Datasets

R script for graph

edist=function(x,y) {

    sumd=0

    for ( i in 1:length(x)) {

        sumd=sumd+(x[i]-y[i])**2

    }

    sumd=sqrt(sumd)

    return(as.numeric(sumd))

}

library(bio3d)

library(igraph)

pdb=read.pdb('1oltA.pdb')

calpha=pdb$atom[pdb$calpha, c("resno","x","y","z")]

head(calpha,n=2)

edges_list=c()

## find distances between all calpha atoms for network

nres=length(calpha$resno)

nres

#Lower triangle of matrix

for ( i in 1:nres){

  X=c(calpha$x[i],calpha$y[i],calpha$z[i])

  for ( j in 1:i){

    if ( i == j ) { next }

    Y=c(calpha$x[j],calpha$y[j],calpha$z[j])

    dist=edist(X,Y)

    if (dist <= 7) {

        edges_list=c(edges_list,calpha$resno[i],calpha$resno[j])

    }

  }

}

g=make_graph(edges=edges_list,directed=F)

## Random network

ranGraph=erdos.renyi.game(5000,p=0.02,directed=FALSE)

ranGraph_deg=degree(ranGraph)

rdeg.dist=degree_distribution(ranGraph)

meanranK=mean(ranGraph_deg)

plot(rdeg.dist,pch=20,xlab="degree(k)",ylab="p(k)",las=1,main="Log plot",log="xy")

## Scale free network

gscale=barabasi.game(5000,power=1,m=3,directed=FALSE)

gscale_deg=degree(gscale)

gdeg.dist=degree_distribution(gscale)

meanK=mean(gscale_deg)

plot(gdeg.dist,pch=20,xlab="degree(k)",ylab="p(k)",las=1,main="Log plot",log="xy")