Mathematical framework on molecular interactions
A new mathematical framework on molecular interactions will make it easier and more efficient for scientists to create new medications and other therapies for diseases such as cancer, HIV and autoimmune diseases, say reseachers.
The mathematical framework simulates the impacts of the key parameters that control interactions between molecules that have multiple binding sites, as is true for many medicines, the researchers said in a study, published in the journal Proceedings of the National Academy of Sciences (PNAS).
The researchers have planned to use this model to develop an online app which researchers can use to accelerate the development of new therapies for diseases.
“The significant advance with this study is that usually researchers use a trial-and-error experimental method in the laboratory for studying these kinds of molecular interactions, but here we developed a mathematical model where we know the parameters so we can make precise predictions using a computer,” said Indian-origin researcher and study senior author Casim Sarkar from University of Minnesota in the US.
Casim Sarkar”This computational model will make research much more efficient and could accelerate the production of new treatments for many kinds of diseases.” For those findings, the research team studied three main parameters of molecular interactions–binding power of each site, rigidity of the linkages between the sites, and the size of the linkage arrays.
They looked at these three parameters could be’dialled up’ or’dialled down’ to control how molecule chains with three or two binding sites interact with one another.
Their model predictions were then confirmed by the team .
Study lead author Wesley Errington”At a basic level, many ailments can be traced to a molecule not binding properly,”
“By understanding how we could manipulate these’dials’ that control molecular behavior, we’ve developed a new programming language which may be used to predict how molecules will bind,” Errington added.
The requirement for a mathematical framework to decipher this programming language is emphasized by the researchers’ finding that, even when the interacting receptor chains have only three binding sites each, there are a total of 78 unique binding configurations, most of which can’t be experimentally observed.
By dialling the parameters in this mathematical model, researchers can understand how these binding configurations are changed, and tune them for a broad range of medical and biological applications.
“We think we’ve hit on principles which are fundamental to all molecules, like proteins, DNA, and medications, and can be scaled up for more complex interactions,” said Errington.
“It’s really a molecular signature that we can use to research and to engineer molecular systems. The sky is the limit with this strategy,” Errington added.