Molecular Applications Group (MAG) and Monsanto Company announced today an agreement under which MAG will apply their proprietary technology to support Monsanto scientists in identifying, selecting, and prioritizing targets for agricultural and pharmaceutical applications.

The technology improves the prediction of gene and protein function and draws upon MAG's expertise in protein sequence and structure analysis.

"Determining the function of novel proteins continues to be one of the most difficult and time-consuming challenges we face. Yet it is an essential step in efficiently identifying, prioritizing, and selecting targets,'' says Dr. Paul Spence, Head of Biotechnology, within the Searle Division of Monsanto. "MAG's unusual depth of expertise, particularly in understanding the sequences and structures of proteins, makes them an ideal partner to help us surmount this challenge.''

In its work with Monsanto, MAG intends to employ three proprietary and complementary techniques that rely on Hidden Markov Models, protein threading, and phylogenetic analysis. The core technology is captured in three proprietary components, SHMMs, ATHOS, and BETE.

"In combination,'' says Paul Thomas, Ph.D., Executive Director of Research at MAG, ``these algorithms produce a discovery system that greatly increases the reach of remote homolog detection, as well as the ability to classify novel genes in the context of related sequences. In addition, this system is highly scaleable, and will enable Monsanto to rapidly process large amounts of data.''

Monsanto will be the first company to receive access to this technology with a goal of improving the effectiveness of their new gene discovery efforts. The partnership will deploy this system on both human and agricultural protein targets. The project will utilize MAG's methods for associating target genes with genes that perform similar functions even when there is minimal sequence similarity.

In addition, automated subfamily classification of target sequences will be demonstrated on a large-scale basis. This project addresses the fact that new approaches are urgently needed to maximize the value of genomics information.

Currently used methods fail to correctly identify the function of about 70% of known or newly discovered genes. Significant improvement in this methodology would speed the development of pharmaceuticals and other biologically useful products. MAG's expertise in using structural motifs and weak sequence clues for predicting function holds tremendous promise in this area.

"This unique approach,'' according to Thomas, ``goes well beyond comparing pairs of gene sequences to determine similarity in function. It is at this point,'' he says, ``that computational representations of molecular structure and of protein sequence families become particularly important, and where MAG's proprietary technology offers information beyond what is publicly or commercially attainable elsewhere.''

"This is the first in a series of Discovery Partnerships we will be undertaking,'' John Andrews, Executive Vice President and Chief Operating Officer at MAG explained. ``Our activities moving forward will not only continue in our traditional area of strength, protein visualization and modeling software, but will also reflect more of our unique and sophisticated competencies in protein function determination.''

Terms of the agreement were not disclosed.

Monsanto is a life sciences company, committed to finding solutions to the growing global needs for food and health by sharing common forms of science and technology among agriculture, nutrition and health. The company's 31,800 employees worldwide make and market high-value agricultural products, pharmaceuticals and food ingredients.

Molecular Applications Group Inc., located in Palo Alto, through its proprietary technology and expertise in the science of bioinformatics, enables pharmaceutical, biotechnology, and agricultural companies to better understand the role of proteins, and to therefore dramatically accelerate the identification, selection, and prioritization of drug targets.

MAG offers strong capabilities in elucidating gene function through software, transformed content
databases and partnerships, based upon its expertise in determining biochemical function and in cellular role analysis.

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