across many books and journals. To address this issue, we used modern metabolomics techniques and modern bioinformatics techniques to compile a comprehensive list of >6000 chemical constituents in commercial cannabis. The metabolomics methods included a combination of high- and low-resolution liquid chromatography-mass spectrometry (MS), gas chromatography-MS, and inductively coupled plasma-MS. The bioinformatics methods included computer-aided text mining and computational genome-scale metabolic inference. This information, along with detailed compound descriptions, physicochemical data, known physiological effects, protein targets, and referential compound spectra, has been made available through a publicly accessible database called the Cannabis Compound Database (https://cannabisdatabase.ca). Such a centralized, open-access resource should prove to be quite useful for the cannabis community.

Nucleoid-associated proteins shape the global protein occupancy and transcriptional landscape of a clinical isolate of Vibrio cholerae

Vibrio cholerae, the causative agent of the diarrheal disease cholera, poses an ongoing health threat due to its wide repertoire of horizontally acquired elements (HAEs) and virulence factors. New clinical isolates of the bacterium with improved fitness abilities, often associated with HAEs, frequently emerge. The appropriate control and expression of such genetic elements is critical for the bacteria to thrive in the different environmental niches they occupy. H-NS, the histone-like nucleoid structuring protein, is the best-studied xenogeneic silencer of HAEs in gamma-proteobacteria. Although H-NS and other highly abundant nucleoid-associated proteins (NAPs) have been shown to play important roles in regulating HAEs and virulence in model bacteria, we still lack a comprehensive understanding of how different NAPs modulate transcription in V. cholerae. By obtaining genome-wide measurements of protein occupancy and active transcription in a clinical isolate of V. cholerae, harboring recently discovered HAEs encoding for phage defense systems, we show that a lack of H-NS causes a robust increase in the expression of genes found in many HAEs. We further found that TsrA, a protein with partial homology to H-NS, regulates virulence genes primarily through modulation of H-NS activity. We also identified few sites that are affected by TsrA independently of H-NS, suggesting TsrA may act with diverse regulatory mechanisms. Our results demonstrate how the combinatorial activity of NAPs is employed by a clinical isolate of an important pathogen to regulate recently discovered HAEs.

IMPORTANCE

New strains of the bacterial pathogen Vibrio cholerae, bearing novel horizontally acquired elements (HAEs), frequently emerge. HAEs provide beneficial traits to the bacterium, such as antibiotic resistance and defense against invading bacteriophages. Xenogeneic silencers are proteins that help bacteria harness new HAEs and silence those HAEs until they are needed. H-NS is the best-studied xenogeneic silencer; it is one of the nucleoid-associated proteins (NAPs) in gamma-proteobacteria and is responsible for the proper regulation of HAEs within the bacterial transcriptional network. We studied the effects of H-NS and other NAPs on the HAEs of a clinical isolate of V. cholerae. Importantly, we found that H-NS partners with a small and poorly characterized protein, TsrA, to help domesticate new HAEs involved in bacterial survival and in causing disease. A proper understanding of the regulatory state in emerging isolates of V. cholerae will provide improved therapies against new isolates of the pathogen.

Proteomic and metabolic analysis of Moorella thermoacetica-g-C3N4 nanocomposite system for artificial photosynthesis

Artificial photosynthesis by microbe-semiconductor biohybrid systems has been demonstrated as a valuable strategy in providing sustainable energy and in carbon fixation. However, most of the developed biohybrid systems for light harvesting employ heavy metal materials, especially cadmium sulfide (CdS), which normally cause environmental pollution and restrict the widespread of the systems. Herein, we constructed an environmentally friendly biohybirid system based on a typical acetogenic bacteria, Moorella thermoacetica, coupling with a carbon-based semiconductor, graphitic carbon nitride (g-C3N4), to realize light-driven carbon fixation. The proposed biohybrid system displayed outstanding acetate productivity with a quantum yield of 2.66 ± 0.43 %. Non-targeted proteomic analysis indicated that the physiological activity of the bacteria was improved, coupling with the non-toxic material. We further proposed the mechanisms of energy generation, electron transfer and CO2 fixation of the irradiated biohybrid system by proteomic and metabolomic characterization. With the photoelectron generated in g-C3N4 under illumination, CO2 is finally converted to acetate via the Wood-Ljungdahl pathway (WLP). Other associated pathways were also proved to be activated, providing extra energy or substrates for acetate production. The study reveals that the future focus of the development of biohybrid systems for light harvesting can be on the metal-free biocompatible material, which can activate the expression of the key enzymes involved in the electron transfer and carbon metabolism under light irradiation.

Are Most Human-Specific Proteins Encoded by Long Noncoding RNAs?

By looking for a lack of homologs in a reference database of 27 well-annotated proteomes of primates and 52 well-annotated proteomes of other mammals, 170 putative human-specific proteins were identified. While most of them are deemed uncertain, 2 are known at the protein level and 23 at the transcript level, according to UniProt. Interestingly, 23 of these 25 proteins are found to be encoded or to have close homologs in an open reading frame of a long noncoding human RNA. However, half of them are predicted to be at least 80% globular, with a single structural domain, according to IUPred, and with at least 80% of ordered residues, according to flDPnn. Strikingly, there is a near-complete lack of structural knowledge about these proteins, with no tertiary structure presently available in the Protein Data Bank and a fair prediction for one of them in the AlphaFold Protein Structure Database. Moreover, knowledge about the function of these possibly key proteins remains scarce.

Central role of the ramAR locus in the multidrug resistance in ESBL-Enterobacterales

The aim of this study was to evaluate the proportion of resistance to a temocillin, tigecycline, ciprofloxacin, and chloramphenicol phenotype called t2c2 that resulted from mutations within the ramAR locus among extended-spectrum β-lactamases-Enterobacterales (ESBL-E) isolated in three intensive care units for 3 years in a French university hospital. Two parallel approaches were performed on all 443 ESBL-E included: (i) the minimal inhibitory concentrations of temocillin, tigecycline, ciprofloxacin, and chloramphenicol were determined and (ii) the genomes obtained from the Illumina sequencing platform were analyzed to determine multilocus sequence types, resistomes, and diversity of several tetR-associated genes including ramAR operon. Among the 443 ESBL-E strains included, isolates of Escherichia coli (n = 194), Klebsiella pneumoniae (n = 122), and Enterobacter cloacae complex (Ecc) (n = 127) were found. Thirty-one ESBL-E strains (7%), 16 K. pneumoniae (13.1%), and 15 Ecc (11.8%) presented the t2c2 phenotype in addition to their ESBL profile, whereas no E. coli presented these resistances. The t2c2 phenotype was invariably reversible by the addition of Phe-Arg-β-naphthylamide, indicating a role of resistance-nodulation-division pumps in these observations. Mutations associated with the t2c2 phenotype were restricted to RamR, the ramAR intergenic region (IR), and AcrR. Mutations in RamR consisted of C- or N-terminal deletions and amino acid substitutions inside its DNA-binding domain or within key sites of protein-substrate interactions. The ramAR IR showed nucleotide substitutions involved in the RamR DNA-binding domain. This diversity of sequences suggested that RamR and the ramAR IR represent major genetic events for bacterial antimicrobial resistance.IMPORTANCEMorbimortality caused by infectious diseases is very high among patients hospitalized in intensive care units (ICUs). A part of these outcomes can be explained by antibiotic resistance, which delays the appropriate therapy. The transferable antibiotic resistance gene is a well-known mechanism to explain the high rate of multidrug resistance (MDR) bacteria in ICUs. This study describes the prevalence of chromosomal mutations, which led to additional antibiotic resistance among MDR bacteria. More than 12% of Klebsiella pneumoniae and Enterobacter cloacae complex strains presented mutations within the ramAR locus associated with a dysregulation of an efflux pump called AcrAB-TolC and a porin: OmpF. These dysregulations led to an increase in antibiotic output notably tigecycline, ciprofloxacin, and chloramphenicol associated with a decrease of input for beta-lactam, especially temocillin. Mutations within transcriptional regulators such as ramAR locus played a major role in antibiotic resistance dissemination and need to be further explored.

Decrypting lysine deacetylase inhibitor action and protein modifications by dose-resolved proteomics

Lysine deacetylase inhibitors (KDACis) are approved drugs for cutaneous T cell lymphoma (CTCL), peripheral T cell lymphoma (PTCL), and multiple myeloma, but many aspects of their cellular mechanism of action (MoA) and substantial toxicity are not well understood. To shed more light on how KDACis elicit cellular responses, we systematically measured dose-dependent changes in acetylation, phosphorylation, and protein expression in response to 21 clinical and pre-clinical KDACis. The resulting 862,000 dose-response curves revealed, for instance, limited cellular specificity of histone deacetylase (HDAC) 1, 2, 3, and 6 inhibitors; strong cross-talk between acetylation and phosphorylation pathways; localization of most drug-responsive acetylation sites to intrinsically disordered regions (IDRs); an underappreciated role of acetylation in protein structure; and a shift in EP300 protein abundance between the cytoplasm and the nucleus. This comprehensive dataset serves as a resource for the investigation of the molecular mechanisms underlying KDACi action in cells and can be interactively explored online in ProteomicsDB.

Multisubstrate specificity shaped the complex evolution of the aminotransferase family across the tree of life

Aminotransferases (ATs) are an ancient enzyme family that play central roles in core nitrogen metabolism, essential to all organisms. However, many of the AT enzyme functions remain poorly defined, limiting our fundamental understanding of the nitrogen metabolic networks that exist in different organisms. Here, we traced the deep evolutionary history of the AT family by analyzing AT enzymes from 90 species spanning the tree of life (ToL). We found that each organism has maintained a relatively small and constant number of ATs. Mapping the distribution of ATs across the ToL uncovered that many essential AT reactions are carried out by taxon-specific AT enzymes due to wide-spread nonorthologous gene displacements. This complex evolutionary history explains the difficulty of homology-based AT functional prediction. Biochemical characterization of diverse aromatic ATs further revealed their broad substrate specificity, unlike other core metabolic enzymes that evolved to catalyze specific reactions today. Interestingly, however, we found that these AT enzymes that diverged over billion years share common signatures of multisubstrate specificity by employing different nonconserved active site residues. These findings illustrate that AT family enzymes had leveraged their inherent substrate promiscuity to maintain a small yet distinct set of multifunctional AT enzymes in different taxa. This evolutionary history of versatile ATs likely contributed to the establishment of robust and diverse nitrogen metabolic networks that exist throughout the ToL. The study provides a critical foundation to systematically determine diverse AT functions and underlying nitrogen metabolic networks across the ToL.

Network pharmacology in combination with bibliometrics analysis on the mechanism of compound Kushen injection in the treatment of radiation pneumonia and lung cancer

Radiation pneumonia is a common adverse reaction during radiotherapy in lung cancer patients, which negatively impacts the quality of life and survival of patients. Recent studies have shown that compound Kushen injection (CKI), a traditional Chinese medicine (TCM), has great anti-inflammatory and anticancer potential, but the mechanism is still unclear. We used CiteSpace, the R package "bibliometrix," and VOSviewers to perform a bibliometrics analysis of 162 articles included from the Web of Science core collection. A network pharmacology-based approach was used to screen effective compounds, screen and predict target genes, analyze biological functions and pathways, and construct regulatory networks and protein interaction networks. Molecular docking experiments were used to identify the affinity of key compounds and core target. The literature metrology analysis revealed that over 90% of the CKI-related studies were conducted by Chinese scholars and institutions, with a predominant focus on tumors, while research on radiation pneumonia remained limited. Our investigation identified 60 active ingredients of CKI, 292 genes associated with radiation pneumonia, 533 genes linked to lung cancer, and 37 common targets of CKI in the treatment of both radiation pneumonia and lung cancer. These core potential targets were found to be significantly associated with the OS of lung cancer patients, and the key compounds exhibited a good docking affinity with these targets. Additionally, GO and KEGG enrichment analysis highlighted that the bioinformatics annotation of these common genes mainly involved ubiquitin protein ligase binding, cytokine receptor binding, and the PI3K/Akt signaling pathway. Our study revealed that the main active components of CKI, primarily quercetin, luteolin, and naringin, might act on major core targets, including AKT1, PTGS2, and PPARG, and further regulated key signaling pathways such as the PI3K/Akt pathway, thereby playing a crucial role in the treatment of radiation pneumonia and lung cancer. Moreover, this study had a certain promotional effect on further clinical application and provided a theoretical basis for subsequent experimental research.

Accessing and exploring the unusual chemistry by radical SAM-RiPP enzymes

Radical SAM enzymes involved in the biosynthesis of ribosomally synthesized and post-translationally modified peptides catalyze unusual transformations that lead to unique peptide scaffolds and building blocks. Several natural products from these pathways show encouraging antimicrobial activities and represent next-generation therapeutics for infectious diseases. These systems are uniquely configured to benefit from genome-mining approaches because minimal substrate and cognate modifying enzyme expression can reveal unique, chemically complex transformations that outperform late-stage chemical reactions. This report highlights the main strategies used to reveal these enzymatic transformations, which have relied mainly on genome mining using enzyme-first approaches. We describe the general biosynthetic components for rSAM enzymes and highlight emerging approaches that may broaden the discovery and study of rSAM-RiPP enzymes. The large number of uncharacterized rSAM proteins, coupled with their unpredictable transformations, will continue to be an essential and exciting resource for enzyme discovery.

Neuroprotective Effect and Mechanism of Tanreqing Injection on Ischemic Stroke: Insights from Network Pharmacology and in vivo Experiments

OBJECTIVE

To explore the neuroprotective effects and mechanism of Tanreqing Injection (TRQ) on treating ischemic stroke based on network pharmacology and in vivo experimental validation.

METHODS

The chemical compounds of TRQ were retrieved based on published data, with targets retrieved from PubChem, Therapeutic Target Database and DrugBank. Network visualization and analysis were performed using Cytoscape, with protein-protein interaction networks derived from the STRING database. Enrichment analysis was performed using Kyoto Encyclopedia of Genes Genomes pathway and Gene Ontology analysis. In in vivo experiments, the middle cerebral artery occlusion (MCAO) model was used. Infarct volume was determined by 2,3,5-triphenyltetrazolium hydrochloride staining and protein expressions were analyzed by Western blot. Molecular docking was performed to predict ligand-receptor interactions.

RESULTS

We screened 81 chemical compounds in TRQ and retrieved their therapeutic targets. Of the targets, 116 were therapeutic targets for stroke. The enrichment analysis showed that the apelin signaling pathway was a key pathway for ischemic stroke. Furthermore, in in vivo experiment we found that administering with intraperitoneal injection of 2.5 mL/kg TRQ every 6 h could significantly reduce the infarct volume of MCAO rats (P<0.05). In addition, protein levels of the apelin receptor (APJ)/phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) pathway were increased by TRQ (P<0.05). In addition, 41 chemical compounds in TRQ could bind to APJ.

CONCLUSIONS

The neuroprotective effect of TRQ may be related to the APJ/PI3K/AKT signaling pathway. However, further studies are needed to confirm the findings.

Understanding the Differences of Danusertib's Residence Time in Aurora Kinases A/B: Dissociation Paths and Key Residues Identified using Conventional and Enhanced Molecular Dynamics Simulations

The accurate experimental estimation of protein-ligand systems' residence time (τ) has become very relevant in drug design projects due to its importance in the last stages of refinement of the drug's pharmacodynamics and pharmacokinetics. It is now well-known that it is not sufficient to estimate the affinity of a protein-drug complex in the thermodynamic equilibrium process in in vitro experiments (closed systems), where the concentrations of the drug and protein remain constant. On the contrary, it is mandatory to consider the conformational dynamics of the system in terms of the binding and unbinding processes between protein and drugs in in vivo experiments (open systems), where their concentrations are in constant flux. This last model has been proven to dictate much of several drugs' pharmacological activities in vivo. At the atomistic level, molecular dynamics simulations can explain why some drugs are more effective than others or unveil the molecular aspects that make some drugs work better in one molecular target. Here, the protein kinases Aurora A/B, complexed with its inhibitor Danusertib, were studied using conventional and enhanced molecular dynamics (MD) simulations to estimate the dissociation paths and, therefore, the computational τ values and their comparison with experimental ones. Using classical molecular dynamics (cMD), three differential residues within the Aurora A/B active site, which seems to play an essential role in the observed experimental Danusertib's residence time against these kinases, were characterized. Then, using WT-MetaD, the relative Danusertib's residence times against Aurora A/B kinases were measured in a nanosecond time scale and were compared to those τ values observed experimentally. In addition, the potential dissociation paths of Danusertib in Aurora A and B were characterized, and differences that might be explained by the differential residues in the enzyme's active sites were found. In perspective, it is expected that this computational protocol can be applied to other protein-ligand complexes to understand, at the molecular level, the differences in residence times and amino acids that may contribute to it.

Protein-Protein Interaction Prediction via Structure-Based Deep Learning

Protein-protein interactions (PPIs) play an essential role in life activities. Many artificial intelligence algorithms based on protein sequence information have been developed to predict PPIs. However, these models have difficulty dealing with various sequence lengths and suffer from low generalization and prediction accuracy. In this study, we proposed a novel end-to-end deep learning framework, RSPPI, combining residual neural network (ResNet) and spatial pyramid pooling (SPP), to predict PPIs based on the protein sequence physicochemistry properties and spatial structural information. In the RSPPI model, ResNet was employed to extract the structural and physicochemical information from the protein three-dimensional structure and primary sequence; the SPP layer was used to transform feature maps to a single vector and avoid the fixed-length requirement. The RSPPI model possessed excellent cross-species performance and outperformed several state-of-the-art methods based either on protein sequence or gene ontology in most evaluation metrics. The RSPPI model provides a novel strategy to develop an AI PPI prediction algorithm.

Biophysical characterization of high-confidence, small human proteins

Significant efforts have been made to characterize the biophysical properties of proteins. Small proteins have received less attention because their annotation has historically been less reliable. However, recent improvements in sequencing, proteomics, and bioinformatics techniques have led to the high-confidence annotation of small open reading frames (smORFs) that encode for functional proteins, producing smORF-encoded proteins (SEPs). SEPs have been found to perform critical functions in several species, including humans. While significant efforts have been made to annotate SEPs, less attention has been given to the biophysical properties of these proteins. We characterized the distributions of predicted and curated biophysical properties, including sequence composition, structure, localization, function, and disease association of a conservative list of previously identified human SEPs. We found significant differences between SEPs and both larger proteins and control sets. In addition, we provide an example of how our characterization of biophysical properties can contribute to distinguishing protein-coding smORFs from noncoding ones in otherwise ambiguous cases.

TDC-2: Multimodal Foundation for Therapeutic Science

Therapeutics Data Commons (tdcommons.ai) is an open science initiative with unified datasets, AI models, and benchmarks to support research across therapeutic modalities and drug discovery and development stages. The Commons 2.0 (TDC-2) is a comprehensive overhaul of Therapeutic Data Commons to catalyze research in multimodal models for drug discovery by unifying single-cell biology of diseases, biochemistry of molecules, and effects of drugs through multimodal datasets, AI-powered API endpoints, new multimodal tasks and model frameworks, and comprehensive benchmarks. TDC-2 introduces over 1,000 multimodal datasets spanning approximately 85 million cells, pre-calculated embeddings from 5 state-of-the-art single-cell models, and a biomedical knowledge graph. TDC-2 drastically expands the coverage of ML tasks across therapeutic pipelines and 10+ new modalities, spanning but not limited to single-cell gene expression data, clinical trial data, peptide sequence data, peptidomimetics protein-peptide interaction data regarding newly discovered ligands derived from AS-MS spectroscopy, novel 3D structural data for proteins, and cell-type-specific protein-protein interaction networks at single-cell resolution. TDC-2 introduces multimodal data access under an API-first design using the model-view-controller paradigm. TDC-2 introduces 7 novel ML tasks with fine-grained biological contexts: contextualized drug-target identification, single-cell chemical/genetic perturbation response prediction, protein-peptide binding affinity prediction task, and clinical trial outcome prediction task, which introduce antigen-processing-pathway-specific, cell-type-specific, peptide-specific, and patient-specific biological contexts. TDC-2 also releases benchmarks evaluating 15+ state-of-the-art models across 5+ new learning tasks evaluating models on diverse biological contexts and sampling approaches. Among these, TDC-2 provides the first benchmark for context-specific learning. TDC-2, to our knowledge, is also the first to introduce a protein-peptide binding interaction benchmark.

Metaproteomics reveals parallel utilization of colonic mucin glycans and dietary fibers by the human gut microbiota

A diet lacking dietary fibers promotes the expansion of gut microbiota members that can degrade host glycans, such as those on mucins. The microbial foraging on mucin has been associated with disruptions of the gut-protective mucus layer and colonic inflammation. Yet, it remains unclear how the co-utilization of mucin and dietary fibers affects the microbiota composition and metabolic activity. Here, we used 14 dietary fibers and porcine colonic and gastric mucins to study the dynamics of mucin and dietary fiber utilization by the human fecal microbiota in vitro. Combining metaproteome and metabolites analyses revealed the central role of the Bacteroides genus in the utilization of complex fibers together with mucin while Akkermansia muciniphila was the main utilizer of sole porcine colonic mucin but not gastric mucin. This study gives a broad overview of the colonic environment in response to dietary and host glycan availability.

Integrating In Silico and In Vitro Approaches to Identify Natural Peptides with Selective Cytotoxicity against Cancer Cells

Anticancer peptides (ACPs) are bioactive compounds known for their selective cytotoxicity against tumor cells via various mechanisms. Recent studies have demonstrated that in silico machine learning methods are effective in predicting peptides with anticancer activity. In this study, we collected and analyzed over a thousand experimentally verified ACPs, specifically targeting peptides derived from natural sources. We developed a precise prediction model based on their sequence and structural features, and the model's evaluation results suggest its strong predictive ability for anticancer activity. To enhance reliability, we integrated the results of this model with those from other available methods. In total, we identified 176 potential ACPs, some of which were synthesized and further evaluated using the MTT colorimetric assay. All of these putative ACPs exhibited significant anticancer effects and selective cytotoxicity against specific tumor cells. In summary, we present a strategy for identifying and characterizing natural peptides with selective cytotoxicity against cancer cells, which could serve as novel therapeutic agents. Our prediction model can effectively screen new molecules for potential anticancer activity, and the results from in vitro experiments provide compelling evidence of the candidates' anticancer effects and selective cytotoxicity.

NADPHnet: a novel strategy to predict compounds for regulation of NADPH metabolism via network-based methods

Identification of compounds to modulate NADPH metabolism is crucial for understanding complex diseases and developing effective therapies. However, the complex nature of NADPH metabolism poses challenges in achieving this goal. In this study, we proposed a novel strategy named NADPHnet to predict key proteins and drug-target interactions related to NADPH metabolism via network-based methods. Different from traditional approaches only focusing on one single protein, NADPHnet could screen compounds to modulate NADPH metabolism from a comprehensive view. Specifically, NADPHnet identified key proteins involved in regulation of NADPH metabolism using network-based methods, and characterized the impact of natural products on NADPH metabolism using a combined score, NADPH-Score. NADPHnet demonstrated a broader applicability domain and improved accuracy in the external validation set. This approach was further employed along with molecular docking to identify 27 compounds from a natural product library, 6 of which exhibited concentration-dependent changes of cellular NADPH level within 100 μM, with Oxyberberine showing promising effects even at 10 μM. Mechanistic and pathological analyses of Oxyberberine suggest potential novel mechanisms to affect diabetes and cancer. Overall, NADPHnet offers a promising method for prediction of NADPH metabolism modulation and advances drug discovery for complex diseases.

Molecular insights into the activation of Mre11-Rad50 endonuclease activity by Sae2/CtIP

In Saccharomyces cerevisiae (S. cerevisiae), Mre11-Rad50-Xrs2 (MRX)-Sae2 nuclease activity is required for the resection of DNA breaks with secondary structures or protein blocks, while in humans, the MRE11-RAD50-NBS1 (MRN) homolog with CtIP is needed to initiate DNA end resection of all breaks. Phosphorylated Sae2/CtIP stimulates the endonuclease activity of MRX/N. Structural insights into the activation of the Mre11 nuclease are available only for organisms lacking Sae2/CtIP, so little is known about how Sae2/CtIP activates the nuclease ensemble. Here, we uncover the mechanism of Mre11 activation by Sae2 using a combination of AlphaFold2 structural modeling of biochemical and genetic assays. We show that Sae2 stabilizes the Mre11 nuclease in a conformation poised to cleave substrate DNA. Several designs of compensatory mutations establish how Sae2 activates MRX in vitro and in vivo, supporting the structural model. Finally, our study uncovers how human CtIP, despite considerable sequence divergence, employs a similar mechanism to activate MRN.

The multi-dimensional impact of captopril modification on human serum albumin

Captopril is a thiol drug, widely used for the management of hypertension and cardiovascular diseases. Reactive thiols are found to covalently modify the cysteines of plasma proteins and affect their structure and function. Human serum albumin (HSA) is prone to undergo modification by various low molecular weight compounds, including drugs. Cysteine34 (Cys34) in HSA has a free thiol group with antioxidant properties, considered to be the most redox-sensitive amino acid in plasma. Through mass-spectrometric analysis, we demonstrate for the first time that captopril forms a disulfide adduct at Cys34 residue and increases the protease susceptibility of HSA to trypsin. As evidenced by our biophysical and electron microscopy studies, HSA undergoes structural alteration, aggregation and morphological changes when treated with different captopril concentrations. Molecular dynamics studies further revealed the regions of secondary structural changes in HSA due to disulfide adduct formation by captopril at Cys34. It also elucidated the residues involved in the noncovalent interactions with captopril. It is envisaged that structural change in HSA may influence the efficacy of drug delivery as well as its own biological function. These findings may thus provide significant insights into the field of pharmacology intriguing further investigation into the effects of long-term captopril treatment.

De novo assembly of transcriptomes and differential gene expression analysis using short-read data from emerging model organisms - a brief guide

Many questions in biology benefit greatly from the use of a variety of model systems. High-throughput sequencing methods have been a triumph in the democratization of diverse model systems. They allow for the economical sequencing of an entire genome or transcriptome of interest, and with technical variations can even provide insight into genome organization and the expression and regulation of genes. The analysis and biological interpretation of such large datasets can present significant challenges that depend on the 'scientific status' of the model system. While high-quality genome and transcriptome references are readily available for well-established model systems, the establishment of such references for an emerging model system often requires extensive resources such as finances, expertise and computation capabilities. The de novo assembly of a transcriptome represents an excellent entry point for genetic and molecular studies in emerging model systems as it can efficiently assess gene content while also serving as a reference for differential gene expression studies. However, the process of de novo transcriptome assembly is non-trivial, and as a rule must be empirically optimized for every dataset. For the researcher working with an emerging model system, and with little to no experience with assembling and quantifying short-read data from the Illumina platform, these processes can be daunting. In this guide we outline the major challenges faced when establishing a reference transcriptome de novo and we provide advice on how to approach such an endeavor. We describe the major experimental and bioinformatic steps, provide some broad recommendations and cautions for the newcomer to de novo transcriptome assembly and differential gene expression analyses. Moreover, we provide an initial selection of tools that can assist in the journey from raw short-read data to assembled transcriptome and lists of differentially expressed genes.

Lianhua Qingwen exerts anti-liver cancer effects and synergistic efficacy with sorafenib through PI3K/AKT pathway: Integrating network pharmacology, molecular docking, and experimental validation

Liver cancer is one of the most lethal malignancies and sorafenib resistance is the main treatment obstacle for patients with advanced liver cancer. Developing drugs that sensitize liver cancer patients to sorafenib is of great importance. Lianhua Qingwen (LHQW), a sort of Traditional Chinese Medicine (TCM) approved by the Chinese Food and Drug Administration (CFDA), is reported to exert synergistic effects with oseltamivir against Influenza virus. However, whether LHQW could exhibit anti-liver cancer effects and enhance the efficacy of sorafenib against liver cancer have not been reported. In the present study, the potential anti-liver cancer effects of LHQW and its synergistic effects with sorafenib were investigated via applying network pharmacology, molecular docking, and in vitro experiments. An "ingredient-compound- target-liver cancer" network was constructed which included 12 ingredients, 164 compounds, and 402 targets. AKT1 was identified as the most hub gene and the PI3K/AKT pathway was revealed as the most enriched pathway. Subsequently, the molecular docking results showed that kaempferol, luteolin, and quercetin were screened as the top 3 compounds which showed the tightest binding to AKT1. Further, the in vitro experiments verified that LHQW significantly inhibited liver cancer cell proliferation and induced apoptosis. Western blot assays confirmed that LHQW could attenuate the PI3K/AKT pathway. Interestingly, LHQW showed a synergistic effect with sorafenib against liver cancer via reducing cell viability, inducing apoptosis, and down- regulating PI3K/AKT pathway. This study broadens the potential application of LHQW and provides insights for liver cancer treatment.

The substrate quality of CK2 target sites has a determinant role on their function and evolution

Most biological processes are regulated by signaling modules that bind to short linear motifs. For protein kinases, substrates may have full or only partial matches to the kinase recognition motif, a property known as "substrate quality." However, it is not clear whether differences in substrate quality represent neutral variation or if they have functional consequences. We examine this question for the kinase CK2, which has many fundamental functions. We show that optimal CK2 sites are phosphorylated at maximal stoichiometries and found in many conditions, whereas minimal substrates are more weakly phosphorylated and have regulatory functions. Optimal CK2 sites tend to be more conserved, and substrate quality is often tuned by selection. For intermediate sites, increases or decreases in substrate quality may be deleterious, as we demonstrate for a CK2 substrate at the kinetochore. The results together suggest a strong role for substrate quality in phosphosite function and evolution. A record of this paper's transparent peer review process is included in the supplemental information.

Transcriptomic profiling of haloarchaeal denitrification through RNA-Seq analysis

Denitrification, a crucial biochemical pathway prevalent among haloarchaea in hypersaline ecosystems, has garnered considerable attention in recent years due to its ecological implications. Nevertheless, the underlying molecular mechanisms and genetic regulation governing this respiration/detoxification process in haloarchaea remain largely unexplored. In this study, RNA-sequencing was used to compare the transcriptomes of the haloarchaeon Haloferax mediterranei under oxic and denitrifying conditions, shedding light on the intricate metabolic alterations occurring within the cell, such as the accurate control of the metal homeostasis. Furthermore, the investigation identifies several genes encoding transcriptional regulators and potential accessory proteins with putative roles in denitrification. Among these are bacterioopsin-like transcriptional activators, proteins harboring a domain of unknown function (DUF2249), and cyanoglobin. In addition, the study delves into the genetic regulation of denitrification, finding a regulatory motif within promoter regions that activates numerous denitrification-related genes. This research serves as a starting point for future molecular biology studies in haloarchaea, offering a promising avenue to unravel the intricate mechanisms governing haloarchaeal denitrification, a pathway of paramount ecological importance.IMPORTANCEDenitrification, a fundamental process within the nitrogen cycle, has been subject to extensive investigation due to its close association with anthropogenic activities, and its contribution to the global warming issue, mainly through the release of N2O emissions. Although our comprehension of denitrification and its implications is generally well established, most studies have been conducted in non-extreme environments with mesophilic microorganisms. Consequently, there is a significant knowledge gap concerning extremophilic denitrifiers, particularly those inhabiting hypersaline environments. The significance of this research was to delve into the process of haloarchaeal denitrification, utilizing the complete denitrifier haloarchaeon Haloferax mediterranei as a model organism. This research led to the analysis of the metabolic state of this microorganism under denitrifying conditions and the identification of regulatory signals and genes encoding proteins potentially involved in this pathway, serving as a valuable resource for future molecular studies.

Integrative proteomic and transcriptomic analysis in the female goat ovary to explore the onset of puberty

Puberty is considered a prerequisite for affecting reproductive performance and productivity. Little was known about molecular changes in pubertal goat ovaries. Therefore, we measured and performed a correlation analysis of the mRNA and proteins changes in the pre-pubertal and pubertal goat ovaries. The results showed that only six differentially expressed genes and differentially abundant proteins out of 18,139 genes and 7550 proteins quantified had significant correlations. CNTN2 and THBS1, discovered in the mRNA-mRNA interaction network, probably participated in pubertal and reproductive regulation by influencing GnRH receptor signals, follicular development, and ovulation. The predicted core transcription factors may either promote or inhibit the expression of reproductive genes and act synergistically to maintain normal reproductive function in animals. The interaction between PKM and TIMP3 with other proteins may impact animal puberty through energy metabolism and ovarian hormone secretion. Pathway enrichment analyses revealed that the co-associated key pathways between ovarian genes and proteins at puberty included calcium signalling pathway and olfactory transduction. These pathways were associated with gonadotropin-releasing hormone synthesis and secretion, signal transmission, and cell proliferation. In summary, these results enriched the potential molecules and signalling pathways that affect puberty and provided new insights for regulating and promoting the onset of puberty. SIGNIFICANCE: This study conducted the first transcriptomic and proteomic correlation analysis of pre-pubertal and pubertal goat ovaries and identified six significantly correlated molecules at both the gene and protein levels. Meanwhile, we were drawn to several molecules and signalling pathways that may play a regulatory role in the onset of puberty and reproduction by influencing reproductive-related gene expression, GnRH receptor signals, energy metabolism, ovarian hormone secretion, follicular development, and ovulation. This information contributed to identify potential biomarkers in pubertal goat ovaries, which was vital for predicting the onset of puberty and improving livestock performance.

Identification of microtubule-associated biomarker using machine learning methods in osteonecrosis of the femoral head and osteosarcoma

Background

This study aims to explore the microtubule-associated gene signatures and molecular processes shared by osteonecrosis of the femoral head (ONFH) and osteosarcoma (OS).

Methods

Datasets from the TARGET and GEO databases were subjected to bioinformatics analysis, including the functional enrichment analysis of genes shared by ONFH and OS. Prognostic genes were identified using univariate and multivariate Cox regression analyses to develop a risk score model for predicting overall survival and immune characteristics. Furthermore, LASSO and SVM-RFE algorithms identified biomarkers for ONFH, which were validated in OS. Function prediction, ceRNA network analysis, and gene-drug interaction network construction were subsequently conducted. Biomarker expression was then validated on clinical samples by using qPCR.

Results

A total of 14 microtubule-associated disease genes were detected in ONFH and OS. Subsequently, risk score model based on four genes was then created, revealing that patients with low-risk exhibited superior survival outcomes compared with those with high-risk. Notably, ONFH with low-risk profiles may manifest an antitumor immune microenvironment. Moreover, by utilizing LASSO and SVM-RFE algorithms, four diagnostic biomarkers were pinpointed, enabling effective discrimination between patients with ONFH and healthy individuals as well as between OS and normal tissues. Additionally, 21 drugs targeting these biomarkers were predicted, and a comprehensive ceRNA network comprising four mRNAs, 71 miRNAs, and 98 lncRNAs was established. The validation of biomarker expression in clinical samples through qPCR affirmed consistency with the results of bioinformatics analysis.

Conclusion

Microtubule-associated genes may play pivotal roles in OS and ONFH. Additionally, a prognostic model was constructed, and four genes were identified as potential biomarkers and therapeutic targets for both diseases.

Sensitive and error-tolerant annotation of protein-coding DNA with BATH

Summary

We present BATH, a tool for highly sensitive annotation of protein-coding DNA based on direct alignment of that DNA to a database of protein sequences or profile hidden Markov models (pHMMs). BATH is built on top of the HMMER3 code base, and simplifies the annotation workflow for pHMM-based translated sequence annotation by providing a straightforward input interface and easy-to-interpret output. BATH also introduces novel frameshift-aware algorithms to detect frameshift-inducing nucleotide insertions and deletions (indels). BATH matches the accuracy of HMMER3 for annotation of sequences containing no errors, and produces superior accuracy to all tested tools for annotation of sequences containing nucleotide indels. These results suggest that BATH should be used when high annotation sensitivity is required, particularly when frameshift errors are expected to interrupt protein-coding regions, as is true with long-read sequencing data and in the context of pseudogenes.

Availability and implementation

The software is available at https://github.com/TravisWheelerLab/BATH.

Therapeutic targets of formononetin for treating prostate cancer at the single-cell level

Prostate cancer is one of the serious health problems of older male, about 13% of male was affected by prostate cancer. Prostate cancer is highly heterogeneity disease with complex molecular and genetic alterations. So, targeting the gene candidates in prostate cancer in single-cell level can be a promising approach for treating prostate cancer. In the present study, we analyzed the single cell sequencing data obtained from 2 previous reports to determine the differential gene expression of prostate cancer in single-cell level. By using the network pharmacology analysis, we identified the therapeutic targets of formononetin in immune cells and tissue cells of prostate cancer. We then applied molecular docking to determine the possible direct binding of formononetin to its target proteins. Our result identified a cluster of differential gene expression in prostate cancer which can serve as novel biomarkers such as immunoglobulin kappa C for prostate cancer prognosis. The result of network pharmacology delineated the roles of formononetin's targets such CD74 and THBS1 in immune cells' function of prostate cancer. Also, formononetin targeted insulin receptor and zinc-alpha-2-glycoprotein which play important roles in metabolisms of tissue cells of prostate cancer. The result of molecular docking suggested the direct binding of formononetin to its target proteins including INSR, TNF, and CXCR4. Finally, we validated our findings by using formononetin-treated human prostate cancer cell DU145. For the first time, our result suggested the use of formononetin for treating prostate cancer through targeting different cell types in a single-cell level.

Genes required for survival and proliferation of Mycoplasma bovis in association with host cells

Mycoplasma bovis is an important emerging pathogen of cattle and bison, but our understanding of the genetic basis of its interactions with its host is limited. The aim of this study was to identify genes of M. bovis required for interaction and survival in association with host cells. One hundred transposon-induced mutants of the type strain PG45 were assessed for their capacity to survive and proliferate in Madin-Darby bovine kidney cell cultures. The growth of 19 mutants was completely abrogated, and 47 mutants had a prolonged doubling time compared to the parent strain. All these mutants had a similar growth pattern to the parent strain PG45 in the axenic media. Thirteen genes previously classified as dispensable for the axenic growth of M. bovis were found to be essential for the growth of M. bovis in association with host cells. In most of the mutants with a growth-deficient phenotype, the transposon was inserted into a gene involved in transportation or metabolism. This included genes coding for ABC transporters, proteins related to carbohydrate, nucleotide and protein metabolism, and membrane proteins essential for attachment. It is likely that these genes are essential not only in vitro but also for the survival of M. bovis in infected animals.

IMPORTANCE

Mycoplasma bovis causes chronic bronchopneumonia, mastitis, arthritis, keratoconjunctivitis, and reproductive tract disease in cattle around the globe and is an emerging pathogen in bison. Control of mycoplasma infections is difficult in the absence of appropriate antimicrobial treatment or effective vaccines. A comprehensive understanding of host-pathogen interactions and virulence factors is important to implement more effective control methods against M. bovis. Recent studies of other mycoplasmas with in vitro cell culture models have identified essential virulence genes of mycoplasmas. Our study has identified genes of M. bovis required for survival in association with host cells, which will pave the way to a better understanding of host-pathogen interactions and the role of specific genes in the pathogenesis of disease caused by M. bovis.

Gut microbial β-glucuronidases influence endobiotic homeostasis and are modulated by diverse therapeutics

Hormones and neurotransmitters are essential to homeostasis, and their disruptions are connected to diseases ranging from cancer to anxiety. The differential reactivation of endobiotic glucuronides by gut microbial β-glucuronidase (GUS) enzymes may influence interindividual differences in the onset and treatment of disease. Using multi-omic, in vitro, and in vivo approaches, we show that germ-free mice have reduced levels of active endobiotics and that distinct gut microbial Loop 1 and FMN GUS enzymes drive hormone and neurotransmitter reactivation. We demonstrate that a range of FDA-approved drugs prevent this reactivation by intercepting the catalytic cycle of the enzymes in a conserved fashion. Finally, we find that inhibiting GUS in conventional mice reduces free serotonin and increases its inactive glucuronide in the serum and intestines. Our results illuminate the indispensability of gut microbial enzymes in sustaining endobiotic homeostasis and indicate that therapeutic disruptions of this metabolism promote interindividual response variabilities.