ABSTRACT In the past, many benchmarking studies have been performed on protein-protein and protein-ligand docking however there is no study on peptide-ligand docking. In this study, we evaluated the performance of seven widely used docking methods (AutoDock, AutoDock Vina, DOCK 6, PLANTS, rDock, GEMDOCK and GOLD) on a dataset of 57 peptide-ligand complexes. Though these methods have been developed for docking ligands to proteins but we evaluate their ability to dock ligands to peptides. First, we compared TOP docking pose of these methods with original complex and achieved average RMSD from 4.74Å for AutoDock to 12.63Å for GEMDOCK. Next we evaluated BEST docking pose of these methods and achieved average RMSD from 3.82Å for AutoDock to 10.83Å for rDock. It has been observed that ranking of docking poses by these methods is not suitable for peptide-ligand docking as performance of their TOP pose is much inferior to their BEST pose. AutoDock clearly shows better performance compared to the other six docking methods based on their TOP docking poses. On the other hand, difference in performance of different docking methods (AutoDock, AutoDock Vina, PLANTS and DOCK 6) was marginal when evaluation was based on their BEST docking pose. Similar trend has been observed when performance is measured in terms of success rate at different cut-off values. In order to facilitate scientific community a web server PLDbench has been developed ( http://webs.iiitd.edu.in/raghava/pldbench/ ).
cis-Splicing between adjacent genes (cis-SAGe) is being recognized as one way to produce chimeric fusion RNAs. However, its detail mechanism is not clear. Recent study revealed induction of transcriptions downstream of genes (DoGs) under osmotic stress. Here, we investigated the influence of osmotic stress on cis-SAGe chimeric RNAs and their connection to DoGs. We found,the absence of induction of at least some cis-SAGe fusions and/or their corresponding DoGs at early time point(s). In fact, these DoGs and their cis-SAGe fusions are inversely correlated. This negative correlation was changed to positive at a later time point. These results suggest a direct competition between the two categories of transcripts when total pool of readthrough transcripts is limited at an early time point. At a later time point, DoGs and corresponding cis-SAGe fusions are both induced, indicating that total readthrough transcripts become more abundant. Finally, we observed overall enhancement of cis-SAGe chimeric RNAs in KCl-treated samples by RNA-Seq analysis.
Once believed to be unique features of neoplasia, chimeric RNAs are now being discovered in normal physiology. We speculated that some chimeric RNAs may be functional precursors of genes, and that forming chimeric RNA at the transcriptional level may be a ‘trial’ mechanism before the functional element is fixed into the genome. Supporting this idea, we identified a chimeric RNA, HNRNPA1L2-SUGT1 (H-S), whose sequence is highly similar to that of a ‘pseudogene’ MRPS31P5. Sequence analysis revealed that MRPS31P5 transcript is more similar to H-S chimeric RNA than its ‘parent’ gene, MRPS31. Evolutionarily, H-S precedes MRPS31P5, as it can be detected bioinformatically and experimentally in marmosets, which do not yet possess MRPS31P5 in their genome. Conversely, H-S is minimally expressed in humans, while instead, MRPS31P5 is abundantly expressed. Silencing H-S in marmoset cells resulted in similar phenotype as silencing MRPS31P5 in human cells. In addition, whole transcriptome analysis and candidate downstream target validation revealed common signalling pathways shared by the two transcripts. Interestingly, H-S failed to rescue the phenotype caused by silencing MPRS31P5 in human and rhesus cells, whereas MRPS31P5 can at least partially rescue the phenotype caused by silencing H-S in marmoset cells, suggesting that MRPS31P5 may have further evolved into a distinct entity. Thus, multiple lines of evidence support that MRPS31P5 is not truly a pseudogene of MRPS31, but a likely functional descendent of H-S chimera. Instead being a gene fusion product, H-S is a product of cis-splicing between adjacent genes, while MRPS31P5 is likely produced by genome rearrangement.
Abstract The conventional understanding that chimeric RNAs are unique to carcinoma and are the products of chromosomal rearrangement is being challenged. However, experimental evidence supporting the function of chimeric RNAs in normal physiology is scarce. We decided to focus on one particular chimeric RNA, CTNNBIP1-CLSTN1 . We examined its expression in various tissues and cell types and compared it quantitatively among cancer and noncancer cells. We further investigated its role in a panel of noncancer cells and investigated the functional mechanism. We found that this fusion transcript is expressed in almost all tissues and a wide range of cell types, including fibroblasts, epithelial cells, stem cells, vascular endothelial cells, and hepatocytes. In addition, the CTNNBIP1-CLSTN1 expression level in noncancerous cell lines was not evidently different from that in cancer cell lines. Furthermore, in at least three cell types, silencing CTNNBIP1-CLSTN1 significantly reduced the cell proliferation rate by inducing G2/M arrest and apoptosis. Importantly, rescue experiments confirmed that cell cycle arrest was restored by exogenous expression of the chimera but not the wild-type parental gene. Further evidence is provided that CTNNBIP1-CLSTN1 regulates cell proliferation through SERPINE2 . Thus , CTNNBIP1-CLSTN1 is an example of a new class of fusion RNAs, dubbed “housekeeping chimeric RNAs”.
Abstract Gene fusions and their chimeric products are commonly linked with cancer. However, recent studies have found chimeric transcripts in non-cancer tissues and cell lines. Large-scale efforts to annotate structural variations have identified gene fusions capable of generating chimeric transcripts even in normal tissues. In this study, we present a bottom-up approach targeting population-specific chimeric RNAs, identifying 58 such instances in the GTEx cohort, including notable cases such as SUZ12P1–CRLF3, TFG–ADGRG7 and TRPM4–PPFIA3, which possess distinct patterns across different ancestry groups. We provide direct evidence for an additional 29 polymorphic chimeric RNAs with associated structural variants, revealing 13 novel rare structural variants. Additionally, we utilize the All of Us dataset and a large cohort of clinical samples to characterize the association of the SUZ12P1–CRLF3-causing variant with patient phenotypes. Our study showcases SUZ12P1–CRLF3 as a representative example, illustrating the identification of elusive structural variants by focusing on those producing population-specific fusion transcripts.
CancerPPD(http://crdd.osdd.net/raghava/cancerppd/) is a repository of experimentally verified anticancer peptides (ACPs) and anticancer proteins.Data were manually collected from published research articles, patents and from other databases.The current release of CancerPPD consists of 3491 ACP and 121 anticancer protein entries.Each entry provides comprehensive information related to a peptide like its source of origin, nature of the peptide, anticancer activity, N-and C-terminal modifications, conformation, etc.Additionally, Can-cerPPD provides the information of around 249 types of cancer cell lines and 16 different assays used for testing the ACPs.In addition to natural peptides, CancerPPD contains peptides having non-natural, chemically modified residues and D-amino acids.Besides this primary information, CancerPPD stores predicted tertiary structures as well as peptide sequences in SMILES format.Tertiary structures of peptides were predicted using the state-of-art method, PEPstr and secondary structural states were assigned using DSSP.In order to assist users, a number of web-based tools have been integrated, these include keyword search, data browsing, sequence and structural similarity search.We believe that CancerPPD will be very useful in designing peptide-based anticancer therapeutics.
Abstract DNA double-stranded breaks (DSBs) trigger human genome instability, therefore identifying what factors contribute to DSB induction is critical for our understanding of human disease etiology. Using an unbiased, genome-wide approach, we found that genomic regions with the ability to form highly stable DNA secondary structures are enriched for endogenous DSBs in human cells. Human genomic regions predicted to form non-B-form DNA induced gross chromosomal rearrangements in yeast and displayed high indel frequency in human genomes. The extent of instability in both analyses is in concordance with the structure forming ability of these regions. We also observed an enrichment of DNA secondary structure-prone sites overlapping transcription start sites (TSSs) and CCCTC-binding factor (CTCF) binding sites, and uncovered an increase in DSBs at highly stable DNA secondary structure regions, in response to etoposide, an inhibitor of topoisomerase II (TOP2) re-ligation activity. Importantly, we found that TOP2 deficiency in both yeast and human leads to a significant reduction in DSBs at structure-prone loci, and that sites of TOP2 cleavage have a greater ability to form highly stable DNA secondary structures. This study reveals a direct role for TOP2 in generating secondary structure-mediated DNA fragility, advancing our understanding of mechanisms underlying human genome instability.
ParaPep is a repository of antiparasitic peptides, which provides comprehensive information related to experimentally validated antiparasitic peptide sequences and their structures. The data were collected and compiled from published research papers, patents and from various databases. The current release of ParaPep holds 863 entries among which 519 are unique peptides. In addition to peptides having natural amino acids, ParaPep also consists of peptides having d -amino acids and chemically modified residues. In ParaPep, most of the peptides have been evaluated for growth inhibition of various species of Plasmodium , Leishmania and Trypanosoma . We have provided comprehensive information about these peptides that include peptide sequence, chemical modifications, stereochemistry, antiparasitic activity, origin, nature of peptide, assay types, type of parasite, mode of action and hemolytic activity. Structures of peptides consisting of natural, as well as modified amino acids have been determined using state-of-the-art software, PEPstr. To facilitate users, various user-friendly web tools, for data fetching, analysis and browsing, have been integrated. We hope that ParaPep will be advantageous in designing therapeutic peptides against parasitic diseases. Database URL:http://crdd.osdd.net/raghava/parapep/
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