Corporate Banner
Satellite Banner
Informatics
Scientific Community
 
Become a Member | Sign in
Home>News>This Article
  News
Return

Computer Model Successfully Predicts Drug Side Effects

Published: Tuesday, June 12, 2012
Last Updated: Tuesday, June 12, 2012
Bookmark and Share
Research based on the similarity between a drugs chemical structures and those molecules known to cause side effects, according to a paper appearing online this week in the journal Nature.

The team, co-led by researchers in the UCSF School of Pharmacy, Novartis Institutes for BioMedical Research (NIBR) and SeaChange Pharmaceuticals, Inc. — a UCSF spinoff company launched by two of the paper’s authors — set out to test how well a computer model could help researchers eliminate risky drug prospects by identifying which ones were most likely to have adverse side effects.

Drugs frequently interact with more than one target, with hundreds of these targets linked to the side effects of clinically used therapeutics. Focusing on 656 drugs that are currently prescribed, with known safety records or side effects, the team was able to predict such undesirable targets — and thus potential side effects — half of the time.

That’s a significant leap forward from previous work, which has never tackled hundreds of compounds at once, according to Brian Shoichet, Ph.D., a UCSF professor of pharmaceutical chemistry who was the joint advisor on the project alongside Laszlo Urban, M.D., Ph.D., at Novartis.

As a result, it offers a possible new way for researchers to focus their efforts on developing the compounds that will be safest for patients, while potentially saving billions of dollars each year that goes into studying and developing drugs that fail.

“The biggest surprise was just how promiscuous the drugs were, with each drug hitting more than 10 percent of the targets, and how often the side-effect targets were unrelated to the previously known targets of the drugs,” said Shoichet, whose lab is renowned for its work in using computational simulations to identify new targets for known drugs. “That would have been hard to predict using standard scientific approaches.”

Adverse drug effects are the second most common reason, behind effectiveness, that potential drugs fail in clinical trials, according to the paper. The cost of developing an approvable drug is frequently cited at about $1 billion across 15 years, although recent estimates have ranged as high as $4 billion to $12 billion per drug, depending upon how many of these failures are included in the estimate.

“This basically gives you a computerized safety panel, so someday, when you’re deciding among hundreds of thousands of compounds to pursue, you could run a computer program to prioritize for those that may be safest,” said Michael Keiser, Ph.D., co-first author of the paper, who started working on the project as a doctoral student in Shoichet’s lab and co-founded SeaChange with Shoichet and John Irwin, Ph.D., also of UCSF, upon graduation.

It also offers the possibility for identifying possible new uses for medications that are already on the market, according to Peter Preusch, Ph.D., who oversees structure-based drug design grants at the National Institutes of Health’s National Institute of General Medical Sciences, which partly supported the study.

“By providing a way to identify the unintended targets of a drug, this advance will not only help streamline the drug development pipeline, but also will provide valuable guidance in efforts to repurpose existing drugs for new diseases and conditions,” Preusch said. “This work represents a notable contribution that is likely to find broad applications in the pharmaceutical arena.”

The project builds on UCSF’s legacy as a leader in developing computer-based approaches to efficiently screen millions of chemicals for those with the best potential for drug development. The UCSF School of Pharmacy was the first to develop computer-based molecular “docking” software, which both public and private researchers use to visualize how potential drugs might attach to target molecules to inhibit their function. It also builds upon UCSF’s commitment to industry collaborations that advance pharmaceutical science. Novartis has one of the strongest and most productive drug pipelines in the industry, with more than 130 projects in clinical development, according to the company.

The current project is based on technology UCSF developed, known as the “similarity ensemble approach” (SEA), which compares the shape of each drug to thousands of other compounds and uses that to predict which proteins they might both bind to — essentially, guilt by association. The technique was named among Wired magazine’s “Top Scientific Breakthroughs of 2009.”

In this project, the UCSF and SeaChange team ran a computer screen on 656 drugs that are currently in clinical use to predict which ones were most likely to bind to the 73 target proteins that appear on Novartis’ safety panel for testing drugs for side effects such as heart attacks.  Meanwhile, NIBR developed a statistical method of relating those targets to known side effects.

The computer model identified 1,241 possible side-effect targets for the 656 drugs, of which 348 were confirmed by Novartis’ proprietary database of drug interactions. Another 151 hits revealed potential side effects that had never been identified for these drugs, yet which Novartis confirmed through lab testing. Among those was a synthetic form of estrogen that has been known for years to cause stomach pain, with no known cause. The screen showed that it binds strongly to a target known as COX-1, which is the protein target of non-steroidal anti-inflammatory drugs, such as aspirin, which also can cause stomach pain, ulceration, and bleeding.

Keiser is co-first author on the Nature paper alongside Eugen Lounkine, Ph.D., a postdoctoral scholar in the Novartis Institutes for Biomedical Research whose postdoctoral advisors are Urban and Shoichet.

Additional authors include Steven Whitebread, Dmitri Mikhailov and Jeremy Jenkins, from the NIBR’s facilities in Cambridge, Mass.; Jacques Hamon, Eckhard Weber and Serge Côté, from NIBR in Basel, Switzerland; and Allison Doak, in the UCSF Department of Pharmaceutical Chemistry.

The project was supported by the National Institutes of Health and by the QB3 Rogers Family Foundation Bridging-the-Gap Award. The authors declare competing financial interests in the project: both Shoichet and Keiser are co-founders of SeaChange, which is developing the method to find new therapeutic uses of known drugs and address toxicology issues. Details are available in the online version of the article at www.nature.com/nature.


Further Information
Access to this exclusive content is for Technology Networks Premium members only.

Join Technology Networks Premium for free access to:

  • Exclusive articles
  • Presentations from international conferences
  • Over 2,500+ scientific posters on ePosters
  • More than 3,700+ scientific videos on LabTube
  • 35 community eNewsletters


Sign In



Forgotten your details? Click Here
If you are not a member you can join here

*Please note: By logging into TechnologyNetworks.com you agree to accept the use of cookies. To find out more about the cookies we use and how to delete them, see our privacy policy.

Related Content

Designing New Pain Relief Drugs
Researchers have identified the molecular interactions that allow capsaicin to activate the body’s primary receptor for sensing heat and pain, paving the way for the design of more selective and effective drugs to relieve pain.
Thursday, June 11, 2015
Fast-Mutating DNA Sequences Shape Early Development
What does it mean to be human? According to scientists the key lies, ultimately, in the billions of lines of genetic code that comprise the human genome.
Wednesday, November 13, 2013
Pan-Cancer Studies Find Common Patterns Shared by Different Tumor Types
Findings may open up new treatment options by extending therapies effective in one cancer type to others with a similar genomic profile.
Wednesday, October 02, 2013
New Center for Data Storage Research Established
Researchers in the Baskin School of Engineering at UC Santa Cruz are partnering with data storage industry to establish the Center for Research in Storage Systems (CRSS).
Thursday, March 28, 2013
New Network Being Built to Support Transfer of Big Data
The University of California, San Diego, is taking another leap forward in the name of enabling data-intensive science.
Thursday, March 21, 2013
Personalized Medicine From Genomics and Bioinformatics Highlighted at UCSF Genetics Symposium
Personalized medicine advances arising from genetic discoveries were the primary focus of wide-ranging presentations at the UCSF Institute for Human Genetics 2012 Symposium.
Thursday, November 15, 2012
National Data Center for Cancer Genome Research
In the wake of personalized medicine, scientists at the University of California, Santa Cruz, make progress in the management and analysis of large data sets.
Wednesday, May 02, 2012
Scientific News
Searching Big Data Faster
Theoretical analysis could expand applications of accelerated searching in biology, other fields.
Imaging Software Could Speed Breast Cancer Diagnosis
Technology could improve access to diagnostic services in developing countries.
Data Mining DNA For Polycystic Ovary Syndrome Genes
A new Northwestern Medicine genome-wide association study of PCOS – the first of its kind to focus on women of European ancestry – has provided important new insights into the underlying biology of the disorder.
Firefly Protein Enables Visualization of Roots in Soil
A new imaging tool from a team led by Carnegie’s José Dinneny allows researchers to study the dynamic growth of root systems in soil, and to uncover the molecular signaling pathways that control such growth.
UEA Research Could Help Build Computers From DNA
New research from the University of East Anglia could one day help build computers from DNA.
Viral Comparisons
ORNL team applies genomics expertise to analyze, map virus sequence database.
Preserving Fleeting Digital Information with DNA
A team has demonstrated that DNA they encapsulated can preserve information for at least 2,000 years, and they’re now working on a filing system to make it easier to navigate.
TGAC Leads Development to Diminish Threat to Vietnam’s Most Important Crop
Advanced bioinformatics capabilities for next-generation rice genomics in Vietnam to aid precision breeding.
Mass Extinctions Can Accelerate Evolution
A computer science team at The University of Texas at Austin has found that robots evolve more quickly and efficiently after a virtual mass extinction modeled after real-life disasters such as the one that killed off the dinosaurs.
Furthering Data Analysis of Next-gen Sequencing to Facilitate Research
Researchers at Cincinnati Children's Hospital Medical Center have developed a user-friendly, integrated platform for analyzing the transcriptomic and epigenomic "big data.
Scroll Up
Scroll Down
Skyscraper Banner

Skyscraper Banner
Go to LabTube
Go to eposters
 
Access to the latest scientific news
Exclusive articles
Upload and share your posters on ePosters
Latest presentations and webinars
View a library of 1,800+ scientific and medical posters
2,500+ scientific and medical posters
A library of 2,500+ scientific videos on LabTube
3,700+ scientific videos
Close
Premium CrownJOIN TECHNOLOGY NETWORKS PREMIUM FREE!