Computational chemistry: A faster way to untangle intermolecular interactions

Jan 30, 2013
The MDM2 protein (gray) binds the p53 peptide (orange and magenta). Each end of p53 undergoes conformational changes during the simulations, yielding subpopulations with different binding energies. Credit: 2013 A*STAR Bioinformatics Institute

A powerful computational technique used by the pharmaceutical industry to expedite new drug development has just received a performance boost. Chandra Verma and his co-workers at the A*STAR Bioinformatics Institute in Singapore have developed a method for extracting greater information from the simulations that are used to predict how candidate drug molecules will interact with biomolecular targets. The technique could enable drug makers to create highly effective medicines for a broader range of individuals.

Pharmaceutical researchers currently process using a technique known as 'MM-PBSA' free-energy calculations. These calculations predict how tightly a will bind to its inside the body. In general, the more tightly a drug binds to its target, the more effective it will be. "MM-PBSA can be used to rapidly assess the relative binding propensities of a series of molecules to a protein to distil out a select few candidates that can then be tested experimentally," Verma explains. By cutting down on experimental work, companies can save time and money.

Since the MM-PBSA method was first developed in the late 1990s, computer processing power has increased significantly. Researchers can now run simulations that map drug–protein interactions over much longer timeframes. As simulation times have lengthened, the complexity of has become an increasingly important consideration. Proteins are inherently flexible structures with multiple possible conformations, each of which interacts differently with the drug molecule over time. Taking these differences into account provides more reliable results.

Verma and his co-workers' method for analyzing and reporting the results of MM-PBSA calculations, which they named MM-PBSA_segmentation, separately captures the free energies of binding for multiple protein conformations. MM-PBSA_segmentation is based on an algorithm that can extract the binding behavior of individual protein subpopulations from the overall free-energy calculations. For example, using their method on the well-characterized interaction between two proteins called p53 and MDM2, the researchers identified six distinct subpopulations of p53 conformations (see image). They also established each subpopulation's relative size and hence overall importance.

MM-PBSA_segmentation, which is freely available from the team, expands the range of protein conformations accessible for analysis, Verma says. This ability to examine multiple protein conformations could be particularly important for cancer drug development, for example, where protein targets can become mutated and so change their conformation. As these changes can differ among individuals, Verma and his team are currently investigating whether they can use their technique to develop drugs targeted to individual patients.

Explore further: Pterostilbene, a molecule similar to resveratrol, as a potential treatment for obesity

More information: Zhou, W., Motakis, E., Fuentes, G. & Verma, C. S. Macrostate identification from biomolecular simulations through time series analysis. Journal of Chemical Information and Modeling 52, 2319–2324 (2012). dx.doi.org/10.1021/ci300341v

add to favorites email to friend print save as pdf

Related Stories

Measuring protein movements with nanosecond resolution

Mar 15, 2010

Researchers at the Department of Chemistry at the Technische Universität München (TUM, Germany) have developed a method that allows the observation of local movements in proteins on a time scale of nanoseconds to microseconds. ...

Intrinsic changes in protein shape influence drug binding

Aug 19, 2009

Computational biologists at the University of Pittsburgh School of Medicine have shown that proteins have an intrinsic ability to change shape, and this is required for their biological activity. This shape-changing also ...

New computational technique can predict drug side effects

Dec 11, 2007

Early identification of adverse effects of drugs before they are tested in humans is crucial in developing new therapeutics, as unexpected effects account for a third of all drug failures during the development process.

Recommended for you

Why plants don't get sunburn

Oct 29, 2014

Plants rely on sunlight to make their food, but they also need protection from its harmful rays, just like humans do. Recently, scientists discovered a group of molecules in plants that shields them from ...

Viral switches share a shape

Oct 27, 2014

A hinge in the RNA genome of the virus that causes hepatitis C works like a switch that can be flipped to prevent it from replicating in infected cells. Scientists have discovered that this shape is shared by several other ...

'Sticky' ends start synthetic collagen growth

Oct 27, 2014

Rice University researchers have delivered a scientific one-two punch with a pair of papers that detail how synthetic collagen fibers self-assemble via their sticky ends.

Cell membranes self-assemble

Oct 27, 2014

A self-driven reaction can assemble phospholipid membranes like those that enclose cells, a team of chemists at the University of California, San Diego, reports in Angewandte Chemie.

Emergent behavior lets bubbles 'sense' environment

Oct 27, 2014

Tiny, soapy bubbles can reorganize their membranes to let material flow in and out in response to the surrounding environment, according to new work carried out in an international collaboration by biomedical ...

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.