Difference between revisions of "Analysis Tools Repository"
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An example of the .pdf output from this script is given by: | An example of the .pdf output from this script is given by: | ||
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=== MMGBSA error calculation/estimation using autocorrelation function (ACF) and Block Average standard error of the mean (BASEM) === | === MMGBSA error calculation/estimation using autocorrelation function (ACF) and Block Average standard error of the mean (BASEM) === | ||
Revision as of 12:20, 23 January 2020
This is intended to be the one-stop-shop for analysis tools and scripts for the lab.
See below for the intended list of things to be added (LastAdded: 01/07/2020 JDB)
- MMGBSA - execution and analysis
- Footprinting with amber
- Single Footprint Plot using DOCK output
- Multifootprint with dock
- ACF - BASEM
- Making 2D structures (JMOL, MarvinSketch)
- Sequence alignments
- Test set statistics
- MOE inputs, descriptions, files, scripts?
Using this repository
What is this repository?
This wiki page will serve as a jumping off point for any sort of structural biology application analysis. It should provide a streamlined, straightforward and updatable means of performing typical analyses (E.g. RMSD's of ligand from MD simulation with respect to docked pose, mmgbsa error calculation determination using autocorrelation function and block average standard error of the mean, etc.) Each writeup should ideally be able to walk the user through the purpose, functionality or usage, text output and ultimately visual output for a particular analysis allowing new users to make publication quality figures in a straightforward manner.
How to update this repository
How to add new analysis/what should each entry contain
1) A brief description of what the tool/function/set of scripts does and what it would be used for.
2) How the scripts or tools are utilized, any caveats with the scripts as they're written
3) An example figure of what the output should yield.
4) A link to the necessary scripts or code on the Rizzo Lab Github.
5) If possible a link to a publication where the analysis was used.
Analyses
RMSD - Molecular Dynamics
Single Footprint Plot using DOCK output
This analysis is used to make a plot of a single ligand's footprint to a single reference ligand's footprint in the same active site. This analysis takes in the .txt output from a DOCK6 foot print experiment. An example of the input necessary is given here:
####################################
### Molecule: 3JQZ
####################################
########## Footprint_Similarity_Score: 16.789881
########## FPS_vdw_energy: -39.298157
########## FPS_es_energy: -0.876973
########## FPS_vdw+es_energy: -40.175129
########## FPS_num_hbond: 1
########## FPS_vdw_fps: 9.620435
########## FPS_es_fps: 7.169445
########## FPS_hb_fps: 1.000000
########## FPS_vdw_fp_numres: 582
########## FPS_es_fp_numres: 582
########## FPS_hb_fp_numres: 582
resname resid vdw_ref es_ref hb_ref vdw_pose es_pose hb_pose
ASP 1 -0.000034 -0.003793 0 -0.000114 -0.005528 0
ALA 2 -0.000013 -0.000241 0 -0.000036 -0.000104 0
HIS 3 -0.000026 -0.000039 0 -0.000070 -0.000669 0
LYS 4 -0.000018 0.030323 0 -0.000047 0.047062 0
SER 5 -0.000018 -0.000741 0 -0.000050 -0.001367 0
GLU 6 -0.000045 -0.048775 0 -0.000150 -0.085807 0
VAL 7 -0.000049 -0.001396 0 -0.000145 -0.002414 0
ALA 8 -0.000025 -0.001057 0 -0.000065 -0.001366 0
HIS 9 -0.000049 -0.001855 0 -0.000140 -0.002446 0
ARG 10 -0.000105 0.055728 0 -0.000347 0.101644 0
PHE 11 -0.000088 -0.001446 0 -0.000206 -0.001470 0
LYS 12 -0.000053 0.042200 0 -0.000118 0.062812 0
ASP 13 -0.000065 -0.053499 0 -0.000161 -0.080764 0
LEU 14 -0.000148 -0.001055 0 -0.000385 0.000664 0
GLY 15 -0.000054 -0.003380 0 -0.000112 -0.006003 0
GLU 16 -0.000104 -0.059889 0 -0.000186 -0.079039 0
GLU 17 -0.000227 -0.089700 0 -0.000368 -0.113150 0
ASN 18 -0.000253 -0.005105 0 -0.000552 -0.008797 0
PHE 19 -0.000219 -0.002475 0 -0.000560 -0.007674 0
LYS 20 -0.000268 0.071310 0 -0.000540 0.096399 0
...etc (The .txt file will have as many lines as there are number of residues in the receptor.
The python script is called plot_footprint_single_magnitude.py
The usage for this script is:
python plot_footprint_single_magnitude.py {footprint_similarity_output_text_file} 50
{footprint_similarity_output_text_file} is the path/to/the/.txt file described above 50 is the number of residues considered when making the plot, the remaining values are lumped together into a reminder field.
The output of this experiment is a .pdf file that can easily be opened in preview on a mac and converted to jpeg or png.
An example of the .pdf output from this script is given by:
