Protool/electrostatics.py
def Gaussian_chain_matrix(self,ss=False):
        """Calculate electrostatic interactions between residues based on a Gaussian-chain
        defined unfolded state"""
        #
        # Check if we have the titratable groups
        #
        if not getattr(self,'titratable_groups',None):
            self.get_titratable_groups()
        #
        self.matrix={}
        self.distmatrix={}
        titgrps=self.titratable_groups
        residues=titgrps.keys()
        residues.sort()
        #
        for grp1 in titgrps:
            self.matrix[grp1]={}
            for grp2 in titgrps:
                res_dist=self.res_reparation(self.resid(grp1),self.resid(grp2),ss=ss)
                effective_dist=7.5*math.sqrt(float(res_dist))+5
                d=effective_dist
                import numpy as np
                import math
                for probe_dist in np.arange(0,20,0.1):
                    p=math.pow(4*math.pi,2)*probe_dist*(3/(2*math.pi*d**2))**(3.0/2.0)*math.exp(-3*probe_dist**2/(2.0*d**2))                
        return matrix
Calculate electrostatic interactions between residues based on a Gaussian-chain
        defined unfolded state
Calculate electrostatic interactions between residues based on a Gaussian-chain
defined unfolded state
Calculate electrostatic interactions between residues based on a Gaussian - chain defined unfolded state
def Gaussian_chain_matrix(self,ss=False):
         Check if we have the titratable groups
        if not getattr(self,'titratable_groups',None):
            self.get_titratable_groups()
        self.matrix={}
        self.distmatrix={}
        titgrps=self.titratable_groups
        residues=titgrps.keys()
        residues.sort()
        for grp1 in titgrps:
            self.matrix[grp1]={}
            for grp2 in titgrps:
                res_dist=self.res_reparation(self.resid(grp1),self.resid(grp2),ss=ss)
                effective_dist=7.5*math.sqrt(float(res_dist))+5
                d=effective_dist
                import numpy as np
                import math
                for probe_dist in np.arange(0,20,0.1):
                    p=math.pow(4*math.pi,2)*probe_dist*(3/(2*math.pi*d**2))**(3.0/2.0)*math.exp(-3*probe_dist**2/(2.0*d**2))                
        return matrix
def Gaussian_chain_matrix ( self , ss = False ) : if not getattr ( self , 'titratable_groups' , None ) : self . get_titratable_groups ( ) self . matrix = { } self . distmatrix = { } titgrps = self . titratable_groups residues = titgrps . keys ( ) residues . sort ( ) for grp1 in titgrps : self . matrix [ grp1 ] = { } for grp2 in titgrps : res_dist = self . res_reparation ( self . resid ( grp1 ) , self . resid ( grp2 ) , ss = ss ) effective_dist = 7.5 * math . sqrt ( float ( res_dist ) ) + 5 d = effective_dist import numpy as np import math for probe_dist in np . arange ( 0 , 20 , 0.1 ) : p = math . pow ( 4 * math . pi , 2 ) * probe_dist * ( 3 / ( 2 * math . pi * d ** 2 ) ) ** ( 3.0 / 2.0 ) * math . exp ( - 3 * probe_dist ** 2 / ( 2.0 * d ** 2 ) ) return matrix
Calculate electrostatic interactions between residues based on a Gaussian-chain
defined unfolded state
Calculate electrostatic interactions between residues based on a Gaussian - chain defined unfolded state
"""Calculate electrostatic interactions between residues based on a Gaussian-chain
        defined unfolded state""" # # Check if we have the titratable groups # # #
self
ss