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INTERACTION OF 3L3K PROTEIN WITH LIGANDS USING AUTODOCK

B.V.S ANIKETH (13BCE0031)

B.Tech Computer Science and Engineering

VIT UNIVERSITY

Vellore, India

[email protected]

B. ROHITH NAIDU (13BCE0424)

B.Tech Computer Science and Engineering

VIT UNIVERSITY

Vellore, India

[email protected]

SOURABH SHARMA (13BCE0791)

B.Tech Computer Science and Engineering

VIT UNIVERSITY

Vellore, India

[email protected]

Abstract—Proteins are the workhouse molecules of life which take part in every essential structure and activity in our life. Ligand is a molecule which bonds to any central atom which makes the co-ordination complex. 3L3K is a 3 chain structure with sequence that is from humans which deals with their immune systems. We interact 3L3K with 3 ligands namely 6-deacetylnimbin, Nimbin pp, Nimbin mw which are related to medicinal plants mainly neem. Nimbin and other associated group of compounds have been isolated from a methanol extract of neem oil at room temperature. Interaction of the protein and ligand will be performed and an analysis of their interaction will be available through this. AutoDock has shown continued success for the application of virtual screening to a variety of targets and is the software that will be used. Applications studied in our laboratory have ranged from the development of enzyme inhibitors, compounds that stabilize protein dimerization, antitoxins, and nucleicacid-binding compounds. Through the use of simple and automated scripting methods such as virtual screening with AutoDock is currently available to a wide user community.

1 INTRODUCTION

3L3K protein deals with the human system. The immune system is a system of biological structures and processes within an organism that protects against disease. To function properly, an immune system must detect a wide variety of agents, known as pathogens, from viruses to parasitic worms, and distinguish them from the organism's own healthy tissue.  Nimbin is the active compound from the Neem leaf extract which is our main ligand. Nimbin has some antiseptic properties and it can also used for manufacturing antiseptics/medicines and nimbin is an alkaloid. Nimbin is the first bitter compound isolated from neem oil, more than 135 compounds have been found, which are divided into two major classes: isoprenoids. The isoprenoids include diterpenoids and triterpenoids containing protomeliacins, limonoids, azadirone and its derivatives, gedunin and its derivatives, vilasinin type of compounds and Csecomeliacins such as nimbin, salanin and azadirachtin. Neem has anti-bacterial properties that help in fighting against skin infections such as acne, psoriasis, scabies, eczema, etc. Neem extracts also help in treating diabetes, AIDS, cancer, heart disease, herpes, allergies, ulcers, hepatitis and several other diseases. There are quite a few neem benefits, and they include a salve for skin diseases, plus the versatility to function as an aid to one’s hygiene, and even an insecticide. It can be used as a source of protective oil that may be ingested to safeguard against disease, plus it’s also frequently lauded as a kitchen spice. Historically, the whole neem plant, including the fruit, leaves, and bark, has been smashed, dried or ground into fine powder to keep one healthy and take care of illnesses. Because the general ability has been shown by the plant to kill viruses, fungi, and microorganisms that bring disorder the gum and seeds have been processed for medication. Interaction of these medicinal ligands related to neem will be known.

Nimbin

Molecular Formula C30H3606 and

CA index Name 2H-Cyclopenta[b]naphtha [2, 3-d] furan-10-acetic acid.

2 LIGANDS

  2.1 6-deacetylnimbin ( C28H34O8)

A limonoid that is nimbin in which the acetyloxy group at position 6 is replaced by a hydroxy group. It has been isolated from Azadirachta indica.

Limonin is a limonoid, and a bitter, white, crystalline substance found in citrus and other plants. Limonin is enriched in citrus fruits and is often found higher concentrations in seed, for example orange and lemon seeds.

2.2 Nimbin pp ( C30H36O11)

Chemical name is Isonimbinolide. Ploysaccharides from bark have strong antitumor and anti-inflammatory action. Bark is regarded as a bitter tonic,astringent,useful in fever,thirst,nausea, vomiting and skin diseases. Almost every part of the tree has been used for treatment of variety of human ailments, particularly against bacterial and fungal diseases. Various factors derived from neem possess diverse biological effects against insects like repellence, phagode.The leaves has been used in the treatment of ulcer, eczema.

2.3 Nimbin mw  ( C30H36O10)

 Nimbin mw is a triterpenoid isolated from Neem. Nimbin is thought to be responsible for much of the biological activities of neem oil, and other essentials. It has Hydrogen Bond donor count of 0 and Hydrogen Bond acceptor count of 10. It has rotatable bond count of 8.

3 REQUIREMENTS AND METHODS

 3.1 Data set definition and preparation

The crystalline structure of 3L3K is obtained from the RCSB Protein Data Bank.

The 3 ligands namely 6-deacetylnimbin, Nimbin pp, Nimbin mw were obtained from PCB NCBI website. So we have 1 protein and 3 ligands.

3.2 Virtual Screening

Virtual screening (VS) is a computational technique used in drug discovery to search libraries of small molecules in order to identify those structures which are most likely to bind to a drug target, typically a protein receptor or enzyme. Virtual screening techniques play crucial role in the lead discovery process. Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules.

  3.3  Software Required

Autodock and AutoGrid Suite, MGL Tools 1.5.6, Open Babel, Python molecular viewer, Discovery Visual Studio.

Operating system: Microsoft windows 8.1 / Ubuntu 14

  3.4  Preperation

Download the ligands from the NCBI website and save them in sdf format. Now they are converted to pdbqt format in openBabael and saved in the working directory.

The receptor is downloaded from the RCBS website by its PDB ID and saved in pdb format in the working directory. Unrequired chains are deleted from it by virtual screening techniques in Discovery Visual Studio software and saved.

3.5 Run Time Setup

Open MGL tools and create a working directory. Then read the pdb file of the receptor. Delete selected atoms of chains that are not required and delete water, add hydrogens and merge non polar. Add gastegier Charge.

Write the PDB and save it. Load the pdbqt file of the receptor, detect its root and we are ready for auto grid. If Structure is in 2D convert it to 3D using open Babel software.

3.6 Auto Grid

Choose the receptor as the macromolecule and chose the ligand and save as pdbqt. Set a covalent map if required. Set a grid box of 60X60X60 and spacing, center if required. Save as .gpf format and go to run and launch auto grid. Wait for the process manager to close and the gpf file is created in our working directory. We are ready for auto dock. Any sort of error would be displayed in the terminal window.

3.7 Auto Dock

Autodock is a suite of software for predicting the optimal bound conformations of ligands to proteins. The initial applications of AutoDock were in the analysis of binding modes and catalytic properties of protein and nucleic acid complexes, and a typical study would include results from several dozen docking simulations. More recently, however, enhancements in the performance of AutoDock combined with the availability of high speed computers and clusters of computers has allowed much larger experiments, where entire compound libraries are screened against pharmaceutically-relevant targets

Choose macromolecule and set rigid filename and select the .pdbqt macromolecule created during the setup of autogrid. In docking, choose the ligand and click defaults. For search parameters use Genetic Algorithm and set number of GA runs as 10 (higher is suggested for better results but consumes more time) and use remaining defaults. Set docking output as Lamarckian GA (4.2) and save the output as .dpf. Now run AutoDock and click launch and wait for the program manager to close (may take some time). Any sort of error would be displayed in the terminal window.

3.8 Analyze

Once AutoDock completes the calculations, you can then go to: Analyze>Confirmations>Play, ranked by energy. This will show all binding confirmations in order of energy. At this point, you may analyze the results, interactions, and confirmations as needed.

4 RESULTS

We note down the results after running the interactions between the protein 3L3K and ligands. The values and their results are depicted in tabular fashion below. We have mainly tabulated the binding energy and inhibition constant.

S.no Protein_Ligand Binding Energy Inhibition Constant

1. 3L3K- 6deacetylnimbin -5.02 208.26

2. 3L3K-nimbin pp -3.58 2.38

3. 3L3K-nimbin mw -4.64 399.6

5 SCREENSHOTS

5.1)  6-deacetylnimbin with 3L3K

The above figure shows the values of binding energy, ligand efficiency, inhib. constant, intermol energy, torsional energy and others.

On increase of the value the ligand moves over the protein and the values of the binding energy changes.

5.2)  Nimbin pp with 3L3K

 The ligand interaction is clearly visible with the yellow portion moving throughout the protein on increase of the running values.

5.3)  Nimbin mw with 3L3K

6 CONCLUSION

The interaction between the protein 3L3K and the ligands related to medicinal structure have performed and analyzed with their values on their interaction. Auto Dock is a popular non-commercial docking program that docks a ligand to its protein and performs well and fast it is user-friendly for docking ligands with target protein. In this paper we propose an easier user-friendly docking protocol for docking ligands with target protein that utilizes Auto Dock . Auto Dock helps in reducing the cost and time for drug discovery process which otherwise takes many years. Virtual screening and docking studies helped to obtain ligand molecules that can inhibit the important proteins involved. Ligand can react with the protein in all patterns and their values can be depicted in change with their binding energy. If the range of binding energy varies from -3 to -6 then the result would be a clear value that is required. Using all these Auto dock and open babel tools we can infer the binding energy and inhibition constant values of the given ligands and proteins.

           (Detection of Ligand interaction points using Cygwin)

           7     ACKNOWLDGEMENT

We would like to thank Prof. Kannadasan R for supporting our work throughout.

                             8     REFERENCES

I. http://www.rcsb.org/pdb/explore.do?structureId=3l3k

II. https://www.ebi.ac.uk/pdbe/entry/pdb/3l3k/analysis

III. http://pdbj.org/mine/summary/3l3k

IV. https://pubchem.ncbi.nlm.nih.gov/compound/10505484#section=Top

V. Edible Medicinal and Non Medicinal Plants: Volume 8, Flowers

VI. NEEM: TODAY AND IN THE NEW MILLENNIUM - edited by Opender Koul, Seema Wahab

VII. Anderson AC. The process of structurebased drug design. Chem Biol 2003;10: 787–97.

VIII. Lazarova M. Virtual screening-models, methods and software systems. InternationalScientific Conference Computer Science 2008;55-60.

IX. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK et al. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem 1998;19: 1639–62.

X. Warren G, Andrews C, Capelli A, Clarke B, LaLonde J, Lambert MH et al. A critical assessment of docking programs and scoring functions. J Med Chem 2006;49:5912-31.

                                                                                                                                                                                  

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