New Data Resource to Advance Computer-Aided Drug Design
News Oct 10, 2008
Advances in information technology have shaped not only how we find or share information, but also how we make new medicines. A project just funded by the National Institutes of Health plans to take computer-aided drug design to the next level.
The University of Michigan will lead the effort to expand and enhance the molecular data needed to develop computer programs that more accurately predict potential drug candidates.
The data will be housed in a Web-based resource that the scientific community and others interested in this information can access for free. The resource is estimated to receive up to $5 million over five years from NIH's National Institute of General Medical Sciences (NIGMS).
"If we know the structure of a compound bound to a drug target, we should be able to tell how tightly the compound binds -- information critical to drug development. But, in practice, we are not able to do this well enough to contribute significantly to research progress," said NIGMS Director Jeremy M. Berg, Ph.D. "This resource has been established to make important structural and binding data available so researchers can tackle this problem."
Chemist Heather Carlson, Ph.D., of the University of Michigan's College of Pharmacy will oversee the creation and operation of the new Community Structure-Activity Resource, which will include detailed molecular information about proteins that bind small, drug-like molecules called ligands.
Most drugs work by latching onto proteins and altering a biological process. Researchers can use computational tools to study the structural and biophysical properties of a target protein and, from among tens of thousands of possible ligands, predict the relatively few that bind to the protein in a potentially useful way. These ligands may warrant further study as so-called lead compounds for drug discovery.
Computational tools can also indicate which compounds may interact with other proteins and cause unwanted side effects that could limit therapeutic use.
To build the resource, Carlson and her co-investigators at the University of Michigan will gather molecular data from existing resources and will work with others to generate new data.
A major activity will be the collection of unpublished data from pharmaceutical company scientists, who emphasized both the need for this information and a willingness to share it during public meetings leading to the establishment of the new resource.
The team also will draw from published literature as well as from Carlson's Binding MOAD (Mother of All Databases), which contains more than 11,000 protein-ligand complexes, and the PDBbind database, which was developed by co-investigator Shaomeng Wang, Ph.D., and provides experimentally measured binding data. The team will conduct experiments to address any gaps in the data and sponsor community-wide events to facilitate collaboration among scientists.
"The ability to screen compounds and accurately predict their binding properties using only computers would greatly impact the drug development process and many other aspects of biomedical research." said Berg.
Small imperfections in a wine glass or tiny creases in a contact lens can be tricky to make out, even in good light. In almost total darkness, images of such transparent features or objects are nearly impossible to decipher. But now, engineers at MIT have developed a technique that can reveal these “invisible” objects, in the dark.
For scientists wrestling with problems as diverse as containing superhot plasma in a fusion reactor, improving the accuracy of weather forecasts, or probing the unexplained dynamics of a distant galaxy, turbulence-spawning shear flow is a serious complicating factor. A new supercomputer-powered effort aims to make modelling shear far easier.
18th International Conference on Pharmaceutics & Novel Drug Delivery Systems
May 27 - May 28, 2019