#!/usr/bin/python import sys import os.path import re import time import numpy as np from scipy.stats import norm , gamma from scipy import special from scipy import signal from scipy import ndimage #from numba import njit, prange ###################################################################################################### ###################################################################################################### ###################################################################################################### ############### POPC/POPG 95/5 mol/mol LUVs ############### ############### Reconstitution buffer: TRIS 20 mM, EDTA 2 mM ############### ############### Buffer used for PLUV exp. in DESY in 2017: ############### ###################################################################################################### ###################################################################################################### ###################################################################################################### ############### GLOBAL VARIABLES ############### # POPG molar ratio CONST_x_PG = 0.05 # ############## POPC and POPG ############### # 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine # 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol # number of chain groups CONST_n_CH = 2 CONST_n_CH2 = 28 CONST_n_CH3 = 2 #X-ray scattering length chain groups (nm) CONST_b_CH = 1.97256E-05 ; CONST_b_CH2 = 2.25435E-05 ; CONST_b_CH3 = 2.53615E-05 ; ### POPC # Lipid-head volume CONST_V_HL_PC = 0.331 # 0.320 # X-ray scattering length of head groups (nm) CONST_b_PC = 2.73340E-04 CONST_b_CG = 1.88802E-04 CONST_b_PCN = 1.97256E-04 CONST_b_Chol = 7.60844E-05 # Lipid-volume temperature-dependencies a0 + a1*T (nm^3) CONST_a0_V_POPC = 1.22810311835285 CONST_a1_V_POPC = 0.000934915795086395 ### POPG # Lipid-head volume CONST_V_HL_PG = 0.289 ; # X-ray Scattering length of head groups (nm) CONST_b_PG = 2.47979E-04 CONST_b_PG1 = 1.32443E-04 CONST_b_PG2 = 1.15536E-04 # Lipid-volume temperature-dependencies a0 + a1*T (nm^3) CONST_a0_V_POPG = 1.17881068602663 CONST_a1_V_POPG = 0.00108364914520327 ############### Other variables ############### ### Water # V_PW = 24.5e-3 #(nm^3) Perkins 2001 (Hydration shell in proteins) # polynome coefficient for T-dependency of bulk-water-molecule volume (V_HW) # Units in degree Celsius CONST_p0_VW = 0.0299218 CONST_p1_VW = -2.25941e-06 CONST_p2_VW = 2.5675e-07 CONST_p3_VW = -1.69661e-09 CONST_p4_VW = 6.52029e-12 # polynome coefficient for T-dependency of bulk-water molar concentration (Cw) #Units in degree Celsius CONST_p0_Cw = 55.5052 CONST_p1_Cw = 0.00131894 CONST_p2_Cw = -0.000334396 CONST_p3_Cw = 9.10861e-07 CONST_b_HW = 2.8179E-05 CONST_d_shl = 0.31 # (nm) Perkins 2001 (Hydration shell in proteins) # Composition of the Reconstitution buffer (M) CONST_ctris = 0.02 CONST_cEDTA = 0.002 ### Extra molecules # TRIS buffer CONST_b_tris = 1.860E-04 CONST_V_tris = 0.15147 # (nm^3) # EDTA CONST_b_EDTA = 4.340E-04 ; CONST_V_EDTA = 0.56430 # (nm^3) ################################################################################################################## ################################################################################################################## ######################################################### #@njit(parallel=True) def PDF_normal(x, mu, sig) : return np.exp(-(x-mu)**2 / (2*sig**2) ) /( sig*np.sqrt(2*np.pi)) ######################################################### #@njit(parallel=True) def PDF_lognormal(x, mu_x, sig_x) : # https://en.wikipedia.org/wiki/Log-normal_distribution mu = np.log(mu_x**2 / np.sqrt(mu_x**2 + sig_x**2)) sig = np.sqrt(np.log(1 + sig_x**2 / mu_x**2)) return np.exp(-(np.log(x)-mu)**2 / (2*sig**2) ) /( x*sig*np.sqrt(2*np.pi)) ######################################################### def lipid_volume(T) : return (1-CONST_x_PG) * (CONST_a0_V_POPC +T * CONST_a1_V_POPC) + CONST_x_PG * (CONST_a0_V_POPG + T * CONST_a1_V_POPG) ######################################################### def water_volume(T) : return CONST_p0_VW + CONST_p1_VW*T + CONST_p2_VW*T**2 + CONST_p3_VW*T**3 + CONST_p4_VW*T**4 ######################################################### #@njit(parallel=True) def FTreal_erf(q, mu, d, sig) : """ FTreal_erf(q, mu, d, sig) """ return np.where(q==0, 1, np.sin(q*d/2.)/(q*d/2.) * np.exp(-(q*sig)**2/2.) * np.cos(q*mu) ) ######################################################### #@njit(parallel=True) def FTreal_gauss(q, mu, sig) : """ FTreal_gauss(q, mu, sig) """ return np.exp(-(q*sig)**2/2.) * np.cos(q*mu) ######################################################### def Slab(x, mu, L, sig) : return 0.5 * ( special.erf( (x - (mu-L/2.))/(np.sqrt(2)*sig) ) - special.erf( (x - (mu+L/2))/(np.sqrt(2)*sig) ) ) ######################################################### def Gauss( x, V, mu, sig, A_L ) : return V * PDF_normal(x, mu, sig) / A_L #################################### j0^2 MOMENTS (SCHULZ PDF) ######################################### #################################### (checked!) ######################################### #@njit(parallel=True) def mu4(q, Z, a) : return np.where(q==0, a**4*(Z+1)*(Z+2)*(Z+3)*(Z+3), a**2 * (Z+2)*(Z+1) * ( 1 - (1+4*q*q*a*a)**(-(Z+3)/2.) * np.cos((Z+3)*np.arctan(2*q*a)) ) / ( 2*q**2 ) ) ################################################################################################################## ################################################################################################################## ################################ SYMMETRIC VESICLE FOR X-RAY SLDs ######################################### ######################################## SDP MODELLING ######################################### #################################### SEPARATED FORM FACTOR ######################################### ################################################################################################################## ################################################################################################################## ######################################################### ######### Symmetric POPC bilayer ######################## ######### liposomes and proteoliposomes ################# ######################################################### class SDP_POPC_RecBuf: ################## def __init__(self, q, PAR) : self.q = q [self.Norm, self.nv, self.Rm, self.Z, self.n_TR, self.d_TR, self.s_TR, self.d_Chol, self.s_Chol, self.d_PCN, self.s_PCN, self.d_CG, self.s_CG, self.A_L, self.s_D_C, self.s_CH2, self.d_CH, self.s_CH, self.s_CH3, self.r_PCN, self.r_CG, self.r12, self.r32, self.T, self.V_BW, self.Con] = PAR # [Example 1], fixed parameters: # Norm 1e5 # Normalization # n_TR 0.0 # Tris fraction # d_TR 1.0 # Tris width (nm) # s_TR 0.29 # Tris position (nm) # d_CH 0.90 # CH position (nm) # s_CH 0.305 # CH width (nm) # r12 0.81 # V_CH/V_CH2 # T 37 # Temperature (°C) # [example 1] fixed Cw = CONST_p0_Cw + CONST_p1_Cw*self.T + CONST_p2_Cw*self.T**2 + CONST_p3_Cw*self.T**3 xtris = CONST_ctris / Cw # mole fraction of free TRIS in bulk xEDTA = CONST_cEDTA / Cw # mole fraction of free EDTA in bulk # Volumes # [example 1] fixed self.V_L = lipid_volume(self.T) V_HW = water_volume(self.T) V_HC = self.V_L - ( (1-CONST_x_PG) * CONST_V_HL_PC + CONST_x_PG * CONST_V_HL_PG ) # Calculation of mean D_C self.D_C = V_HC / self.A_L # Quasi-molecular volumes # [example 1] r12 fixed V_CH2 = V_HC / ( CONST_n_CH2 + CONST_n_CH*self.r12 + CONST_n_CH3*self.r32 ) # Volume of CH2 groups V_CH = V_CH2 * self.r12 # Volume of CH groups V_CH3 = V_CH2 * self.r32 # Volume of CH3 groups self.V_CG = CONST_V_HL_PC * self.r_CG # Volume of CG group self.V_PCN = CONST_V_HL_PC * self.r_PCN # Volume of PCN group self.V_Chol = CONST_V_HL_PC * (1-self.r_PCN-self.r_CG) # Volume of CholCH3 group # CONST CONST_V_PG1 = CONST_V_HL_PG * 0.16 # Kucerka 2012 CONST_V_PG2 = CONST_V_HL_PG * ( 1 - 0.51 - 0.16) # Kucerka 2012 ############### X-ray scattering lengths (nm) # [example 1] rho_sol fixed rho_sol = ( CONST_b_HW + xtris*CONST_b_tris + xEDTA*CONST_b_EDTA ) / V_HW drho_Chol = ( (1-CONST_x_PG)*CONST_b_Chol/self.V_Chol + CONST_x_PG*CONST_b_PG2/CONST_V_PG2 ) - rho_sol drho_PCN = ( (1-CONST_x_PG)*CONST_b_PCN/self.V_PCN + CONST_x_PG*CONST_b_PG1/CONST_V_PG1 ) - rho_sol drho_CG = CONST_b_CG / self.V_CG - rho_sol drho_TR = CONST_b_tris/ CONST_V_tris - rho_sol drho_CH = CONST_b_CH / V_CH - rho_sol drho_CH2 = CONST_b_CH2 / V_CH2 - rho_sol drho_CH3 = CONST_b_CH3 / V_CH3 - rho_sol drho_HW = CONST_b_HW / self.V_BW - rho_sol ############### D_C polydispersity # Number of integration points N = 201 # Parameter dependent integration bounds # HC_min, HC_max = self.D_C-3*self.s_D_C, self.D_C+3*self.s_D_C # # Hardcoded integration bounds for POPC, fixed T = 37, A_L in [0.598, 0.719] HC_min, HC_max = V_HC/0.719-0.5, V_HC/0.589+0.5 # Minimum and maximum samples (offset by 1/2 of the integration step w.r.t integration bounds for the midpoint rule) integration_step = (HC_max - HC_min) / N HC_first, HC_last = HC_min + 0.5*integration_step, HC_max - 0.5*integration_step HC_array = np.linspace(HC_first, HC_last, N) Normal = PDF_normal(HC_array, self.D_C, self.s_D_C) ############### calculating scattering amplitude ----------------------------------------------- self.Am = np.zeros([N,self.q.shape[0]],dtype=float) c_CH = np.zeros(N,dtype=float) c_CH3 = np.zeros(N,dtype=float) ############### c-prefactors c_Chol = ( (1-CONST_x_PG)*self.V_Chol + CONST_x_PG*CONST_V_PG2 ) / self.A_L c_PCN = ( (1-CONST_x_PG)*self.V_PCN + CONST_x_PG*CONST_V_PG1 ) / self.A_L c_CG = self.V_CG / self.A_L c_TR = CONST_V_tris*self.n_TR / self.A_L for hc in range(N): c_CH[hc] = V_CH * CONST_n_CH / (V_HC / HC_array[hc] ) c_CH3[hc] = V_CH3 * CONST_n_CH3 / (V_HC / HC_array[hc] ) for hc in range(N): # Adding hydrocarbon-chain envelope self.Am[hc] += 2 * drho_CH2 *HC_array[hc] * FTreal_erf(self.q, 0, 2*HC_array[hc], self.s_CH2) # Adding CH and CH3 groups self.Am[hc] += 2 * (drho_CH - drho_CH2) * c_CH[hc] * FTreal_gauss(self.q, self.d_CH, self.s_CH) self.Am[hc] += 2 * (drho_CH3 - drho_CH2) * c_CH3[hc] * FTreal_gauss(self.q, 0, self.s_CH3) # Adding hydration-water envelope self.Am[hc] += 4 * drho_HW * ( self.d_CG + self.d_PCN + self.d_Chol + CONST_d_shl) * FTreal_erf(self.q, (HC_array[hc]+(self.d_CG+self.d_PCN+self.d_Chol+CONST_d_shl)/2.), (self.d_CG+self.d_PCN+self.d_Chol+CONST_d_shl), self.s_CH2) # Adding CG, PCN and CholCH3 groups self.Am[hc] += 2 * (drho_TR - drho_HW) * c_TR * FTreal_gauss(self.q, (HC_array[hc]+self.d_TR/2.), self.s_TR) self.Am[hc] += 2 * (drho_CG - drho_HW) * c_CG * FTreal_gauss(self.q, (HC_array[hc]+self.d_CG/2.), self.s_CG) self.Am[hc] += 2 * (drho_PCN - drho_HW) * c_PCN * FTreal_gauss(self.q, (HC_array[hc]+self.d_CG+self.d_PCN/2.), self.s_PCN) self.Am[hc] += 2 * (drho_Chol - drho_HW) * c_Chol * FTreal_gauss(self.q, (HC_array[hc]+self.d_CG+self.d_PCN+self.d_Chol/2.), self.s_Chol) ############### Ensemble average # multiply each columns of Am by Normal and sum along the columns, # then multiply by integration step self.I = np.einsum('ij,i->j', self.Am**2, Normal) * integration_step ################## def intensity(self): alp = self.Rm/(self.Z+1) return ( self.Norm * self.nv*1e-6 ) * self.I * ( 16*np.pi**2*mu4(self.q,self.Z,alp) ) + self.Con*( 0.99*(1./(1+np.exp(-8*(self.q-1.)))) + 0.01 ) ################## def negative_water(self): self.check = 0 z_array = np.linspace(0.,4.,81) CG = Gauss(z_array, self.V_CG, self.D_C+self.d_CG/2., self.s_CG, self.A_L) PCN = Gauss(z_array, self.V_PCN, self.D_C+self.d_CG+self.d_PCN/2., self.s_PCN, self.A_L) Chol = Gauss(z_array, self.V_Chol, self.D_C+self.d_CG+self.d_PCN+self.d_Chol/2., self.s_Chol, self.A_L) TRIS = Gauss(z_array, self.n_TR*CONST_V_tris, self.D_C+self.d_TR/2., self.s_TR, self.A_L) BW = Slab(z_array, self.D_C+(self.d_CG+self.d_PCN+self.d_Chol+CONST_d_shl)/2., self.d_CG+self.d_PCN+self.d_Chol+CONST_d_shl, self.s_CH2) - CG - PCN - Chol - TRIS for i in(BW) : if i <-0.001 : self.check+= 1 return self.check ################################################################################################################## ################################################################################################################## class SDP_POPC_RecBuf_LogNormal: ################## def __init__(self, q, PAR) : self.q = q [self.Norm, self.nv, self.Rm, self.Z, self.n_TR, self.d_TR, self.s_TR, self.d_Chol, self.s_Chol, self.d_PCN, self.s_PCN, self.d_CG, self.s_CG, self.A_L, self.s_D_C, self.s_CH2, self.d_CH, self.s_CH, self.s_CH3, self.r_PCN, self.r_CG, self.r12, self.r32, self.T, self.V_BW, self.Con] = PAR # [Example 1], fixed parameters: # Norm 1e5 # Normalization # n_TR 0.0 # Tris fraction # d_TR 1.0 # Tris width (nm) # s_TR 0.29 # Tris position (nm) # d_CH 0.90 # CH position (nm) # s_CH 0.305 # CH width (nm) # r12 0.81 # V_CH/V_CH2 # T 37 # Temperature (°C) # [example 1] fixed Cw = CONST_p0_Cw + CONST_p1_Cw*self.T + CONST_p2_Cw*self.T**2 + CONST_p3_Cw*self.T**3 xtris = CONST_ctris / Cw # mole fraction of free TRIS in bulk xEDTA = CONST_cEDTA / Cw # mole fraction of free EDTA in bulk # Volumes # [example 1] fixed self.V_L = lipid_volume(self.T) V_HW = water_volume(self.T) V_HC = self.V_L - ( (1-CONST_x_PG) * CONST_V_HL_PC + CONST_x_PG * CONST_V_HL_PG ) # Calculation of mean D_C self.D_C = V_HC / self.A_L # Quasi-molecular volumes # [example 1] r12 fixed V_CH2 = V_HC / ( CONST_n_CH2 + CONST_n_CH*self.r12 + CONST_n_CH3*self.r32 ) # Volume of CH2 groups V_CH = V_CH2 * self.r12 # Volume of CH groups V_CH3 = V_CH2 * self.r32 # Volume of CH3 groups self.V_CG = CONST_V_HL_PC * self.r_CG # Volume of CG group self.V_PCN = CONST_V_HL_PC * self.r_PCN # Volume of PCN group self.V_Chol = CONST_V_HL_PC * (1-self.r_PCN-self.r_CG) # Volume of CholCH3 group # CONST CONST_V_PG1 = CONST_V_HL_PG * 0.16 # Kucerka 2012 CONST_V_PG2 = CONST_V_HL_PG * ( 1 - 0.51 - 0.16) # Kucerka 2012 ############### X-ray scattering lengths (nm) # [example 1] rho_sol fixed rho_sol = ( CONST_b_HW + xtris*CONST_b_tris + xEDTA*CONST_b_EDTA ) / V_HW drho_Chol = ( (1-CONST_x_PG)*CONST_b_Chol/self.V_Chol + CONST_x_PG*CONST_b_PG2/CONST_V_PG2 ) - rho_sol drho_PCN = ( (1-CONST_x_PG)*CONST_b_PCN/self.V_PCN + CONST_x_PG*CONST_b_PG1/CONST_V_PG1 ) - rho_sol drho_CG = CONST_b_CG / self.V_CG - rho_sol drho_TR = CONST_b_tris/ CONST_V_tris - rho_sol drho_CH = CONST_b_CH / V_CH - rho_sol drho_CH2 = CONST_b_CH2 / V_CH2 - rho_sol drho_CH3 = CONST_b_CH3 / V_CH3 - rho_sol drho_HW = CONST_b_HW / self.V_BW - rho_sol ############### D_C polydispersity N = 200 HC_array = np.linspace(self.D_C-3*self.s_D_C, self.D_C+3*self.s_D_C, N) LogNormal = PDF_lognormal(HC_array, self.D_C, self.s_D_C) ############### calculating scattering amplitude ----------------------------------------------- self.Am = np.zeros([HC_array.shape[0],self.q.shape[0]],dtype=float) c_CH = np.zeros(HC_array.shape[0],dtype=float) c_CH3 = np.zeros(HC_array.shape[0],dtype=float) ############### c-prefactors c_Chol = ( (1-CONST_x_PG)*self.V_Chol + CONST_x_PG*CONST_V_PG2 ) / self.A_L c_PCN = ( (1-CONST_x_PG)*self.V_PCN + CONST_x_PG*CONST_V_PG1 ) / self.A_L c_CG = self.V_CG / self.A_L c_TR = CONST_V_tris*self.n_TR / self.A_L for hc in range(HC_array.shape[0]): c_CH[hc] = V_CH * CONST_n_CH / (V_HC / HC_array[hc] ) c_CH3[hc] = V_CH3 * CONST_n_CH3 / (V_HC / HC_array[hc] ) for hc in range(HC_array.shape[0]): # Adding hydrocarbon-chain envelope self.Am[hc] += 2 * drho_CH2 *HC_array[hc] * FTreal_erf(self.q, 0, 2*HC_array[hc], self.s_CH2) # Adding CH and CH3 groups self.Am[hc] += 2 * (drho_CH - drho_CH2) * c_CH[hc] * FTreal_gauss(self.q, self.d_CH, self.s_CH) self.Am[hc] += 2 * (drho_CH3 - drho_CH2) * c_CH3[hc] * FTreal_gauss(self.q, 0, self.s_CH3) # Adding hydration-water envelope self.Am[hc] += 4 * drho_HW * ( self.d_CG + self.d_PCN + self.d_Chol + CONST_d_shl) * FTreal_erf(self.q, (HC_array[hc]+(self.d_CG+self.d_PCN+self.d_Chol+CONST_d_shl)/2.), (self.d_CG+self.d_PCN+self.d_Chol+CONST_d_shl), self.s_CH2) # Adding CG, PCN and CholCH3 groups self.Am[hc] += 2 * (drho_TR - drho_HW) * c_TR * FTreal_gauss(self.q, (HC_array[hc]+self.d_TR/2.), self.s_TR) self.Am[hc] += 2 * (drho_CG - drho_HW) * c_CG * FTreal_gauss(self.q, (HC_array[hc]+self.d_CG/2.), self.s_CG) self.Am[hc] += 2 * (drho_PCN - drho_HW) * c_PCN * FTreal_gauss(self.q, (HC_array[hc]+self.d_CG+self.d_PCN/2.), self.s_PCN) self.Am[hc] += 2 * (drho_Chol - drho_HW) * c_Chol * FTreal_gauss(self.q, (HC_array[hc]+self.d_CG+self.d_PCN+self.d_Chol/2.), self.s_Chol) ############### Ensemble average self.I = np.zeros(self.q.shape[0], dtype=float) for hc in range(HC_array.shape[0]): if hc==0 or hc==N-1 : self.I+= self.Am[hc]**2 * LogNormal[hc] / 2 else : self.I+= self.Am[hc]**2 * LogNormal[hc] self.I*= 6*self.s_D_C/(N-1) ################## def intensity(self): alp = self.Rm/(self.Z+1) return ( self.Norm * self.nv*1e-6 ) * self.I * ( 16*np.pi**2*mu4(self.q,self.Z,alp) ) + self.Con*( 0.99*(1./(1+np.exp(-8*(self.q-1.)))) + 0.01 ) ################## def negative_water(self): self.check = 0 z_array = np.linspace(0.,4.,81) CG = Gauss(z_array, self.V_CG, self.D_C+self.d_CG/2., self.s_CG, self.A_L) PCN = Gauss(z_array, self.V_PCN, self.D_C+self.d_CG+self.d_PCN/2., self.s_PCN, self.A_L) Chol = Gauss(z_array, self.V_Chol, self.D_C+self.d_CG+self.d_PCN+self.d_Chol/2., self.s_Chol, self.A_L) TRIS = Gauss(z_array, self.n_TR*CONST_V_tris, self.D_C+self.d_TR/2., self.s_TR, self.A_L) BW = Slab(z_array, self.D_C+(self.d_CG+self.d_PCN+self.d_Chol+CONST_d_shl)/2., self.d_CG+self.d_PCN+self.d_Chol+CONST_d_shl, self.s_CH2) - CG - PCN - Chol - TRIS for i in(BW) : if i <-0.001 : self.check+= 1 return self.check ################################################################################################################## ################################################################################################################## # vim ts=4,sts=4,sw=4