inst/scripts/analysis/plots/hbonds/chi_sinBAH_polar_scatter_by_chem_type_long_range.R

In momeara/RosettaFeatures: Tools for analyzing macromolecular feature distributions with Rosetta

# -*- tab-width:2;indent-tabs-mode:t;show-trailing-whitespace:t;rm-trailing-spaces:t -*-
# vi: set ts=2 noet:
#
# (c) Copyright Rosetta Commons Member Institutions.
# (c) This file is part of the Rosetta software suite and is made available under license.
# (c) The Rosetta software is developed by the contributing members of the Rosetta Commons.
# (c) For more information, see http://www.rosettacommons.org. Questions about this can be
# (c) addressed to University of Washington UW TechTransfer, email: license@u.washington.edu.

library(ggplot2)
library(plyr)
library(dplyr)

source("hbond_geo_dim_scales.R")

feature_analyses <- c(feature_analyses, methods::new("FeaturesAnalysis",
id = "chi_sinBAH_polar_scatter_by_chem_type_long_range",
author = "Matthew O'Meara",
brief_description = "",
feature_reporter_dependencies = c("HBondFeatures"),
run=function(self, sample_sources, output_dir, output_formats){



d_ply(sample_sources, .variables=("sample_source"), function(sample_source){
  ss <- sample_source[1,"sample_source"]

  sele <-"
  SELECT
    geom.cosBAH,
    geom.chi,
  	acc_atoms.base2_x AS p1x, acc_atoms.base2_y AS p1y, acc_atoms.base2_z AS p1z,
  	acc_atoms.base_x  AS p2x, acc_atoms.base_y  AS p2y, acc_atoms.base_z  AS p2z,
  	acc_atoms.atm_x   AS p3x, acc_atoms.atm_y   AS p3y, acc_atoms.atm_z   AS p3z,
	  don_atoms.atm_x   AS p4x, don_atoms.atm_y   AS p4y, don_atoms.atm_z   AS p4z,
    acc_site.HBChemType AS acc_chem_type,
    don_site.HBChemType AS don_chem_type,
    CASE acc_site.HBChemType
			WHEN 'hbacc_IMD' THEN 'ring' WHEN 'hbacc_IME' THEN 'ring'
			WHEN 'hbacc_AHX' THEN 'sp3'  WHEN 'hbacc_HXL' THEN 'sp3'
			WHEN 'hbacc_CXA' THEN 'sp2'  WHEN 'hbacc_CXL' THEN 'sp2'
			WHEN 'hbacc_PBA' THEN 'sp2'  END AS hybrid
  FROM
    hbond_geom_coords AS geom,
    hbonds AS hbond,
    hbond_sites AS don_site,
    hbond_sites AS acc_site,
	  hbond_site_atoms AS don_atoms,
  	hbond_site_atoms AS acc_atoms
  WHERE
    hbond.struct_id = geom.struct_id AND hbond.hbond_id = geom.hbond_id AND
    hbond.struct_id = don_site.struct_id AND hbond.don_id = don_site.site_id AND
    hbond.struct_id = acc_site.struct_id AND hbond.acc_id = acc_site.site_id AND
    ABS(don_site.resNum - acc_site.resNum) > 5 AND
	  don_atoms.struct_id = hbond.struct_id AND don_atoms.site_id = hbond.don_id AND
  	acc_atoms.struct_id = hbond.struct_id AND acc_atoms.site_id = hbond.acc_id;"
  f <- query_sample_sources(sample_source, sele)

	f$acc_chem_type_name <- acc_chem_type_name_linear(f$acc_chem_type)
	f$don_chem_type_name <- don_chem_type_name_linear(f$don_chem_type)
	f <- na.omit(f, method="r")

	normalize <- function(xin,yin,zin) {
		len = sqrt(xin*xin+yin*yin+zin*zin)
		data.frame(x=xin/len, y=yin/len, z=zin/len)
	}

	vlen <- function(xin,yin,zin) {
		sqrt(xin*xin+yin*yin+zin*zin)
	}

	cross <- function(x1,y1,z1,x2,y2,z2){
		data.frame(x=(y1 * z2 ) - (z1 * y2 ),y=(z1 * x2 ) - (x1 * z2 ),z=(x1 * y2 ) - (y1 * x2 ))
	}

	dot_prod <- function(p1,p2){
		p1$x*p2$x + p1$y*p2$y + p1$z*p2$z
	}

	dihedral_angle <- function(x1,y1,z1,x2,y2,z2,x3,y3,z3,x4,y4,z4){
		v1 <- normalize(x2-x1, y2-y1, z2-z1)
		v2 <- normalize(x3-x2, y3-y2, z3-z2)
		v3 <- normalize(x4-x3, y4-y3, z4-z3)
		x <- dot_prod(v1,v2) * dot_prod(v2,v3) - dot_prod(v1,v3)
		y <- dot_prod(v1,cross(v2$x, v2$y, v2$z, v3$x, v3$y, v3$z))
		atan2(y,x)
	}

	alt_chi_dihedral_angle <- function(x1,y1,z1,x2,y2,z2,x3,y3,z3,x4,y4,z4){
		vbx <- (x2+x1)/2; vby <- (y2+y1)/2; vbz <- (z2+z1)/2  # virtual base
		v1x <- x2-x1;     v1y <- y2-y1;     v1z <- z2-z1      # b2 -> b
		v2x <- x3-x2;     v2y <- y3-y2;     v2z <- z3-z2      # b2 -> b
		vb2 <- cross(v1x, v1y, v1z, v2x, v2y, v2z)            # virtual abase2
#		print(paste("vb2:", vb2$x, vb2$y, vb2$z))
#		print(paste("vb: ", vbx, vby, vbz))
#		print(paste("p3: ", x3, y3, z3))
#		print(paste("p4: ", x4, y4, z4))
		dihedral_angle(vb2$x, vb2$y, vb2$z, vbx, vby, vbz, x3, y3, z4, x4, y4, z4)
	}

#	print(dihedral_angle(1,0,0, 0,1,0, 0,0,0, -1,-1,-1))
#	print(alt_chi_dihedral_angle(1,0,0, 0,1,0, 0,0,0, -1,-1,1))
#	print(alt_chi_dihedral_angle(c(1,1),c(0,0),c(0,0), c(0,0),c(1,1),c(0,0), c(0,0),c(0,0),c(0,0), c(-1,-1),c(-1,-1), c(1,-1)))

	f[f$hybrid == "sp3" | f$hybrid == "ring", "chi"] <- with(f[f$hybrid == "sp3" | f$hybrid == "ring",],
		alt_chi_dihedral_angle(p1x, p1y, p1z, p2x, p2y, p2z, p3x, p3y, p3z, p4x, p4y, p4z))

	alt_sp3_cosBAH <- function(x1,y1,z1, x2,y2,z2, x3,y3,z3, x4,y4,z4){
		vbx <- (x2+x1)/2; vby <- (y2+y1)/2; vbz <- (z2+z1)/2  # virtual base
		v1 <- normalize(x3-vbx, y3-vby, z3-vbz)
		v2 <- normalize(x4-x3, y4-y3, z4-z3)
		dot_prod(v1, v2)
	}
	f[f$hybrid == "sp3", "cosBAH"] <- with(f[f$hybrid == "sp3",],
		alt_sp3_cosBAH(p1x, p1y, p1z, p2x, p2y, p2z, p3x, p3y, p3z, p4x, p4y, p4z))

  #equal area projection
  f <- transform(f,
    capx = 2*sin(acos(cosBAH)/2)*cos(chi),
    capy = 2*sin(acos(cosBAH)/2)*sin(chi))

	sub_f <- f %>%
		group_by(don_chem_type_name, acc_chem_type_name) %>%
		filter(sample.int(n()) <= 5000)

  plot_id = "hbond_sinBAH_eq_polar_scatter_by_chem_type_long_range"
  ggplot(data=sub_f) + theme_bw() +
		polar_equal_area_grids_bw() +
    geom_point(aes(x=capx, y=capy), size=.4, alpha=.5) +
    facet_grid(acc_chem_type_name ~ don_chem_type_name) +
    ggtitle(paste("Hydrogen Bonds chi vs sinBAH Angles by Chemical Type with Sequence Separation > 5\nEqual Coordinate Projection   Sample Source: ", ss, sep="")) +
    scale_x_continuous('', breaks=c(-1, 0, 1)) +
    scale_y_continuous('', breaks=c(-1, 0, 1))
  save_plots(self, plot_id, sample_source, output_dir, output_formats)

	ddply(f, .(acc_chem_type_name, don_chem_type_name), function(df){
		don_chem_type <- as.character(df$don_chem_type[1])
		acc_chem_type <- as.character(df$acc_chem_type[1])
		don_chem_type_name <- as.character(df$don_chem_type_name[1])
		acc_chem_type_name <- as.character(df$acc_chem_type_name[1])

		plot_id = paste("hbond_sinBAH_eq_polar_scatter_long_range", don_chem_type, acc_chem_type, ss, sep="_")
  	ggplot(data=df) + theme_bw() +
			polar_equal_area_grids_bw(bgcolor="#00007F") +
  	  geom_point(aes(x=capx, y=capy), size=.4, alpha=.5) +
  	  ggtitle(paste("Hydrogen Bonds chi vs sinBAH Angles ", don_chem_type_name, acc_chem_type_name, " with Sequence Separation > 5\nEqual Coordinate Projection   Sample Source: ", ss, sep="")) +
  	  scale_x_continuous('', breaks=c(-1, 0, 1)) +
  	  scale_y_continuous('', breaks=c(-1, 0, 1))
  	save_plots(self, plot_id, sample_source, output_dir, output_formats)
	})


#  #orthographic projection
#  f <- transform(f,
#    capx = sin(acos(cosBAH))*cos(chi),
#    capy = sin(acos(cosBAH))*sin(chi))
#
#  sub_f <- ddply(f, .variables=c("don_chem_type_name", "acc_chem_type_name"),
#    function(df){sample_rows(df, 5000)})
#
#  plot_id = paste("hbond_sinBAH_ortho_polar_scatter_by_chem_type_long_range", ss, sep="_")
#  ggplot(data=sub_f) + theme_bw() +
#    geom_point(aes(x=capx, y=capy), size=.5, alpha=.4) +
#    facet_grid(acc_chem_type_name ~ don_chem_type_name) +
#    ggtitle(paste("Hydrogen Bonds chi vs sinBAH Angles by Chemical Type with Sequence Separation > 5\nOrthographic Projection   Sample Source: ", ss, sep="")) +
#    scale_x_continuous('', breaks=c(-1, 0, 1)) +
#    scale_y_continuous('', breaks=c(-1, 0, 1))
#  save_plots(self, plot_id, sample_source, output_dir, output_formats)

})



})) # end FeaturesAnalysis