Shruti Journal Document

EXPERIMENT NO. 1 AIM: Homology Modelling using MODELLER REQUIREMENT: Monitor, CPU, Mouse, Operating system, internal connection. THEORY: MODELLER is used for homology or comparative modeling of protein three-dimensional structures. It implements a technique inspired by nuclear magnetic resonance known as satisfaction of spatial restraints, by which a set of geometrical criteria are used to create a probability density function for the location of each atom in the protein. The method relies on an input sequence alignment between the target amino acid sequence to be modeled and a template protein whose structure has been solved. The user provides an alignment of a sequence to be modeled with known related structures and MODELLER automatically calculates a model containing all non-hydrogen atoms. MODELLER implements comparative protein structure modeling by satisfaction of spatial restraints. and can perform many additional tasks, including de novo modeling of loops in protein structures, optimization of various models of protein structure with respect to a flexibly defined objective function, multiple alignment of protein sequences and/or structures, clustering, searching of sequence databases, comparison of protein structures, etc. PROCEDURE: 1.

Take query sequence whose structure needs to be modelled in PIR format.

2.

Save the file with .ali extension in the bin folder of modeller.

3.

Open build_profile.py file. Change the append filename to the query sequence.

4.

Open the command line by clicking the 'Modeller' link from the Start Menu in Windows.

5.

Run the build_profile.py.This will search for potentially related sequences of known structure. Two files are created build_profile.ali file and build_profile.prf file.

6.

Open the build_profile.prf file and select the sequences which has an e value 0.0 .

7.

Download the structures of the selected protein from the PDB and save it in bin folder of modeller.

8.

Open the compare.py file.Write the the name of the selected proteins.

9.

Run compare.py command in command line. A compare.log output file is created.

10.

Choose the sequence with high resolution and moderate identity.

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11.

Align the query sequence with the template by using align2d command.

12.

Two output files are created .pap file and .ali file.

13.

Open model_single.py file .Use the above created .ali file .Run the model_single.py command in the command line.

14.

5 possible models are generated .Select the best model which has the lowest dope score.

15.

Run evaluate_model.py command for evaluating the selected model.Note the Dope score.

16.

Run evaluate_template.py command for evaluating the template. Note the Dope score.

17.

Compare the dope score of both model and template.

OUTPUT: Build_profile.py file:

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Build_profile.ali file :

Compare.py file :

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Compare.log file :

Model_single.py file :

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Evaluate_model.py file :

Evaluate_template.py file :

RESULT: homology modelling was carried out successfully using modeller baseic_example

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EXPERIMENT NO. 2 AIM: Advanced Homology Modelling using MODELLER and PRoSa REQUIREMENT: Monitor, CPU, Mouse, Operating system, internal connection. THEORY: MODELLER: MODELLER is used for homology or comparative modeling of protein three-dimensional structures. It implements a technique inspired by nuclear magnetic resonance known as satisfaction of spatial restraints, by which a set of geometrical criteria are used to create a probability density function for the location of each atom in the protein. The method relies on an input sequence alignment between the target amino acid sequence to be modeled and a template protein whose structure has been solved. The user provides an alignment of a sequence to be modeled with known related structures and MODELLER automatically calculates a model containing all non-hydrogen atoms. MODELLER implements comparative protein structure modeling by satisfaction of spatial restraints. and can perform many additional tasks, including de novo modeling of loops in protein structures, optimization of various models of protein structure with respect to a flexibly defined objective function, multiple alignment of protein sequences and/or structures, clustering, searching of sequence databases, comparison of protein structures, etc. ProSa: ProSa is a powerful tool in protein structure research. ProSa supports and guides studies aimed at the determination of a protein's native fold. It is helpful for experimental structure determinations and modeling studies. It helps to determine whether the protein structure is correct and if there any faulty parts PROCEDURE: Prosa 1.

Go to ProSA website https://prosa.services.came.sbg.ac.at/prosa.php

2.

Click on browse and load the model CaLDH.B99990003.pdb and click Analyse.

3.

Note the Z-score.

4. ProSA-web shows the 3D structure of the input protein using the molecule viewer Jmol.Select the loop region which is highly unstable (red coloured portion).Note the range of amino acid that loop region. Loop refinement using modeler : 7

1.

Open loop_refine.py file. Write the range of the selected loop region.

2. Run the loop_refine.py in command line.This generates 10 models of the model with refined loop regions. 3.

Compute energies of all the 10 generated models using model_energies.py command.

4.

Select the model with lowest energy.

OUTPUT:

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Loop_refine.py file :

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Evaluate_model.py file :

RESULT: advanced homology modelling was done using Modeller and Prosa.

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EXPERIMENT NO. 3 AIM: Protein manipulation using SPDBv REQUIREMENT: Monitor, CPU, Mouse, Operating system, internal connection. THEORY: Swiss-Pdb viewer is an application that provides a user friendly interface allowing analyzing several proteins at the same time. The protein can be superimposed in order to deduce structural slignments and compare their active sites or any other relevant parts. Amino acid mutation, Hbonds, angle and distances between atoms are easy to obtain from the intuitive graphics and menu interface. Swiss-Pdb viewer can also read electron density maps, and provides various tools to build into the density. In, addition various modeling tools are integrated and command files for popular energy minimization packages can be generated. PROCEDURE: Wild Protein : 1.

Open the structure in Swiss PDB viewer.

2.

Go to build->Add hydrogens.

3.

Go to tools->Compute hydrogen.

4.

Select the residue we want to mutate(e.g VAL 11).

5.

Go to Display->Show only H-bonds from selection

6.

Go to Display->Show only groups with visible H-bonds .This will show the neighbouring residue which is interacting with the selected residue.

7.

Select all residue.Go to Tools->Energy minimization.

8.

Go to Tools->Compute energy (Force Field).Note the energies of the selected and neighbouring residues.

9.

Go window->Ramachandran plot.

Mutant protein 10.

Open the structure in Swiss PDB viewer.

11.

Select residue Val11 from the control panel.

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12.

Select the Mutate tool from the tool bar .Select the Val11 and mutate it to Ala in the structure.

13.

Select the rotamer with highest negative score.

14.

Select all residues.Go to build->Add hydrogens.

15.

Go to tools->Compute hydrogen.

16.

Select Ala11 from the control panel.

17.

Go to Display->Show only H-bonds from selection

18.

Go to Display->Show only groups with visible H-bonds .This will show the neighbouring residue which is interacting with the selected residue.

19.

Select all residue.Go to Tools->Energy minimization.

20.

Go to Tools->Compute energy (Force Field).Note the energies of the selected and neighbouring residues.

21.

Go window->Ramachandran plot.

OUTPUT:

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Fig 1: Multiple Alignment in ClustalW

Fig 2: Results in ClustalW

RESULT: protein manipulation was done using Swiss PDB viewer

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EXPERIMENT NO. 4 AIM: Protein – Ligand docking using HEX REQUIREMENT: Monitor, CPU, Mouse, Operating system, internal connection. THEORY: HEX Hex is an interactive molecular graphics program for calculating and displaying feasible docking modes of pairs of protein and DNA molecules. Hex can also calculate protein-ligand docking, assuming the ligand is rigid, and it can superpose pairs of molecules using only knowledge of their 3D shapes. Hex has been available for about 12 years now, it is still the only docking and superpostion program to use spherical polar Fourier (SPF) correlations to accelerate the calculations, and its still one of the few docking programs which has built-in graphics to view the results. The graphical nature of Hex came about largely to visualise the results of such docking calculations in a natural and seamless way, without having to export unmanageably many (and usually quite big) coordinate files to one of the many existing molecular graphics programs. For this reason, the graphical capabilities in Hex are generally relatively primitive compared to professional molecular graphics packages, but you're aiming to use Hex to do docking, not to make publication-quality images. In Hex's docking calculations, each molecule is modelled using 3D expansions of real orthogonal spherical polar basis functions to encode both surface shape and electrostatic charge and potential distributions. Essentially, this allows each property to be represented by a vector of coefficients (which are the the components of the basis functions). Hex represents the surface shapes of proteins using a two-term surface skin plus van der Waals steric density model, whereas the electrostatic model is derived from classical electrostatic theory. By writing expressions for the overlap of pairs of parametric functions, one can obtain an overall docking score as a function of the six degrees of freedom in a rigid body docking search. Hex will remain primarily a docking program, the 3D superposition calculations implemented in Hex demonstrate the potential for performing fast 3D superpositions using the SPF correlation approach. Work is in progress to develop this approach further as a separate program for high throughput ligand screening. PROCEDURE: 1.

Download structure which is bound to a ligand from pdb.

2.

Open the structure in swisspdb viewer.

3.

Select ligand(eg GDP) from the structure. Save the ligand as gdp.pdb file.

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4.

Select the chain A without the ligand and save it as receptor.pdb

5.

Open Hex.

6.

Open the receptor (receptor.pdb).Go to File->open->Receptor.

7.

Open the ligand(gdp.pdb).Go to File->Open->Ligand.

8.

Go to Controls->Docking. Set the steric scan

9.

Go to File ->save->range->save.

10.

pdb files are created.

11.

Load these structures these structures in swisspdb.

OUTPUT:

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RESULT: protein – ligand docking was done successfully using HEX 5 software.

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EXPERIMENT NO. 5 AIM: To prepare structure for docking using CHIMERA REQUIREMENT: Monitor, CPU, Mouse, Operating system, internal connection. THEORY: UCSF Chimera is a highly extensible program for interactive visualization and analysis of molecular structures and related data, including density maps, supramolecular assemblies, sequence alignments, docking results, trajectories, and conformational ensembles. High-quality images and animations can be generated. Chimera includes complete documentation and several tutorials, and can be downloaded free of charge for academic, government, non-profit, and personal use. PROCEDURE: CHIMERA PROCEDURE1. Open chimera in linux 2. Upload a protein in pdb file format in chimera. The structure will be opened. 3. Remove all the ions from the structure by selecting ions from Structure menu and then go to Actions menu to delete those ions 4. Delete the ligand from the structure as well as solvent from the structure in the same way as ions 5. Go to Tools menu and select Structure Editing option and select DockPrep, a window will open. 6. Save the session as both mol2 file and pdb file. 7. Go to Actions and select surface and click on show. 8. Go to tools and structure editing and select write DMS 9. Save the session 10. Open protein and select ligand. 11. Select Invert selected models and then go to Actions, then atoms and then click on delete. 12. Add H atoms and Charges and save the mol2 and pdb files

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OUTPUT: CHIMERA Protein extracted:

Protein without ligand mol2 file-

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Ligand

Surface generation file:

RESULT: interactive visualization and analysis of molecular structure was done and a protein tructure was generated for further docking purpose using Chimera.

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EXPERIMENT NO. 6 AIM: Drug Designing using DOCK6 REQUIREMENT: Monitor, CPU, Mouse, Operating system, internal connection. THEORY: DOCK addresses the problem of "docking" molecules to each other. In general, "docking" is the identification of the low-energy binding modes of a small molecule, or ligand, within the active site of a macromolecule, or receptor, whose structure is known. A compound that interacts strongly with, or binds, a receptor associated with a disease may inhibit its function and thus act as a drug. Solving the docking problem computationally requires an accurate representation of the molecular energetics as well as an efficient algorithm to search the potential binding modes. Historically, the DOCK algorithm addressed rigid body docking using a geometric matching algorithm to superimpose the ligand onto a negative image of the binding pocket. Important features that improved the algorithm's ability to find the lowest-energy binding mode, including force-field based scoring, on-the-fly optimization, an improved matching algorithm for rigid body docking and an algorithm for flexible ligand docking, have been added over the years. DOCK can be used for the following applications: predict binding modes of small molecule-protein complexes search databases of ligands for compounds that inhibit enzyme activity search databases of ligands for compounds that bind a particular protein search databases of ligands for compounds that bind nucleic acid targets examine possible binding orientations of protein-protein and protein-DNA complexes • help guide synthetic efforts by examining small molecules that are computationally derivatized • • • • •

PROCEDURE: 1.

Open dock 6 in terminal window in linux.

2.

Paste all the files of structure we have got from chimera in bin folder of dock 6.

3. In bin, a file called INSPH is there. In it write the name of the dms file and the file name in which we want our output. 4. Give command ./sphgen –I INSPH –o OUTSPH in terminal, where outsph is the name of our terminal file. 5. Press enter.We get two files in bin. In one. The number of clusters are given and in the other clusters are shown.

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6.

Give command ./showsphere in terminal to view the clusters.

7.

Open the clusters in chimera now.

8. Give command ./showbox to create boxes around the spheres n terminal window. Create two boxes. 9.

Open the boxes in chimera to view them.

10. Give command ./grid –i grid.in to create grids..We will get two files as output- grid.bmp and grid.nrg. 11. Give command ./dock 6 –i rigid.in –o rigid.out for final docking. OUTPUT: Clusters

Spheres:

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Spheres of two clusters opened in chimera:

Boxes generated:

RESULT: as the docking problem computationally requires an accurate representation of the molecular energetics as well as an efficient algorithm to search the potential binding modes dock 6 algorithm is addressed for rigid body docking and ligand is superimposed to the binding pocket with help of grids and boxes.

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EXPERIMENT NO. 7 AIM: Peptide designing using BALL View REQUIREMENT: Monitor, CPU, Mouse, Operating system, internal connection. THEORY: BALLView is a free molecular modeling and molecular graphics tool. It provides fast OpenGLbased visualization of molecular structures, molecular mechanics methods (minimization, MD simulation using the AMBER, CHARMM, and MMFF94 force fields), molecular editing, as well as calculation and visualization of electrostatic properties (FDPB). Its development started in 1996, initially as a tool box for protein-protein docking. It rapidly evolved into a large framework covering a broad range of applications. The visualization component relies on OpenGL for platform-independent 3D graphics and on QT for a portable graphical user interface (GUI). BALL classes can also be used as extensions in the object-oriented scripting language Python and it is possible to embed this scripting language into BALL applications. Besides the rapid prototyping capabilities of the library itself, this provides a very efficient method to create software prototypes and improves the capabilities of BALL applications through the embedding of a scripting language. PROCEDURE: Design a peptide[buildbuild peptide ASNVILKHADAclick build] 1. Select system and highlight from structure window and right click and select focus to zoom the image. 2. Create trajectory[molecular mechanicsmolecular dynamicsset parametersclick save to (to create trajectory) simulatetrajectory created] 3. Right click on trajectory to buffer it and the again right click to visualize trajectory. 4. Select export to pnj and animate. 5. Create video in mencoder.

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OUTPUT: Build peptide

Trajectory creatory with 150 images

RESULT: peptide designing carried out by using ball view as it is a free molecular modeling and molecular graphics tool.

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EXPERIMENT NO: 8 Aim: To perform protein manipulation using Swiss PDB Viewer. Algorithm: Start Opened the url: http://www.uniprot.org/ to access the uniprot database. Retrieved information on p16 protein that regulates the cell cycle from uniprot. We selected the entry with accession number P51480 and utilized the mutagenesis information provided within it. We downloaded the corresponding PDB protein structure (PDB ID: 1LNN). We opened the protein structure in SPDBV and induced the C to G mutation at 60th position in the structure. After this we calculated the energy of Cys at 60th position and also that of the adjacent residues in the normal structure. Then we determined the residues with which the Cys was forming hydrogen bonds. The same two steps were repeated for the structure with the mutant structure, with Gly at the 60th position. Stop.

Result: The energies of the C(60) and its adjacent residues are as follows N(59): -158.7. C(60): 4.9. E(61): 12.3. C(60) showed hydrogen bonding with D(57).

The energies of the G(Mutant 60) and its adjacent residues are as follows

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N(59): -120.2. G(60): 48.7. E(61): -13.13. G(Mutant 60) showed hydrogen bonding with D(57).

Conclusion: we conclude that the mutation that was induced was not very detrimental to the protein structure and probably no loss of protein function occurs. Structures:

Fig1: 1LNN.pdb

Fig2: H bonding of Cys.

Fig3: C_G_mut.pdb

Fig4: H bonding of Gly.

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