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Biomatic Therapies - Biomatics.org

Biomatic Therapies

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The inner workings of the cell contain complex protein networks that are similar in some sense to computer networks. Proteins are no longer seen solely as fixed shape entities that interact in the lock and key mechanism.  There is the "healthy state" associated for the known medical conditions, as well as unhealthy states. This applies from the molecular to the populational parameters or dynamics. Therapy is a matter of closing the gap between these tywo stater. Every food we eat or drink, even the air we breathe changes our state. This means tailoring diet, lifestyle, medication toward this goal. 

The simplest example would have to be the telemeres. These structures appear to be a molecular counting mechanism. And apparently we could all benefit from keeping these numbers from decreasing. So a regimen that keeps these counters from counting down may affect our health. Amino acids and proteins in general serve a rich computational model, and are central to all medical conditions. Every food has a catalytic profile. Matching the optimal regimen to a known condition is in this light ...Biomatic. The goal may be to affect something similar to an electronic circuit...a collection of logic gates. We may want to change an "OR" gate to  an "AND" gate, for example.  Or, perhaps modify a faulty fibonacci sequence.

The protein images in the RCSB PDB files are a rich source of protein state information. Also we are growing in our understanding of protein function. Kinetic Hub behaviour seems a ripe target for therapeutic intervention.  A kinetic-hub is a finite state machine. Every rotation about a covalent bond represents a change of state. This is a very powerful computational architecture.  Even with low numbers of dynamically changing bond states there is rich potential for computation.  Biomatic therapies seek to control these processes. We need to develope some fomal way of describing or modeling the process.  A normal state vector vs actual, the difference being some sort of biomatic vector. Before and a after sets of ramachandran angles. But this tells only part of mthe story. The other part is the precise sequence of transformations, as modeled by finite state machine theory.










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