Presentation to explain homology modeling and docking statergies

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Homology Modeling and Docking to Potential Novel Inhibitor for Chikungunya Protein nsP2 Protease Limpon Bora, Assistant Professor, Dept of Molecular Biology and Biotechnology, Tezpur University, Tezpur- 784028, India JOURNAL OF PROTEOMICS & BIOINFORMATICS | JANUARY 31, 2012 | 5: 054-059 PRESENTED BY: DANISH I JASNAIK B.Tech Bioinformatics (11006), D Y Patil University, School of Biotechnology and Bioinformatics, CBD Belapur, Navi Mumbai,400614, India.

Transcript of Presentation to explain homology modeling and docking statergies

Homology Modeling and Docking to Potential Novel Inhibitor for

Chikungunya Protein nsP2 Protease

Limpon Bora, Assistant Professor, Dept of Molecular Biology and Biotechnology, Tezpur University, Tezpur- 784028, India

JOURNAL OF PROTEOMICS & BIOINFORMATICS | JANUARY 31, 2012 | 5: 054-059

PRESENTED BY: DANISH I JASNAIK

B.Tech Bioinformatics (11006),D Y Patil University,

School of Biotechnology and Bioinformatics,CBD Belapur, Navi Mumbai,400614, India.

OBJECTIVE

• To investigate nsP2 protease of CHIKV and use various computation methods to find potent novel inhibitors

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INTRODUCTION/ABSTRACT• Chikungunya virus (CHIKV) is an Arbovirus that is

transmitted to humans primarily by the mosquito species Aedes aegypti

• Infection with this pathogen is often associated with fever, rash, etc.

• Neither a vaccine nor an antiviral drug is available for the prevention or treatment of this disease.

• In the present study, we report on the discovery of a novel series of compounds that inhibit CHIKV replication. In particular, we have initially performed a virtual screening simulation of data set of compounds on the CHIKV nsP2, a viral protease

• The study of such selective inhibitors will contribute to a better understanding of the CHIKV replication cycle and represents also a first step towards the development of a clinical candidate drug for the treatment of this disease.

MATERIALS AND MATHEODS• SELECTION OF RECEPTOR PROTEIN

• SELECTION OF LIGAND

• COMPOUND LIBRARY

• SCREENING OF LIGANDS

• MODELLING OF RECEPTOR PROTEIN

• ANALYSIS AND VALIDATION OF PROTEIN MODEL

• BINDING SITE PREDICTION

• DOCKING

• EVALUATION

SELECTION OF RECEPTOR PROTEIN

• The cause of Chikungunya is mainly due to the replication of CHIKV virus inside the human body

• In this study literature survey was done to find out which non structural protein to be chosen for further analysis. After literature survey was done the protein that was selected was nsP2

• nsP2 protease is responsible for cleavages in the non structural polyprotein that are important for the viral replication cycle. Therefore this protease constitutes an attractive drug target for the development of antiviral compounds

SELECTION OF LIGAND

• Work is mainly focused on the interaction of protease protein with the potent novel inhibitor. The ligands were screened form PubChem database by ADMET Properties that is aqueous solubility, Blood Brain Barrier penetration, Hepatotoxicity, and Plasma Protein Binding and Drug likeness properties

• PubChem Database compound contains validated chemical depiction information

• Structures that are stored in PubChem contain calculated properties and description which helps in searching and filtering of chemical structures

COMPOUD LIBRARY• Working with

bioinformatics approach and finding of a novel inhibitor for a particular virus or disease, preparation of compound libraries plays an important role

• In this case the chemical structure of the Protease inhibitor such as S-adenosyl methionine was collected from published literature with their biological activity data

• In this study, 2D analogues of the nsP2 protease inhibitors were retrieved from the PubChem database using PubChem Structure search tool

SCREENING OF LIGANDS

• Usually many drugs fail in clinical trials because of unrelated side effects and Bio-Unavailability. To overcome these problems, we screen drug like molecules that exhibit physicochemical properties for favorable absorption, distribution, metabolism, excretion and toxicological parameters

• In this study physicochemical properties of compounds such as Molecular weight, logP, Heavy atoms, HBA (Hydrogen Bond Acceptor), HBD (Hydrogen Bond donor), Rotatable bonds, and number of Rings were considered in this analysis

• For screening purpose Discovery studio was used as it helps in assessing the disposition and potential toxicity of a ligand within an organism

MODELLING OF RECEPTOR PROTEIN

• 3D modeling of a receptor protein is a very important task when we don’t have a 3D structure of a protein available and when we work with in silico approach towards drug designing

• Modeling of a receptor servers as a important factor to proceed with the standard protocol of generating drug like molecule or a potential drug

• In this study Protein HomologY Recognition Engine (PHYRE2) was used to model the receptor using the principles of homology modeling

• Phyre - (http://www.imperial.ac.uk/phyre/)• I-TASSER - (http://zhang.bioinformatics.ku.edu/I-TASSE) • HHpred – (http://toolkit.tuebingen.mpg.de/hhpred)• Bioinfo - (http://meta.bioinfo.pl)• Robetta – (http://ffas.ljcrf.edu)• SP4 – (http://sparks.informatics.iupui.edu/SP)

ANALYSIS AND VALIDATION OF PROTEIN MODEL

• Analysis and validation of 3D model is the process of evaluating reliability for 3-dimensional atomic models of large biological molecules like protein

• Analysis and validation has three aspects;

1. Checking on the validity of the thousands to millions of measurements in the experiment

2. Checking how consistent the atomic model.

3. Checking consistency of the model with known physical and chemical properties,

• In this study Structural Analysis and Verification Server (SAVES) server was used for validating the 3D structure of protein whether the protein is stable or not

BINDING SITE PREDICTION

• The accurate prediction of putative binding sites on the protein surface can be very helpful for rational drug design on target proteins, for predicting the geometry of protein-protein as well as protein-ligand complexes

• In the current study 3DLigandSite, a web server was used to predict the ligand binding sites based upon the structure similar to the protein submitted as query

• The modelled nsP2 Protease structure was submitted to 3D Ligand Site Prediction Server. The server found the ligands bound to structures similar to the query and superimposed them onto the model and to predict the binding site

• The following residues are predicted as best binding sites for the lead compound LEU67, GLU68, ILE85, THR87, PRO88, ARG90, LEU100, LYS103, TYR104, VAL119, ASN132, ILE134, ALA136, ASN137 AND ARG138

DOCKING

• Molecular docking is the process by which two molecules fit together in 3D space to predict the binding modes of a ligand with a protein of known sequences

• Docking problem is concerned with generation and evaluation of possible structures of protein-ligand complexes

• In this study the preferred orientation of one molecule with relation to a second, when bound to each other to form a stable complex in three dimensional spaces was predicted

EVALUATION

• In the current study Docking score was used to rank the ligands on the basis of their relative binding affinities

• Evaluating the results was done by analyzing docked drugs based on their scores . The best docked result was analyzed by the best score of docking that is greatest value of dock score

RESULTS AND DISCUSSION

• An integrated approach to model the nsP2 Protease protein of Chikungunya and to identify the potential nsP2 Chikungunya protease inhibitors, structure based virtual screening has been used in this study

• After searching in PDB the best template structure was selected based on the sequence homology

• Here 2HWK_Chain A, Crystal structure of Venezuelan equine encephalitis2 alpha virus nsP2 Protease domain, shows the highest similarity of 41% for the nsP2 Protease Protein of Chikungunya

• 320 residues of nsP2 Chikungunya Protease were modelled with 100.0% confidence

Cartoon representation of nsP2 Chikungunya Protease Protein Model predicted by PHYRE2 Protein Modeling Server

• The modelled nsP2 Protease structure was submitted to 3D Ligand Site Prediction Server

• The server found the ligands bound to structure similar to the query and superimposed them onto the model and to predict the binding site

• A 2D similarity search for the available inhibitor was done by the PubChem structure search with 85% as threshold value. In this search, totally “11000” analogues were retrieved by using the inhibitor SAM

• In further screening 197 library compounds were filtered from “11000” compounds

• The ADMET properties of the compound were analyzed .The compounds that were obeying the drug likeliness property were tabulated

Typical range of Physicochemical properties for drug likeliness

Ligand Screening Work Flow

• The software used for Docking was Genetic Optimization for Ligand Docking (GOLD) is a program for docking models of small molecules in protein binding site

• Among these tow compound LIGAND_4 [N-butyl-9-[3, 4-dipropoxy-5 (propoxymethyl) oxolan-2-yl] purin-6-amine] was found to bind with the target more efficiently than other compound with best gold score (47.6163) Hence, LIGAND_4 has been emerged as a promising Anti-viral drug candidate with potential effects

The binding mode of the LIGAND_3 to active site of CHIKV nsP2 Protease showing formation of two hydrogen bonds during docking process.

The binding mode of the LIGAND_4 to active site of CHIKV nsP2 Protease.

CONCLUSIONS

• The study describes the nsP2 Protease to be a promising drug target for the treatment of Chikungunya

• Based on this observations LIGAND_4 [N-butyl-9-[3, 4-dipropoxy-5-(propoxymethyl) oxolan-2-yl] purin-6-amine] is found to bind with the target more efficiently than LIGAND_3 compound

• Further, QSAR studies can be done to identify conformational changes

FUTURE ASPECTS

• As from the study the ligand which was found to show best activity in complex with the receptor nsP2 protein can be further studied using 2D-QSAR and 3D-QSAR methodologies to make the results more accurate

• By doing this we could contribute in the development of potential novel inhibitor for Chikungunya virus which currently has no potential drug available

• Further studies are been carried out to achieve this

• Once a hypothesis has been made using an in-silico approach wet lab experimentations could be used to validate the results and develop a potential drug for Chikungunya virus

REFRENCES• Bora L (2012). Homology Modeling and Docking to Potential Novel Inhibitor for Chikungunya Protein nsP2 Protease. JOURNAL OF PROTEOMICS & BIOINFORMATICS | JANUARY 31, 2012 | 5: 054-059

• http://www.ncbi.nlm.nih.gov/pubmed/20166931

• http://www.rcmd.it/rcmd-portal/RR/Molecular_Docking.pdf

THANK YOU!!!