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 scr
Contact: Robert Pini
Rensselaer Polytechnic Institute