Aug 10
24
The technological advances that led to the advent of target-based drug discovery in the 1990s enabled researchers to chemically target specific genes and molecules, thus allowing for the development of drugs that can be more precisely delivered. The drawback to this approach lies in the often time-consuming “hit-and-miss” process of matching the right drug with the right molecular target. Researchers at the University of Missouri-Kansas City (UMKC) School of Biological Sciences, working in collaboration with private industry partner Vassa Informatics, may be close to providing a solution.
Gerald Wyckoff, Ph.D., associate professor of Molecular Biology and Biochemistry, recently received a Small Business Technology Transfer Grant from the National Institutes of Health to continue his work with Vassa Informatics (formerly Bioinfomatica) in developing a data analysis software program to help researchers better utilize chemical information content for drug discovery.
“The problem with current methods used in target-based drug discovery is that the pharmaceutical companies are, at the same time, suffering from both too much information and too little information,” Wyckoff said. “Too much information in the sense that technology now allows pharmaceutical researchers to identify countless potentially relevant targets, each with a universe of potential chemical candidates. Too little information in the sense that even today’s cutting-edge chemical screening methods cannot narrow that field of candidates down to a manageable number.”
At present, Wyckoff noted, the process of taking a candidate chemical compound from a “hit” to a “lead” takes years and costs tens of millions of dollars. To overcome this, pharmaceutical researchers need a way to streamline this phase of development — a mathematically and biologically sound method for identifying and optimizing novel compounds and ranking these lead candidate chemical compounds and their relationships to promising biological targets.
The software being developed by Dr. Wyckoff and Vassa Informatics is intended to solve this problem through the implementation of an entirely novel approach to identifying novel compounds that existing methods are unable to find. The team’s focus is to develop a “cheminformatic” module that will analyze target-to-compound relationships and the trends in that data, which could vastly improve candidate identification and shorten the hits-to-leads cycle in the drug discovery process. Dr. Wyckoff and his colleagues at Vassa Informatics are also in the process of applying for the second phase of this grant.
