Binding of difloro-proflavine to a segment of DNA. Image: Georgia Institute of Technology.
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
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 laboratory,
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 Institute of Technology (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 non-covalent 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
“Our fast energy component analysis program is designed to improve our
knowledge about why certain molecules are attracted to one another,” explains 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 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,” says Sherrill.
Sherrill’s team next plans to use the software to study the non-covalent
interactions involving indinavir, which is used to treat HIV patients.