1) Different models.  
	a Compare Hlavacek mechanism for nucleotide exchange to the "simple" model - is all the complexity needed (see email)?
	b Add positive feedback loop to Das model and compare to Stites model
	c Add positive feedback to Hlavacek model
	d Add Diffusion to my model of the Stites paper 
	e Extend model up (to cell membrane) or down (to nucleus)

2) mutations, 
	a GAP-insensitive point mutants (eg 50/50 WT to mutant)
		with positive feedback
		without positive feedback
	b Fast-cycling RAS point mutants
		with positive feedback
		without positive feedback

3) drugs

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Idea #1: (1c above)
The students could try to add the positive feedback to my model (RasGDP and RasGTP binding to REM, which increases GEF activity, meaning the rate of GDP-to-GTP exchange upon GEF binding, by a little bit and by a lot, respectively) and look for bistability. I don't think that the effect of REM binding has been characterized at the microscopic level, meaning the effects on the rate constants of Reactions 2, 3, 4, 6 and 7 (in my scheme) are unknown (there are many changes of the rate constants that could yield faster exchange). So… some assumptions probably need to be made about how REM binding affects Reactions 2, 3, 4, 6 and 7. Changes to KD values need to be made carefully so as to satisfy the detailed balance constraints (namely, KD2 times KD6 must always equal KD5 times KD7 and furthermore, KD1 times KD3 must always equal KD2 times KD4). 

Idea #2: (2a above)
The students could compare WT Ras behavior (with or without positive feedback) against a case where there's 50% WT Ras + 50% GAP-insensitive mutant form of Ras (G12V) - this case would arise from a point mutation affecting only one of the two copies of the KRAS gene. Based on Ed's Table S2, the effects of a G12V mutation are 1) a change of the intrinsic GTPase activity of Ras (khyd is decreased by 6.67-fold), 2) a change of the guanine nucleotide binding properties of Ras (kp1, km1, kp4, km4, kp5, km5, kp6, and km6; smaller dissociation rate constants and larger association rate constants; I would assume the following: kp1 and kp4 both increase by 2.27-fold; km1 and km4 both decrease by 3.23-fold; kp5 and kp6 both increase by 4.14-fold; and km5 and km6 both decrease by 1.25-fold), 3) complete loss of GAP-assisted hydrolysis (kcat is set to the same value as the rate constant for intrinsic mutant Ras GTPase activity), and 4) an increase in affinity of effector protein (CRAF) for RasGTP (the ratio kaEff/kdEff increases by 2.25-fold).

Idea #3: -related to 1d above 
The students could also start with the model I sent and then add inducible GEF (and optionally GAP) recruitment to the plasma membrane (where Ras is localized). This would just require, mainly, adding reactions for plasma membrane localized GEF that have a different, smaller effective volume. Here's an example of steps that could be taken to include inducible GEF recruitment:
add a site to SOS1 in the molecule types block: SOS1(GEF,PRR), where PRR represents proline-rich region.
Introduce a volume Vpm (the effective volume explored by plasma membrane localized proteins), which should be 100- to 1000-fold smaller than the cytoplasmic volume V (Ed says it's 250-fold smaller).
Add a rule that recruits SOS1 to the plasma membrane, meaning a rule that defines an interaction with the new PRR site (in the EGFR pathway, the PRR interaction partner is the C-terminal SH3 domain EGFR-bound GRB2, an adaptor protein) - the activity of the rule can be viewed as an input function (e.g., a step increase in the amount of the PRR binding parter at time t=0)
Define new association rate constants for PRR-bound SOS1; thee are the same as before except Vpm is used instead of V in the unit conversions in the .bngl parameters block.
Adding recruited RASA1 would be similar (in the EGFR pathway, one or both of the tandem SH2 domains in RASA1 bind directly to a phosphotyrosine in EGFR.