Masterarbeit, 2021
68 Seiten
Abstract
Acknowledgement
1. Introduction
2. Thesis Background
2.1. Detecting COVID-19
2.2. Age Risk
2.3. Testing Process of COVID-19
2.4. Forestall the spread of COVID 19
2.5. UniportKB
2.6. Swiss Model
2.7. CASTp
2.8. E-LEA3D
2.9. FAF drugs4
3. Objectives
4. Methodology
4.1. Data Collection
4.2. Structure Validation
4.3. Pocket Detection
4.4. Virtual Screening
4.5. Generation of 2D & 3D Structure
4.6. Analysis of Pharmacokinetics Properties
5. Results
5.1. Protein Sequence
5.2. Pocket Detection of Obtained Protein
5.3. Image of Selected Pockets
5.4. Information of Accepted Ligands
5.5. Virtual Screening
5.6. Pharmacokinetics Profiles
6. Discussion
7. Conclusion
8. Reference
There is a manifest concern globally pertaining the fact about the outgoing COVID-2019 is also known as novel (COVID-19) that is worldwide public health threat. As the prevalence of COVID-19 causes by the severe acute respiratory syndrome (COVID-19) go ahead rapidly not only China but also all over the world. So that as soon as possible available epidemiological data are needed to precursor strategies for situational awareness and intervention. According to the WHO the most well-known manifestations of COVID-19 are fever. Coughing, migraine, sleepiness, loss of smell, sore throat, sickness, diarrhea, any case a couple of individuals with the disease probably won't have any signs at all. In this situation, two methods are used to detect the COVID-19 disease. The tests are:
• genomic detection-based (molecular)
• immunoglobulin detection-based (serology)
According to current evidence, COVID-19 is primarily spread from person to person. We can likewise get tainted from respiratory beads when a contaminated individual hacks, sniffles, or talks. Moreover we may also be able to get it by touching a surface or object which has the virus on it, and then by touching our mouth, nose, or eyes. So we have to prevent the spread of COVID-19 and also have to accept
• Stay home
• Avoid public transportation
• Separate from other people and pets in our home
• Maintain convivial space
• Wash hands frequently for 20 seconds alongside cleanser and water
• Cover mouth and nose with tissue or mask and wear hand gloves.
I would like to thank my supervisor, Dr. G. M. Sayedur Rahman (Associate Professor & Chairman, Department of Pharmaceutical Sciences), for his guidance, patience and useful advices during this work. Without his step by step guidance, help, encouragements and motivations, I would have never completed my thesis.
I would also like to thank my family members who gave me full support during my thesis work, the support without which it would be very difficult for me to complete this work.
COVID-19 illness 2019 (COVID-19) which is an irresistible sickness. It is brought about by extreme intense respiratory disorder COVID-19 and that additionally called (SARS-CoV-2).It was first distinguished in December 2019 in Wuhan, China. Now-a-days, it has spread all over the world and resulting in an ongoing pandemic. The first people with COVID-19 that had connects to not only an animal but also seafood market. This suggests that animals primarily dispatched the virus to humans. Then, people with no links to the market but raised the disease and ascertaining that, the humans who can pass the virus to each other. [2] Some general symptoms comprise such as, fever, cough, fatigue, shortness of breath, and also loss of smell and taste. Acute respiratory distress syndrome (ARDS), multi-organ failure, septic shock, and blood clots are mild symptoms. The onset of symptoms is usually around five days nevertheless may range from two to fourteen days. COVID-19 is an infected person who breathes, sneezes, coughs, or speaks while the fluid that comes out of the mouth comes out through a droplet. If you touch that place, the virus can be transmitted from a hand to a healthy person through nose, eyes and mouth. [3] The standard method of diagnosis is by real-time reverse transcription polymerase chain reaction also called (RT-PCR) from a nasopharyngeal swab. Besides, Chest CT imaging may also be beneficial for diagnosis in individuals where there is a high mistrust of infection based on symptoms and risk factors; however, guidelines do not advise applying it for routine screening.[4] To prevent infection include, repeated hand washing and not applying hands to nose-face-eyes is the best prevention. Soapy water is most effective in hand washing. If there is no soapy water, hands should be cleaned with antiseptic hand wash or alcohol sanitizer. Maintaining physical distance is very important. At any rate three feet from one another. Furthermore, the utilization of a face covering is suggested for the individuals who questionable they have the infection and their caregivers.[5]
Suggestion Background (COVID-19) which are a colossal gathering of diseases. This contamination that cause infirmity going from the normal infection to more genuine diseases for example Middle East Respiratory Syndrome that generally called (MERS-COVID-19) and Severe Acute Respiratory Syndrome, in like manner called (SARS-COVID-19). An epic COVID-19 is another strain and it has not been before recognized in individual.[6]
[The image is not included for copyright reasons.]
- (COVID-19)
Following crown in people The brooding time of COVID-19, which is the time between presentation to the infection and indication beginning, is on normal 5-6 days, yet can be up to 14 days. Thus, isolate should be set up for 14 days from the last presentation to an affirmed case. [7]
Day 1-3 (Onset of side effects)
• Sars-CoV-2 infection may begin with upper respiratory manifestations after the brooding period.
• Fever for the most part seems first day.
• Upper respiratory side effects, for example, hack and sore throat may show up by day 3.
Day 4-9 (In the lungs)
• The infection may arrive at the lungs anyplace between 3 to 4 days
• Labored breathing may begin by fourth to ninth day.
• Inflammation in the lungs may prompt intense respiratory trouble. This can be occur between day 8 - 15.
Day 8-14 (In the blood)
• From the lungs, the contamination may move to the blood.
• Sepsis, a perilous intricacy, may create before the finish of the main week.[8]
Cardiovascular disease
Cardiovascular disease which is known as increase the risk of death. If cardiovascular patient contract COVID-19 that increased stress the patient’s and damaged cardiovascular system and that not able to cope with, when the lungs are no longer able to provide enough oxygen to the body.[9]
Diabetes
Diabetes Patient’s have an increased risk of getting very sick from the new COVID-19. There are two types of diabetes which known as type 1 and type 2 and both cause an increase in blood sugar. Poorly controlled blood sugar can make viral diseases, including COVID-19 which is more dangerous.
Kidney disease
Patients with kidney disease are commonly immune suppressed which meaning that they are not sufficient able to fight infections. So People with kidney disease may be at higher risk of getting very sick from COVID-19.
Asthma
Individuals with asthma might be at higher danger of becoming ill from COVID-19.COVID-19 can attack respiratory tract (nose, throat, lungs) and that cause an asthma attack . It possibly lead to pneumonia and acute respiratory disease.
Lung Disease
Chronic airway and lung diseases also known as asthma, pulmonary fibrosis and intestinal lung disease can set the stage for a more severe infection with the new COVID-19 because of scarring, inflammation or lung damage.[10]
As of now, polymerase chain response (PCR) and immunizer testing or serologic testing are applied for COVID-19 testing reason.
What is PCR testing?
"At the present time a large portion of the current Covid-19 tests that all the reports are coming from are using PCR," says University of Sussex senior educator in microbiology Dr Edward Wright. "They perceive the hereditary data of the infection, the RNA. That is simply possible if the disease is there and someone is viably defiled." A model is looked over pieces of the body where the COVID-19 aggregates, for example a person's nose or throat. The model is acted with a couple of manufactured plans which pull out substances, for instance, proteins and fats, and focuses only the RNA present in the model. This removed RNA is a mix of a person's own innate material and, if present, the COVID-19 RNA.[11] [12]
What is serologic difficult? Wright says: "A neutralizer test notification to us what level of everyone has been spoiled. It won't unveil to you who is polluted, in light of the fact that the antibodies are made after as long as 14 days, so, all things considered the contamination should have been cleared from the structure. In any case, it unveils to you who's been corrupted and who should be protected to the contamination." [13] [14]
The neutralizer test is generally called a "serological test". The test is finished by taking a drop of blood and a short time later examination the presence of antibodies made express to the disease defilement. It might be done with an unassuming lab setting and results are typically gotten in around 15 minutes. This procedure doesn't check for contamination itself, rather it checks body's response to the disease. Thusly, to be effective, the patient likely got some safety, which can require 7-15 days depending upon body's invulnerable response. From time to time, it may not recognize at all when pollution was not too genuine. This test can moreover check if an individual has had past sickness anyway recovered. [15] [16]
1. Wash hands much of the time for at any rate 20 seconds all at once with warm water and cleanser.
2. Try not to contact face, eyes, nose, or mouth when hands are messy.
3. Try not to go out in the event that somebody feeling wiped out or have any cold or influenza manifestations.
4. Remain in any event 6 feet from individuals.
5. Cover mouth with a mask or tissues.
6. Avoid public transportation, ride-sharing, or taxis.
7. Use hand sanitizer if water and soap is not available.[17]
UniprotKB (http://www.uniprot.org/uniprot/) is a key internet site that used for protein information. Its mission is to give the scientific community with a comprehensive, not only high-quality and freely approachable resource of protein sequence but also functional information.Over 95% of the protein arrangements gave by UniprotKB which are gotten from the interpretation of the coding groupings that have been acquainted with the public nucleic corrosive information bases, as EMBL-Bank, Gen Bank, and so forth Every one of these successions, just as the connected information presented by the creators which are consequently coordinated into UniprotKB. UniprotKB is additionally isolated into segments, for example, Swiss-port and TrEMBL. Swissport isn't just top notch physically clarified yet in addition non-excess protein succession information base, which unites test results, registered highlights and logical ends While TrEMBL is enriched with automatically annotated and classified computationally analyzed records. These are un reviewed entries which are divided from Swiss Port in order to make Swiss-Port more reliable and reviewed data base.[18]
SWISS-model (https://swissmodel.expasy.org/) is a server which makes automated 3D protein structures automatically. It is the most widely used automated modeling facility now-a-days. It spearheaded the field of robotized demonstrating beginning in 1993 and in 2002 the worker registered 120,000 client demands for 3D protein models. SWISS-MODEL gives a few degrees of client communication through its World Wide Web interface: in the primary, approach mode just an amino corrosive grouping of a protein is submitted to fabricate a 3D model. Format determination, arrangement and model structure are done totally robotized by the worker. In the arrangement mode, the displaying cycle depends on a client characterized target-layout arrangement. Complex demonstrating errand can be taken care of with the undertaking mode utilizing Deep View (Swiss-PdbViewer), a coordinated succession to-structure workbench. All models are sent back by means of email with an itemized demonstrating report. What Check investigations and ANOLEA assessments are given alternatively? The dependability of SWISS-MODEL is consistently assessed in the EVA-CM project. The SWISS-MODEL worker is under consistent advancement to improve the fruitful execution of master information into a simple to-utilize worker. Displaying of protein structures generally requires broad aptitude in primary science and the utilization of exceptionally specific PC programs for every one of the individual strides of the demonstrating cycle. Among all current hypothetical methodologies, similar demonstrating is the solitary strategy that can dependably produce a 3D model of a protein (focus) from its amino corrosive arrangement.[19]
Structure based Drug Design (SBDD) is a computational way to deal with lead disclosure that utilizes the three-dimensional structure of a protein to fit medication like atom into a ligand restricting site to adjust work. Distinguishing the area of the coupling site is thusly an essential advance in this cycle, confining the inquiry apace for SBDD or virtual screening examines. The location and portrayal of utilitarian locales on proteins has progressively become a zone of interest. Primary genomics projects are progressively yielding protein structures with obscure capacities and restricting locales. Restricting site expectation was spearheaded by pocket identification since the coupling site regularly found in the biggest pocket. Later techniques include phylogenetic investigation to distinguish primary likeness with proteins of known capacity. Restricting site forecast has been utilized in a few SBDD projects. WE examine various techniques for ligand restricting site expectation.[20]
E-LEA3D web server (http://chemoinfo.ipmc.cnrs.fr/lea.html) integrates three complementary tools to perform computer-aided drug design based on molecular fragments. In medication disclosure projects, there is a significant interest in distinguishing novel and assorted atomic platforms to improve odds of achievement. The anew drug configuration device is utilized to concoct new ligands to streamline a client indicated scoring capacity. The composite scoring function includes both structure and ligand based evaluations. The once more methodology is an option in contrast to a visually impaired virtual screening of huge compound assortments. A heuristic dependent on a hereditary calculation quickly discovers which sections or blend of parts fit a QSAR model or the coupling site of a protein. While the methodology is obviously appropriate for framework jumping, this module likewise permits a sweep for conceivable substituent to a client indicated platform. The subsequent apparatus offers a customary virtual screening and separating of a transferred library of mixes. The third module tends to the combinatorial library plan that depends on a client drawn framework and reactants coming, for instance, from a compound provider.[21]
Medication revelation and synthetic science are extremely intricate and requesting endeavors. As of late there are been expanding mindfulness about the significance of foreseeing/streamlining the ingestion, dissemination, digestion, discharge and harmfulness (ADMET) properties of little synthetic mixes along the inquiry cycle as opposed to at the last stages. Quick strategies for assessing ADMET properties of little particles frequently include applying a bunch of basic experimental standards (taught surmises) and in that capacity, compound assortments' property profiling can be acted in silico. Obviously, these guidelines can't survey the full unpredictability of the human body however can give important data and help dynamic. FAF-drugs4 is an online assistance dependent on Frowns (a chemoinformatics toolbox) that permits clients to deal with their own compound assortments (SMILES, CANSMILES and SDF records input) by means of straightforward ADME/Tox separating rules, for example, atomic weight, polar surface region, logP or number of rotatable bonds. The FAF-Drugs4 web worker just acknowledges SDF documents (we limit the quantity of mixes to 50000) where every atom has an extraordinary recognizable proof number (ID). In addition, we have implemented the service Bank-Formatter on Mobyle to facilitate the preparation of the input file. (using Openbabel libraries) The Bank-Formatter service is to convert SMILES input file to a suitable SDF file for FAF-Drugs4. Similarly if the input SDF file does not have the right format with an ID field, then the service can help in preparing the appropriate input SDF file. Once the FAF-Drugs3 process is finished, the user is redirected to the result pages. Everything information can be downloaded and two key online interfaces are advertised.[22]
The objective of this research is to find out drug molecules against COVID-19 through virtual screening. Furthermore, to determine pharmacokinetics profile of those screened drug molecules.
Since, the cost associated with the discovery of a drug from its initial trials till clinical trial is very high and the time being consumed in drug analysis in-vivo or in-vitro is much lengthy, even though many drugs failed to get approved by FDA. The use of computer-aided techniques not only cut-short the time associated with the drug discovery but it also makes the initial trial easier and more accurate.
The first step is to search the database of UniprotKB (http://www.uniprot.org/uniprot/) . UniprotKB has two sections of sequence data, which UniprotKB Consortium termed as ―Reviewed and ―Un reviewed”. The part containing physically commented on records with data separated from writing and custodian assessed computational examination is designated "Looked into Section", and a segment with computationally dissected records that anticipate full manual explanation is the "Unreviewed" one. For progression and name acknowledgment, the two areas are alluded to as "UniProtKB/Swiss-Prot" (inspected, physically clarified) and "UniProtKB/TrEMBL" (unreviewed, consequently commented on), individually.
Next step is to validate the structures generated by SWISS-MODEL. This study uses one fold Validations of generated structures
1) Validation provided by SWISS-Model (https://swissmodel.expasy.org/)
A PDB format file of required model is used by this validation methods mentioned above. There are several software both online and offline which can find the cavity in any given protein. Auto ligand, CASTp, Pocket Analyzer, are a portion of the product utilized for depression distinguishing proof.
Once the full structures of these proteins are generated, they can be used for pocket identification by using CASTp. In simpler terms, a protein pocket or cavity is a hollow space in the protein where a ligand or possible drug can attach/bind itself. First of all, we uploaded the selected protein in CASTp , then we analyze the score in UCSF Chimera. The Pockets with the score of 1 opening mouth are taken to determine their dimension by using chimera.
To find out drug molecules based on pocket dimension, we need to know the coordinates for each pocket ID. We upload the protein in E-LEA3D website and put the coordinates for each pocket ID to generate ligands that would be best to bind in the pockets.
After the completion of virtual screening, we need to generate the 2d and 3D structures of these molecules by using different software and sites as UCSF Chimera.
First of all, we take sdf file for each of the drug from e-LEA3D. Then we upload these file in FAF-drugs4 software to determine the pharmacokinetics parameter.
In this section, all the results obtained from each step mentioned in the previous section is shown in the respective manner as presented in methodology.
Protein-1 (Host translation inhibitor nsp1)
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Figure: nsp1
Protein-2 (Non-structural protein2 or nsp2)
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Figure: nsp2
Protein-3 (Non-structural protein6 or nsp6)
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Figure: nsp6
Protein-4 (Non-structural protein7 or nsp7)
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Figure: nsp7
Protein-4 (Non-structural protein8 or nsp8)
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Figure: nsp8
Protein-1 (Host translation inhibitor nsp1)
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Protein-2(Non-structural protein-2 or nsp2)
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Protein-3(Non-structural protein-3 or nsp3)
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Protein-4(Non-structural protein-4 or nsp4 )
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Protein-5(Non-structural protein-5 or nsp5)
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Protein-1 (Host translation inhibitor nsp1)
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Pocket ID 2
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Pocket ID 6
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Pocket ID 7
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Pocket ID 9
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Pocket ID 10
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Pocket ID 11
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Pocket ID 12
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Pocket ID 13
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Pocket ID 14
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Pocket ID 15
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Pocket ID 18
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Pocket ID 19
Protein-2 (Non-structural protein2 or nsp2)
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Pocket ID 1
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Pocket ID 2
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Pocket ID 4
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Pocket ID 5
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Pocket ID 7
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Pocket ID 8
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Pocket ID 9
Pocket ID 10
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Pocket ID 11
Pocket ID 13
Protein-3 (Non-structural protein6 or nsp6)
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Pocket ID 2
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Pocket ID 5
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Pocket ID 6
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Pocket ID 7
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Pocket ID 10
Pocket ID 11
Protein-4 (Non-structural protein7 or nsp7)
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Pocket ID 1
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Pocket ID 2
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Pocket ID 3
Protein-5 (Non-structural protein8 or nsp8)
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Pocket ID 1
Protein-1 (Host translation inhibitor nsp1)
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Protein-2 (Non-structural protein2 or nsp2)
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Protein-3 (Non-structural protein6 or nsp6)
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Protein-4 (Non-structural protein7 or nsp7)
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Protein-5 (Non-structural protein8 or nsp8)
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Selected pockets of containing one opening and the remainder of the pockets generated some Acceptable ligand molecules together with some intermediates and rejected.
Pocket ID_2: Accepted Ligands
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Pocket Id:02 Generation:0/1
Pocket ID_9: Accepted Ligands
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Pocket Id:09 Generation: 0
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Pocket Id:09 Generation: 01/02/03/04
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Pocket Id:09 Generation: 05
Pocket ID_13: Accepted Ligands
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Pocket Id:13 Generation: 04
Pocket ID_2: Accepted Ligands
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Pocket Id:2 Generation: 0/01
Pocket ID_13: Accepted Ligands
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Pocket Id:13 Generation: 0/01/02
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Pocket Id:13 Generation: 03
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Pocket Id:13 Generation:04
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Pocket Id:13 Generation:05/06
Pocket ID_2: Accepted Ligands
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Pocket Id:02 Generation: 05/06/07
Pocket ID_5: Accepted Ligands
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Pocket Id:05 Generation:0
Pocket ID_10: Accepted Ligands
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Pocket Id:10 Generation:0/01
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Pocket Id:10 Generation:02
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Pocket Id:10 Generation:03/04
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Pocket Id:10 Generation:05
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Pocket Id:10 Generation:06
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Pocket Id:10 Generation:0
Pocket ID_11: Accepted Ligands
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Pocket Id:11 Generation:06
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Pocket Id:11 Generation:09
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Pocket Id:11 Generation:10
Pocket ID_2: Accepted Ligands
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Pocket Id:02 Generation: 0/01
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Pocket Id:02 Generation: 02
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Pocket Id:02 Generation:03
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Pocket Id:02 Generation:04/05/07
Pocket ID_3: Accepted Ligands
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Pocket Id:03 Generation:01/02/03/04
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Pocket Id:03 Generation:06
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Pocket Id:03 Generation:09
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Pocket Id:03 Generation:10
Pocket ID_1: Accepted Ligands
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Pocket Id:01 Generation:0
Complete table of Pharmacokinetic Profiles of the individual Ligands generated for the selected pockets are recorded and provided after the end of Reference page for further investigation if required.
The table provides the number of ligands that are Accepted, Intermediate or Rejected for the selected pockets:
Protein-1(Host translation inhibitor or nsp1)
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Protein-2 (Non-structural protein-2 or nsp2)
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Protien-3 (Non-structural protein-3 or nsp3)
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Protein-4 (Non-structural protein-4 or nsp4)
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Protein-5 (Non-structural protein-5 or nsp5)
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Using SWISS MODEL and CASTp we obtained the pocket information for our target protein. Only the pockets with 1 opening were selected. A total of 32 pockets were obtained to further our study.
With the help of e-LEA3D de-novo drug designing, we generated 11 ligands for each of the 32 individual pockets by uploading out target protein file and the x,y,z coordinates of the individual pockets. In total we generated 352 ligands.
For the final screening, we used our generated ligands for pharmacokinetics profiling using FAF_DRUGS4 software. This created the pharmacokinetics profile for all the generated 352 ligands for the 32 pockets. Even though 352 ligands were generated, after the final screening process and pharmacokinetics profiling, a total of 61 ligands were ACCEPTED, 226 ligands were REJECTED and the remaining 65 ligands were INTERMEDIATE and required further structural modifications to become of use.
These result generated by using FAF-drugs4. Oral bioavailability of all the drugs are good. The values of logP, logD, logSw, tPSA, rotatable bonds, flexibility, HBD, HBA, total charge, heavy atoms, carbon atoms are supposed to be within the range. Some of the drugs are out of molecular weight and solubility acceptable profile range according to Lipinski rule. Though all the drugs are violated one or two of Lipinski rule, still they all are acceptable because all molecules are approved by FDA and marketed.
The point of this examination was to build up some FDA affirmed drugs against COVID-19.There are techniques available to find and validate the a target protein using SWISS MODEL and CASTp and undergo virtual screening process using e-LEA3D to generate ligands complimentary to target protein pockets. The later stage is to find the pockets inside the protein. To find out the best pocket cavity in which drugs molecule bind with high affinity. Through virtual screening we generated 352 drug molecules. The pharmacokinetic profiles for these molecules were generated with FAF_DRUGS4. After taking in to the account of the pharmacokinetic profiles of all the generated drug molecules we have come to the conclusion that 226 of the generated molecules do not meet the pharmacokinetic criteria and thus are rejected. However, there are 61 drug molecules that fit all the pharmacokinetic criteria and are accepted to be of further use. The remainder of the 65 drug molecules can still be of use if undergone some further modifications.
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