[1] This document outlines Hassen Mohammed Abdullah Alsafi's final year project on rational drug design using a genetic algorithm to find candidate drugs for malaria.
[2] The project aims to use computational molecular docking via AutoDock 4.2 to screen drug compounds and identify those that are best able to bind to the malaria parasite's target protein 2GHU, with the goal of proposing new drug candidates.
[3] The document details the methodology, which involves preparing the target protein and drug ligands, running molecular docking simulations with AutoDock's genetic algorithm, and analyzing the results to evaluate potential drug candidates based on their binding affinity scores. Challenges faced and future work are also discussed.
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This is a talk i'm giving for the EBI's industry programme on 18th Sept. The slides are mostly what you may have seen before with a few new ones thrown in to not make it too boring! With grateful acknowledgment of all the folks in Open PHACTS who make this stuff happen.
In spite of extensive effort by industry and academia to develop new drugs, there are still several diseases that are in need of therapeutic agents and have yet to be developed.
10 years the identification rate of disease-associated targets has been higher than the therapeutics identification rate.
Nevertheless, it is apparent that computational tools provide high hopes that many of the diseases under investigation can be brought under control.
Open PHACTS (Sept 2013) EBI Industry ProgrammeSciBite Limited
This is a talk i'm giving for the EBI's industry programme on 18th Sept. The slides are mostly what you may have seen before with a few new ones thrown in to not make it too boring! With grateful acknowledgment of all the folks in Open PHACTS who make this stuff happen.
In spite of extensive effort by industry and academia to develop new drugs, there are still several diseases that are in need of therapeutic agents and have yet to be developed.
10 years the identification rate of disease-associated targets has been higher than the therapeutics identification rate.
Nevertheless, it is apparent that computational tools provide high hopes that many of the diseases under investigation can be brought under control.
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Rational Drug Design using Genetic Algorithm
1. Final Year project
Rational Drug Design Using Genetic
Algorithm
Case of Malaria Disease
Supervision by
Assoc.Prof.Imad Fakhri Taha Alshaikhli
Presented By
Hassen Mohammed Abdullah
Alsafi
International Islamic University Malaysia
2. Agenda
• Introduction.
• Problem statement.
• Objectives.
• Proposed methods.
• Findings and Analysis.
• Challenges and Difficulties faced.
• Conclusion and Future work.
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3. Introduction
How a drug works and how we can expect the body
to respond to the administration of a drug?
Drug design is known as approach uses specifics
tools to explore and search for the best drug
candidate.
Drug Compound
Hassen Alsafi
Protein Medicine 3 3
International Islamic university Malaysia
4. problem statement
What is the best drug candidate for x disease ?
Drug design and discovery take years for
discovering a new drug and very costly.
Effort to cut down the research timeline and cost
by reducing laboratory experiment use
computational computer modeling.
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5. Rational drug design approach(rdda)
Foundation of drug design and discovery.
Answer the question , which molecule fit best
to the protein active site?
Computational Molecular Docking (CMD)
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6. Objectives
1. Find and Select the target disease in the human
body.(e.g malaria)
2. Search and choose the best drug candidate.
3. Conduct computational drug design simulation.
4. Propose some drugs against certain disease
based on results.
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7. Drug design and development process
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9. Proposed methods
1. Target selection and identification.
1.1 Protein preparation in ADT
1. Drug or ligand identification.
2.1 Ligand preparation in ADT
1. Perform the molecular docking simulation.
2. Techniques used in docking algorithm.
3. Evaluation .
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10. Methodology
Computational Molecular docking
Ligand database Target Protein
AutoDock 4.2 Molecular docking
Ligand docked into protein’s active site
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11. AutoDock 4.2
Automated computational molecular docking
programs .
It is designed to predict how small molecules, bind
to a receptor of known 3D structure.
It uses Genetic Algorithm (GA) .
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12. AutoDock 4.2
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13. Methods and materials
1. Target selection and identification .
Target disease Target protein
Malaria 2GHU.pdb
The protein 3D structured was retrieved form
RCSB database.
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14. Autodock workflow
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16. Protein databank (pdb)
Molecular protein repository .
Contains a tons of protein stored in the repository.
In order to convert the drug compound from .sdf to
pdb <openbabel> software used by the following
commend line:
-i: input type(i.e .sdf and pdb)
-o: output(convert) type
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17. Grid file parameters(gfp)
After finish the preparation of protein and
drug , now the task is to precalculate the grids
using the following Linux commend line:
autogrid4 –p filename.gpf –l
filename.glg
-p: used to specifics the grid parameter file
gpf: grid parameters file
–i: used as log file output 17
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19. Docking file parameters in adt
Primary goal of AutoDock is to instruct the drug to
move inside the space search grid.
GA selected as search algorithm in the experiment.
Run the following Linux commend line :
autodock4 –p filename.dpf –l filename.dlg
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20. Experiment results
Setup the environment
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21. Equipments used in the experiment
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22. Tools and materials
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23. Genetic algorithm in autodock
ADT represent chromosome as a vector of real
number .
Quaternion genes
Tx Ty Tz Qx Qy Qz Qw R1 Rn
Translation genes
GA features in ADT:
1. Solution space.
2. Genetic code (chromosome)
3. Genetic operations
4. Fitness function
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24. Results and discussion
Experiment conduct of 3 cases.
Case 1 : Default parameters.
Case 2 : Parametric study.
Case 3: Computational Docking Time (CDT).
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25. Case 1 : default parameters
Run CMD in 20 drugs compound with 1
target protein.
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26. [1]
Log p: octanol/water partition coefficient
Case 1 : default parameters
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27. Case 1 : default parameters
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28. Case 1 : default parameters
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29. [1]
Log p: octanol/water partition coefficient
Case 1 : default parameters
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30. Case 2 : Parametric study
480 samples has been investigated with
different parametric value.
Parameter Value
Pop size(50) 50,100,150
Crossover rate(0.2) 0.2, 0.4, 0.6, and 0.8
Mutation(0.01) 0.01 and 0.02
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31. Case 2 : Parametric study
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32. Case 2 : Parametric study
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33. se 3 : computational docking time
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34. Challenges faced
Compiling the python source code under ADT
environment.
Installing the openbabel software.
Dealing with the bioinformatics tools.
Time given to complete the project.
Moving from the old building to the new building
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35. Conclusion and future work
Computational molecular docking with GA are
crucial tools in RDD.
Using the ADT we can reduce the use of
laboratory experiments(but not at all)
RDD helps to reduce the time required to design
and discover new drugs .
Future work
Further investigation is needed to select the best
potential drug candidate .
I propose to deploy the grid computing in the
CMD. 35
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36. Conclusion and future work
In order to perform the CMD faster and accurate ,
the high speed computers is needed.
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37. Acknowledgments
Special thanks to My beloved supervisor
Assco.Prof.Dr.Imad Fakhri Taha Alshaikhli
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38. Thank you for your attention
Q&A
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Editor's Notes
Today I talk about the importance of protein flexibility in protein-ligand docking. In order to illustrate the relevance I present two examples of protein-ligand interaction.
First of all I give you an brief overview of my talk. At the beginning I shortly explain why it is so interesting to examine protein-ligand docking and why the aspect of protein flexibility is so curcial for it. Then I give some information about my two examples and the way I process them to get gorgeous complexes. In doing so I explain a bit about the free available docking tools AutoGrid and AutoDock. After that I introduce the interesting parts of the results, which I obtained. And finally I discuss the results.
A first hint to answer this question one gets by taking a look at the important role, protein-ligand interactions play in a cell. There, these interactions can be found in many cellular processes, such as signal transduction, immune response, energy generation, DNA repair and apoptosis. Events and mechanisms that are essential for all organisms.
A first hint to answer this question one gets by taking a look at the important role, protein-ligand interactions play in a cell. There, these interactions can be found in many cellular processes, such as signal transduction, immune response, energy generation, DNA repair and apoptosis. Events and mechanisms that are essential for all organisms.
A first hint to answer this question one gets by taking a look at the important role, protein-ligand interactions play in a cell. There, these interactions can be found in many cellular processes, such as signal transduction, immune response, energy generation, DNA repair and apoptosis. Events and mechanisms that are essential for all organisms.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.
The motivation answers the question, why so many people are interested in protein-ligand docking.