Monday, January 20, 2014

Systems-level Thinking Helps to Address Protein Folding

Deciphering protein folding is critical to a fundamental understanding of biology as proteins conduct most cellular operations, and since misfolded proteins are often causally implicated in disease.

The status of protein folding (describing proteins as folded into their final 3D shape) is that as of January 2014, the main resource, the Protein Data Bank, has 96,000 listed known protein structures. There has been much technological advance in determining the static and dynamic features of protein structures, including in X-ray crystallography, NMR (nuclear magnetic resonance spectroscopy), cryo-electron microscopy, small-angle X-ray scattering, and other spectroscopic techniques.

This sounds like good progress, however, taking the human example, only 24,000 of the Protein Data Bank's 96,000 listed proteins are human, and this is of an estimated total of 2 million human proteins. Further, all of the protein conformations have been determined empirically (e.g.; manually) rather than with prediction (e.g.; digitally). It was proposed that given the amino acid string, it should be possible to predict the 3D conformation of the protein as finally folded, but this has proved elusive. Both scientific and crowdsourced efforts are looking at the problem. Crowdsourced projects include games like, community projects like Protein Folding@Home, and prediction contests like CASP (Critical Assessment of Protein Structure Prediction), a community-wide, worldwide experiment for protein structure prediction, the next one taking place May – August 2014. All of these projects focus on the unitary folding of one target, such as TM019, as opposed to more universal system dynamics.

Complexity scientist Sandra D. Mitchell presented work at Stanford on January 15, 2014 suggesting that we need a plurality of conceptual representations and models (any model is only partial in some way), and that any complex problem should be addressed with an integrated multiplicity of approaches. Many (and possibly most) complex biological issues such as cancer and aging are now understood as deeply dynamic and systemic phenomena. Similarly, proteins do not fold in isolation, the local environment is highly involved with protein chaperones and other signaling processes (one example is the intricate behavior of toxic amyloid HSPs (heat shock proteins)).

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