| |
Name | Pathway Name /
Pathway No. | Accession
Type | Initial
Conc.
(uM) | Volume
(fL) | Buffered | Sum Total Of |
| 1 | AA | Shared_Object_
Synaptic_
Network
Pathway No. 70Network | 0 | 1000 | No | - | |
| | Arachidonic Acid. This messenger diffuses through membranes as well as cytosolically, has been suggested as a possible retrograde messenger at synapses. |
| 2 | AC1 | AC
Pathway No. 85 | Network | 0.02 | 1000 | No | - |
| | AC concentrations are tricky due to poor antibodies. I refer to an estimate from Jacobowitz, PhD Thesis, Mount Sinai School of Medicine around Pg 149 which estimates cyclase as 1/12600 of membrane protein. This gives a whole-cell conc of about 33 nM using assumptions of 2% of cell mass being membrane protein. Defer et al 2000 Am J Physiol Renal Physiol 279:F400-F416 in a good review put AC1 and AC8 (which has similar properties) as among the highly expressed form of brain cyclase. We therefore estimate its levels as a good fraction of the 33 nM, at 20 nM. |
| 3 | AC1-CaM | AC
Pathway No. 85 | Network | 0 | 1000 | No | - |
| | This state of AC1 is bound to Calmodulin and therefore activated. Gs stimulates it but betagamma inhibits. |
| 4 | AC1-Gs | AC
Pathway No. 85 | Network | 0 | 1000 | No | - |
| | This is the generic Gs-Stimulated state of AC1. Note that the enzyme is normally saturated, so all reactions involving AC1-Gs actually relate to the enzyme-substrate complex. |
| 5 | AC2 | AC
Pathway No. 85 | Network | 0.015 | 1000 | No | - |
| | AC concentrations are tricky due to poor antibodies. I refer to an estimate from Jacobowitz, PhD Thesis, Mount Sinai School of Medicine around Pg 149 which estimates cyclase as 1/12600 of membrane protein. This gives a whole-cell conc of about 33 nM using assumptions of 2% of cell mass being membrane protein. Defer et al 2000 Am J Physiol Renal Physiol 279:F400-F416 in a good review put AC2 among the highly expressed form of brain cyclase. We therefore estimate its levels as a good fraction of the 33 nM, at 15 nM. This actually adds up to a little more than 33, but it is well within error estimates. |
| 6 | AC2* | AC
Pathway No. 85 | Network | 0 | 1000 | No | - |
| | This is the phosphorylation-activated form of AC2. |
| 7 | AC2*-Gs | AC
Pathway No. 85 | Network | 0 | 1000 | No | - |
| | This is the form activated synergistically by phosphorylation as well as Gs binding. |
| 8 | AC2-Gs | AC
Pathway No. 85 | Network | 0 | 1000 | No | - |
| | This is the generic Gs-Stimulated form of AC2 |
| 9 | AMP | AC
Pathway No. 85 | Network | 10 | 0.0016667 | Yes | - |
| | AMP is a tightly regulated metabolite, so here we simply buffer it to its resting value. The value doesn't really matter to any of the calculations since it acts like a one-way sink. |
| 10 | APC | PLA2
Pathway No. 72 | Network | 30 | 1000 | Yes | - |
| | arachodonylphosphatidylcholine is the favoured substrate from Wijkander and Sundler, JBC 202 pp 873-880, 1991. Their assay used 30 uM substrate, which is what the kinetics in this model are based on. For the later model we should locate a more realistic value for APC. For now it is treated as a buffered metabolite. |
| 11 | ATP | AC
Pathway No. 85 | Network | 5000 | 1000 | Yes | - |
| | ATP is present in all cells between 2 and 10 mM. See Lehninger. |
| 12 | BetaGamma | Shared_Object_
Synaptic_
Network
Pathway No. 70Network | 0 | 1000 | No | - | |
| | The betagamma subunits of Gq. This is an approximation to the possible combinations of betagamma subunits. Here they are all treated as a single pool. |
| 13 | Blocked-rec-Gq | Gq
Pathway No. 74 | Network | 0 | 1000 | No | - |
| | This represents the blocked state of the receptor when bound to a competitive antagonist. Note that this is in the Gq bound form. Simulations had shown that with the available rates, the blocking was minimal if only the unbound receptor could bind the antagonist. |
| 14 | Ca | Shared_Object_
Synaptic_
Network
Pathway No. 70Network | 0.08 | 1000 | No | Ca_stim
Ca_intracell
| |
| | This calcium pool is treated as being buffered to a steady 0.08 uM, which is the resting level. |
| 15 | Ca-ext | CaRegulation
Pathway No. 86 | Network | 4000 | 100000 | Yes | - |
| | Extracell Ca conc = 4 mM Extracell vol assumed 100 X cell vol It is kept buffered anyway for the puroposes of the model, so the concentration won't change. |
| 16 | Ca-leak-from-ext
racell | CaRegulation
Pathway No. 86 | Network | 0.0008 | 1000 | No | - |
| | This represents the pool of Ca leak channels. The concentration gradient is so large that this pool only needs a small number of molecules. For an equilibrium at 0.1 uM we need flow of 36e3/sec. With a permeability of 0.01 and a concentration gradient of 4mM->0.1 uM (4e4) we get flux = N * perm * grad => N = 36e3 / (1e-2 * 4e3) = 900 if flux = 20e3, N =500, which is what we use. This works out to a concentration of 0.83 nM. |
| 17 | Ca-leak-to-cytop
lasm | CaRegulation
Pathway No. 86 | Network | 0.024 | 1000 | Yes | - |
| | This pool represents the channels which leak Ca into the cytoplasm. It is a probably a composite of various channels depending on cell type. Membrane potential will obviously affect the leak amount, but that is not considered. The amounts and total flux are constrained by the need to balance the Ca flux and keep basal Ca levels around 80 nM. |
| 18 | Ca-sequester | CaRegulation
Pathway No. 86 | Network | 6.3328 | 160 | No | - |
| | This is the sequestered Calcium pool. The vol is 0.16 * the vol of the cell as a whole. This pool should really equilibrate with a highly buffered pool of Calcium, but that is not present in this version of the model. |
| 19 | Ca.PLC_g | PLC_g
Pathway No. 79 | Network | 0 | 1000 | No | - |
| 20 | Ca.PLC_g* | PLC_g
Pathway No. 79 | Network | 0 | 1000 | No | - |
arrow indicates that ordering is done according to ascending or descending order.
and 
color.