DL COMP BIOTECH

There are various tools for the identification of the pockets from the dynamic structures i.e, MD simulation traj 

The step-by-step tutorial for calculations are well elaborated in this link: http://ambermd.org/tutorials/advanced/tutorial3/ However, the purpose of this blog is to provide briefings on the main calculation steps. After MD trajectory: you need to source the amber.sh file before running any PBSA/GBSA calculations. source $AMBERHOME/amber.sh  for running the mm-gbsa/pbsa, run the following command: mpirun -np 6 $AMBERHOME/bin/MMPBSA.py.MPI -O -i mmpbsa16.in -o FINAL_RESULTS_MMPBSA16.dat -eo pbsa.csv -do decom.dat -deo decom.csv -sp comp_solv.prmtop -cp comp.prmtop -rp pro.prmtop -lp lig.prmtop -y md_100ns.nc here, both MM-GBSA and MM-PBSA calculations are performed. Their outputs are in the following files: FINAL_RESULTS_MMPBSA16.dat: contains the date/time, any warnings based on the values and files given, the mm-pbsa.in text, the files used by the script, the number of frames analyzed, and which PB solver (if any) was used. The rest of the statistics file includes all the average...

PCA analysis through CPPTRAJ module of AmberTools: > source $AMBERHOME/amber.sh > $AMBERHOME/bin/cpptraj > parm comp_solv.prmtop > trajin comp_150ns.nc > center > autoimage > rms first @CA mass > average crdset avg_set > createcrd traj_set > run > crdaction traj_set rms ref avg_set @CA > crdaction traj_set matrix covar :116-229@CA name pro_covar out covmat.dat #writes covariance matrix based on the selection of residues > runanalysis diagmatrix pro_covar out evecs.dat vecs 100 name myevecs nmwiz nmwizvecs 100 nmwizfile porcupine.nmd nmwizmask :116-229@CA #writes the information about 100 principal components (first 100 PCs) for that particular selection,  produces .nmd file that can be used to generate porcupine plots in normal mode wizard plugin of VMD. > runanalysis modes eigenval name myevecs out evalfrac.dat  gives output about the eigen values, fraction of contribution, cumulative contributions of  eigen vectors(or PCs) (in ...

 The basic instructions remain same as  FEL 3D plots .  These plots are published in  Interplay among Structural Stability, Plasticity, and Energetics Determined by Conformational Attuning of Flexible Loops in PD-1 Fel2d.py ## FEL using plot_surface import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import random from matplotlib import cm from scipy.interpolate import griddata from scipy.interpolate import Rbf from numpy import linspace #from matplotlib.ticker import LinearLocator, FormatStrFormatter import matplotlib from scipy import interpolate import matplotlib.mlab as ml fig = plt.figure(figsize=None, dpi=300, facecolor=None, edgecolor=None, linewidth=0.0, frameon=None, subplotpars=None, tight_layout=None) ax = fig.add_subplot(111) ### input file with x,y,z coordinates x,y,z = np.loadtxt('5wt9gibbs.txt').T  X,Y = np.unique(x),np.unique(y) xi = linspace(min(X),max(X),len(X)) yi = linspace(min(Y),max(Y),len(Y)) xi,yi = ...

  Principal component analysis and Free energy landscapes of protein systems in gromacs. >gmx covar -f md_t14cnopbc.xtc -s md_t14c.tpr -o eigenval.xvg -v eigenvect.trr -xpm covara.xpm [least squares fit:c-alpha; covariance: c alpha] >gmx xpm2ps -f covara.xpm -o covara.eps -do covar.m2p >gmx anaeig -v eigenvect.trr -f md_t14cnopbc.xtc -s md_t14c.tpr -first 1 -last 2 -proj proj_eig.xvg -2d 2d_proj.xvg >gmx sham -f 2d_proj.xvg -ls gibbs.xpm -notime #for free energy, "sham" module uses PC1 and PC2 file gmx xpm2ps -f gibbs.xpm  -o gibbs.eps -rainbow red python xpm2txt.py -f gibbs.xpm -o gibbs.txt  #xpm2txt.py is mentioned here. Just copy and paste this script. Run in command line as mentioned above #!/usr/bin/env python import sys """ Utility tool to convert xpm files generated by GROMACS to a 3-column text file. """ USAGE = "USAGE: xpm2txt.py -f <input xpm file> -o <output txt file> [-s]\n" USAGE+= "Options:\n...

  # To plot FEL in 3D use this python script and run as python2.7 fel3d.py. Here the file uses gibbs.txt. therefore before running the script make sure u have the gibbs.txt in the same folder of this script or else provide the location of the script.  I have attached some images from my research article using the same script for 3D FEL plot These plots are published in  Interplay among Structural Stability, Plasticity, and Energetics Determined by Conformational Attuning of Flexible Loops in PD-1 The 2D FEL scripts are also mentioned in the next blog:  Python script to plot 2D FEL Another point to consider is: when u r plotting FEL plots for multiple systems, make sure your color bar/gradient should be same in all the plots. So u can  change the values in vmax,  ax.set_zlim(0, 18),  ticks=range(0, 21, 2)) in the script below.  Like in my case the highest value was 18 in gibbs free energy (the z axis) in all the axis. therefore i mentioned 18 there...

ParmEd supports reading and writing to a broad variety of file types, including Amber topology and coordinate files, CHARMM PSF, parameter, topology, and coordinate files, and Tinker parameter, topology, and coordinate files. (Ref: https://github.com/ParmEd/ParmEd) installing ParmED 1. download from https://github.com/ParmEd/ParmEd.git  or type this command in the terminal: wget https://github.com/ParmEd/ParmEd/archive/refs/heads/master.zip 2. cd parmedED-master 3. python2.7 setup.py install 4. python setup.py install --prefix=$AMBERHOME 5. source $AMBERHOME/amber.sh python2.7 >>>import parmed as pmd >>> amber=pmd.load_file('pro_solv.prmtop', 'pro_solv.inpcrd') >>> amber.save('prosolv.top') >>> amber.save('prosolv.gro') vmd >>> save .trr trajectory file  OR  trajout .xtc file in cpptraj It can also convert various files to other formats such as: 1. convert GROMACS topology to AMBER format 2. convert AMBER to...

Before beginning any homology modelling, verify that the templates in Blastp (protein blast) are suitable for constructing the model for your query sequence using the pdb as the search set.  If you obtain greater than 40% sequence similarity, you can proceed with homology modelling.  If you have Schrodinger, you can use the PRIME homology modelling module in this suite. Otherwise, I-TASSER, SWISS-MODEL, or Phyre2 servers may be used.  Additionally, Modeller can be utilized. It is a self-contained programme. If the sequence similarity of your protein is really low, then try to search with  DELTA-BLAST  (Domain Enhanced Lookup Time Accelerated BLAST) option in BLASTp . It will yield better homology detection. Or you can proceed with threading-based or ab-initio modelling.  Additionally, secondary structure prediction can be performed prior to modelling. This can be accomplished with PSIPRED or JPRED, for example. There are two forms of modelling: single templ...

#here the command measures the distance between two loops (considering the c-alpha atoms in the loop) and prints output in L1-L2.dat. For amber MD trajectory you may try using the following commands in CPPTRAJ: $AMBERHOME/bin/cpptraj >parm pro_solv.prmtop >trajin md-autoimage.nc >rmsd pro @CA,C,O,N,H first mass >distance :135-149@CA :156-166@CA out L1-L2.dat >run Reference: Interplay among Structural Stability, Plasticity, and Energetics Determined by Conformational Attuning of Flexible Loops in PD-1. https://doi.org/10.1021/acs.jcim.0c01080 https://www.researchgate.net/publication/348511593_Interplay_among_Structural_Stability_Plasticity_and_Energetics_Determined_by_Conformational_Attuning_of_Flexible_Loops_in_PD-1

#Web servers for calculation of RMSD values between a ligand poses.  Please note: One pose should be a reference pose and another should be a query pose. PLDbench:  The RMSD value between two molecules can be calculated using PLDbench. There are four modules in this webserver. Single: This module's functionality is limited to calculating RMSD for the 57 complexes utilized in the benchmarking study. Users must submit the docked pose of a ligand that corresponds to one of the 57 PDB-IDs offered in the drop down option in this module. It accepts three file formats: '.pdb', '.mol2', and '.sdf'. Users can choose the type of RMSD they want to compute. Standard heavy-atom RMSD, Hungarian (symmetry-corrected) heavy-atom RMSD, and Minimum-distance heavy-atom RMSD can all be calculated using this module. As a result, the Hungarian (symmetry-corrected) heavy-atom RMSD value is returned by default.  Link for the server:https://webs.iiitd.edu.in/raghava/pldbench/single.p...

Simple life hacks of bygone times: Clock in a candle  Time is a valuable commodity. One can never reclaim the time he has already lived. Since ancient times, time management has been a necessary skill to acquire. Although the art of time management is not everyone's cup of tea, the ever-evolving technology has aided us significantly in accomplishing this feat. In comparison to now, the old days, when technology was still a baby, lacked many conveniences, as managing time could not have been more difficult in the absence of a clock. However, as the proverb 'necessity is the mother of invention' states, our forefathers came up with a simple yet magnificent idea that resulted in the discovery of an alarm clock made entirely of candles. A candle, a few screws, and a metal plate were all they required. Screws were used to denote time intervals. When the candle burns all the way to the first screw, it falls into the metal plate, producing a "clang," and the proces...

 Blog #6 Hi everyone. There is an extremely useful database called "DIA-DB: A Database and Web Server for the Prediction of Diabetes Drugs," which is recently reported in the American Chemical Society's Journal of Chemical Information and Modeling (JCIM). This is the first and open access web server for the prediction of diabetes drugs. It does not require any registrations and the user receives an email with a comprehensive report containing the prediction results.  It employs two distinct approaches: a) 3D shape-based similarity approach for comparison of antidiabetic approved and experimental compounds. b) inverse virtual screening of the input molecules chosen by users: It performs large-scale inverse docking (using Autodock Vina) on a collection of proteins involved in diabetes with the goal of identifying a query compound's possible target. Researchers may also use the DIA-DB to find out whether any of the already-approved or experimental compounds are included ...

Blog#5 ChemProp can be used to estimate the properties of molecules by utilising a Message Passing Neural Network (MPNN). To make predictions, an MPNN must first be trained on a dataset of molecules with known property values. Once trained, the MPNN can be used to predict similar properties in any new molecule. Here is the link:http://chemprop.csail.mit.edu Till now it has provided models for predicting that molecules can inhibit the growth of bacteria ( antibiotic property), 3Cl pro/mpro of sars-cov. The SARS balanced model is for more exhaustive prediction. AMU SARS-CoV-2 in vitro is for the  estimation of probability that molecule with inhibit the virus replication in vitro)

 Blog #4 Novel drug targets and their mechanism of action : In the United States, the European Union, and Japan, 61 novel drugs were FDA approved in 2020.  Therefore, we feel that this would help students to shortlist their dissertation or Ph.D. topics and explore them. The details are mentioned in the link below. https://www.nature.com/articles/d41573-021-00057-z The main reference is: https://www.nature.com/articles/nrd.2016.230

BLOG #3  Hi Guys,           This is a new tutorial on how to simulate a protein-ligand system: basic steps using AMBER. Before we begin, I hope you have read our previous post on AMBER TUTORIAL-1, since I will only be providing additional information with the ligand here, rather than repeating the previous instructions. #To parameterize the ligand file, we start with Antechamber and then parmchck.  These are a series of tools for creating files for organic molecules and some protein metal centers, which can then be read into LEaP. Junmei Wang created the Antechamber suite, which is intended to be used in conjunction with the general AMBER force field (GAFF) (gaff.dat). This is the package's most crucial program. It can convert a variety of files and assign atomic charges and types to them as well. Sqm (or, alternatively, mopac or divcon), atomtype, am1bcc, bondtype, espgen, respgen, and prepgen are among the programs that antechamber runs in respo...

  Blog #2 Hii guys, This is a new blog for researchers looking to publish their work in reputable journals. You can use  JounalFinder:  https://journalfinder.elsevier.com/ Springer Journal Suggester: https://journalsuggester.springer.com/ Taylor and Francis Journal Suggester : https://authorservices.taylorandfrancis.com/publishing-your-research/choosing-a-journal/journal-suggester/ Here you need to e nter the title and abstract of your paper to easily find journals that could be best suited for publishing.  They uses smart search technology and field-of-research-specific vocabularies to match your paper to scientific journals. Thanks. :)

BLOG #1 This blog is for beginners in MD simulation. After installation of AMBER, you may start this tutorial by choosing any protein with no ligand or water i.e. APO protein.  Key points to consider: - Prepare your protein in terms of bond order, terminal capping (add ACE and NME on the N and C- terminals to prevent terminal residues interaction with the solvent), add disulfide bonds if exists in a protein structure like in the case of an immunoglobulin protein family (eg. CD28, PD-1, PD-L1, CD80, etc.), fill the missing regions or breaks in your crystal, etc. #if you have prepared the protein in Maestro (Schrodinger), change the NMA to NME, increment the residue number, convert CA to CH3 in the pdb file with help of a text editor .. see example below:) file before editing: ATOM   1011  CE1 HIS A 143      26.670  14.396 200.638  1.00  0.00           C ATOM   1012  NE2 HIS A 143    ...