novo design, in vitro , in silico AMET screening and structure â based drug design. ... (b) De novo design (target 3D structure available but no ligands).
CHHATRAPATI SHAHU JI MAHARAJ UNIVERSITY KANPUR
A DISSERTATION ON
STRUCTURE - BASED DRUG DESIGN FOR MALARIA SUBMITTED TO Department of Biotechnology Saaii College of Medical Science &Technology, Kanpur For
The partial Fulfillment of the Requirements For the Degree of
Bachelor of Science in Biotechnology
UNDER GUIDANCE OF
SUBMITTED BY:-
Mr. Sandeep Goswami
Sujit Kumar B.Sc. Biotechnology 3rd Year
Lecturer Department of Biotechnology (SCMAT), Kanpur
(SCMAT), Kanpur 1
Department of Biotechnology CERTIFICATE This is to certify that Mr. Sujit Kumar S/O Mr. Ram Gopal Kushwaha has completed the project on In Structure-Based Drug Designing For Malaria under my guidance in partial fulfillment of course of B.Sc.Biotechnology as prescribed by Chhatrapati Sahu Ji Maharaja University Kanpur in the laboratory of the Saaii College Of Medical Science And Technology, Kanpur during the year 2010-2011.
Mr. Sandeep Goswami Lecturer Department of Biotechnology Saaii College of Medical Science and Technology
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PREFACE The application of computation sciences to pharmaceutical & Biotechnology research is a discipline whose time has come. A tranche of techniques, both old and new, have recently matured into potent weapons in the war against disease. Molecular informatics –computational chemistry or molecular modeling, Bioinformatics & chemo informatics - has reached new heights of sophisticated and utilitarian value within drug discovery. Bioinformatics now entails the creation and advancement of database, algorithms, computational and statistical techniques and theory to solve formal and practical problems arising from the management and analysis of biological data. Major research efforts in the field include sequence alignment, protein structure alignment, gene folding, genome assembly, drug design, drug discovery, protein structure prediction, prediction of gene expression and protein – protein interaction, genome – wide association studies and the modeling of evolution. I focused on the discovery end of the pharmaceutical sciences. It is active in discovery and development novel lead- drug candidates and molecular diagnostics using a variety of approaches, including rational drug –design methods and natural sources. WHO estimates that the largest number of new MALARIA cases in 2008 occurred in the SouthEast Asia region, which accounted for 34% of incident cases globally. However, the estimated incidence rate in sub- Saharan Africa is nearly twice that of the South- East Asia Region with over 350 cases per 100,000 populations. An estimated 1.3 million people died from MALARIA in 2008. The highest number of deaths was in the South- East Asia Region, while the highest mortality per capita was in the Africa Region. Quinine & Chloroquine are the first- line ant malarial medication in prevention and treatment. I had used some software for completing this Project i.e. Argus lab, CORINA server, Portable Molegro Virtual Docker. The present Project dissertation work was undertaken as part of the last year of B.Sc. Biotechnology of Saaii College of Medical Science and Technology, Kanpur to get an onsite exposure of various frontline bioinformatics tools at the division of Department of Biotechnology of S.C.M.A.T, Kanpur.
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ACKNOWLEDGEMENT I take this opportunity to present our sincere thanks gratitude towards all those who helped us in making this project a success. Completing this assignment report has been only possible because of the spontaneous & continuous support of our teachers. Our heartfelt thanks to Mr. Sandeep Goswami, Lecture in Department of Biotechnology, for his moral boosting co-operation, love & kind support during the fulfillment of project. I express my thanks to Dr. R.S. Sharma, director of SCMAT, Kanpur for extending his project. My deep Sense of gratitude to Dr. Rye Ghose , Head of Department of Biotechnology , SCMAT, Kanpur for and guidance . I would also thank my institution and my faculty members without whom this project would have been a distant reality. Our special thanks to Mr. Vijay Sir, for his co-operation for supplying as different books for my assignment. I am thankful to all my classmate for their co- operation & support. Further I want to express my love & respect to my parents.
Sujit Kumar
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INDEX
INTRODUCTION
------------- 1-8
DRUG DESIGNING
------------- 9-18
MALARIA DISEASE
------------- 19-25
DETAIL OF DRUGS FOR MALARIA ------------- 26-36 DOCKING
------------- 37-40
REQUIREMENT OF MY PROJECT
------------- 41-48
HOMOLOGY MODELING
------------- 49-57
VIRTUAL DOCKING
-------------
58-72
CONCLUSION
-------------
73-74
REFERENCES
--------------
75-77
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1.
INTRODUCTION
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Introduction: - The mechanism of drug action generally involves a long chain of interactions with the molecules of the human body. There are numerous experimental and in silico drug design tools describing the terminal link of these chains, i.e. the equilibrium binding affinities (BA) of drug candidates (ligands) to the targeted macromolecules. Although binding affinities is undoubtedly a key property, other pharmacokinetic and non – equilibrium links in the chain such as the absorption, distribution and excretion of the candidate molecules also affect drug likeness.
Ideal feature of drug:= There are some foll.points are given(1) Best possible Activity (Drug bind to its target). (2) Solubility (drug soluble by body when it taken orally). (3) Oral Bioavailability(Drug reaches the tissue). (4) Half life (how long drug stays in the body). (5) Metabolic profile / Toxicity (when the body enzymebreak then any toxic product will formed).
Lipinski’s Rule: - Lipinski's Rule is a rule of thumb to evaluate drug likeness, or determine if a chemical compound with a certain pharmacological or biological activity has properties that would make it a likely drug in humans.
• The rule was formulated by Christopher A Lipinski in 1997 • The rule describes drug's pharmacokinetics in the human body, including their Absorption, Distribution, Metabolism and Excretion (“ADME"). • Not more than 5 hydrogen bond donors • Not more than 10 hydrogen bond acceptors • A molecular weight under 500 Daltons • An octanol-water partition coefficient log P of less than 5
7
ADMET PROPERTIES 1. 2. 3. 4. 5.
Absorption Distribution Metabolism Excretion Toxicity
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2.
DRUG DESIGNINE
9
DRUG DESIGNING:Drug discovery and development is an intense, interdisciplinary endeavor. Drug discovery is mostly portrayed as a linear, consecutive process that starts with target and lead discovery, followed by lead optimization and pre-clinical in vitro and in vivo studies to determine if such compounds satisfy a number of pre-set criteria for initiating clinical development. For the pharmaceutical industry, the number of years to bring a drug from discovery to market is approximately 12-14 years and costing up to $1.2 - $1.4 billion dollars. Traditionally, drugs lengthy and an were discovered by synthesizing compounds in a time-consuming multi-step processes against a battery of in vivo biological screens and further investigating the promising candidates for their pharmacokinetic properties, metabolism and potential toxicity. Such a development process has resulted in high attrition rates with failures attributed to poor pharmacokinetics (39%), lack of efficacy (30%), animal toxicity (11%), adverse effects in humans (10%) and various commercial and miscellaneous factors. Today, the process of drug discovery has been revolutionized with the advent of genomics, proteomics, bioinformatics and efficient technologies like, combinatorial chemistry, high throughput screening (HTS), virtual screening, de novo design, in vitro , in silico AMET screening and structure – based drug design. Computational tools offer the advantage of delivering new drug candidates more quickly and at a lower cost. Major roles of computation in drug discovery are; 1. Vitual screening & de novo design , 2. In silico ADMET prediction 3. Advanced methods for determining protein – ligand binding
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• Method of Drug Designing:• There are many method for drug designing :(1) Direct Method (2) Indirect Method In the availability of the target (Macromolecule or protein) and ligand, drug discovery can be divided into four phases-
Direct Method:(a) Structure Based drug design (Both target 3D structure and ligands available). (b) De novo design (target 3D structure available but no ligands).
Structure Based Drug Design:Structure-based drug design (or direct drug design) relies on knowledge of the three dimensional structure of the biological target obtained through methods such as x-ray crystallography or NMR spectroscopy. If an experimental structure of a target is not available, it may be possible to create a homology model of the target based on the experimental structure of a related protein. Using the structure of the biological target, candidate drugs that are predicted to bind with high affinity and selectivity to the target may be designed using interactive graphics and the intuition of a medicinal chemist.
De novo Design:Target 3D structure available but no ligands. De novo protein design has recently emerged as an attractive approach for studying the structure and function of protein. This approach critically tests our understanding of the principles of protein folding. Only in de novo design must one truly confort the issue of how to specify a protein’s fold and function. If we truly understand proteins, it should be possible to design receptor, enzymes, and ion channels from scratch. Further, as this understanding evolves and is further refined. 11
Indirect Method:(a) Rational Design (no target 3D structure or ligands ). (b) QSAR (No target 3D structure but ligand available). So for detailed knowledge of ligand & receptor, better accuracy and time saver process I select the Structure-based drug design method
Rational Drug Designing:In contrast to traditional methods of drug discovery which rely on trial-and-error testing of chemical substances on cultured cells or animals, and matching the apparent effects to treatments, rational drug design begins with a hypothesis that modulation of a specific biological target may have therapeutic value. The second is that the target is "drug able". This means that it is capable of binding to a small molecule and that its activity can be modulated by the small molecule. Once a suitable target has been identified, the target is normally cloned and expressed. The expressed target is then used to establish a screening assay. In addition, the three-dimensional structure of the target may be determined.
QSAR(Quantitative Structure Activity Relationships)
:-
No target 3D structure but ligand available. This computational technique should be used to detect the functional group in your compound in order to refine your drug. This can be done using QSAR that consist of computing every possible no. that can describe a molecule then doing an enormous curve fit to find out which aspects of the molecule correlation well with drug activity or side effect severity. This information can then be used to suggest new chemical modifications for synthesis and testing.
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----------------------Process of new potential drug-----------------------------
Process of Drug Discovery and Design:As structure of more and more protein targets become available through crystallography, NMR and bioinformatics methods, there is an increasing demand for computational tools that can identify and analyze active active sites and suggest potential drug molecules that can bind to these sites specifically. Also to combat life – threatening disease such as AIDS, TB, Malaria etc. a global push is essential.
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So detailed knowledge of ligand & receptor, better accuracy and time saver process I select the structure – based drug design method.
Structure Based Drug Design:Structure-based drug design (or direct drug design) relies on knowledge of the three dimensional structure of the biological target obtained through methods such as x-ray crystallography or NMR spectroscopy .If an experimental structure of a target is not available, it may be possible to create a homology model of the target based on the experimental structure of a related protein. Using the structure of the biological target, candidate drugs that are predicted to bind with high affinity and selectivity to the target may be designed using interactive graphics and the intuition of a medicinal chemisty. Alternatively various automated computational procedures may be used to suggest new drug candidates. 14
Active site identification Active site identification is the first step in this program. It analyzes the protein to find the binding pocket, derives key interaction sites within the binding pocket, and then prepares the necessary data for Ligand fragment link. The basic inputs for this step are the 3D structure of the protein and a pre-docked ligand in PDB format, as well as their atomic properties. Both ligand and protein atoms need to be classified and their atomic properties should be defined, basically, into four atomic types: • Hydrophobic atom: all carbons in hydrocarbon chains or in aromatic groups. • H-bond donor: Oxygen and nitrogen atoms bonded to hydrogen atom(s). • H-bond acceptor: Oxygen and sp2 or sp hybridized nitrogen atoms with lone electron pair(s). 15
• Polar atom: Oxygen and nitrogen atoms that are neither H-bond donor nor H-bond acceptor, sulfur, phosphorus, halogen, metal and carbon atoms bonded to hetero-atom(s).
Scoring Method:Structure –based drug design attempts to use the structure of protein as a basis for designing new ligands by applying accepted principles of molecular recognition. The basic assumption underlying structure- based drug design is that a good ligand molecule should bind tightly to its target. Thus, one of the most important principles for designing or obtaining potential new ligands is to predict the binding affinity of a certain ligand to it’s as a criterion for selection.
A breakthrough work was done by Bohm to develop a general –purposed empirical function in order to describe the binding energy. The concept of the “Master Equation’’ was raised. The basic idea is that the overall binding free energy can be decomposed into independent component which are known to be important for the binding process. Each component reflects a certain kind of free energy alteration during the binding process between a ligand and its target receptor. The master equation is the linear combination of these components. According to Gibbs free energy equation, the relation between dissociation equilibrium constant, KD and components of free energy alteration was built.
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Advantage of Structure Based Drug Design: Time saver Accuracy will be higher than traditional techniques.
We synthesize new molecule (Ligand) easily by changing their functional groups.
General Steps Involved In Structure Based Drug Designing:-
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•
Clinical Trial or Biological Testing:-
Pharmaceutical clinical
trials are commonly classified into 4 phases:Phase o:- A recently designation for exploration , first-in-human trials ,Designed to expedite the development of promising therapeutic agents by establishing early on whether the agent behaves in human subjects as was anticipated from preclinical studies. Phase 1:- A small group of health volunteers (20-80) are selected to assess the safety, tolerability, pharmacokinetics and pharmacodynamics of a therapy. There are 3 common kinds of phase 1 trials • Single ascending dose (SAD) studies – a small group of patients are given a single dose of the drug and then monitored over a period of time. If they do not exhibit any adverse side effects, the dose is escalated and a new group of patients is given the higher dose. • Multiple ascending dose (MAD) studies- a group of patients receives multiple low doses of the drug, while blood (and other fluid) are various time points and analyses to understand how the drug is processed within the body. The dose is subsequently escalated for further group.
• 80% of drugs Fail the phase 1 clinical trial. Phase 2:- Performed on larger groups (20-300) and are designed to assess the activity of the therapy, and continue Phase 1 safety assessments. Phase 3:- Randomized controlled trials on large patient groups (hundreds to thousands) aimed at being the definitive assessment of the efficacy of the new therapy. Side effects are also monitored. It is typically expected that there be at least two successful phase III clinical trials to obtain approval from the FDA. Phase 4:- Post- launch safety monitoring and ongoing technical support of a drug. May be mandated or initiated by the pharmaceutical company. Designed to detect rare or long term adverse effects over a large patient population and timescale than was possible during clinical trials.
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3. MALARIA
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MALARIA:-
Malaria is a mosquito-borne infectious disease caused by a eukaryotic protist of the genus Plasmodium. It is widespread in tropical and subtropical regions, including parts of the Americas (22 countries), Asia, and Africa. Each year, there are approximately 350–500 million cases of malaria, killing between one and three million people, the majority of whom are young children in sub-Saharan Africa. Malaria is naturally transmitted by the bite of a female Anopheles mosquito. When a mosquito bites an infected person, a small amount of blood is taken, which contains malaria parasites. After a period of between two weeks and several months (occasionally years) spent in the liver, the malaria parasites start to multiply within red blood cells, causing symptoms that include fever, and headache. In severe cases the disease Worsens leading to hallucinations, coma, and death. Malaria is treated with intravenous or intramuscular quinine or, Increasingly, Resistance has developed to several ant malarial drugs, most notably chloroquine. Malaria transmission can be reduced by preventing mosquito Bites by distribution of inexpensive mosquito nets and insect Repellents, or by mosquito-control. Although many are under development, the challenge of Producing a widely available vaccine.
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Signs and Symptoms
Main symptoms of malaria:Symptoms of malaria include fever, shivering, arthralgia (joint Pain), vomiting, anemia (caused by hemolysis), hemoglobinuria, retinal damage, and convulsions.
Causative Agent
Appearance
Plasmodium vivax
Periodicity
tertian
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Persistent in liver?
Yes
Plasmodium ovale
tertian
Yes
Plasmodium falciparum
tertian
No
Plasmodium malariae
quartan
No
• Malaria parasites:Malaria parasites are members of the genus Plasmodium (phylum Apicomplexa). In humans malaria is caused by P. falciparum, P. malariae, P. ovale, P. vivax and P. knowlesi.
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Mosquito vectors and the Plasmodium life cycle:The parasite's primary (definitive) hosts and transmission vectors are female mosquitoes of the Anopheles genus, while humans and other vertebrates are secondary hosts. Young mosquitoes first ingest the malaria parasite by feeding on an infected human carrier and the infected Anopheles mosquitoes carry Plasmodium sporozoites in their salivary glands. A mosquito becomes infected when it takes a blood meal from an infected human. Once ingested the parasite gametocytes taken up in the blood will further differentiate into male or female gametes and then fuse in the mosquito gut. This produces an ookinete that penetrates the gut lining and produces an oocyst in the gut wall. When the oocyst ruptures, it releases sporozoites that migrate through the mosquito's body to the salivary glands, where they are then ready to infect a new human host. Only female mosquitoes feed on blood, thus males do not transmit the disease. The females of the Anopheles genus of mosquito prefer to feed at night.
Pathogenesis:-
23
The life cycle of malaria parasites in the human body. A mosquito infects a person by taking a blood meal. First, sporozoites enter the bloodstream, and migrate to the liver. They infect liver cells (hepatocytes), where they multiply into merozoites, rupture the liver cells, and escape back into the bloodstream. Then, the merozoites infect red blood cells, where they develop into ring forms, trophozoites and schizonts which in turn produce further merozoites. Sexual forms (gametocytes) are also produced, which, if taken up by a mosquito, will infect the insect and continue the life cycle. When an infected mosquito pierces a person's skin to take a blood meal, sporozoites in the mosquito's saliva enter the bloodstream and migrate to the liver. Within 30 minutes of being introduced into the human host, the sporozoites infect hepatocytes, multiplying asexually and asymptomatically for a period of 6–15 days. The parasite is relatively protected from attack by the body's immune system because for most of its human life cycle it resides within the liver and blood cells and is relatively invisible to immune surveillance. Some merozoites turn into male and female gametocytes. If a mosquito pierces the skin of an infected person, it potentially picks up gametocytes within the blood. New sporozoites develop and travel to the mosquito's salivary gland, completing the cycle. Pregnant women are especially attractive to the mosquitoes, and malaria in pregnant women is an important cause of stillbirths, infant mortality and low birth weight, particularly in P.falciparum infection, but also in other species infection, such as P. vivax.
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Treatment:- (Anti malarial drug) The traditional treatment for severe malaria has been quinine but there is evidence that the artemisinins are also superior for the treatment of severe malaria. A large clinical trial is currently under way to compare the efficacy of quinine and artesunate in the treatment of severe malaria in African children. Active malaria infection with P. falciparum is a medical emergency requiring hospitalization. Infection with P. vivax, P. ovale or P. malariae can often be treated on an outpatient basis. Treatment of malaria involves supportive measures as well as specific ant malarial drugs. Most ant malarial drugs are produced industrially and are sold at pharmacies.
Most Effective drug Against Malaria Disease:Following drug involved in Malaria treatment
Proguanil Primaquine Quinine Mefloquine Dapsone Choloquine Doxycycline Clomocycline Demeclocycline Sulfisoxazole Lymecycline Sulfametopyrazine
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4. Details of Drugs for Malaria Diagnosis
26
Some detail About drug which used for diagnosis:1.
Quinine:-
An alkaloid derived from the bark of the cinchona tree. It is
used as an ant malarial drug, and is the active ingredient in extracts of the cinchona that have been used for that purpose since before 1633. Quinine is also a mild antipyretic and analgesic and has been used in common cold preparations for that purpose. It was used commonly and as a bitter and flavoring agent, and is still useful for the treatment of babesiosis. Quinine is also useful in some muscular disorders, especially nocturnal leg cramps and myotonia congenital, because of its direct effects on muscle membrane and sodium channels. The mechanisms of its ant malarial effects are not well understood
Biodata of Quinine:Systematic (IUPAC) name of Quinine:- R)-[(5R,7S)-5-ethenyl-1azabicyclo[2.2.2]octan-7-yl]-(6-methoxyquinolin-4-yl)methanol
Identifiers: CAS Registry Number
130-95-0
PubChem Compound
8592 M09AA01
ATC Codes
P01BC01
27
Chemical Data:Chemical Formula
C20H24N2O2
Average mol. Wt.
324.4168
IsomericSMILES COC1=CC2=C(C=CN=C2C=C1)[C@@H](O)[C@@H]1C[C@H]2CC[N@@]1C[C@@H]2C=C
Pharmacokinetic Data:Biotransformation
Hepatic, over 80% metabolized by the liver.
Half Life
Approximately 18 hours
Absorption
76 - 88%
Pharmacology:Quinine is used parenterally to treat life-threatening infections caused by chloroquine-resistant Plasmodium falciparum malaria. Quinine acts as a blood schizonticide although it also has gametocytocidal activity against P. vivax and P. malariae. Because it is a weak base, it is concentrated in the food vacuoles of P. falciparum. It is thought to act by inhibiting heme polymerase, thereby allowing accumulation of its cytotoxic substrate, heme. As a schizonticidal drug, it is less effective and more toxic than chloroquine. However, it has a special place in the management of severe falciparum malaria in areas with known resistance to chloroquine.
28
• Mechanism of Action:The theorized mechanism of action for quinine and related anti-malarial drugs is that these drugs are toxic to the malaria parasite. Specifically, the drugs interfere with the parasite's ability to break down and digest hemoglobin. Consequently, the parasite starves and/or builds up toxic levels of partially degraded hemoglobin in itself.
3D Structure
2.Dapson:A sulfone active against a wide range of bacteria but mainly employed for its actions against mycobacterium leprae. Its mechanism of action is probably similar to that of the sulfonamides which involves inhibition of folic acid synthesis in susceptible organisms. It is also used with pyrimethamine in the treatment of malaria.
29
Biodata of Dapson(Systematic (IUPAC) name of Dapson):Chemical IUPAC Name
4-(4-aminophenyl)sulfonylaniline
Identifiers:CAS Registry Number
80-08-0
ATC Codes
J04BA02
PubChem Compound
2955
Drug ID Number [DIN]
02041510
Chemical data:-
Chemical Formula
C12H12N2O2S
Average Molecular Weight
248.3010
Pharmacokinetic data:-
Bioavailability
70 to 80%
Protein Binding
70 to 90%
Half Life
28 hours (range 10-50 hours)
Routes
Oral administration. 30
Pharmacology:Dapsone is a sulfone with anti-inflammatory immunosuppressive properties as well as antibacterial and antibiotic properties. Dapsone is the principal drug in a multidrug regimen recommended by the World Health Organization for the treatment of leprosy. As an anti-infective agent, it is also used for treating malaria and, recently, for Pneumocystic carinii pneumonia in AIDS patients. Dapsone is absorbed rapidly and nearly completely from the gastrointestinal tract.
Mechanism of Action:Dapsone acts against bacteria and protozoa in the same way as sulphonamides that are by inhibiting the synthesis of dihydrofolic acid through competition with Para-amino-benzoate for the active site of dihydropteroate synthetase. The anti-inflammatory action of the drug is unrelated to its antibacterial action and is still not fully understood.
•
3-D Structure:-
31
• Chloroquine: The prototypical ant malarial agent with a mechanism that is not well understood. It has also been used to treat rheumatoid arthritis, systemic lupus erythematosus, and in the systemic therapy of amebic liver abscesses
Biodata of Chloroquine:Systematic (IUPAC) name of Chloroqunie:Chemical IUPAC Name
N'-(7-chloroquinolin-4-yl)-N,N-diethylpentane-1,4diamine
Identifiers:CAS Registry Number
540706 P01BA01
ATC Codes P01BA02 PubChem Compound
2719
Drug ID Number [DIN]
00021261
Chemical data:Chemical Formula
C18H26ClN3
Average Mol. Wt.
319.8720
32
• Pharmacokinetic data:Biotransformation Hepatic (partially Half Life
1-2 months
Absorption
Completely absorbed from gastrointestinal tract
Protein Binding
~55% of the drug in the plasma is bound to nondiffusible plasma constituents
Mechanism of Action:The mechanism of plasmodicidal action of chloroquine is not completely certain. Like other quinoline derivatives, it is thought to inhibit heme polymerase activity. This results in accumulation of free heme, which is toxic to the parasites
• 3-D Structure:-
33
• Proguanil:Proguanil is a prophylactic ant malarial drug, which works by stopping the malaria parasite, Plasmodium falciparum and Plasmodium vivax, from reproducing once it is in the red blood cells. It does this by inhibiting the enzyme, dihydrofolate reductase, which is involved in the reproduction of the parasite.
• Biodata of Proguanil:Systematic (IUPAC) name of Proguanil:Chemical IUPAC Name
1-[amino-[(4-chlorophenyl)amino]methylidene]-2-propan-2ylguanidine
• Identifiers:CAS Registry Number
500-92-5
ATC Codes
P01BB01
PubChem Compound
4923
Drug ID Number [DIN]
02043068
34
• Chemical Data:Chemical Formula
C11H16ClN5
Average Molecular Weight
253.7310
• Pharmacokinetic data:Protein Binding
Approximately 75%
Half Life
Approximately 20 hours
Absorption
Rapidly and well absorbed in humans following oral doses ranging from 50 to 500 mg
•
Pharmacology:Proguanil is a biguanide derivative that is converted to an active metabolite called cycloguanil pamoate. It exerts its antimalarial action by inhibiting parasitic dihydrofolate reductase enzyme. It has causal prophylactic and suppressive activity against P. falciparum and cures the acute infection. It is also effective in suppressing the clinical attacks of vivax malaria. However it is slower compared to 4-aminoquinolines.
35
• Mode of Action:Proguanil inhibits the dihydrofolate reductase of plasmodia and thereby blocks the biosynthesis of purines and pyrimidines, which are essential for DNA synthesis and cell multiplication. This leads to failure of nuclear division at the time of schizont formation in erythrocytes and liver .
•
3-D Structure:-
36
5. DOCKING
37
• DOCKING:= Docking is a method which predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex. [1] Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using for example scoring functions. The associations between biologically relevant molecules such as proteins, nucleic acids, carbohydrates, and lipids play a central role in signal transduction.
Furthermore, the relative orientation of the two interacting partners may affect the type of signal produced. Therefore docking is useful for predicting both the strength and type of signal produced. [2] Given the biological and pharmaceutical significance of molecular docking, considerable efforts have been directed towards improving the methods used to predict docking. •
Docking Approaches:Three approaches are particularly popular within the molecular docking community. One approach uses a matching technique that describes the protein and the ligand as complementary surfaces. The second approach simulates the actual docking process in which the ligand – protein pairise interaction energies are calculate:-
38
• Shape
complementary:-
Geometric
matching/
shape
complementarily methods descried the protein and ligand as a set of features that make them dock able.
• Simulation: - The simulation of the docking process as such is a much more complicated process.
• Receptor flexibility: - computational capacity has increased dramatically over the last decade making possible the use of more sophisticated and computationally intensive methods in computer – assisted drug design. •
Mechanism of Docking:-
A binding interaction between a small
molecule ligand and an enzyme protein may result in activation or inhibition of the enzyme. If the protein is a receptor, ligand binding may result in agonism or antagonism. Docking is most commonly in the field of drug design – most drugs are small organic molecule, and docking may be applied to :-
•
Docking Application:-
•
Hit Identification – docking combined with a scoring function can be used to quickly screen large databases of potential drugs in silico to identify molecules that are likely to bind to protein Target of interest.
•
Lead optimization-
docking can be used to predict in where and in
which relative orientation a ligand binds to a protein. This information may in turn to design more potent and selective analogs.
39
• Bioremediation- Protein ligand docking can be used to predict pollutants that can be degraded by enzymes. •
Docking importance:-
A compound (drug) which binds to a
biological macromolecule (protein) ,may inhibit its function and thus act as a drug.
• Most for commonly used software Docking: Flex X Gold Auto dock Virtual dock Dock
DOT
40
6. REQUIRMENT OF MY PROJECT
41
• REQUIREMENT OF MY PROJECT Protein- 30s ribosomal protein download from RCSB Protein Data Bank Ligand- Quinine (DBOO687) & Chloroquine (DBOO608) download from drug bank > take Canonical SMILES format CORINA server for 3-D structure Optimizd ligand from the Argus lab Portable molegro virtual docker to perform dock Protein:- In my project I had used target protein for docking i.e. 30S – ribosomal protein . Its gene name is rpoA & present on locus IPR001892, PF00416. Ribosomal protein 2891 AA. Ribosomal proteins, particularly those of the large subunit, are composed of a globular, surfaced-exposed domain with long finger-like projections that extend into the rRNA core to stabilize its structure. In the large subunit, about 1/3 of the 23S rRNA nucleotides are at least in van der Waal's contact with protein, and L22 interacts with all six domains of the 23S rRNA. Proteins S4 and S7, which initiate assembly of the 16S rRNA, are located at junctions of five and four RNA helices, respective. •
Sequence: MAEDNKKVAEVSTEETQAHTAPTATAQQTNPTEFLDTFDWERYSEGIEKVDEDQ LKAFEKLVEDNFVDTIDNDVMTGVVIKITDRDAIIDINAKSEGVISLNEFRYNPNL KEGDKVEVLVDVREDATGQLVLSHRKARLIKAWERVNNAHDTGEIVNGYVKCR TKGGMIVDVFGIEAFLPGSQIDVKPIRDYDAYVDKTMEFKVVKINHEFKNVVVS HKALIEADIEEQKKEIISRLEKGQVLEGVVKNITSYGVFVDLGGVDGLVHITDLS WSRINHPNEVVELDQTLNVVILDFDEDKSRIQLGLKQLEPHPWEALSDKIKPGDN VKGKVVVIADYGAFVEIEEGVEGLIHVSEMSWSTHLRSAGDFVKVGDTVDAQV LTIDREDRKMSLGMKQLHPDPWTDITTKYPVGSRHTGVVRNFTNFGVFVELEEG VDGLIYISDLSWTKKIKHPSEFCAVGDKLDIVVLELDVEGRKLSLGHKQTMDNP WDKYEAEFGIGTTHDVTITDMVDKGAVVEFNEDITAFIPTRHLEKEDGTKLKKG ESAQIQIIEFNKEFKRVVASHMVIHKEEEAKIVKQAAAKSQESTDKPTLGDANSK LQALKDRMEGKVAAPAASTEE. 42
• Ligand:I have taken these two drugs for docking in this project•
Quinine:- quinoline anti-malarial drugs, the action of quinine has not been fully resolved. The most widely accepted hypothesis of quinine action is based on the well-studied and closely related quinoline drug, chloroquine. This model involves the inhibition of hemozoin biocrystallization, which facilitates the aggregation of cytotoxic heme. Free cytotoxic heme accumulates in the parasites, leading to their death.
43
•
Chloroquine:
Chloroquine can be used for preventing malaria from
Plasmodium vivax, ovale and malariae. Popular drugs based on chloroquine phosphate (also called nivaquine) are Chloroquine FNA, Resochin and Dawaquin. Many areas of the world have widespread strains of chloroquine-resistant P. falciparum, so other antimalarials like mefloquine or atovaquone may be advisable instead. Combining chloroquine with proguanil may be more effective against chloroquine-resistant Plasmodium falciparum than treatment with chloroquine alone, •
CORINA SERVER:- CORINA is a fast and powerful 3D structure generator for small and medium sized, typically drug- like molecule. Its robustness, application to convert large chemical database. CORINA matured through a series of version the past decades
and has become the recognized world-wide go standard in industry and is used by Symyx, NCI/NIH and most major pharmaceutical and chemical companies to convert their 2D structure into 3D.
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Feature
Description
Input file format
SD/RD file, SMILES, SYBYL, MOL/MOL2, Macro Model, Maestro, CTX file.
Output file format
SD/RD file, SYBYL, MOL/MOL2, PDB, Macro Model, Maestro, CIF, CTX file.
Conformer generation
Generates a single , high- quality and low- energy conformation. Optionally generates multiple conformation for ring system
Stereo information
Handles properly stereo chemical information (atoms of up to a co-ordination no. of 6) Optionally generates stereoisomer’s
Structure control
Include optionally structure clean – up and standardization feature Canocicalizes structures internally to ensure atom numbering- independent conformations Orients structures as a function of their principal moment of interia
Speed and reliability
Handle a broad range of organic chemistry organ metallic compound with atoms of up to a co-ordination no. of 6 Process a data set of 100,100 small to medium-sized molecules in 2,301 sec on a 1.0 GHz workstation(23 ms/cpd, 99.99% conversion rate)
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User Interface: Command line interface supporting batch mode. Component for Accelrys Pipeline Pilot. Java- based graphical user interface CORINA.direct to trigger the command line version.
Screenshot of CORINA:-
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Argus Lab:-
Portable Molegro Virtual Docker:Molegro Virtual Docker is an integrated plateform for predicting Protein –Ligand interaction. Molegro Virtual Docker handles all aspects of the docking process from preparation of the molecules to determination of the potential binding sites of the target protein, and prediction of the binding modes of the ligand . Molegro Virtual Docker offers high –quality docking based on a noval optimization technique combined with a user interface experience focusing on usability and productivity. The Molegro Virtual Docker (MVD) has been shown to yield higher docking accuracy than other state – of –the –art docking product (MVD: 87%, Glide: 82%, Surflex:75%, FlexX: 58%).
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• Molegro Virtual Docker Providers:
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7. Homology Modeling
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Performing Homology Modeling:Homology Search-
MOE > SE > Homology > PDB Search
Double click on the Z- Score value, this will open Load alignment window.
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Press Load AllSequence Editor- MOE > Window > Sequence Editor. SE > Display > Actual Secondary Structure
Building a Homology ModelSE > Selection > Invert Chains
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Now MOE – Align applicationSE > Homology > Align
In MOE – Align panel, select Freeze in the chain Selection option. Press – OK to perform the alignment
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In MOE- Align finishes calculating the sequence alignment, SE > Window > Commands.
Open Homology Model with SE > Homology > Homology Model. Press OK.
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Database Viewer:-
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Choose MOE > Render > Hide > All then MOE > Render > Show > Backbone and MOE > Render > Backbone > Cartoon. To render the final model as shown here:-
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Evaluating the Homology ModelSE > Measure > Protein Geometry to investigate the stereo chemical fitness of our Model.
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8. Docking in Virtual Dock
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Docking in virtual dock is divided into following steps -: (A) Preparing the protein file (30s Ribosomal Protein) (B) Preparing the ligand file (Quinine)
STEPS INVOLVED IN Virtual dock:Preparing the macromolecule file:Open PDB file in current Directory •
File >import the molecule>select PDB ID 30s ribosomal protein.pdb>Open
•
IMPORT MOLECULE
File> import molecule > preparation > assign bond, assign bond order & hybridization, create explicit hydrogen’s > always > import.
Preparing a ligand file: Take the desire ligand (drug) in RCSB PDB in Smile Format. File >import the molecule>select PDB ID Quinine.pdb>Open
IMPORT MOLECULE:File> import molecule > preparation > assign bond , assign bond order & hybridization , create explicit hydrogen’s > always > import.
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• Performing of Docking :1.
Open docking wizard
the file where you want > START the DOCKING Scoring method Next>score {Mol Dock Score [Grid]} > grid resolution [Å] 0.50 > Ligand evaluation, internal ES, internal H bond, Sp2-Sp2 – Torsions all selected > radius - > Next Algorithm – Mol Dock SE > no. of runs – 100 > max. Iterations – 500 > max. steps – 9999> next > next > next.
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Customize search Algorithm:-
Set search algorithm Algorithm (mol
dock SE) > number of runs – 50Set parameter population size – 50
Max iterations – 100000 > max
Pose generation is default Set simplex evolution Max steps-500 > neighbor distance factor- 1.00 > next
Post clustering are default > next Errors and warnings is default > next Setup docking execution Choose how to execute the docking > run docking in separate process Data Output directory > choose directory > save found poses as – Mol2 62
Start docking Protein (30s –Ribosomal Protein ) – Ligand (Quinine ) in virtual dock :-
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• (Quinine) Mol dock score of docking:Run 1. 2. 3. 4. 5.
Energy(mol dock) -492.815 -492.813 -492.812 -492.481 -488.416
Rerank Score Total- 5.24558
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Torsion 4
• Graph of 30s- Ribosomal Protein docking:-
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Second Drug (Chloroquine) STEPS INVOLVED IN Virtual dock:Preparing the macromolecule file:• Open PDB file in current Directory •
File >import the molecule>select PDB ID 30s ribosomal protein.pdb>Open
•
IMPORT MOLECULE
File> import molecule > preparation > assign bond, assign bond order & hybridization, create explicit hydrogen’s > always > import.
Preparing a ligand file: Take the desire ligand (drug) in RCSB PDB in Smile Format. File >import the molecule>select PDB ID Chloroquine.pdb>Open
IMPORT MOLECULE:File> import molecule > preparation > assign bond, assign bond order & hybridization, create explicit hydrogen’s > always > import.
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Performing of Docking :-Open docking wizard The file where you want > START the DOCKING Scoring method Next>score {Mol Dock Score [Grid]} > grid resolution [Å] -0.50 > Ligand evaluation, internal ES, internal H bond, Sp2-Sp2 – Torsions all selected > radius - > Next Algorithm – Mol Dock SE > no. of runs – 100 > max. Iterations – 500 > max. Steps – 9999> next > next > next.
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Customize search Algorithm: Set search algorithm Algorithm (mol dock SE) > number of runs – 100 Set parameter Max iterations – 100000 > max population size – 50 Pose generation is default Set simplex evolution Max steps-500 > neighbor distance factor- 1.00 > next
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Post clustering are default > next Errors and warnings is default > next Setup docking execution Choose how to execute the docking > run docking in separate process Data output Output directory > choose directory > save found poses as – Mol2
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Start docking Protein (30s –Ribosomal Protein ) – Ligand (Chloroquine ) in virtual dock :-
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(Chloroquine) Mol dock score of docking:-
Run 1. 2. 3. 4. 5.
Energy(Mol dock score) -489.874 -489.861 -489.176 -489.158 -476.114
Rerank score Total-5.3385
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Torsion 4
Graph of 30s- Ribosomal Protein docking:-
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9. Conclusion
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Conclusion: -
Comparison of two drugs for target (30s
Ribosomal Protein). Target Protein
Ligand 1- Quinine(mol
Ligand 2-
dock score)
Chloroquine (mol dock score)
30s ribosomal protein1
-492.815
-489.774
30s ribosomal protein2
-492.813
-489.761
30s ribosomal protein3
-492.812
-489.176
30s ribosomal protein4
-492.481
-489.158
30s ribosomal protein5
-488.416
-476.114
When I perform docking experiment for two drugs, which is target for 30s Ribosomal Protein then I see that drug Chloroquine (- 476.114k.cal/mol) performing more docking than Quinine (- 488.416k.cal/mol). So finally I say that on the basis of binding energy the drug Chloroquine should be perform best activity against the Malaria. • So, these Chloroquine Drug is going for Clinical Trial.
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10. REFERENCES
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REFERENCE (1) Abad-Zapatero, C. and Metz, J.T. (2005) Ligand efficiency indices as guideposts for drug discovery. Drug Discov. Today, 10, 464–469. (2) Brooijmans, N. and Kuntz, I.D. (2003) Molecular recognition and docking algorithms. Annu. Rev. Biophys. Biomol. Struct., 32, 335–373. (3) Hete´ nyi, C. et al. (2006) Combination of a modified scoring function with twodimensional descriptors for calculation of binding affinities of bulky, flexible, ligands to proteins. J. Am. Chem. Soc., 128, 1233–1239. (4) Kuntz, I.D. et al. (1999) the maximal affinity of ligands. Proc. Natl Sci.USA, 96, 9997–10002.
Acad.
(5) Morris,G.M. et al. (1996) Distributed automated docking of flexible ligands to proteins: parallel applications of Auto Dock 2.4. J. Comput. Aided Mol. Des., 10, 293–304. (6) Schuffenhauer, A. et al. (2006) Relationships between molecular complexity, biological activity, and structural diversity. J. Chem. Inf. Model., 46, 525–535. (7) Poinar G (May 2005). "Plasmodium dominicana n. sp. (Plasmodiidae: Haemospororida) from Tertiary Dominican amber". Syst. Parasitol. 61 . (8) Joy DA, Feng X, Mu J, Furuya T, Chotivanich K, Krettli AU, Ho M, Wang A, White NJ, Suh E, Beerli P, Su XZ. (2003). "Early origin and recent expansion of Plasmodium falciparum.". Science. (9) Hayakawa T, Culleton R, Otani H, Horii T, Tanabe K (2008). "Big bang in the evolution of extant malaria parasites.” Mol Biol Evol2239. (10)
Martin MJ, Rayner JC, Gagneux P, Barnwell JW, Varki A
(2005). "Evolution of human-chimpanzee differences in malaria 76
susceptibility: relationship to human genetic loss of N-glycolylneuraminic acid.". Proc Natl Acad Sci U S A. 102 12824. (11)
Escalante A, Freeland D, Collins W, Lal A (1998). "The evolution of
primate malaria parasites based on the gene encoding cytochrome b from the linear mitochondrial genome.". (12)
Roy SW, Irimia M (2008). "Origins of human malaria: rare genomic
changes and full mitochondrial genomes confirm the relationship of Plasmodium falciparum to other mammalian parasites but complicate the origins of Plasmodium vivax". (13)
Mol Allison AC. (2009). "Genetic control of resistance to human
malaria.” Curr Opin Immunol. 21.
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