Accelerating the search for the missing proteins in the human proteome.
Ontology highlight
ABSTRACT:
SUBMITTER: Baker MS
PROVIDER: S-EPMC5286205 | biostudies-literature | 2017 Jan
REPOSITORIES: biostudies-literature
Publications
Accelerating the search for the missing proteins in the human proteome.
Baker Mark S MS Ahn Seong Beom SB Mohamedali Abidali A Islam Mohammad T MT Cantor David D Verhaert Peter D PD Fanayan Susan S Sharma Samridhi S Nice Edouard C EC Connor Mark M Ranganathan Shoba S
Nature communications 20170124
Similar Datasets
Project description:BackgroundWith the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins.ResultsSince there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the "uncertain" category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases.ConclusionThe analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.
| S-EPMC5259966 | biostudies-literature
Project description:Based on the promising opioid pharmacological profile of the peptide, Tyr-Pro-Trp-Gly-NH(2) (Tyr-W-MIF), Zadina et al. [Zadina, J.E., Hackler, L., Ge, L.-J., Kastin, A.J., 1997. A potent and selective endogenous agonist for the mu-opiate receptor. Nature 386, 499-5502] synthesized and screened other Gly(4)-substituted peptides, culminating in the synthesis of Tyr-Pro-Trp-Phe-NH(2) (endomorphin-1), which displayed high affinity and selectivity for the mu-opioid receptor. The amidated peptide was then isolated from bovine brain frontal cortex, as was a related peptide, Tyr-Pro-Phe-Phe-NH(2) (endomorphin-2), that displayed similar high affinity and selectivity for the mu-opioid receptor. The biosynthesis of the endomorphins in the brain remains obscure, since the putative precursor proteins for the peptides have not been identified. With the completion of the human genome sequencing project, we hypothesized that we should uncover the biological precursors of the peptides using a bioinformatic approach to search the current human proteome for proteins that contained the endomorphin peptide sequences followed by Gly-Lys/Arg, the consensus sequence for peptide alpha-amidation and precursor cleavage. Twelve proteins were identified that contained the endomorphin-1 Tyr-Pro-Trp-Phe sequence, however none contained the Tyr-Pro-Trp-Phe-Gly sequence necessary for alpha-amidation. Twenty-two distinct proteins contained the endomorphin-2 tetrapeptide sequence, and two of those contained the sequence, Tyr-Pro-Phe-Phe-Gly, however, none contained the requisite peptide-Gly-Lys/Arg sequence. Western blot analysis using an endomorphin-2 antibody detected 4 prominent proteins in mouse brain, necessitating reinterpretation of previous immunocytolocalization studies in the brain. Screening of the current human proteome yielded no evidence for endomorphin precursor proteins based on accepted biochemical criteria.
| S-EPMC2144908 | biostudies-literature
Project description:We performed transcriptome sequencing to assess the genes turn on in the cell under epigenetically manipulation. MHCC97H, A549 and HCT116 were treated by GSK126, S2101 and TSA respectively. We detected the missing proteins in the cells under epigenetically manipulation.
2016-05-23 | GSE69420 | GEO
Project description:The vast landscape of RNA-protein interactions at the heart of post-transcriptional regulation remains largely unexplored. Indeed it is likely that, even in yeast, a substantial fraction of the regulatory RNA-binding proteins (RBPs) remain to be discovered. Systematic experimental methods can play a key role in discovering these RBPs--most of the known yeast RBPs lack RNA-binding domains that might enable this activity to be predicted. We describe here a proteome-wide approach to identify RNA-protein interactions based on in vitro binding of RNA samples to yeast protein microarrays that represent over 80% of the yeast proteome. We used this procedure to screen for novel RBPs and RNA-protein interactions. A complementary mass spectrometry technique also identified proteins that associate with yeast mRNAs. Both the protein microarray and mass spectrometry methods successfully identify previously annotated RBPs, suggesting that other proteins identified in these assays might be novel RBPs. Of 35 putative novel RBPs identified by either or both of these methods, 12, including 75% of the eight most highly-ranked candidates, reproducibly associated with specific cellular RNAs. Surprisingly, most of the 12 newly discovered RBPs were enzymes. Functional characteristics of the RNA targets of some of the novel RBPs suggest coordinated post-transcriptional regulation of subunits of protein complexes and a possible link between mRNA trafficking and vesicle transport. Our results suggest that many more RBPs still remain to be identified and provide a set of candidates for further investigation.
| S-EPMC2937035 | biostudies-literature
Project description:The Human Proteome Project (HPP) aims deciphering the complete map of the human proteome. In the past few years, significant efforts of the HPP teams have been dedicated to the experimental detection of the missing proteins, which lack reliable mass spectrometry evidence of their existence. In this endeavor, an in depth analysis of shotgun experiments might represent a valuable resource to select a biological matrix in design validation experiments. In this work, we used all the proteomic experiments from the NCI60 cell lines and applied an integrative approach based on the results obtained from Comet, Mascot, OMSSA, and X!Tandem. This workflow benefits from the complementarity of these search engines to increase the proteome coverage. Five missing proteins C-HPP guidelines compliant were identified, although further validation is needed. Moreover, 165 missing proteins were detected with only one unique peptide, and their functional analysis supported their participation in cellular pathways as was also proposed in other studies. Finally, we performed a combined analysis of the gene expression levels and the proteomic identifications from the common cell lines between the NCI60 and the CCLE project to suggest alternatives for further validation of missing protein observations.
| S-EPMC5737412 | biostudies-literature
Project description:BackgroundBiomedical researchers use alignments produced by BLAST (Basic Local Alignment Search Tool) to categorize their query sequences. Producing such alignments is an essential bioinformatics task that is well suited for the cloud. The cloud can perform many calculations quickly as well as store and access large volumes of data. Bioinformaticians can also use it to collaborate with other researchers, sharing their results, datasets and even their pipelines on a common platform.ResultsWe present ElasticBLAST, a cloud native application to perform BLAST alignments in the cloud. ElasticBLAST can handle anywhere from a few to many thousands of queries and run the searches on thousands of virtual CPUs (if desired), deleting resources when it is done. It uses cloud native tools for orchestration and can request discounted instances, lowering cloud costs for users. It is supported on Amazon Web Services and Google Cloud Platform. It can search BLAST databases that are user provided or from the National Center for Biotechnology Information.ConclusionWe show that ElasticBLAST is a useful application that can efficiently perform BLAST searches for the user in the cloud, demonstrating that with two examples. At the same time, it hides much of the complexity of working in the cloud, lowering the threshold to move work to the cloud.
| S-EPMC10040096 | biostudies-literature
Project description:ObjectiveTo report a unique surgical procedure that was utilized to locate a missing vibrator in the pelvis of a patient. Emergency room admissions and surgery secondary to the malfunctioning of devices intended for sexual stimulation are extremely common. Emergency room staff of hospitals in the United States usually are skilled in the detection and removal of these devices. Occasionally, surgical intervention is warranted if the device enters a cavity that cannot safely be explored in the emergency room setting. We report a case of a vibrator that was lost during sexual activity. A flat plate X-ray showed it to be in the abdominal cavity. Careful questioning of the patient revealed that the device had an unusually small diameter. Surgical intervention showed that the device ultimately ended up in the bladder without causing traumatic injury.MethodsWe created a narrated video to demonstrate the surgical procedure (Canadian Task Force Classification III).ResultsLaparoscopy and cystoscopy were used to visualize and successfully remove the device. The patient recovered uneventfully.ConclusionFollowing laparoscopic confirmation of the location of the device, it was removed via cystoscopy. This case demonstrates how background information, such as the size of the missing device in this case, can be critical to providing high quality patient care.
| S-EPMC7494772 | biostudies-literature
Project description: Not available
| S-EPMC6288998 | biostudies-literature
Project description:AutoDock4 is a widely used program for docking small molecules to macromolecular targets. It describes ligand-receptor interactions using a physics-inspired scoring function that has been proven useful in a variety of drug discovery projects. However, compared to more modern and recent software, AutoDock4 has longer execution times, limiting its applicability to large scale dockings. To address this problem, we describe an OpenCL implementation of AutoDock4, called AutoDock-GPU, that leverages the highly parallel architecture of GPU hardware to reduce docking runtime by up to 350-fold with respect to a single-threaded process. Moreover, we introduce the gradient-based local search method ADADELTA, as well as an improved version of the Solis-Wets random optimizer from AutoDock4. These efficient local search algorithms significantly reduce the number of calls to the scoring function that are needed to produce good results. The improvements reported here, both in terms of docking throughput and search efficiency, facilitate the use of the AutoDock4 scoring function in large scale virtual screening.
| S-EPMC8063785 | biostudies-literature
Project description:The calcium ion (Ca(2+)) is a ubiquitous second messenger that is crucial for the regulation of a wide variety of cellular processes. The diverse transient signals transduced by Ca(2+) are mediated by intracellular Ca(2+)-binding proteins, also known as Ca(2+) sensors. A key obstacle to studying many Ca(2+)-sensing proteins is the difficulty in identifying the numerous downstream target interactions that respond to Ca(2+)-induced conformational changes. Among a number of Ca(2+) sensors in the eukaryotic cell, calmodulin (CaM) is the most widespread and the best studied. Employing the mRNA display technique, we have scanned the human proteome for CaM-binding proteins and have identified and characterized a large number of both known and previously uncharacterized proteins that interact with CaM in a Ca(2+)-dependent manner. The interactions of several identified proteins with Ca(2+)/CaM were confirmed by using pull-down assays and coimmunoprecipitation. Many of the CaM-binding proteins identified belong to protein families such as the DEAD/H box proteins, ribosomal proteins, proteasome 26S subunits, and deubiquitinating enzymes, suggesting the possible involvement of Ca(2+)/CaM in different signaling pathways. The selection method described herein could be used to identify the binding partners of other calcium sensors on the proteome-wide scale.
| S-EPMC1087907 | biostudies-literature