Cellular entropy

In equation (20) superscripts are not used because cells have no standard state. The value for Af5 calculated above is about half of that obtained from experimental measurements, which are taken to be correct. The reason for the failure of this calculation is uncertain. The experimental measurements of cellular entropy were of polymerized cellular fabric (i.e. proteins, phospholipids, nucleic acids, cell wall material, etc.), whereas the value found vith equation (19) made use of A G° values for small molecular weight molecules to obtain a general value for AjG eq that could be used to calculate a value for AfG n. Adding the free energy of polymerization would increase the value for A G and would lower the value for AfG 5 On the other hand, there was no need to do this when calculations were made using the methods described in Section 3.4.2. 

B. Testa, L. B. Kier, C.-K. Cheng, and J. Mayer, A cellular automata study of constraints (dissolvence) in a percolating many-particle systems. Entropy. 2001, 3, 28. 

Students often state the laws of thermodynamics this way. You cant win because you cant get any more energy out of a system than you put into it. You can t break even because no matter what you do, some of your energy will be lost as ambient heat. Lastly, you cant get out of the game because you depend on entropy-increasing processes, such as solar nuclear fusion or cellular respiration, to remain alive. 

Entropy is closely related to heat (enthalpy) and energy. If all the ATP available from catabolic processes were used for anabolism (chemical synthesis), up to ten times more cellular material could be produced. First investigations of this large outflow of entropy from growing cells have been made by Bormann [40] however, classical thermodynamics are hardly applicable to complex, nonequilibrium metabolic systems and must be extended [458]. 

The directionality of a cellular reaction at constant pressure and at a particular temperature (T) (i.e. whether AG is positive or negative) is determined by both the enthalpy change (AH) and the change in disorder of the system described by the change in entropy (AS) ... 

The entire drug discovery process, in particular at the cellular and animal level, has its own challenges [3] that contribute to the innovation deficif . It is thus imperative that computational tools deliver rapid and accurate models. At the molecular level, drug-receptor interactions continue to be too complex to provide failsafe in silico predictions [4] Entropy and the dielectric constant are but two examples of properties still under debate. The challenges of in silico drug discovery include the evaluation of multiple binding modes, accessible conformational... 

Long molecules that compose the cellular cytoskeleton can be treated from the standpoint of polymer mechanics where the response of the material to the application of a force is associated with changes in entropy (transition from disorder to more order). The cytoskeletal fibers are treated either as chains of segments that are completely free to move in three directions (freely joined chain model) or as flexible slender rods (worm-Hke chain model). The same approaches are appUed to ceUular components, such as the cytoskeleton, membrane, and nucleus. There is an important distinction in the models of relatively thin ceUular membranes. They are considered either as sheUs with a certain stress distribution across the thickness or as intrinsicaUy two-dimensional continua. In both cases, the mechanical parameters are spUt into two groups moduU characterizing the in-plane properties and those characterizing the out-of-plane bending and twist of the membrane. 

Boolean variables (p. 382) Car-ParrineUo algorithm (p. 377) cellular automaton (p. 381) characteristic frequency (p. 359) cooling protocol (p. 370) entropy (p. 353) force field (p. 345) free energy (p. 353) global minimum (p. 352) global optimization (p. 354)... 

Trinh CT, Wlaschin A, Srienc F (2009) Elementary mode analysis a useful metabolic pathway analysis tool for characterizing cellular metabolism. Appl Microbiol Biotechnol 81 813-826 Trinh CT, 14 J, Blanch H W, Clark DS (2011) Redesigning Escherichia coli metabolism for anaerobic production of isobutanol. Appl Environ Microbiol 77 4894-4904 Unrean P, Srienc F (2011) Metabolic networks evolve towards states of maximum entropy production. Metab Eng 13 666-673... 

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