Georgia Tech Develops Speedy Software Designed to Improve Drug Development


Contact: Jason Maderer
Nov 15, 2011 | Atlanta, GA


Computer Program Quickly Analyzes Molecular Interactions I
Binding of difloro-proflavine to a segment of DNA.

Creating new, improved pharmaceuticals is sometimes very
similar to cracking the code of a combination lock. If you have the wrong
numbers, the lock won’t open. Even worse, you don’t know if your numbers are
close to the actual code or way off the mark. The only solution is to simply
guess a new combination and try again.

Similarly, when a newly created drug doesn’t bind well to its
intended target, the drug won’t work. Scientists are then forced to go back to
the lab, often with very little indication about why the binding was weak. The
next step is to choose a different pharmaceutical “combination” and hope for
better results. Georgia Tech researchers have now generated a computer model
that could help change that blind process.

Symmetry-adapted perturbation theory (SAPT) allows
scientists to study interactions between molecules, such as those between a
drug and its target. In the past, computer algorithms that study these
noncovalent interactions have been very slow, limiting the types of molecules
that can be studied using accurate quantum mechanical methods. A research team
headed by Georgia Tech Professor of Chemistry David Sherrill has developed a
computer program that can study larger molecules (more than 200 atoms) faster
than any other program in existence.


Computer Program Quickly Analyzes Molecular Interactions II
Initial speedup of our SAPT intermolecular analysis code (2010)
due to density fitting techniques (blue curve), versus conventional code
(black curve) for pairs of molecules of increasing size; (b) Further
speedup of our latest code (2011, blue curve) versus our earlier code
(2010, red curve) for aromatic molecules of increasing size.

“Our fast energy component analysis program is designed to
improve our knowledge about why certain molecules are attracted to one another,“ explained Sherrill, who also has a joint appointment in the School of Computational Science and Engineering. “It can also show us how interactions between molecules
can be tuned by chemical modifications, such as replacing a hydrogen atom with
a fluorine atom. Such knowledge is key
to advancing rational drug design.”

The algorithms can also be used to improve the understanding
of crystal structures and energetics, as well as the 3D arrangement of biological
macromolecules. Sherrill’s team used the software to study the interactions between
DNA and proflavine; these interactions are typical of those found between DNA
and several anti-cancer drugs. The findings are published this month in the Journal of Chemical Physics.

Rather than selling the software, the Georgia Tech
researchers have decided to distribute their code free of charge as part of the
open-source computer program PSI4, developed
jointly by researchers at Georgia Tech, Virginia Tech, the University of
Georgia and Oak Ridge National Laboratory. It is expected to be available in early 2012.

“By giving away our source code, we hope it will be adopted
rapidly by researchers in pharmaceuticals, organic electronics and catalysis,
giving them the tools they need to design better products,” said Sherrill.

Sherrill’s team next plans to use the software to study the
noncovalent interactions involving indinavir, which is used to treat HIV

This project is supported
by the National Science Foundation (NSF) (Award No.
The content is solely the responsibility of the principal investigators and
does not necessarily represent the official views of the NSF.

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