Supplementary Information
Methods
Molecule Preparation for Docking
The file 3CZD.pdb was downloaded from the protein databank, and the dimer was saved as a separate pdb file. This was loaded into AutoDockTools-1.5.2. Water molecules were removed, hydrogens were added using the ‘noBondOrder’ method, and atoms were renumbered to accommodate the new hydrogen atoms. The protein was selected for use in the flexible residues dialog, at which point non-polar hydrogens were merged to the structure and gasteiger charges were added. The protein was then saved as a pdbqt file in the AutoDock format. No separate flexible residues were defined, a rigid structure was used for docking simulations.
The 968 ligand was drawn in ChemBioOffice, minimized with the MMFF94 force field in ChemDraw 3D, then saved as a mol2 file. This file was read into AutoDockTools-1.5.2, gasteiger charges were added, non-polar hydrogens were merged, and all possible torsions were set as active. The molecule was then saved as a pdbqt file.
AutoGrid 4.2 (part of the autodock suite of tools) was run using several different grids. One example grid is indicated by the following parameters file:
npts 122 122 92 # num.grid points in xyz
gridfld 3CZD_3.maps.fld # grid_data_file
spacing 0.647222222222 # spacing(A)
receptor_types A C H HD N OA SA # receptor atom types
ligand_types A C NA OA Br HD # ligand atom types
receptor 3CZD_3.pdbqt # macromolecule
gridcenter 0.001 -0.001 -23.302 # xyz-coordinates or auto
smooth 0.5 # store minimum energy w/in rad(A)
map 3CZD_3.A.map # atom-specific affinity map
map 3CZD_3.C.map # atom-specific affinity map
map 3CZD_3.NA.map # atom-specific affinity map
map 3CZD_3.OA.map # atom-specific affinity map
map 3CZD_3.Br.map # atom-specific affinity map
map 3CZD_3.HD.map # atom-specific affinity map
elecmap 3CZD_3.e.map # electrostatic potential map
dsolvmap 3CZD_3.d.map # desolvation potential map
dielectric -0.1465 # <0, AD4 distance-dep.diel;>0, constant
AutoDock 4.2 was run using several different grids, but genetic algorithm parameters were never changed. One example docking simulation is indicated by the following parameters file:
outlev 1 # diagnostic output level
intelec # calculate internal electrostatics
seed pid time # seeds for random generator
ligand_types A C NA OA Br HD # atoms types in ligand
fld 3CZD_3.maps.fld # grid_data_file
map 3CZD_3.A.map # atom-specific affinity map
map 3CZD_3.C.map # atom-specific affinity map
map 3CZD_3.NA.map # atom-specific affinity map
map 3CZD_3.OA.map # atom-specific affinity map
map 3CZD_3.Br.map # atom-specific affinity map
map 3CZD_3.HD.map # atom-specific affinity map
elecmap 3CZD_3.e.map # electrostatics map
desolvmap 3CZD_3.d.map # desolvation map
move BBP_968.pdbqt # small molecule
about -2.4453 0.3341 -0.0773 # small molecule center
tran0 random # initial coordinates/A or random
quat0 random # initial quaternion
ndihe 1 # number of active torsions
dihe0 random # initial dihedrals (relative) or random
tstep 2.0 # translation step/A
qstep 50.0 # quaternion step/deg
dstep 50.0 # torsion step/deg
torsdof 1 0.274000 # torsional degrees of freedom and coefficient
rmstol 2.0 # cluster_tolerance/A
extnrg 1000.0 # external grid energy
e0max 0.0 10000 # max initial energy; max number of retries
ga_pop_size 150 # number of individuals in population
ga_num_evals 2500000 # maximum number of energy evaluations
ga_num_generations 27000 # maximum number of generations
ga_elitism 1 # num to survive to next generation
ga_mutation_rate 0.02 # rate of gene mutation
ga_crossover_rate 0.8 # rate of crossover
ga_window_size 10 #
ga_cauchy_alpha 0.0 # Alpha parameter of Cauchy distribution
ga_cauchy_beta 1.0 # Beta parameter Cauchy distribution
set_ga # set the above parameters for GA or LGA
sw_max_its 300 # iterations of Solis & Wets local search
sw_max_succ 4 # consecutive successes before changing rho
sw_max_fail 4 # consecutive failures before changing rho
sw_rho 1.0 # size of local search space to sample
sw_lb_rho 0.01 # lower bound on rho
ls_search_freq 0.06 # prob of local search on individual
set_sw1 # set the above Solis & Wets parameters
compute_unbound_extended # compute extended ligand energy
ga_run 10 # do this many hybrid GA-LS runs
analysis # perform a ranked cluster analysis
AutoDock 4.2 provides a number of docking solutions for every run. Due to the nature of a genetic algorithm, it is unlikely two identical solutions will be generated within any reasonable sized batch of docking poses. Many runs, particularly using larger grids, were unstable, and solutions were collected manually until at least 10 unique solutions had been determined.
Figure Legends
Figure S1. The ability of 968 to inhibit GAC is dependent upon the order of addition of substrates versus inhibitor to GAC. 968 (10 mM) is most effective when added to GAC (50 nM) before either glutamine (21 mM) or phosphate (136 mM), and is ineffective if GAC is exposed to phosphate prior to 968 addition. Graphical Nomenclature: A-> B = A was added, then B was added. C + D = C and D were added simultaneously. Q = Glutamine, Pi = inorganic phosphate.
Figure S2. The ability of 968 to inhibit GAC is greatly affected by whether the enzyme is exposed to phosphate before or after 968. (Red) ∆72 GAC in pH 8.6 Tris-acetate buffer was exposed to glutamine (21 mM) and 968, and then inorganic phosphate (136 mM) was added. (Blue) ∆72 GAC in pH 8.6 Tris-acetate buffer was exposed to phosphate (136 mM), then to 968, following which glutamine (21 mM) was added. In either case, the solution was incubated for 10 minutes, at which time glutamate turnover was measured and inhibition rates were determined. Adding phosphate before 968 greatly reduces its ability to inhibit GAC activity. This is especially noticable by 25 mM 968, which inhibits > 60% of GAC activity when added before phosphate, but less than 20% of activity when added after phosphate.
Figure S3. ∆72 GAC in pH 8.6 Tris-acetate buffer was exposed to glutamine (21 mM) and compounds 35 (A) or 40 (B) for 0 (Blue), 10 (Red) or 20 (Green) minutes, and then inorganic phosphate (136 mM) was added. The solution was incubated for 10 minutes, at which time glutamate turnover was measured and inhibition rates were determined. For either compound, inhibitory potency decreased when incubated with GAC for any significant amount of time, though the reduced inhibition still increased with dose.