Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

New Software Developed at Rensselaer Predicts Promising Ingredients for New Drugs

05.04.2004


The DDASSL software can quickly screen large databases, accurately predicting the molecules that show potential for future medicines.


Program speeds drug discovery

Researchers at Rensselaer Polytechnic Institute today announced the release of a software program capable of quickly identifying molecules that show promise for future medicines. The software program enables drug makers to comb through enormous databases of potential molecules and identify the ones that have sound medicinal properties.

Rensselaer researchers with skills in computer science, chemistry, and math allied to create the software program. Chemistry Professor Curt Breneman, Mathematics Associate Professor Kristin Bennett, and Decision Sciences and Engineering Systems Associate Professor Mark Embrechts collaborated in the Drug Discovery and Semi-Supervised Learning project (DDASSL, pronounced “dazzle”), supported by a $1.2 million Knowledge and Distributed Intelligence Award from the National Science Foundation.



“The trick with drug discovery is to have the drug molecule fit like a key in a lock, because shape affects its performance,” Embrechts said. The safety and effectiveness of medicines depend on the shape and chemistry of the molecule. To find the most likely molecules, the new software makes use of two shortcuts in chemistry and math that enable the computer to search a vast molecular database rapidly.

The first shortcut describes the molecule, its shape and chemistry, in terms of numbers a computer can crunch rapidly. “Dr. Breneman has a technique to calculate electronic properties on the surface of a molecule very quickly,” Embrechts said. “It produces a description—basically a set of numbers—that the computer can use easily.”

Then, the second shortcut identifies which molecules have the right chemistry for a specific therapy. Using advanced pattern-recognition techniques known as kernel methods, the software analyzes a small sample database to identify molecules with the right chemical features. Once the key features are identified, the software can quickly screen large databases, accurately predicting the molecules that show potential.

“Conventional techniques are not truly predictive and don’t work,” Bennett said. “So we borrowed pattern recognition techniques already used in the pharmaceutical industry and added algorithms based on support vector machines. That gives us a technique to predict which molecules are promising.”

Rensselaer researchers noted that predictive modeling is one of a new breed of drug discovery methods that marks a shift in industry practice—a shift away from cell-based assays performed in the lab toward math-based models calculated on the computer.

“Our program allows researchers to ‘crash test’ lots of molecules quickly and inexpensively,” Breneman said. “That prevents a lot of false starts. The ultimate pay-off of this methodology may be that it can support the rapid invention of new drugs when diseases develop quickly and threaten society.”

As drug makers increasingly target complex, chronic illness, drug development becomes far more costly and time consuming. Meanwhile, in the search for new drugs, 99.9 percent of compounds tested ultimately fail. Accordingly, drug makers want to be able to predict more accurately which compounds will produce the next blockbuster drug.

The Rensselaer research team will continue work to improve drug discovery methods, which will be carried out in the new Rensselaer Center for Biotechnology and Interdisciplinary Studies, a state-of-the-art facility scheduled to open in September 2004.

About Rensselaer

Rensselaer Polytechnic Institute, founded in 1824, is the nation’s oldest technological university. The school offers degrees in engineering, the sciences, information technology, architecture, management, and the humanities and social sciences. Institute programs serve undergraduates, graduate students, and working professionals around the world. Rensselaer faculty are known for pre-eminence in research conducted in a wide range of research centers that are characterized by strong industry partnerships. The Institute is especially well known for its success in the transfer of technology from the laboratory to the marketplace so that new discoveries and inventions benefit human life, protect the environment, and strengthen economic development.

Robert Pini | Rensselaer News
Further information:
http://www.rpi.edu/web/News/press_releases/2004/ddassl.htm

More articles from Information Technology:

nachricht Japanese researchers develop ultrathin, highly elastic skin display
19.02.2018 | University of Tokyo

nachricht Why bees soared and slime flopped as inspirations for systems engineering
19.02.2018 | Georgia Institute of Technology

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: In best circles: First integrated circuit from self-assembled polymer

For the first time, a team of researchers at the Max-Planck Institute (MPI) for Polymer Research in Mainz, Germany, has succeeded in making an integrated circuit (IC) from just a monolayer of a semiconducting polymer via a bottom-up, self-assembly approach.

In the self-assembly process, the semiconducting polymer arranges itself into an ordered monolayer in a transistor. The transistors are binary switches used...

Im Focus: Demonstration of a single molecule piezoelectric effect

Breakthrough provides a new concept of the design of molecular motors, sensors and electricity generators at nanoscale

Researchers from the Institute of Organic Chemistry and Biochemistry of the CAS (IOCB Prague), Institute of Physics of the CAS (IP CAS) and Palacký University...

Im Focus: Hybrid optics bring color imaging using ultrathin metalenses into focus

For photographers and scientists, lenses are lifesavers. They reflect and refract light, making possible the imaging systems that drive discovery through the microscope and preserve history through cameras.

But today's glass-based lenses are bulky and resist miniaturization. Next-generation technologies, such as ultrathin cameras or tiny microscopes, require...

Im Focus: Stem cell divisions in the adult brain seen for the first time

Scientists from the University of Zurich have succeeded for the first time in tracking individual stem cells and their neuronal progeny over months within the intact adult brain. This study sheds light on how new neurons are produced throughout life.

The generation of new nerve cells was once thought to taper off at the end of embryonic development. However, recent research has shown that the adult brain...

Im Focus: Interference as a new method for cooling quantum devices

Theoretical physicists propose to use negative interference to control heat flow in quantum devices. Study published in Physical Review Letters

Quantum computer parts are sensitive and need to be cooled to very low temperatures. Their tiny size makes them particularly susceptible to a temperature...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

2nd International Conference on High Temperature Shape Memory Alloys (HTSMAs)

15.02.2018 | Event News

Aachen DC Grid Summit 2018

13.02.2018 | Event News

How Global Climate Policy Can Learn from the Energy Transition

12.02.2018 | Event News

 
Latest News

Researchers invent tiny, light-powered wires to modulate brain's electrical signals

21.02.2018 | Life Sciences

The “Holy Grail” of peptide chemistry: Making peptide active agents available orally

21.02.2018 | Life Sciences

Atomic structure of ultrasound material not what anyone expected

21.02.2018 | Materials Sciences

VideoLinks
Science & Research
Overview of more VideoLinks >>>