Since today is my birthday I find myself thinking about aging. I went back and listened to one of the first FIB podcasts. It features Leonard Guarente, who helped start Elixir pharmaceuticals, a company specifically targeting aging and metabolic disease. Here’s a link to the mp3.
Is aging just a disease? Metabolism and aging appear to be very tightly coupled. Even more interesting is how calorie restriction (starvation) has a direct impact on reproduction and lifespan. Dr. Leonard Guarente identified the SIR2 gene 6 or 7 years ago. Sirtuin enzymes (pictured above) are NAD-dependent and activated under special conditions like starvation. The biochemistry suggests that therapies could be possible. Knockout the SIRT1 gene in mice and the quality of life is greatly decreased. Starve any organism from yeast to chimps and they live longer by activating specific pathways. There’s 7 genes in mammals so there’s obviously much left to be understood. Trying to inhibit specific enzymes is pretty common, but targeting pathways and complex signaling in cellular metabolism can be tricky. The signals exist in nature. The technology developed in systems biology and metabolomics could really help answer some important questions in the next 10 years or so.
Avalon pharmaceuticals has a technology for generating pathway signatures, so rather than screening compounds against a single target they claim to be able to target entire pathways. They also have an advanced candidate for solid tumor cancers that’s an IMPDH inhibitor. IMPDH is another NAD-dependent enzyme that I have done a small amount of work on.
A fundamental process of life is the selective and efficient catalysis of chemical reactions by enzymes. Enzymes are usually proteins (ribozymes are one exception), and when these catalysts are chained together they form pathways. Enzyme pathways can be loosely described by their inputs and outputs. An even better abstraction than pathways though is to think in terms of networks. Networks have hubs which are critical to the operation of the network. [Vidal Lab is doing great work in this area of cancer proteomics]
In biology, allosteric enzymes are typically the regulatory elements in a catalytic network. More importantly, interactions distant from the catalytic site can induce changes in activity. One of the first examples of regulated enzyme networks is a system of 5 enzymes in bacteria which catalyze the conversion of L-Threonine to L-Isoleucine. Threonine dehydratase, the first enzyme in the pathway, is specifically inhibited by the end product of the pathway. This is simple feedback-inhibition, where buildup of the end product regulates and slows down the entire pathway by modulating the first step. This simple model illustrates an important aspect of protein interaction. It’s not good enough to simply say that enzyme A “interacts with” enzyme B. We need models that can express things like feedback, messaging, and other more abstracted language about protein relationships.
Compared to genomics, the proteomics universe appears to be pretty messy. Proteins interact in networks with enormous complexity. The challenges for a reverse engineering approach are overwhelming. There is no high-throughput method for reliably characterizing protein functions. Systems Biology is applying simplistic network models, and the Gene Ontology Consortium is working to develop a language for cellular functions. Both of these efforts have much to gain from structural biology.
Further Reading:
Ligand binding and allostery can emerge simultaneously
Is allostery an intrinsic property of all dynamic proteins?
The changing landscape of protein allostery