Can Energy Direct Probability? Energy, Entropy, and the Boltzmann Distribution

The organizing principles that directed the probabilistic self-assembly of life are the State functions and their behavior under transformations of time, space, and energy. The main thrust of the first chapter was a detailed examination of the fidelity with which the macrostate of a System can be defined, even though the microstates are defined only on a purely probabilistic basis. The two most important State functions are Entropy and Energy, each related to the probability of a State. The state of maximum entropy, or maximum probability, is derived. Proteins are shown to be entropically unstable. The Boltzmann probability distribution relates the occupation of a state to its energy. The Gibbs energy is defined and used to show how living systems use energy to bias entropy (probability). Examples are given for the Gibbs energy changes for several biochemical reactions, including the enzyme “creatine kinase,” the tricarboxylic acid cycle, and glycolysis. The Maxwell–Boltzmann probability distribution of molecular speeds is viewed as a source of energy for catalysis as enzymes act as probability amplifiers for biochemical reactions.