Clarify ProteinInterfaceDesign “randomness”

[Anonymous]

Hello, I am using the following protocol, modified from the design raf-rac interface demo, to design a protien protein interface. I ran 2 designs in parallel using nstruct = 1,000 and ran SequenceProfile.py to analyze and found that the results were the same for each. Therefore I wondering exactly how the sequence space is “randomly” searched to identify mutations and how likely these mutations will be to give a more favorable interface in vitro. Thanks in advance

</SCOREFXNS>

        <FILTERS>

    <Ddg name=ddg_binding threshold=0 scorefxn=REF2015 repeats=3 repack=1/>

    DDG filter computes binding score for the complex

    (threshold=0 only allows complexes with negative binding score)

    (repeats=3 calculates binding score three times and returns average)

    (repack=1 repack complex in both bound and unbound states to calculate binding score)

    <Sasa name=sasa threshold=800/>

    SASA filter computes interface solvent-accessible surface area

    (threshold=800 only allows complexes with greater than 800 Å^2

    as per Janin et al., Quarterly Reviews of Biophysics, 2008)

  </FILTERS>

        <TASKOPERATIONS>

                <RestrictResiduesToRepacking name=nodesign residues=/>

                <ProteinInterfaceDesign name=design repack_chain1=1 repack_chain2=1 design_chain1=0 design_chain2=1 interface_distance_cutoff=8/>

                <InitializeFromCommandline name=cmdline/>

                Reads command line options

        </TASKOPERATIONS>

        <MOVERS>

                <FavorNativeResidue name=Fav bonus=1/>

                <Docking name=dock1 fullatom=1 local_refine=1/>

                Runs local refinement stage of full atom docking

                <PackRotamersMover name=packrot scorefxn=REF2015 task_operations=design,cmdline/>

                Runs protein interface design

                <MinMover name=min scorefxn=REF2015 chi=1 bb=1 type=dfpmin_armijo_nonmonotone tolerance=0.01/>

                Runs full atom side-chain and backbone minimization

        </MOVERS>

        <PROTOCOLS>

                Runs movers and filters in this order

                <Add mover_name=Fav/>

                <Add mover_name=dock1/>

                <Add mover_name=packrot/>

                <Add mover_name=min/>

                <Add filter_name=ddg_binding/>

                <Add filter_name=sasa/>

        </PROTOCOLS>

</dock_design>

[Anonymous]

In yout log file there is a line that gives the random seed.

Something like this:

core.init: ‘RNG device’ seed mode, using ‘/dev/urandom’, seed=619811651 seed_offset=0 real_seed=619811651

core.init.random: RandomGenerator:init: Normal mode, seed=619811651 RG_type=mt19937

Are the random seeds diffrent?

[Anonymous]

I guess what I am asking is, is there any order which the residues which are allowed to be mutated are chosen (out of 10 or so fitting the distance criteria), then is there an order in which amino acids are sampled as possible mutants? My ddg filter is very high (0) such that all nstruct do pass so I can see why they would be so similar if there is some order to this? 

 

[Anonymous]

I believe this is answered in another thread: https://www.rosettacommons.org/node/10434

[Author]

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