Membrane Protein Lipid Composition Atlas

How to keep chain ID / IDs in GROMACS?

In GROMACS , while converting pdb file (monomer or multimer) into .gro file, it do not preserve the chain ID information. Due to the lack of chain ID information, pdb file retrieved from .gro file at any stage of the simulation has missing chain IDs and pdb file can not be visualized properly in PYMOL / RASMOL . There are two ways to convert .gro file into .pdb Lets say your protein name is xyz.pdb 1] gmx editconf -f xyz.gro -o xyz.pdb 2] gmx trjconv -f xyz.gro -o xyz.pdb -s xyz.tpr Only ' trjconv ' will retrieve the chain ID information for all the chains. and not ' editconf '. If you have monomer protein and wish to assign any chain ID then following command will be of your interest: gmx editconf -f xyz.gro -o xyz.pdb -label [ chain-ID ]

Python : Turtle tree

Turtle module can be used to draw some very nice patterns in Python. Following are some examples with code. ==================== import turtle import random t = turtle.Turtle( shape = "circle" ) t.lt( 90 ) lv = 14 l = 120 s = 30 t.color( 'indigo' ) t.width(lv) t.penup() t.bk(l) t.pendown() t.fd(l) def draw_tree ( l , level ): width = t.width() # save the current pen width t.width(width * 3.0 / 4.0 ) # narrow the pen width l = 3.0 / 4.0 * l #t.color(R,G,B) #provide the RGB numbers t.color(random.random(), random.random(), random.random()) t.lt(s) t.fd(l) if level < lv: draw_tree(l, level + 1 ) t.color(random.random(), random.random(), random.random()) t.bk(l) t.rt( 2 * s) t.fd(l) if level < lv: draw_tree(l, level + 1 ) t.color(random.random(), random.random(), random.random()) t.bk(l) t.lt(s) t.width(width) # restore the previous pen width t.speed( "fastest" ) draw_tree(l, 5 ) turtle.done() ===========

GNUPLOT: How to draw trend line?

How to draw trend line in the GNUPLOT? If you like to plot graphs in gnuplot and dont know how to plot trendline then here you are. Follow the steps mentioned below... 1. You should have a files with X and Y values 2. Open GNUPLOT (Operating system dosen't change anything here. It works on all systems) 3. Type the command in the gnuplot terminal Lets say I have a file for eg. '1.txt' p '1.txt' u 1:2 w d title '', '1.txt' u 1:2 smooth acsplines title '1.txt' OR p '1.txt' u 1:2 w d title '', '1.txt' u 1:2 smooth bezier title '1.txt' It will plot as below...

How to use MODELLER to build DIMER homology model with ligand?

How to use MODELLER to build DIMER homology model with ligand? Procedure: Get Fasta sequence from UNIPROT database. Predict sequence alignment from HHPRED Prepare INPUT files for MODELLER model-dimer.py (Click to download) ############### from modeller import * from modeller.automodel import * #from modeller import soap_protein_od env = environ() env.io.hetatm = True a = automodel(env, alnfile='TvLDH-1bdm.ali', knowns='1bdm', sequence='TvLDH', assess_methods=(assess.DOPE, #soap_protein_od.Scorer(), assess.GA341)) a.md_level = refine.very_slow a.starting_model = 1 a.ending_model = 1 #Number of output models a.final_malign3d = True a.make() ################ TvLDH-1bdm.ali (Click to download) (Alignment taken from SALI LAB) >P1;1bdm structureX:1bdm.pdb: 0: A: 333: B:u

Plagarism Checker

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1.		Archaebacterial membrane
2.		Bacterial Gram-negative inner membrane
3.		Bacterial Gram-negative outer membrane
4.		Bacterial Gram-positive outer membrane
5.		Bacterial Gram-positive plasma membrane
6.		Chloroplast inner membrane
7.		Chloroplast outer membrane
8.		Cytoplasmic granule membrane
9.		Endoplasmic reticulum membrane
10.		Endosome membrane
11.		Eukaryotic plasma membrane
12.		Golgi membrane
13.		Lysosome membrane
14.		Mitochondrial inner membrane
15.		Mitochondrial outer membrane
16.		Nuclear inner membrane
17.		Nuclear outer membrane
18.		Peroxisome membrane
19.		Secreted
20.		Thylakoid membrane
21.		Undefined
22.		Vacuole membrane
23.		Vesicle membrane
24.		Viral membrane

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