To create our pSEVA3411 plasmid, which will be the backbone for the final plasmid coding our system
To create our “A” and “C” cassettes, which functioned as the binder+linker portion of our complex.
E-Gel Lane | Sample identity |
---|---|
M | 100bp ladder |
1 | HRP |
2 | Blac |
3 | Fluc |
4 | Rluc |
5 | TEV |
6 | pSEVA3411 |
7 | Binder N |
8 | Binder C |
9 | Empty |
10 | 100bp ladder |
To create our “B” cassette, which functioned as the complementing portion of our complex.
HRP, 100kb ladder, Rluciferase, Beta lactamase, TEV protease(left to right). Highest bands all represent lengths that correspond to one fragment of the complementation system. This gel helped us to recognize that an error was made in the initial design of the riboJ complex in which the 5’ BbsI cut site left an incompatible overhang, which prevented the assembly from joining with the N-terminal split proteins.
To assemble the backbone of our final cassette, in which the D-promoter is crucial.
E-Gel Lane | Sample identity |
---|---|
M | 100bp ladder |
1 | HRP |
2 | Blac |
3 | Fluc |
4 | Rluc |
5 | TEV |
6 | pSEVA3411 |
7 | Binder N |
8 | Binder C |
9 | Empty |
10 | 100bp ladder |
Adapted from iGEM Distribution Handbook
Adapted from NEB Protocol
Do the following in 2 PCR tubes, 50 μL each, 100 μL total
Adapted from kit insert of New England Biolabs #T1030, all centrifuging should be carried out at 16,000 RCF
Adapted from New England Biolabs kit #T1020L insert, all centrifuging should be carried out at 16,000 RCF
Use online calculator to determine total pmol and pmol/µL
Calculate using link to determine total pmol and pmol/µL
In-Fusion assembly works best with ~50ng of insert and ~200ng of vector. Determine the required volumes of backbone and insert to get a 2:1 molar ratio of backbone to insert with those approximate final masses of DNA. This procedure in adapted from the manufacturer instructions.
Adapted from IDT protocol
Do the following separately for each biomarker, i.e. all GFAP binders together, but UCHL1 and GFAP binders separately
Separate these reactions by complementation system, only paired complementation systems will interact with each other (n-term GFP only interacts with c-term GFP, etc.). No need to separate by biomarker, cassette B will contain both parts of a complementation system and the riboJ-RBS complex, so it’s binder-agnostic.
pSEVA3411 already contains chloramphenicol resistance, this step only adds a single promoter g block (and a BsaI site) to turn it into Cassette D.
.pdb
files File → open
all .pdb
files click A → align → all to this
interfaceResidues <object-name>, chain A, chain B
in the PyMOL consoleselect mol1, chain A
select mol2, chain B
bg_color white
color → gray90
show → sticks
color → spectrum → b factor
count_atoms byca <interface-object>
set seq_view, 1
)set seq_view_color, <your-color>
]A → find → polar contacts → between chains
AlphaFold is heavily biased by examples of natural binding and folding, so its predictions will probably not be accurate for non-native binding (such as nanobodies) or for point mutations. For these applications, (py)Rosetta or docking would be a better choice.
:
1
1:1
1:2
. The position of these numbers depends on how the original sequences were input, this example assumes that the input was <GFAP Sequence>:<S100β Sequence>
and tells AlphaFold to calculate the interaction between one GFAP and one s100β dimer..zip
file containing several filesmsa.pickle
& msa_coverage.png
: These are the results of the MSA (multiple sequence alignment) from the "Search against genetic databases" cell. You can upload these to that cell during future runs to avoid calculating it from scratch again, but it often isn't worth it since the calculation is so quick.settings.txt
These are the settings you chose during the runrank_#_model_#_ptm_seed_#_unrelaxed.pdb
These are the files you want to analyze in pyMOL later. The most important number is the rank (first number), the higher it is the more confident AlphaFold is in that structure.rank_#_model_#_ptm_seed_#_unrelaxed.png
These are the images that the AlphaFold cell produced while working. They're helpful for a quick overview, but the information is redundant with the .pdb
files.This is only technically necessary for HDOCK, ZDOCK is smart enough to avoid confusing chains for simple settings. For consistency, we recommend keeping as many variables constant as possible, which means adjusting the chain numbers for all docking software, not just those for which it’s absolutely necessary. Note that chain [#]
refers to a chain identifier, which is usually a letter, not a number.
.pdb
file of the receptor protein or PDB ID.pdb
file of the ligand protein or PDB IDset seq_view, 1
in the pyMOL console.pdb
files or getting the structures from PDB by executing fetch [PDB ID]
in the consolelig
and rec
extract rec, chain [#] and [RECEPTOR_OBJECT]
extract lig, chain [#] and [LIGAND_OBJECT]
delete [RECEPTOR_OBJECT]
delete [LIGAND_OBJECT]
extract rec, chain A and chain B and [RECEPTOR_OBJECT]
alter lig, chain = ‘B’
iterate [OBJECT_NAME], resi
. The highest value will be the end of the chain.alter lig, resi = int(resi) + [#]
, where [#]
is one greater than the highest residue number of the receptor.pdb
file by executingsave rec.pdb, rec
.pdb
file by executingsave lig.pdb, lig
HDOCK and ZDOCK work very similarly (for example, they both perform energy minimization), but they use different processes “behind the scenes”. If the outputs of both systems look very similar, that means the protein is more likely to work that way in vitro and the reverse is also true.
.pdb
files of the proteins you want to dock or PDB ID and chain number.pdb
file of the receptor (biomarker). If the receptor is a dimer, make sure to adjust the numbering before proceeding or HDOCK may not work properly.3kw5:A
after the identifier so you only dock that specific part of the structure.tar.gz
file, all of the predictions in .pdb
format are in thereHDOCK and ZDOCK work very similarly (for example, they both perform energy minimization), but they use different processes “behind the scenes”. If the outputs of both systems look very similar, that means the protein is more likely to work that way in vitro and the reverse is also true. Unlike HDOCK, ZDOCK is only able to dock the entirety of PDB structures, and there is no option to specify docking with only a particular chain.
.pdb
files of the proteins you want to dock or PDB ID.pdb
file of the receptor (biomarker). If the receptor is a dimer, make sure to adjust the numbering before proceeding or ZDOCK may not work properly..zip
file, all of the predictions in .pdb
format are in there