ABSTRACT
Lassa fever is a viral hemorrhagic fever caused by the Lassa virus which is found in West Africa and is transmitted through contact with the urine or feces of infected rodents. The fatality rate for Lassa fever is 1-15%. However, the rate is higher in pregnant women and people with underlying medical conditions. GPC protein was identified as the main target for combating of Lassa fever, Lymphocytic Choriomeningitis Virus (LCMV) and also Ebola virus. Molecular docking virtual screening was performed to screen and identify the best lead compounds. SWISSADME and pkCSM were used to predict the drug likeness and ADME properties of the studied compounds. The chemical reactivity of the studied compounds were computed using DFT calculations. Based on the Molecular Virtual Docking Screening performed on compounds 14 of series A and compound 15 of series B, compound 14 and compound 15 were identified as the best lead compounds in this study, with Moldock scores of -165.35 Kcalmol-1 and -168.523Kcalmol-1 respectively. The drug likeness and ADMET properties prediction performed showed that the studied compounds including the best lead compound were drug-like in nature with good pharmacokinetic profile, and they all have Bioavailability Score of 0.55 respectively. Furthermore, based on the DFT calculations, compound 26 and 1 with energy gap 3.9 and -11.4 for series A and B were identified in this study as the most reactive respectively. Base on this research the compound identified can serve as potential drugs for Lassa fever based on their mole dock score, Drug likeness and DFT.
TABLE OF CONTENTS
Cover page i
Fly leaf page ii
Tittle page iii
DECLARATION iv
CERTIFICATION v
ACKNOWLEDGEMENT vi
DEDICATION vii
ABSTRACT viii
TABLE OF CONTENTS ix
LIST OF ABBREVIATIONS xii
LIST OF TABLES xiii
LIST OF FIGURES xiv
CHAPTER ONE
1.0 INTRODUCTION
1.1 Background of the Study 1
1.2 Resistance of Ribavirin and Favipiravir in the treatment of Lassa fever 2
1.3 Treatment Strategies of Lassa fever 3
1.4 Development of Inhibitors of GPC Protein 3
1.5 Mechanism of Action of Anti Lassa fever Drugs 4
1.6 Rational Drug Design / Computer Aided Drug Design 4
1.6.1 Structure-based Drug Design 5
1.6.2 Ligand based drug design 5
1.7 Statement of Research Problem 6
1.8 Research Justification 6
1.9 Research Question 6
1.10 Research Hypothesis 6
1.11 Aims and Objectives 7
1.12 Scope and Limitations 7
CHAPTER TWO
2.0 LITERATURE REVIEW
2.1 Molecular Docking, Pharmacokinetics and DFT Studies 9
2.1.1 Molecular Docking Virtual Screening 10
CHAPTER THREE
3.0 MATERIALS AND METHODS
3.1 Materials 12
3.1.1 Computer specifications 12
3.1.2 Software 12
3.2. Molecular Docking Method 12
3.2.1 Data set 12
3.2.2 Molecular structure generation using ChemDraw Ultra V12.0 12
3.2.3 Geometry optimization with spartan 14 V1.1.0 25
3.2.4 Method of retrieving target receptor 25
3.2.5 Compound and receptor target preparations 25
3.2.6 Receptor-ligand docking using MVD software 25
3.2.8 Procedure in viewing interaction residues of the complex with Discovery Studio 26
3.3 Pharmacokinetics properties prediction method 26
3.4 DFT method 27
CHAPTER 4
4.0 Results and discussions
4.1 Molecular Docking Result for Series A 29
4.2 Drug-likeness study of series A compounds 34
4.2 Drug Likeness table of Series A 34
4.3 Summary of rules Violated by Series A compounds 36
4.3 ADME-Toxic properties of Series A 37
4.4 ADME-Toxic properties of table Series A 37
4.4 Density functional theory calculations for series A 38
4.5 DFT calculations of series A 38
4.5 Molecular Docking Result for Series B 43
4.6 Molecular Docking Result for Series B 44
4.6 Drug-likeness study of series B compounds 49
4.7 Drug Likeness table of Series B 49
4.8 Violations table of Series B 50
4.7 ADME-Toxic properties of Series B 51
4.8 ADME-Toxic properties table of Series B 51
4.8 Density functional theory calculations for series B 51
4.9 DFT calculations table of series B 51
CHAPTER FIVE
5.0 Summary, Conclusion and Recommendation
5.1 SUMMARY 58
5.2 CONCLUSION 58
5.3 RECOMMENDATION 58
REFERENCES 60
LIST OF ABBREVIATIONS
GPC, Glycoprotein Complex
LCMV, Lymphocytic Choriomeningitis Virus
ADMET, Absorption, Distribution, Metabolism, Excretion, Toxicity
DFT, Density Functional Theory
GPC, Glycoprotein Complex
MVD, Molegro Virtual Docker
QSAR, Quantitative Structure-activity Relationship
2D , 2 Dimensional
HOMO, Highest Occupied Molecular Orbital
LUMO, Lowest Unoccupied Molecular Orbital
GP , Glycoprotein
SMILES. Simplified Molecular Input Line Entry System
RNA, Ribonuclei Acid
LBDD, Ligand Based Drug Design
UK, United Kingdom
SBDD, Structure Based Drug Design
MDPI, Multidisciplinary Digital Publishing Institute
MFA, Multifacor Authentication
3D, 3 Dimensional
LASV, Lassa Fever Virus
QSAR, Quantity Structure Activity Relationship
CDC, Center for Disease Control
WHO, World Health Organization
LASV GPC , Lassa Fever Virus Glycoprotein Complex
GP2, Glycoprotein 2
HF, Hemorrhagic Fever
RAM, Random Access Memory
ADME, Absorption, Distribution, Metabolism, Excretion
GB, Gigabyte
PDB, Protein Data Bank
V14.1, Version 14.1
SSP, Stable Signal Peptide
LIST OF TABLES
Table 3.1: Series A data set……………………………………………….…………………….25
Table 3.2: Series B data set…….……………………………………………………………….27
Table 4.1: Series A docking results………………………….………….………………………42
Table 4.2: Series A drug likeness result................................................................................…...48
Table 4.3: Summary of violation of filtering criteria…………………………..……………….49
Table 4.4: Series A ADMET (Pharmacokinetic) result…...........................................................50
Table 4.5: Series A DFT Calculations….....................................................................................50
Table 4.6: Series B docking results…..........................................................................................57
Table 4.7: Series B drug likeness result…...................................................................................63
Table 4.8: Summary of violation of the filtering criteria….........................................................64
Table 4.9: Series B ADMET (Pharmacokinetic) result………………………………………...65
Table 4.10: Series B DFT Calculations……………………………………………..………….66
LIST OF FIGURES
Figure 1.0 Schematic flow chart of the methodology………………………… 11
Figure 1.1 showing 2D structure of compound 14………………………….... 31
Figure 1.2 showing 2D structure of compound 7…………………………… 31
Figure 1.3 showing 2D structure of compound 18…………………………… 32
Figure 1.4 showing 2D structure of compound 15…………………………… 32
Figure 1.5 showing 2D structure of compound 24…………………………… 33
Figure 2.0 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 26 ………………………………38
Figure 2.1 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 27 ……………………………………39
Figure 2.2 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 28………………………………………………….........40
Figure 2.3 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 29……………………………………………41
Figure 2.4 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 21……………………………………………………42
Figure 3.0 showing 2D structure of compound 16………………………….... 45
Figure 3.1 showing 2D structure of compound 15…………………………… 45
Figure 3.2 showing 2D structure of compound 13…………………………… 46
Figure 3.3 showing 2D structure of compound 12…………………………… 47
Figure 3.4 showing 2D structure of compound 14…………………………… 47
Figure 4.0 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 1………………………………………………………52
Figure 4.1 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 2………………………………………………53
Figure 4.2 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 3………………………………………………54
Figure 4.3 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 4……………………………………………………………............
55
Figure 4.4 (a, b & c) showing Lumo, Homo and electrostatic potential of compound 21…………………………………………………56
CHAPTER ONE
1.0 INTRODUCTION
1.1 Background of the Study
Lassa fever is a viral hemorrhagic fever caused by the Lassa virus(Mark, 2022). It is a zoonotic disease, meaning that it is spread from animals to humans(Hitlon, 2021). The virus is found in West Africa, and is transmitted through contact with the urine or feces of infected rodents, such as the multimammate rat. The incubation period for Lassa fever is typically between 2-21 days, the onset of symptoms is usually gradual, starting with fever, general weakness, and malaise(Ibekwe et al., 2011). Other symptoms may include headache, sore throat, cough, muscle pain, chest pain, nausea, vomiting, diarrhea, and conjunctivitis(Macher, 2006). In severe cases, Lassa fever can lead to bleeding, shock, and organ failure(Mark, 2022). The case fatality rate for Lassa fever is 1-15%. However, the fatality rate is higher in pregnant women and people with underlying medical conditions. There is no specific treatment for Lassa fever, but supportive care can help to improve the chances of survival(Houlihan, 2017).
GPC protein, or glycoprotein polyprotein GP complex, is a protein found in a number of enveloped viruses, including lymphocytic choriomeningitis virus (LCMV), Lassa virus, and Ebola virus. It is a precursor protein that is cleaved into three smaller proteins: glycoprotein G1, glycoprotein G2, and the stable signal peptide (SSP)(Madu et al., 2018). The GPC protein is responsible for mediating the fusion of the viral and host cell membranes(Cashman et al., 2011). This fusion is triggered by a drop in pH, which occurs when the virus enters the endosome of the host cell(Chen et al., 2023). The GPC protein then undergoes a conformational change that exposes its fusion peptide, which inserts into the host cell membrane and fuses the two membranes together(Chen, 2019). The GPC protein is a target for antiviral drugs. Some antiviral drugs, such as favipiravir, work by inhibiting the activity of the GPC protein, preventing it from mediating the fusion of the viral and host cell membranes(Houlihan, 2017).
Some additional details about the GPC protein are:
i. It is a large protein, with a molecular weight of around 40 kDa(Houlihan and Behrens, 2017).
ii. It is made up of about 350 amino acids(Madu et al., 2018).
iii. It is found in the envelope of the virus.
iv. It is cleaved into three smaller proteins after the virus enters the host cell(Bell et al., 2017).
v. It is essential for the fusion of the viral and host cell membranes(Acciani et al., 2017).
vi. It is a target for antiviral drugs(Cashman et al., 2022).
There is no specific treatment for Lassa fever, but supportive care can help to improve the chances of survival(Robert F Garry, 2023). This may include fluids, electrolytes, and medications to treat fever and pain. In some cases, antiviral drugs may be used. However, there are two main drugs used for the treatment of Lassa fever(Robert F Garry, 2023):
Ribavirin is an antiviral drug that has been used to treat Lassa fever for more than 30 years(Kyle, 2018). It is most effective when given early in the course of the illness. Ribavirin is a small molecule that inhibits the replication of RNA viruses. It is thought to work by interfering with the synthesis of viral RNA(Kyle, 2018). Favipiravir is a newer antiviral drug that has been shown to be effective in treating Lassa fever in animal studies. It is not yet approved for use in humans, but it is being considered for emergency use in Lassa fever outbreaks(Chen et al., 2023).
Both ribavirin and favipiravir are taken orally. Ribavirin is also available as an intravenous infusion. The side effects of ribavirin and favipiravir can include nausea, vomiting, diarrhea, and liver damage(Kyle, 2018).
1.2 Resistance of Ribavirin and Favipiravir in the treatment of Lassa fever
In some cases, the Lassa virus can develop resistance to anti-Lassa fever drugs(Madu et al., 2018). This is because the virus can mutate, which can change the structure of the proteins that are targeted by the drugs. When the structure of the proteins changes, the drugs may no longer be able to bind to the proteins and inhibit their activity(Kyle, 2018).
Ribavirin and favipiravir are both effective antiviral drugs for treating Lassa fever, but there is evidence that resistance to these drugs may be emerging. In a study published in 2018, it was reported that a small number of Lassa virus strains had developed resistance to ribavirin(Dalhat, 2020) and was associated with a mutation in the viral genome. It was reported that a small number of Lassa virus strains had developed resistance to favipiravir and the resistance to was associated with a mutation in the viral genome(Kyle, 2018). Also the emergence of resistance to ribavirin and favipiravir is a concern, as it could make it more difficult to treat Lassa fever(Dalhat, 2020). However, it is important to note that these studies were small, and more research is needed to confirm the findings. The resistance to ribavirin and favipiravir is not common, and most patients who are treated with these drugs will still respond to treatment. However, the potential for resistance, and to monitor patients for signs of treatment failure(Zhang et al., 2019).
1.3 Treatment Strategies of Lassa fever
There is no specific treatment for Lassa fever, but supportive care can help to improve the chances of survival(Chen et al., 2023). This may include fluids, electrolytes, and medications to treat fever and pain. In some cases, antiviral drugs may be used. The best way to prevent Lassa fever is to avoid contact with infected rodents(Hitlon, 2021). This can be done by:
i. Avoiding areas where rodents are common
ii. Wearing gloves and a mask when cleaning or handling materials that may be contaminated with rodent urine or feces
iii. Keeping food and water in rodent-proof containers
iv. Sealing up any cracks or holes in your home that rodents could use to enter(Houlihan and Behrens, 2017).
1.4 Development of Inhibitors of GPC Protein
The GPC protein is a key target for the development of antiviral drugs against Lassa fever(Huo, 2021). There are a number of different approaches that are being used to develop inhibitors of the GPC protein. One approach is to target the fusion peptide, which is a short sequence of amino acids that is responsible for inserting the viral membrane into the host cell membrane(Zhang et al., 2020). Another approach is to target the stable signal peptide (SSP), which is a region of the GPC protein that is essential for the correct folding and assembly of the protein(P. Wang et al., 2018).
A number of different inhibitors of the GPC protein have been identified in preclinical studies. Some of these inhibitors have shown promising activity in animal models of Lassa fever. However, further research is needed to develop these inhibitors into safe and effective drugs for human use(Huo, 2021).
Some of the challenges that need to be addressed in the development of inhibitors of the GPC protein are:
i. The GPC protein is a large and complex protein, which makes it difficult to target with small molecule drugs(Chen et al., 2023).
ii. The GPC protein is also highly conserved among different arenavirus species, which makes it difficult to develop inhibitors that are specific to a particular virus(Guo, 2020).
iii. The GPC protein is essential for the replication of arenavirus, which means that any inhibitor of the GPC protein is likely to have significant side effects(Madu et al., 2018).
Despite these challenges, the development of inhibitors of the GPC protein is an active area of research. With continued research, it is possible that these inhibitors will be developed into safe and effective drugs for the treatment of Lassa fever and other arenavirus infections(Hitlon, 2021).
1.5 Mechanism of Action of Anti Lassa fever Drugs
There are two main drugs used to treat Lassa fever: Ribavirin and Favipiravir. Both drugs work by inhibiting the replication of the Lassa virus(P. Wang et al., 2018).
Ribavirin is a small molecule that inhibits the synthesis of viral RNA. It does this by binding to the RNA-dependent RNA polymerase, an enzyme that is essential for the replication of RNA viruses(Rosenke et al., 2018). Ribavirin is thought to work by interfering with the binding of the RNA-dependent RNA polymerase to the viral RNA, which prevents the enzyme from copying the viral RNA(Liu et al., 2021).
Favipiravir is a newer antiviral drug that is also thought to inhibit the replication of RNA viruses(Kyle, 2018). It is a prodrug, meaning that it is converted into its active form in the body. Favipiravir is thought to work by targeting the polymerase complex, a complex of proteins that is responsible for copying the viral RNA(Lingas et al., 2021). Favipiravir is thought to work by interfering with the activity of the polymerase complex, which prevents the complex from copying the viral RNA(P. Wang et al., 2018).
1.6 Rational Drug Design / Computer Aided Drug Design
Rational drug design is a process of designing drugs that are specifically targeted to a particular biological target(Chen et al., 2023). This is in contrast to traditional drug discovery methods, which typically involve screening large libraries of compounds for those that have some desired activity. Rational drug design is based on the understanding of the molecular basis of disease. By understanding how a disease works, it is possible to design drugs that specifically target the molecules that are involved in the disease process. This can lead to more effective and targeted drugs with fewer side effects(Pushpakom et al., 2019).
There are two basic approaches that are employed in rational drug design; the structure and ligand based drug design(Perole, 2013).
1.6.1 Structure-based Drug Design
This approach uses the three-dimensional structure of a target molecule to design drugs that will bind to it. This is the most common approach to rational drug design, and it has been used to design a number of successful drugs. There are two methods used in his approach; the molecular docking and fragment based virtual screening(Perole, 2013).
1.6.2 Ligand based drug design
Ligand-based drug design (LBDD) is a drug discovery approach that relies on knowledge of molecules that bind to the biological target of interest. It is an indirect approach, as it does not require knowledge of the target's structure(Liu et al., 2021). Instead, LBDD is based on the chemical information of the active and non-active compounds within a tested series in order to correlate the biological activity with the chemical structure (SAR – Structure Activity Relationship)(Perole, 2013). This approach is based on the principle that the binding of a ligand to a receptor is driven by the formation of specific interactions between the two molecules. By understanding the nature of these interactions, it is possible to design new ligands that will interact with the receptor in a more favorable way(Perole, 2013).
LBDD is a complementary approach to structure-based drug design (SBDD), which is often used when the structure of the receptor is not known, or when the structure is not well-defined(Larson, 2013). There are a number of different methods that can be used for LBDD, including:
i. Comparative molecular field analysis (CoMFA): CoMFA is a method that uses the 3D coordinates of a ligand-receptor complex to calculate a number of molecular descriptors, which are then used to build a quantitative structure-activity relationship (QSAR) model. This model can then be used to predict the binding affinity of new ligands(Perole, 2013).
ii. Pharmacophore mapping: Pharmacophore mapping is a method that identifies the essential features of a ligand that are required for binding to a receptor. These features can then be used to design new ligands that contain these features(Perole, 2013).
iii. Ligand-based virtual screening: Ligand-based virtual screening is a method that uses a library of known ligands to search for new ligands that have the desired binding properties. This method is often used to identify new leads for drug discovery(Perole, 2013).
LBDD is a powerful tool for drug discovery, and it has been used to design a number of successful drugs. However, LBDD also has some limitations. For example, LBDD is only as good as the quality of the data that is used to build the QSAR model. If the data is not accurate, the model will not be accurate, and the predictions will not be reliable(Perole, 2013).
1.7 Statement of Research Problem
Lassa fever is a serious and potentially fatal disease that is endemic in parts of West Africa(Hitlon, 2021). The disease is caused by the Lassa virus, which is spread through contact with the urine or feces of infected rodents. There is no specific treatment for Lassa fever, but supportive care can help to improve the chances of survival. As such there is need to develop an effective drug for the treatment of the virus. Drug design is a costly and time consuming process. A huge amount of resources and time are consumed(Hitlon, 2021).
1.8 Research Justification
Lassa fever is a major public health problem in West Africa, and it has the potential to spread to other parts of the world. Effective prevention and control measures are essential to protect public health. Due to the need for effective drug against Lassa fever in order to address the spread of the virus, computer aided drug design technique such as molecular docking, drug likeness, ADME properties evaluation and DFT calculations can play a vital role by reducing the amount of money, and time involved in search of new drug against Lassa fever.
1.9 Research Question
1. Are the studied compounds drug like in nature?
2. Do the studied compounds have good ADMET properties?
3. Are the compounds reactive?
4. Can the DFT calculations give hints or review on the reactivity of the compounds?
1.10 Research Hypothesis
Null hypothesis:
1. The studied compounds does not have favorable binding interaction against the target.
2. The studied compounds are not orally bioavailable.
3. The studied compounds are not very reactive.
Alternate hypothesis:
1. The studied compounds have favorable binding interaction against the target.
2. The studied compounds are orally bioavailable.
3. The studied compounds are very reactive.
1.11 Aims and Objectives
The aim of this work is to carry out molecular docking, pharmacokinetic properties evaluation and DFT calculations on some anti-Lassa fever agents. This aim would be achieved through the following objectives, to;
1. Collect data from literatures.
2. Generate and optimize the structures of the data sets.
3. Carry out molecular docking virtual screening of data sets.
4. Carry out pharmacokinetic and ADMET properties evaluation of data sets.
5. Carry out DFT calculations on data set.
1.12 Scope and Limitations
The research will focus on the molecular docking virtual screening drug-likeness pharmacokinetic properties prediction and DFT calculations of compounds specifically targeting Lassa fever.
Click “DOWNLOAD NOW” below to get the complete Projects
FOR QUICK HELP CHAT WITH US NOW!
+(234) 0814 780 1594
Login To Comment