NEW YORK (GenomeWeb) – DNAStar said this week that it has received a $150,000 Small Business Innovation Research grant from the National Institutes of Health's fast track award program to support the first phase of its efforts to improve and expand NovaFold, its cloud-based protein structure and function prediction software.
NovaFold is based on I-TASSER, a package that was developed in the laboratory of Yang Zhang, a professor in University of Michigan's department of computational medicine and bioinformatics and biochemistry department. I-TASSER — which according to a 2008 paper in BMC Bioinformatics is based on "profile-profile threading alignment and the iterative implementation of the Threading Assembly Refinement (TASSER) program" — has placed first in four incarnations of the Critical Assessment of Protein Structure Prediction experiments. DNAStar licensed the software from the university about two years ago and made it one of the components of Protean 3D, its suite of tools for exploring macromolecular structure, motion, and function.
Steve Darnell, a senior scientist at DNAStar and the principal investigator on the grant, said in a statement that the funds would be used to develop capabilities that would enable users to incorporate protein motion with structure prediction to improve the tool's accuracy.
During the six-month grant period, DNAStar researchers will work on rewriting some of the underlying code to make it easier to incorporate other improvements into the software that are planned for the second phase of the project, Tom Schwei, DNAStar's vice president and general manager, told BioInform this week. Those second phase changes, he said, include enabling the I-TASSER algorithm to spread its computations across multiple computers in the cloud allowing it to run more calculations and work faster.
The company believes that the improvements it is making to NovaFold should make the software more attractive to researchers in the pharmaceutical and biotechnology industry as well as academia who want a reliable and accurate solution for determining protein shape and function. It should also help DNAStar secure the interest of a new crop of customers who may not have been exposed to its solutions before, Schwei said. For example, clients that study proteins using mass spectrometry techniques might use NovaFold to screen virtual models of various proteins and select only those that they truly have to resolve using mass spec, he said. The company is already publicizing and educating customers about the product in posters and oral presentations at conferences as well as through its own website and in interactions with clients.
Proteins are a relatively new area for DNAStar which has catered historically to the DNA sequence analysis market with its Lasergene software suite. Current customers include the Indian Research Institute, Northwestern University, Wellcome Trust Sanger Institute, Babraham Institute, and ShrimpEx Biotech Services. However Schwei said that customers at these and other institutions and companies also see the value of the Novafold solution and some have expressed interest in using it internally.
In addition to the NovaFold grant, DNAStar is currently in the middle of the second phase of a separate grant that aims to take tools developed and successfully used in the research market and apply them to the clinical research market. DNAStar received the first round of funding for that particular project — also awarded under the NIH's fast-track program — in 2012. Like the latest grant, the company received $150,000 for the first phase of the project, and then received almost $500,000 from the NIH last year to support the first year of a second round of development.
Schwei told BioInform at the time the second grant was awarded that the company's pipeline would consist of two modules that are already available in DNAStar's SeqMan NGen and ArrayStar software packages. The former, which is a genome assembly and analysis program, forms the front end of the pipeline and will provide capabilities for verifying "putative variations" in sequence data. On the back end, ArrayStar, a tool for analyzing gene expression experiments and sequence variation across samples, will provide multiple sample comparison and analysis capabilities. He also said at the time that the company would put together a mechanism for pulling in information from external repositories.
Schwei said this week that the company's efforts so far have included developing workflows and tools that will allow researchers to analyze data from gene panels and sequenced data from families and larger cohorts. The company has also improved the accuracy of the sequence assembly algorithm that underlies Lasegene — it plans to make the updated algorithm available in the 12th version of the software which comes out next week.
DNAStar continues to work on its clinical analysis product and expects to receive additional funding to support the second year of the second phase of the project next month, Schwei said. The company has also submitted a separate grant application focused on developing tools and capabilities to support projects involving antibody engineering. That project has not yet been funded.