Systems Biology - Projects

Predicting Protein Function and Mechanisms

Finding out how proteins work - and what roles they play - is essential to understanding disease mechanisms. That information, in turn, can guide the development of new approaches to treating human diseases.

Over the last decade, scientists around the world have generated a treasure trove of data by sequencing the genomes of humans and other organisms. Exploiting that data, IGS scientists are developing and applying sophisticated statistical methods to understand how proteins work on the molecular level.

By using Bayesian statistical approaches that cast a broad net and allow genomic sequence data to speak for itself, IGS scientists are deciphering--in the light of available biochemical, structural and genetic information--life's own blueprints for encoding biological mechanisms. For example, this approach has shed new light on the mechanism of Ras-like GTPases - protein signaling pathway on-off switches that are associated with cancer and other human diseases.

More than a century ago, Gregor Mendel and other pioneer geneticists used statistical analysis of patterns of inherited traits to identify genetic mechanisms long before it was possible to characterize genes at the cellular and molecular levels. Similarly, IGS scientists and others are now breaking ground by using the statistical analysis of sequence patterns to characterize components of the cell's molecular machinery - in many cases well before those components can be characterized more directly.

More Information:

  • Andrew Neuwald Ph.D.
  • The CHAIN Program - A tool for characterizing protein functional divergence in atomic detail.
  • MAPGAPs - A tool for identification, classification and accurate alignment of up to a million or more protein sequences.

Principal Investigator: