Drug2Gene

Drug2Gene is a free knowledge integrated data repository unifying a number of popular public resources to provide structured and organized information for identified and reported relations between genes/proteins and drugs/compounds. It allows user's interactive management by the ability to flag, comment and update relations, to import new drug-gene relations valuable for a specific project. Gene orthology and similarity information is matched to certain relationship entries assisting the prediction of new unreported drug-gene associations. You can go to the original source of the reported relation and explore for more facts, details and evidences. 

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New Roles Emerge For Non-Coding RNAs In Directing Embryonic Development

Scientists at the Broad Institute of MIT and Harvard have discovered that a mysterious class of large RNAs plays a central role in embryonic development, contrary to the dogma that proteins alone are the master regulators of this process. The research, published online August 28 in the journal Nature, reveals that these RNAs orchestrate the fate of embryonic stem (ES) cells by keeping them in their fledgling state or directing them along the path to cell specialization.

Broad scientists discovered several years ago that the human and mouse genomes encode thousands of unusual RNAs — termed large, intergenic non-coding RNAs (lincRNAs) —but their role was almost entirely unknown. By studying more than 100 lincRNAs in ES cells, the researchers now show that these RNAs help regulate development by physically interacting with proteins to coordinate gene expression and suggest that lincRNAs may play similar roles in most cells.

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Predicting liver transplant rejection

"The survival rate of liver transplant patients one year after treatment has improved from about 30% in the 1970s to more than 80%, with acute cellular rejection (ACR) the most common complication. It occurs in about 30% of cases and is generally arrested by drug treatment. However, if ACR occurs more than one year after the transplant, survival rates plummet.

The diagnosis of ACR requires a tissue biopsy, which is risky and uncomfortable for the patient. Even then, the interpretation of samples is difficult because the three clinical predictors are not always present.

These problems have prompted scientists in the US to look for a non-invasive alternative diagnosis for ACR and they turned to proteomics for the solution. Michael Charlton and colleagues from the Mayo Clinic and Foundation, Rochester, MN, and the University of Alabama at Birmingham decided to look at the serum proteome to see if any indicators of ACR were detectable.

Human serum contains many high-abundant proteins but, if they are removed before protein analysis, it is possible to detect low-abundant proteins which are transiently present in serum.

So, proteins secreted by cells or produced during cell destruction become visible. These include hormones and cytokines which are transported in serum to their destinations within the human body."

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Get SMRT: Pacific Biosciences Unveils Software Suite with Commercial Launch

April 29, 2011 | Third-generation sequencing company Pacific Biosciences (PacBio) began commercial shipment of its PacBio RS single-molecule sequencer this week. The instrument has been in beta testing at 11 institutions in North America and elsewhere for the past year. A notable success was the recent sequencing and identification of the cholera strain sweeping Haiti after the devastating 2010 earthquake.  

In a briefing with Bio-IT World, PacBio staffers Kevin Corcoran, Jon Sorenson and Edwin Hauw previewed the new suite of software tools on the RS sequencer. The SMRT (single molecule/real time) Analysis software suite features web-based software, an analysis pipeline framework, and algorithms for sequence alignment and de novo assembly.  

“We’re accelerating the development of software with the community,” says Kevin Corcoran. “A key feature of third-generation sequencing is that [the technology] doesn’t match up with what’s out there now. The key features of the PacBio system include fast time to result, high granularity, long read lengths, and new sequencing modes, including a circular mode and strobe sequencing.”  

PacBio’s single-molecule sequencing system offers significantly longer read lengths (1,000 bases on average) than its second-generation sequencing rivals, and faster run times. That said, the total sequence throughput per run is currently less than other commercial platforms. The single-read accuracy hovers in the 85-90% range.   

A revelatory feature of the SMRT software portal is that it captures kinetic information – the time for each registered nucleotide to be captured and incorporated into the growing DNA strand. “This is the first time you can watch DNA polymerase in real time, so that kinetic information will provide additional applications that have never been enabled before,” says Corcoran.   

The genome browser is called SMRT View. “This takes advantage of our longer reads and kinetic information,” says Sorenson. It includes strobe and consensus sequence modes, allowing the user tovisualize and interact with secondary analysis sequence data. PacBio says the interactive graphical representations of variants, quality values, and other metrics is the first data visualization application that can visualize kinetics and structure information unique to PacBio's SMRT technology.

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Published Study Validates New Protein Enrichment Approach For Low-Abundance Biomarker Detection

Hercules, CA — April 20, 2011 — University of Minnesota researchers found that Bio-Rad Laboratories' ProteoMiner protein enrichment kit enhanced identification of changes to low-abundance proteins and detection of post-translationally modified (PTM) proteins in human saliva. These findings offer promise for improving differential proteomic analyses and biomarker studies aimed at identifying disease-specific proteins and their PTM variants in various types of biological samples and fluids. The study was published in the Dec. 13, 2010, issue of the Journal of Proteome Research.

ven when highly sensitive mass spectrometers are used to analyze complex biological samples and bodily fluids, high-abundance proteins obscure the detection of lower-abundance proteins and their post-translational modifications," said Sri Bandhakavi, who led the study at the University of Minnesota in 2010. (Bandhakavi is now a senior scientist at Bio-Rad.) "These lower-abundance proteins and PTMs are often of most interest to researchers, given their association with specific disease or physiological states."

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Natural Language Processing to Play Major Role in Bringing Watson into Clinics

Under the terms of a recently inked agreement between IBM And Nuance, Watson's deep question answering, natural language processing, and machine learning capabilities will be linked with Nuance's speech recognition and Clinical Language Understanding, CLU, solutions to help physicians more accurately diagnose and treat their patients (BI02/11/2011).

In the months leading up to the first offerings from the collaboration, researchers at IBM and Nuance will work with collaborators at Columbia University and the University of Maryland, to figure out how Watson can best help in the clinical setting as well as to incorporate some healthcare-specific adaptations to the system, Jennifer Chu-Carroll, a member of the Watson Research Team, told BioInform.

"For the most part, the natural language analytics, the machine learning and the whole architecture are domain independent so we expect to be able plug these into the medical domain," she said. However, "there [will] be some ... research and development that is specific to the medical domain that we are going to have to bring in."

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Super-SILAC Technology for Quantitative Proteomics in Neoplasms

A group of investigators under Dr. Matthias Mann at Max Planck Institute of Biochemistry in Martinsried, Germany is working on an interesting quantitative proteomics technology that might offer a new way to analyze cell proteins in a range of disorders, such as cancer and autoimmune diseases. Called super-SILAC (stable-isotope labeling by amino acids in cell culture), the method generates thousands of isotopically labeled peptides in unique amounts to serve as "internal standards for mass spectrometry-based analysis."

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Research scientists develop powerful new methodology for stabilizing proteins

A team of scientists at The Scripps Research Institute has discovered a new way to stabilize proteins - the workhorse biological macromolecules found in all organisms. Proteins serve as the functional basis of many types of biologic drugs used to treat everything from arthritis, anemia, and diabetes to cancer.

As described in the February 4, 2011 edition of the journal Science, when the team attached a specific oligomeric array of sugars called a "glycan" to proteins having a defined structure, the proteins were up to 200 times more stable in the test tube. In the body, this stability may translate into longer half-lives for therapies, possibly lowering the overall cost of treatment for certain protein-based drugs and requiring patients to have fewer injections during a course of treatment.

The work may have major implications for the drug industry because there are a large number of protein-based drugs on the market, more in clinical trials, and many more under development worldwide. Nearly all of these protein-based drugs have glycans attached to them and are therefore called "glycoproteins". Glycoprotein-based drugs can be quite expensive to produce and usually need to be administered intravenously.

One of the challenges in producing these drugs has been increasing their stability, which generally extends their half-life in the bloodstream - issues that the new discovery appears to address directly.

"We've now provided engineering guidelines for glycoprotein stability," said Scripps Research Professor Jeffery W. Kelly, who is chair of the Department of Molecular and Experimental Medicine, Lita Annenberg Hazen Professor of Chemistry, and member of The Skaggs Institute for Chemical Biology at Scripps Research. Kelly led the study with Scripps Research Associate Professor Evan Powers and Staff Scientist Sarah R. Hanson, in collaboration with Research Associates Elizabeth K. Culyba, Joshua Price, and colleagues.

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Highly Sensitive & Specific Chromatin Immunoprecipitation (ChIP) Assay Kit from Porvair Filtration Group

orvair Filtration Group has developed a new technology that has particular relevance to the rapidly expanding Epigenetics market and will be unveiling it at the Epigenetics World Congress in Boston in April 2011. Using a new approach, based on a rigid porous polymer matrix rather than the traditional sepharose or magnetic beads, Porvair has developed a novel Chromatin ImmunoPrecipitation (ChIP) assay kit called Chromatrap™.

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DNAnexus Launches First Complete Cloud-Based Solution for Genomic Variation Identification

DNAnexus, Inc. announces the availability of a comprehensive set of new informatics tools that enable life science researchers to efficiently analyze and manage large-scale genomic variation datasets in a cloud-based workflow. DNAnexus will discuss results from a study using this solution at the 12th annual Advances in Genome Biology and Technology (AGBT) meeting in Marco Island, Florida. 
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A single blood drop could detect heart disease, cancer

A University of Victoria researcher hopes to change the nature of testing forheart disease, cancer and drug toxicity using a highly sensitive and fast machine that would only require a single drop of blood from a patient.

Called a mass spectrometer, this machine determines the weight of protein molecules in the blood, and would allow researchers to determine if key marker proteins related to heart disease or cancer are present. The mass spectrometer being used in this research is among the most sensitive spectrometers that are commercially available, and is currently the only one of its kind in Canada.

Dr. Christoph Borchers at the University of Victoria-Genome BC Proteomics Centre will use the Agilent ion funnel 6490 mass spectrometer to develop methodologies for early diagnostic tests. These tests will detect and measure biomarkers, which are proteins in a patient’s blood that can signal early and subtle health changes. Dr. Borchers hopes to apply the technology to develop inexpensive, fast, and reproducible biomarker tests for early diagnosis of cardiovascular disease (CVD), the leading cause of death in the Western hemisphere.

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Hope Offered For New Diagnostics Following Research Into Synthetic Antibodies

Antibodies are watchdogs of human health, continuously prowling the body and registering minute changes associated with infection or disease with astonishing acuity. They also serve as biochemical memory banks, faithfully recording information about pathogens they encounter and efficiently storing this data for later use. 

Stephen Albert Johnston, Neal Woodbury and their colleagues at the Biodesign Institute at Arizona State University have been exploring mechanisms of antibody activity, particularly the ability of these sentries to bind - with high affinity and specificity - to their protein targets. A more thorough understanding of the antibody universe may lead to a new generation of rapid, low-cost diagnostic tools and speed the delivery of new vaccines and therapeutics. 

Borrowing a script from nature, the group has been working to construct synthetic antibodies or synbodies, through a simple method developed in Johnston's Center for Innovations in Medicine. They have also examined the broad portrait of antibody activity revealed in a sample of blood, harnessing this information for the presymptomatic diagnosis of disease. These immunosignatures, as Johnston has named them, provide a dynamic report card on human health. 

In a pair of new papers, the group demonstrated a simple means of improving the binding affinity of synbodies, which are composed of 20 unit chains of amino acids, strung together in random order. They also used random peptide sequences spotted onto glass microarray slides to mine information concerning the active regions or epitopes of naturally occurring antibodies. These two projects recently appeared in the journals PloS ONE and Molecular and Cellular Proteomics, respectively. 

While antibodies have been in use for biomedical research for a long time, conventional techniques for producing them have been time consuming and expensive. Normally, antibodies used for research are produced in animals, which respond to a given injected protein by producing a protein-specific antibody, which may then be extracted. 

In earlier work, Johnston's group showed that high-affinity antibody mimics can be produced synthetically by simple means. Their technique turns the traditional production approach on its head. Rather than beginning with a given protein and trying to generate a corresponding antibody, the new method involves building a synthetic antibody first, later determining the protein it effectively binds with, by screening it against a library of potential protein mates. 

The first step in this process is to generate random strings of 20 amino acids. Roughly 10,000 such random peptides are then spotted onto a glass microarray slide. The protein one is seeking an antibody to is screened against this random sequence array and peptides with high binding affinity are identified. Two such peptides can be linked together to form a synbody, whose binding affinity is the product of each separate peptide. In this way, two weakly binding peptides join forces to form a high affinity unit, useful for investigations into the proteome, the vast domain of proteins essential to virtually all biological processes. 
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Scientists find the 'master switch' for key immune cells in inflammatory diseases

Scientists have identified a protein that acts as a "master switch" in certain white blood cells, determining whether they promote or inhibit inflammation. The study, published in the journal Nature Immunology, could help researchers look for new treatments for diseases such as rheumatoid arthritis that involve excessive inflammation.

Inflammatory responses are an important defence that the body uses against harmful stimuli such as infections or tissue damage, but in many conditions, excessive inflammation can itself harm the body. In rheumatoid arthritis, the joints become swollen and painful, but the reasons why this happens are not well understood.

Cells of the immune system called macrophages can either stimulate inflammation or suppress it by releasing chemical signals that alter the behaviour of other cells. The new study, by scientists from Imperial College London, has shown that a protein called IRF5 acts as a molecular switch that controls whether macrophages promote or inhibit inflammation.

The results suggest that blocking the production of IRF5 in macrophages might be an effective way of treating a wide range of autoimmune diseases, such as rheumatoid arthritis, inflammatory bowel disease, lupus, and multiple sclerosis. In addition, boosting IRF5 levels might help to treat people whose immune systems are compromised.

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Model predicts a drug's likelihood of causing birth defects

Bioinformatic analysis crunches data on drug effects on genes involved in fetal development

Boston, Mass. – When pregnant women need medications, there is often concern about possible effects on the fetus. Although some drugs are clearly recognized to cause birth defects (thalidomide being a notorious example), and others are generally recognized as safe, surprisingly little is known about most drugs' level of risk. Researchers in the Children's Hospital Boston Informatics Program (CHIP) have created a preclinical model for predicting a drug's teratogenicity (tendency to cause fetal malformations) based on characterizing the genes that it targets.

The model, described in the March 2011 issue of Reproductive Toxicology (published online in November), used bioinformatics and public databases to profile 619 drugs already assigned to a pregnancy risk class, and whose target genes or proteins are known. For each of the genes targeted, 7426 in all, CHIP investigators Asher Schachter, MD, MMSc, MS, and Isaac Kohane, MD, PhD, crunched databases to identify genes involved in biological processes related to fetal development, looking for telltale search terms like "genesis," "develop," "differentiate" or "growth."

The researchers found that drugs targeting a large proportion of genes associated with fetal development tended to be in the higher risk classes. Based on the developmental gene profile, they created a model that showed 79 percent accuracy in predicting whether a drug would be in Class A (safest) or Class X (known teratogen).

For example, the cholesterol-lowering drugs cerivastatin, lovastatin, pravastatin and fluvastatin are all in Class X. All of these drugs also targeted very high proportions of high-risk genes (98 to 100 percent). The anti-coagulant warfarin, also in Class X, had a proportion of 88 percent.

When Schachter and Kohane applied the model to drugs across all risk classes, the proportion of developmental genes targeted roughly matched the degree of known risk (see graph). However, the model needs further validation before Schachter is willing to share actual predictions for specific drugs. "We don't want to risk misleading pregnant women from taking necessary medicines," he says.

One difficulty in validating the model is that the "known" teratogenicity it's being tested against often isn't known. Between Class A and Class X are Classes B, C and D, with increasing amounts of risk, but the boundaries between them are based on minimal data. Teratogenic effects may be difficult to spot, since most drugs are taken relatively rarely in pregnancy, some may be taken along with other drugs, and any effects tend to be rare or too subtle to be noted in medical records. Moreover, data from animal testing doesn't necessarily apply to humans.

"A lot of drugs in the middle of the spectrum, and maybe even some in Class A, may cause subtle defects that we haven't detected," says Schachter. "We can't provide a yes/no answer, but we found a pattern that can predict which are riskier."

Given the degree of uncertainty, Schachter and Kohane believe their model may be of interest to drug developers and prescribing physicians, and might provide useful information to incorporate in drug labeling.

"We can now say to patients, 'This drug targets a ton of genes that are involved in developmental processes,'" says Schachter.

Or, conversely, if a young pregnant woman has a heart condition and needs to be treated, physicians may be reassured by a cardiac drug's profile, he adds. "Instead of saying, 'we don't know,' we can now say that the drug is more likely to be safe in pregnancy."

"We have here a prismatic example of the utility of a big-picture, macrobiological approach," says Kohane, director of CHIP. "By combining a comprehensive database of protein targets of drugs and a database of birth defects associated with drugs, we find a promising predictive model of drug risk for birth defects."

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The study was funded by a grant from the National Institute of General Medical Sciences.

Children's Hospital Boston is home to the world's largest research enterprise based at a pediatric medical center, where its discoveries have benefited both children and adults since 1869. More than 1,100 scientists, including nine members of the National Academy of Sciences, 12 members of the Institute of Medicine and 13 members of the Howard Hughes Medical Institute comprise Children's research community. Founded as a 20-bed hospital for children, Children's Hospital Boston today is a 392-bed comprehensive center for pediatric and adolescent health care grounded in the values of excellence in patient care and sensitivity to the complex needs and diversity of children and families. Children's also is the primary pediatric teaching affiliate of Harvard Medical School. For more information about research and clinical innovation at Boston Children's visit: Vector Blog.