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How to predict 3D structure of a peptide from its sequence |
plotBestEnergies "f1" 100. "append display"); and the lowest energy conformation in different simulations are close, e.g.
# peptide "pep.se" ; runs: "f1" and "f2" build "pep" display read conf "f1" 0 show stack read conf "f2" 0 show stackWatching trajectory files f1.mov and f2.mov may also be useful. (See also How to evaluate helicity of a peptide from the BPMC simulation and How to calculate an ensemble average). Now, the script:
# Example folding script. Use as directed. read libraries build "pep16" # your peptide sequence is in pep16.se file. rename a_*. "f2" # specifies current name. # Several runs (f2,f3, etc.) are recommended nvar = Nof( v_//* ) # number of variables nProc=4 # if you are using parallel version. mncallsMC = nvar*50000 # maximal number of energy evaluations mncalls = 170+nvar*3 # maximal n_of minimization calls after # each random change temperature = 600 # optimal temperature for the simulation tolGrad = 0.01 # exit minimization when gradient is < 0.01 mcBell = 1.0 # the default width of the MC probability distributions mnconf = 40 # maximal n_of low-energy conformations saved # in the stack (f2.cnf file) mnvisits = 25 # if stuck for >= 25 times, push it out mnreject = 10 mnhighEnergy = 30 l_bpmc = yes # use biased probability electroMethod = "MIMEL" surfaceMethod = "constant tension" set terms "vw,14,hb,el,to,sf,en" # ECEPP/2 energy + solvation + entropy (see icm.hdt file) fix v_//?vt* # exclude irrelevant virtual variables specifying # absolute molecular position set vrestraint a_/* # load preferred backbone and side-chain angle zones # for the biased probability MC randomize v_//!omg 180.0 # create random starting conformation vicinity = 15.0 compare v_//phi,psi # use these variables to compare structure montecarlo trajectory # run it and record a trajectory file. # watch the movie later by: # read trajectory "f2"; display ribbon # display trajectory "f2" 4. 8. # analyze the best conf. in the stack by: # build "pep16"; read stack; show stack all # load conf 1 quit
How to perform local flexible docking of two protein molecules using the grid potentials |
How to perform an explicit flexible docking of two simplified protein molecules |
vicinity = 4. compare static a_2//ca compress stack
How to build a model by homology |
How to create a table with the residue properties? |
Sometimes you like to turn a show a_/* command for residue selections into a proper table. To create an ICM table with this one needs to create columns separately and add them as columns to a table. For example if we have a residue selection res with n residues:
read pdb "1crn" align number # to have numbers from 1 to n show surface area mute # compute surface areas res = a_/10:20 # residue range of interest n = Nof(res) # the number of residues. add column t Sarray(n, Name(Obj(res))[1]),Trim(Label(res),all),Area(res),Area(res)/Area(res type)
The last column is the relative residue accessibility.
The add column command will create a table with four columns, the last being the relative residue accessibility.
#>T t #>-A-----------B-----------C-----------D---------- 1mui T12 85.264893 0.560953 1mui I13 2.073181 0.010687 1mui K14 102.661064 0.479725 1mui I15 2.916692 0.015034 1mui G16 44.870205 0.50416 1mui G17 66.557358 0.747835 1mui Q18 67.372437 0.354592 1mui L19 141.619446 0.71525 1mui K20 49.295151 0.230351
A number of other properties which can be calculated for residue selections can be added to this table, e.g.
Then you can also append rows or other tables from different pdbs to the same table tt with another pdb with this:
add t tt # will append rows of tt to column t
Ligand overlays |
How to superimpose multiple compounds with similar activity? |
Use the chemSuperBG macro that is designed to take one molecule as a template and flexibly overlay in an optimal way other chemicals from a chemical table to the template.
Method.The chemical table can contain 0D, 2D or 3D representation of a compound. The compounds will be optimally superimposed to one or several templates. The flex-overlay tool will convert them on the fly to a flexible 3D form, optimize and dock it to the average property representation of the template compounds.
From the template 3D seven grids ( m_g1,m_g2,.. ) will be generated for different atom types. These grids will use the Gaussian expansion of the properties and will be averaged for the superimposed molecules. Each ligand will globally optimize both its internal energy and the grid-map fit.
The result will be saved as a 3D .sdf file.
From ICM command line the syntax is the following:
chemSuperBG ms_template(s)> <chem_table r_thoroughness l_Sample_Rings
From the operating system you need to run the _chemSuper script with the following arguments:
_chemSuper templates.mol chem_table.sdf superimposed_output.sdf [thoroughness=1.] [-r] The -r option means that the rings will be considered as flexible.
From GUI: Select rows in your chemical table, click on the mol-column and select Chemistry/Chemical Template Superposition
Frequently asked questions on cheminformatics and compound property prediction. |
[ Faq molcart query | Faq molcart dump | Diverse subset ]
How to read compounds one by one from a Molcart table? |
This script will read each molecule one by one and convert them to 3D
connect molcart "myhost"//"user"//"pass"//"dbase" # use Name(molcart connect) to see if you are connected. for i=1,Nof("asgsynth") # name of a vendor table query molcart "select * from asgsynth where molid="+i name="t" if Nof(t)!=1 | Smiles(Parray(t.mol[1] mol))[1] == "" continue read mol input=t.mol[1] convert2Dto3D a_ yes yes no no # or anything else. this is a macro delete a_*. # clean up endfor
How to export/dump a molcart table to an sdf file? |
Read the molcart page for a general set ICM-molcart commands. Follow these steps:
write molcart table="asgsynth" "tmp2.sdf"
See: molcart
How to select a diverse subset from a chemical table? |
Use the make tree command. The group command will then select unique molecules and one will be able to add the columns needed in the cntrs table. Example:
read table mol "drugs.sdf" make tree drugs column={"mol"} split="cl" cntrs = drugs group cntrs.cl cntrs.mol # group by .cl and retain .mol
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