Thanks a lot Tsjerk,
It iw really going to be helpful. I will update you when I play with it.
best,
Abhi
On Sat, Nov 9, 2013 at 12:46 PM, Tsjerk Wassenaar <tsje...@gmail.com> wrote:
>
> Hey :)
>
> I thought there was a post recently about showing secondary structure in
> C-alpha only models. I can't find it anymore, but in any case it's
> something popping up now and again. For reconstruction of high-resolution
> models out of coarse-grained ones, I came up with a very simple algorithm
> for rebuilding the backbone based on C-alpha atoms only. I realized that
> that could work for determining secondary structure, and made a function
> out of it. It's not perfect, as sometimes a residue gets a flipped
> backbone, but overall it seems to work pretty nicely. The following can be
> put in a script (bbpredict.py):
>
> from pymol import cmd
> import math
>
> def oprod(a,b): return
> a[1]*b[2]-a[2]*b[1],a[2]*b[0]-a[0]*b[2],a[0]*b[1]-a[1]*b[0]
> def vsub(a,b): return [i-j for i,j in zip(a,b)]
> def cest(u,v,w): return [i+0.37*j+0.45*k for i,j,k in zip(u,v,w)]
> def oest(u,v,w): return [i+0.37*j+1.75*k for i,j,k in zip(u,v,w)]
> def hest(u,v,w): return [i-0.37*j-1.45*k for i,j,k in zip(u,v,w)]
> def nest(u,v,w): return [i-0.37*j-0.45*k for i,j,k in zip(u,v,w)]
> def norm(a): return math.sqrt(sum([i**2 for i in a]))
> def vdiv(a,b): return [i/b for i in a]
>
> def bbpredict(selection,name="bbpred"):
> m=cmd.get_model(selection+' and n. ca')
> x=m.get_coord_list()
> d=[(vsub(j,i),vsub(k,i)) for i,j,k in zip(x,x[1:],x[2:])]
> o=[oprod(*i) for i in d]
> no=[vdiv(i,norm(i)) for i in o]
>
> CA = [("ATOM %5d CA %3s %1s%4d "+("%8.3f%8.3f%8.3f"%tuple(i)))
> for i in x]
> N = [("ATOM %5d N %3s %1s%4d
> "+("%8.3f%8.3f%8.3f"%tuple(nest(i,j[0],k)))) for i,j,k in zip(x[1:],d,no)]
> H = [("ATOM %5d H %3s %1s%4d
> "+("%8.3f%8.3f%8.3f"%tuple(hest(i,j[0],k)))) for i,j,k in zip(x[1:],d,no)]
> C = [("ATOM %5d C %3s %1s%4d
> "+("%8.3f%8.3f%8.3f"%tuple(cest(i,j[0],k)))) for i,j,k in zip(x,d,no)]
> O = [("ATOM %5d O %3s %1s%4d
> "+("%8.3f%8.3f%8.3f"%tuple(oest(i,j[0],k)))) for i,j,k in zip(x,d,no)]
>
> j = m.atom[0]
> bb = [CA[0]%(3,j.resn,j.chain,int(j.resi))]
> bb.append(C[0]%(4,j.resn,j.chain,int(j.resi)))
> bb.append(O[0]%(5,j.resn,j.chain,int(j.resi)))
> stuff = zip(m.atom[1:],zip(N,H,CA[1:],C[1:],O[1:]))
> bb.extend([ i%(num,j.resn,j.chain,int(j.resi)) for j,k in stuff for
> i,num in zip(k,range(5)) ])
>
> cmd.read_pdbstr("\n".join(bb),name)
>
> #### END
>
> Then it can be used e.g. as follows (yes, a full atomistic structure for
> demonstration):
>
> run bbpredict.py
> fetch 6lzm
> bbpredict('6lzm','pred')
> dss pred
>
>
> I'll see if I can get the flips out and tidy the code up a bit. Then I'll
> add this to the wiki. I hope it'll be of some use to anyone. The routine is
> explained in a manuscript we just submitted.
>
> Cheers,
>
> Tsjerk
>
> --
> Tsjerk A. Wassenaar, Ph.D.
>
>
>
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