The identification of drug-target interactions (DTIs) is a critical step in drug development. Experimental methods that are based on clinical trials to discover DTIs are time-consuming, expensive, and challenging. Therefore, as complementary to it, developing new computational methods for predicting novel DTI is of great significance with regards to saving cost and shortening the development period. In this paper, we present a novel computational model for predicting DTIs, which uses the sequence information of proteins and a rotation forest classifier. Specifically, all of the target protein sequences are first converted to a position-specific scoring matrix (PSSM) to retain evolutionary information. We then use local phase quantization (LPQ) descriptors to extract evolutionary information in the PSSM. On the other hand, substructure fingerprint information is utilized to extract the features of the drug. We finally combine the features of drugs and protein together to represent features of each drug-target pair and use a rotation forest classifier to calculate the scores of interaction possibility, for a global DTI prediction. The experimental results indicate that the proposed model is effective, achieving average accuracies of 89.15%, 86.01%, 82.20%, and 71.67% on four datasets (i.e., enzyme, ion channel, G protein-coupled receptors (GPCR), and nuclear receptor), respectively. In addition, we compared the prediction performance of the rotation forest classifier with another popular classifier, support vector machine, on the same dataset. Several types of methods previously proposed are also implemented on the same datasets for performance comparison. The comparison results demonstrate the superiority of the proposed method to the others. We anticipate that the proposed method can be used as an effective tool for predicting drug-target interactions on a large scale, given the information of protein sequences and drug fingerprints.

Pseudomonas sp. QTF5 was isolated from the continuous permafrost near the bitumen layers in the Qiangtang basin of Qinghai-Tibetan Plateau in China (5,111 m above sea level). It is psychrotolerant and highly and widely tolerant to heavy metals and has the ability to metabolize benzoic acid and salicylic acid. To gain insight into the genetic basis for its adaptation, we performed whole genome sequencing and analyzed the resistant genes and metabolic pathways. Based on 120 published and annotated genomes representing 31 species in the genus Pseudomonas, in silico genomic DNA-DNA hybridization (<54%) and average nucleotide identity calculation (<94%) revealed that QTF5 is closest to Pseudomonas lini and should be classified into a novel species. This study provides the genetic basis to identify the genes linked to its specific mechanisms for adaptation to extreme environment and application of this microorganism in environmental conservation.

Potentilla tanacetifolia Willd. ex Schltdl. is a perennial herb in China, which has high ecological and economic values. Its complete chloroplast genome was reported in this study for the first time. The whole chloroplast genome was 157, 051 base pairs in length with 129 genes, including 84 protein-coding genes, 37 tRNAs, and 8 rRNAs. In addition, phylogenetic analysis showed a sister relationship between P. tanacetifolia and P. chinensis.

Paris polyphylla is a medicinal plant commonly used in southwest of China. In this study, we sequenced the complete chloroplast (cp) genome sequence of P. polyphylla to investigate its phylogenetic relationship in the genus Paris. The chloroplast genome of P. polyphylla was 163,533 bp in length with 37.1% overall GC content, including a large single copy (LSC) region of 84,272 bp, a small single copy (SSC) region of 12,899 bp and a pair of inverted repeats (IRs) of 33,181 bp. The cp genome contained 114 genes, including 79 protein coding genes, 30 tRNA genes, and 4 rRNA genes. The phylogenetic analysis indicated P. polyphylla was closely related to P. marmorata.

Endocrine fibroblast growth factors (FGFs) require Klotho transmembrane proteins as necessary co-receptors to activate FGF receptor (FGFR) signaling. In particular, FGF19 and FGF21 function through β-Klotho to regulate glucose and lipid metabolism. Recent research has focused on elucidating how these two FGFs interact with β-Klotho and FGFRs to activate downstream signaling. In this study, using hydrogen deuterium exchange coupled to mass spectrometry (HDX-MS), we identified regions on the β-Klotho protein that likely participate in ligand interaction, and vice versa. Alanine and arginine mutagenesis were carried out to further probe the contributions of individual residues to receptor/ligand interactions. Using biochemical and cell-based signaling assays with full-length proteins, we show that both the KL1 and KL2 domains of β-Klotho participate in ligand interaction, and these binding sites on β-Klotho are shared by FGF19 and FGF21. In addition, we show that two highly conserved regions in the C-terminal tail of FGF19 and FGF21 are responsible for interaction with the co-receptor. Our results are consistent with recent publications on the crystal structures of the Klotho proteins and provide insight into how endocrine FGFs interact with co-receptors for signal transduction.

The interferon-induced proteins with tetratricopeptide repeats (IFITs) protein family mediates antiviral effects by inhibiting translation initiation, cell proliferation, and migration in the interferon (IFN) dependent innate immune system. Several members of this family, including IFIT1, IFIT2, IFIT3 and IFIT5, have been heavily studied in mammals. Avian species contain only one family member, IFIT5, and little is known about the role of this protein in birds. In this study, duck IFIT5 (duIFIT5) full-length mRNA was cloned by reverse transcription polymerase chain reaction (RT-PCR) and rapid amplification of the cDNA ends (RACE). Based on the sequence obtained, we performed a series of bioinformatics analyses, and found that duIFIT5 was most similar to homologs in other avian species. Also, duIFIT5 contained eight conserved TPR motifs and two conserved multi-domains (TPR_11 and TPR_12). Finally, we used duck hepatitis virus type 1 (DHV-1) and polyriboinosinicpolyribocytidylic acid (poly (I:C)) as a pathogen or a pathogen-associated molecular pattern induction to infect three-day-old domestic ducklings. The liver and spleen were collected to detect the change in duIFIT5 transcript level upon infection by quantitative real-time PCR (qRT-PCR). DuIFIT5 expression rapidly increased after DHV-1 infection and maintained a high level, while the transcripts of duIFIT5 peaked at 8h after poly (I:C) infection and then returned to normal. Taken together, these results provide a greater understanding of avian IFIT5.

Endophytic Herbaspirillum sp. strain WT00C was isolated from tea plant (Camellia sinensis L.). Here, we report the 6.08 Mb draft genome sequence of this strain, providing bioinformation about its agronomic benefits and capability to reduce selenate/selenite into red elemental selenium.

Here we report the draft genome sequence of Pseudoalteromonas strain A2, isolated from Arctic seawater in the pack-ice zone, which has high antioxidative activity against H2O2. The genomics information of this strain will facilitate the study of antioxidative mechanisms, cold adaptation properties, and evolution of this genus.

Various biochemical functions of organisms are performed by protein-protein interactions (PPIs). Therefore, recognition of protein-protein interactions is very important for understanding most life activities, such as DNA replication and transcription, protein synthesis and secretion, signal transduction and metabolism. Although high-throughput technology makes it possible to generate large-scale PPIs data, it requires expensive cost of both time and labor, and leave a risk of high false positive rate. In order to formulate a more ingenious solution, biology community is looking for computational methods to quickly and efficiently discover massive protein interaction data. In this paper, we propose a computational method for predicting PPIs based on a fresh idea of combining orthogonal locality preserving projections (OLPP) and rotation forest (RoF) models, using protein sequence information. Specifically, the protein sequence is first converted into position-specific scoring matrices (PSSMs) containing protein evolutionary information by using the Position-Specific Iterated Basic Local Alignment Search Tool (PSI-BLAST). Then we characterize a protein as a fixed length feature vector by applying OLPP to PSSMs. Finally, we train an RoF classifier for the purpose of identifying non-interacting and interacting protein pairs. The proposed method yielded a significantly better results than existing methods, with 90.07% and 96.09% prediction accuracy on Yeast and Human datasets. Our experiment show the proposed method can serve as a useful tool to accelerate the process of solving key problems in proteomics.

Gossypium hirsutum contributes the most production of cotton fibre, but G. barbadense is valued for its better comprehensive resistance and superior fibre properties. However, the allotetraploid genome of G. barbadense has not been comprehensively analysed. Here we present a high-quality assembly of the 2.57 gigabase genome of G. barbadense, including 80,876 protein-coding genes. The double-sized genome of the A (or At) (1.50 Gb) against D (or Dt) (853 Mb) primarily resulted from the expansion of Gypsy elements, including Peabody and Retrosat2 subclades in the Del clade, and the Athila subclade in the Athila/Tat clade. Substantial gene expansion and contraction were observed and rich homoeologous gene pairs with biased expression patterns were identified, suggesting abundant gene sub-functionalization occurred by allopolyploidization. More specifically, the CesA gene family has adapted differentially temporal expression patterns, suggesting an integrated regulatory mechanism of CesA genes from At and Dt subgenomes for the primary and secondary cellulose biosynthesis of cotton fibre in a "relay race"-like fashion. We anticipate that the G. barbadense genome sequence will advance our understanding the mechanism of genome polyploidization and underpin genome-wide comparison research in this genus.

Natrinema sp. J7-2 is an extreme haloarchaeon capable of growing on synthetic media without amino acid supplements. Here we report the complete genome sequence of Natrinema sp. J7-2 which is composed of a 3,697,626-bp chromosome and a 95,989-bp plasmid pJ7-I. This is the first complete genome sequence of a member of the genus Natrinema. We demonstrate that Natrinema sp. J7-2 can use gluconate, glycerol, or acetate as the sole carbon source and that its genome encodes complete metabolic pathways for assimilating these substrates. The biosynthetic pathways for all 20 amino acids have been reconstructed, and we discuss a possible evolutionary relationship between the haloarchaeal arginine synthetic pathway and the bacterial lysine synthetic pathway. The genome harbors the genes for assimilation of ammonium and nitrite, but not nitrate, and has a denitrification pathway to reduce nitrite to N(2)O. Comparative genomic analysis suggests that most sequenced haloarchaea employ the TrkAH system, rather than the Kdp system, to actively uptake potassium. The genomic analysis also reveals that one of the three CRISPR loci in the Natrinema sp. J7-2 chromosome is located in an integrative genetic element and is probably propagated via horizontal gene transfer (HGT). Finally, our phylogenetic analysis of haloarchaeal genomes provides clues about evolutionary relationships of haloarchaea.

Upon assembling the first Gossypium herbaceum (A1) genome and substantially improving the existing Gossypium arboreum (A2) and Gossypium hirsutum ((AD)1) genomes, we showed that all existing A-genomes may have originated from a common ancestor, referred to here as A0, which was more phylogenetically related to A1 than A2. Further, allotetraploid formation was shown to have preceded the speciation of A1 and A2. Both A-genomes evolved independently, with no ancestor-progeny relationship. Gaussian probability density function analysis indicates that several long-terminal-repeat bursts that occurred from 5.7 million years ago to less than 0.61 million years ago contributed compellingly to A-genome size expansion, speciation and evolution. Abundant species-specific structural variations in genic regions changed the expression of many important genes, which may have led to fiber cell improvement in (AD)1. Our findings resolve existing controversial concepts surrounding A-genome origins and provide valuable genomic resources for cotton genetic improvement.

Casparian strip membrane domain protein-like (CASPL) genes are key genes for the formation and regulation of the Casparian strip and play an important role in plant abiotic stress. However, little research has focused on the members, characteristics, and biological functions of the patchouli PatCASPL gene family. In this study, 156 PatCASPL genes were identified at the whole-genome level. Subcellular localization predicted that 75.6% of PatCASPL proteins reside on the cell membrane. A phylogenetic analysis categorized PatCASPL genes into five subclusters alongside Arabidopsis CASPL genes. In a cis-acting element analysis, a total of 16 different cis-elements were identified, among which the photo-responsive element was the most common in the CASPL gene family. A transcriptome analysis showed that p-hydroxybenzoic acid, an allelopathic autotoxic substance, affected the expression pattern of PatCASPLs, including a total of 27 upregulated genes and 30 down-regulated genes, suggesting that these PatCASPLs may play an important role in the regulation of patchouli continuous cropping obstacles by affecting the formation and integrity of Casparian strip bands. These results provided a theoretical basis for exploring and verifying the function of the patchouli PatCASPL gene family and its role in continuous cropping obstacles.

Reversible lysine acetylation is one of the most important protein posttranslational modifications that plays essential roles in both prokaryotes and eukaryotes. However, only a few lysine deacetylases (KDACs) have been identified in prokaryotes, perhaps in part due to their limited sequence homology. Herein, we developed a 'clip-chip' strategy to enable unbiased, activity-based discovery of novel KDACs in the Escherichia coli proteome. In-depth biochemical characterization confirmed that YcgC is a serine hydrolase involving Ser200 as the catalytic nucleophile for lysine deacetylation and does not use NAD(+) or Zn(2+) like other established KDACs. Further, in vivo characterization demonstrated that YcgC regulates transcription by catalyzing deacetylation of Lys52 and Lys62 of a transcriptional repressor RutR. Importantly, YcgC targets a distinct set of substrates from the only known E. coli KDAC CobB. Analysis of YcgC's bacterial homologs confirmed that they also exhibit KDAC activity. YcgC thus represents a novel family of prokaryotic KDACs.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 is closely related to the more lethal but less transmissible coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction and viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on coronavirus proliferation, including Tom70, a mitochondrial chaperone protein that interacts with both SARS-CoV-1 and SARS-CoV-2 ORF9b, an interaction we structurally characterized using cryo-electron microscopy. Combining genetically validated host factors with both COVID-19 patient genetic data and medical billing records identified molecular mechanisms and potential drug treatments that merit further molecular and clinical study.

Elucidating the role of secreted frizzled-related protein 5 (SFRP5) in metabolism and obesity has been complicated by contradictory findings when knockout mice were used to determine metabolic phenotypes. By overexpressing SFRP5 in obese, prediabetic mice we consistently observed elevated hyperglycemia and glucose intolerance, supporting SFRP5 as a negative regulator of glucose metabolism. Accordingly, Sfrp5 mRNA expression analysis of both epididymal and subcutaneous adipose depots of mice indicated a correlation with obesity. Thus, we generated a monoclonal antibody (mAb) against SFRP5 to ascertain the effect of SFRP5 inhibition in vivo. Congruent with SFRP5 overexpression worsening blood glucose levels and glucose intolerance, anti-SFRP5 mAb therapy improved these phenotypes in vivo. The results from both the overexpression and mAb inhibition studies suggest a role for SFRP5 in glucose metabolism and pancreatic β-cell function and thus establish the use of an anti-SFRP5 mAb as a potential approach to treat type 2 diabetes.

After decades of development, protein and peptide drugs have now grown into a major drug class in the marketplace. Target identification and validation are crucial for the discovery of protein and peptide drugs, and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection. However, owing to the developmental history in the pharmaceutical industry, previous systematic exploration of the target spaces has mainly focused on traditional small-molecule drugs, while studies related to protein and peptide drugs are lacking. Here, we systematically explore the target spaces in the human genome specifically for protein and peptide drugs. Compared with other proteins, both successful protein and peptide drug targets have many special characteristics, and are also significantly different from those of small-molecule drugs in many aspects. Based on these features, we develop separate effective genome-wide target prediction models for protein and peptide drugs. Finally, a user-friendly web server, Predictor Of Protein and PeptIde drugs' therapeutic Targets (POPPIT) (http://poppit.ncpsb.org.cn/), is established, which provides not only target prediction specifically for protein and peptide drugs but also abundant annotations for predicted targets.

The kinase domain transfers phosphate from ATP to substrates. However, the Legionella effector SidJ adopts a kinase fold, yet catalyzes calmodulin (CaM)-dependent glutamylation to inactivate the SidE ubiquitin ligases. The structural and mechanistic basis in which the kinase domain catalyzes protein glutamylation is unknown. Here we present cryo-EM reconstructions of SidJ:CaM:SidE reaction intermediate complexes. We show that the kinase-like active site of SidJ adenylates an active-site Glu in SidE, resulting in the formation of a stable reaction intermediate complex. An insertion in the catalytic loop of the kinase domain positions the donor Glu near the acyl-adenylate for peptide bond formation. Our structural analysis led us to discover that the SidJ paralog SdjA is a glutamylase that differentially regulates the SidE ligases during Legionella infection. Our results uncover the structural and mechanistic basis in which the kinase fold catalyzes non-ribosomal amino acid ligations and reveal an unappreciated level of SidE-family regulation.

The members of the solute carrier (SLC) superfamily are vital membrane transporters in human cells. In the present study, we determine the expression and function of SLC5 family members in colorectal cancer (CRC). Expression analysis based on The Cancer Genome Atlas database and potential clinical relation analysis based on the Oncomine database indicate that SLC5A7 is downregulated and is predicted to correlate with the staging, and prognosis response of CRC. Additional results demonstrate that SLC5A7 is downregulated and correlates with good prognosis in patients with CRC. Ectopic expression of SLC5A7 either by overexpression, or uptake of choline efficiently inhibits CRC growth. Examination of the molecular mechanism reveals that SLC5A7 promotes p53 protein expression by directly interacting with and modifying p53 and disrupting the interaction between p53 and MDM2 in wild type p53 CRC cells. Our findings establish the clear correlation between SLC5A7 and tumour growth, providing a novel potential therapeutic target for CRC.

Meiosis entry during spermatogenesis requires reprogramming from mitotic to meiotic gene expression profiles. Transcriptional regulation has been extensively studied in meiosis entry, but gain of function for master transcription factors is insufficient to down-regulate mitotic genes. RNA helicase YTHDC2 and its partner MEIOC emerge as essential posttranscriptional regulators of meiotic entry. However, it is unclear what governs the RNA binding specificity of YTHDC2/MEIOC. Here, we identified RNA binding protein RBM46 as a component of the YTHDC2/MEIOC complex. Testis-specific Rbm46 knockout in mice causes infertility with defective mitotic-to-meiotic transition, phenocopying global Ythdc2 or Meioc knockout. RBM46 binds to 3' UTR of mitotic transcripts within 100 nucleotides from YTHDC2 U-rich motifs and targets these transcripts for degradation. Dysregulated RBM46 expression is associated with human male fertility disorders. These findings establish the RBM46/YTHDC2/MEIOC complex as the major posttranscriptional regulator responsible for down-regulating mitotic transcripts during meiosis entry in mammalian spermatogenesis, with implications for understanding meiosis-related fertility disorders.