Computational Biology and Chemistry
The tremendous innovation in computational sciences supported the genomics revolution and advances in combinatorial chemistry, but also fundamentally changed the way pharmaceutical researchers completed mundane, every day tasks.
"Twenty-five years ago, scientists had to document the results of many experiments manually, which, of course, significantly impeded the ability to generate a lot of drug leads," says Peter Coggins, Ph.D., president of PerkinElmer Life & Analytical Sciences (www.perkinelmer.com). "Documenting and evaluating the results of lab and drug discovery experiments" consumed significant time and money.
"The incorporation of the PC in daily life of drug discovery is now a fact of life," says David Edwards, director of computational biology at Accelrys (www.accelrys.com), a provider of computational science and informatics software.
According to Edwards, many of today's current computational methods trace their earliest roots back to the early 1980s. "Tools were just emerging" in the area of 3-D modeling, and "people were starting to develop algorithms for the analysis of protein and DNA sequences."
"We have a product called Accelrys GCG. It came out of the University of Wisconsin at Madison, and was the first set of algorithms for protein and DNA sequence analysis back in 1980," says Edwards. "Now the product has over 140 algorithms, things like BLAST and ClustalW. Things that people use on a daily basis."
Computational biology is now routinely used for analysis of protein pathways, 3-D protein modeling, virtual libraries, and in silico screening. Twenty-five years has resulted in the ability to discover leads "faster, better, and cheaper," he adds.
Advances in automation, LIMS, and informatics allow pharma to "interpret and act upon the results of lab activity much more rapidly," Dr. Coggins agrees.
As an example, Edwards explains that Biogen Idec (www.biogen.com) employed Accelrys' in silico screening software to identify a lead compound for a new cancer target, TGF kinase. The process took only about two months, significantly less time than it took another group that independently discovered the same lead through traditional methods.