PharmaDesign, a Tokyo-based drug discovery firm with a focus on bioinformatics, plans to jump into the commercial software market this fall with the launch of POODLE (prediction of order and disorder by machine learning), a software package for predicting unfolded regions in proteins.
A free version of the software, developed in collaboration with the Computational Biology Research Center at Japan’s National Institute of Advanced Industrial Science and Technology, was launched this summer at the CBRC website.
The company says the commercial version, which is expected to be of interest to pharmaceutical firms that do not want to submit their protein sequences to a public server, will be available in the fall.
PharmaDesign has a three-pronged business model built upon a suite of in-house bioinformatics software. The firm uses these tools to develop libraries of predicted peptides and small molecules, which it markets under the brands PharmaGPep and PharmaGChem, respectively. In addition, the company offers contract research services based on its bioinformatics expertise, and also maintains an in-house drug discovery effort.
The company serves as the Japanese distributor for Inpharmatica’s bioinformatics software products, but historically has not had much of an interest in selling its own software. At one time, PharmaDesign marketed a SNP annotation package called PharmaSNP, but now uses it solely for in-house projects, says Satoru Kanai, director, chief scientific officer, and head of R&D.
Nevertheless, the company thinks that there is strong demand among pharmaceutical firms for POODLE. Many proteins that contain unfolded regions are involved in gene transcription and DNA binding. However, it is nearly impossible to crystallize proteins with these regions, so it has been very difficult to study them.
According to PharmaDesign, accurately predicting these regions will enable scientists to design and synthesize proteins without disordered regions, making them easier to crystallize.
— Bernadette Toner
US Patent 7,096,167. System and method for molecular dynamic simulation. Inventors: Ruhong Zhou, Bruce Berne, Edward Harder, and Huafeng Xu. Assignee: International Business Machines. Issued: August 22, 2006. According to the abstract, this invention covers “a system and method for molecular dynamic simulation [which] includes a database for storing data pertaining to at least one biomolecular system, a memory device for storing instructions for performing at least one algorithm having an electrostatic interaction calculation function and a multiple time step function ... and a processor for processing the data by executing the instructions in order to propagate the biomolecular systems from a first set of coordinates to a second set of coordinates.”
US Patent 7,085,652. Methods for searching polynucleotide probe targets in databases. Inventors: Charles Scaf, Nicolas Peyret, Francisco De La Vega, Ryan Koehler, and Eugene Spier. Assignee: Applera. Issued: August 1, 2006. This invention provides “methods for determining the binding affinity of a probe to a target or targets in a polynucleotide composite using an automated system. Such methods determine relative binding sites based on thermodynamic principles...with appropriate computer software, such as BlastP.”
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