In-silico Structural and Molecular Docking-Based Drug Discovery Against Viral Protein (VP40) of Marburg Virus: A Causative Agent of MAVD

AbstractThe Marburg virus (MARV) is reported to induce extreme hemorrhagic fever (MHF) with a high degree of infectivity and lethality in both human and non-human primates. An appropriate vaccination for this virus’s treatment is not yet usable, and thus needs intensive attempts on multiple scales. In this study, we employed the Computer-Aided Drug Design (CADD) based approach to identify the drug-like compounds inhibiting the replication of the Viral protein (VP40) of MARV. Our database search using an online database “PubChem” retrieved ∼3000 compounds structure-based similarity. Lipinski’s rule was applied to evaluate further the drug-like compounds, followed by molecular docking-based screening, and the selection of screening ligand complex with VP40 based on S-score (lower than reference Favipiravir inhibitor) and root-mean-square-deviation (RMSD) value (probably less than 2) using AutoDock 4.2. Resultantly, ∼100 compounds were identified having strong interaction with VP40 of MARV. After evaluating their binding energy using the AutoDock 4.2 software, four compounds (CID-67534452, CID-72201087, CID-123273976, CID-153708661) were identified that showed strongest binding energy with VP40 of MARV and strong inhibition effect than the Favipiravir. Robust binding energy, useful ADMET parameters and drug-likeness suggest that these candidates “CID-67534452, CID-72201087, CID-123273976, CID-153708661” have tremendous potential to stop the replication of MARV, hence might lead to the cure of MAVD.

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In-silico Structural and Molecular Docking-Based Drug Discovery Against Viral Protein (VP35) of Marburg Virus: A potent Agent of MAVD

10.1101/2021.02.09.430405 ◽

2021 ◽

Author(s):

Sameer Quazi ◽

Javed Malik ◽

Arnaud Martino Capuzzo ◽

Kamal Singh Suman ◽

Zeshan Haider

Keyword(s):

Molecular Docking ◽

Binding Energy ◽

Viral Protein ◽

In Silico ◽

Core Protein ◽

Hemorrhagic Fever ◽

Inhibitory Effect ◽

Marburg Virus ◽

Pubchem Database ◽

Strong Inhibitory Effect

ABSTRACTThe Marburg virus (MARV) is a highly etiological agent of hemorrhagic fever in humans. MARV has spread across the world, including America, Australia, Europe, and different Asia countries. However, there is no approved vaccine to combat MARV, combined with a high mortality rate, which makes antiviral drugs against MARV urgent. The viral protein (VP35) is a core protein of MARV that involves multiple functions of the infection cycle. This research used an in-silico drug design technique to discover the new drug-like small molecules that inhibit VP35 replication. First, several combinations of ∼ 4260 showed that structure-based similarity above 90% was retrieved from an online “PubChem” database. Molecular docking was performed using AutoDock 4.2, and ligands were selected based on docking / S score lower than reference CID_5477931 and RMSD value between 1-2. Finally, about 50 compounds showed greater bonding producing hydrogen, Van der Waals, and polar interactions with VP35. After evaluating their binding energy strength and ADMET analysis, only CID_ 3007938 and CID_11427396 were finalized, which showed the most vital binding energy and a strong inhibitory effect with MARV’s VP35. The higher binding energy, suitable ADMET, and drug similarity parameters suggest that these “CID_ 3007938 and CID_11427396” candidates have incredible latency to inhibit MARV replication; hence, these strengths led to the treatment of MAVD.

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In-silico pharmacophore and Molecular Docking based drug discovery against Marburg Virus Viral Protein VP35; A potent of MAVD.

10.1101/2021.07.01.450693 ◽

2021 ◽

Author(s):

Sameer Quazi ◽

Shreelaxmi Gavas ◽

Javed Ahmad Malik ◽

Komal Singh Suman ◽

Zeshan Haider

Keyword(s):

Molecular Docking ◽

Viral Protein ◽

Virus Disease ◽

Antiviral Drug ◽

Computational Approach ◽

Marburg Virus ◽

Online Tool ◽

Lipinski’S Rule ◽

Zinc Database ◽

Lipinski’S Rule Of Five

Marburg virus is a member of filoviridae and spreads severe Marburg hemorrhagic illness in humans and animals. Nowadays, there is no vaccine available that can completely stop the replication of Marburg replication. Therefore, this study is designed to repurpose the effective therapeutic antiviral drug by using a computational approach against exploring the mechanism of Marburg virus Viral protein 35. We have retrieved about 40570 drug-like small compounds from the ZINC database using the "ZINC Pharmer" online tool. Molecular docking of the ligands from the ready-to-dock database has been carried out using MOE. The five drugs have been identified to bind with VP35 possibly. A study was also performed to evaluate the drug-like characteristics of the substances for absorption, distribution, metabolism, and excretion (ADME). The findings clearly showed that ligands are interacting with the MARV VP35 protein. Interestingly, Lipinski's rule of five was observed by all ligands. These findings provide the foundation for reconstituting and utilizing molecules as a possible therapy for Marburg Virus Disease (MVD).

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Discovery of potential drug-like compounds against Viral protein (VP40) of Marburg Virus using pharmacophoric based virtual screening from ZINC database.

10.1101/2021.05.13.444037 ◽

2021 ◽

Author(s):

Sameer Quazi ◽

Javid Ahmad Malik ◽

Komal Singh Suman ◽

Arnaud Martino Capuzzo ◽

Zeshan Haider

Keyword(s):

Binding Energy ◽

Hemorrhagic Fever ◽

Inhibitory Effect ◽

Marburg Virus ◽

Working Environment ◽

Computer Aided Drug Design ◽

Lipinski’S Rule ◽

Zinc Database ◽

Novel Drug ◽

Selection Of

Marburg virus (MARV) has been confirmed to cause extreme hemorrhagic fever (HFM) in human and animals. The effective and suitable vaccine to treat the MARV virus is not commercialized in public and demands rigorously tested on several scales. This research used a CADD (Computer-Aided Drug Design) computational based technology to find novel drug-like compounds that could inhibit the replicating of the VP40. The pharmacophoric features bases screening was done using an online computational based software, "ZINC Pharmer". We retrieved about 32456 compounds mainly focused on the properties of pharmacophores from the ZINC database. Lipinski's rule was also used to predict these drug-like compounds. as well as molecular coupling-dependent screening and selection of VP40 screening ligand complexes based on S-rank (lower than reference) and value of root, mean square (RMSD) (bottom) to examine for reference) using the Molecular Working Environment (MOE) machine. As a result, 100 compounds were found to have a close interaction with MARV VP40, followed by the Binding energy (BE) analysis of these 100 compounds. Only 50 were the strongest binding energy than favipiravir [reference inhibitor] after using the MOE-LigX algorithm to compare their binding energy. After that, ADMET analysis predicted only five compounds (ZINC95457352, ZINC38752258, ZINC38752253, ZINC39272175, and ZINC38752377) passed the ADMET parameters and have the strongest inhibitory effect against the MARV's VP40. It has been suggested that these "drug-like" candidates have an increased ability to inhibit MARV replication, leading to treatment of MARVD.

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In Silico Discovery of Novel Inhibitors Against Main Protease (Mpro) of SARS-CoV-2 Using Pharmacophore and Molecular Docking Based Virtual Screening from ZINC Database

10.20944/preprints202002.0431.v1 ◽

2020 ◽

Cited By ~ 3

Author(s):

Zeshan Haider ◽

Muhammad Muneeb Subhani ◽

Muhammad Ansar Farooq ◽

Maryum Ishaq ◽

Maryam Khalid ◽

...

Keyword(s):

Molecular Docking ◽

Binding Energy ◽

Effective Vaccine ◽

Ligand Complex ◽

Online Tool ◽

Public Health Emergencies ◽

Main Protease ◽

Zinc Database ◽

Recent Outbreak ◽

Selection Of

Recent outbreak of Coronavirus Disease 2019 (COVID-19) caused by a novel ‘SARS-CoV-2’ virus resulted public health emergencies across the world. An effective vaccine to cure this virus is not yet available, thus requires concerted efforts at various scales. In this study, we employed Computer Aided Drug Design (CADD) based approach to identify the drug-like compounds - inhibiting the replication of main protease (Mpro) of SARS-CoV-2. Our database search using online tool “ZINC pharmer” retrieved ~1500 compounds based on pharmacophore features. Lipinski’s rule was applied to further evaluate the drug-like compounds, followed by molecular docking-based screening, and the selection of screening ligand complex with Mpro based on S-score (higher than reference inhibitor) and root-mean-square deviation (RMSD) value (less than reference inhibitor) using Molecular Operating Environment (MOE) system. Resultantly, ~200 compounds were identified having strong interaction with Mpro of SARS-CoV-2. After evaluating their binding energy using the MOE LigX algorithm, three compounds (ZINC20291569, ZINC90403206, ZINC95480156) were identified that showed highest binding energy with Mpro of SARS-CoV-2 and strong inhibition effect than the reference inhibitor. It is suggested that these candidate “drug-like compounds” have greater potential to stop the replication of SARS-CoV-2, hence might lead to the cure of COVID-19.

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Molecular Docking Studies of Phytochemicals of Allophylus serratus Against Cyclooxygenase-2 Enzyme

10.1101/866152 ◽

2019 ◽

Author(s):

Kero Jemal

Keyword(s):

Molecular Docking ◽

Binding Energy ◽

Cyclooxygenase 2 ◽

Molecular Docking Study ◽

Leaf Extracts ◽

Sulfurous Acid ◽

Lipinski’S Rule ◽

Phytochemical Compounds ◽

Cox 2 ◽

Anti Inflammatory

AbstractAllophylus serratus is a medicinal plant used traditionally as anti-inflammatory agent. The main objectives of this study are to identify phytochemical compounds that have anti-inflammatory properties from the leaf extracts of Allophylus serratus and to search for cyclooxygenase-2 (COX-2) enzyme inhibitors through molecular docking. From the GC-MS analysis of leaf extracts of this plant, various phytochemicals were identified. About 10of these phytochemical compounds were analyzed for their drug likeliness based on Lipinski’s rule of five and inhibitor property against the cyclooxygenase (COX-2) enzyme, a protein responsible for inflammation The phytochemical compounds which satisfy the Lipinski’s rule such as 1H-Benzocycloheptene, 2,4a,5,6,7,8-hexahydro-3,5,5,9-tetramethyl-,(R) and Sulfurous acid, dipentyl ester were subjected to docking experiments using AutoDock Vina. The results from molecular docking study revealed that 1H-Benzocycloheptene, 2,4a,5,6,7,8-hexahydro-3,5,5,9-tetramethyl-, (R)-, Sulfurous acid, dipentyl ester and 1,2-Benzenedicarboxylic acid, bis(2-methylpropyl) ester bind effectively to the active site region of COX-2 with a binding energy of −8.9, −8.4, and −7.9, respectively. The binding energy of the phyto-compounds were compared with the known antiinflammatory drug Diclofenac that inhibit COX-2 enzyme. It was found that the phytochemical compounds from leaf extracts of Allophylus serratus have strong inhibitory effect on COX-2 enzyme and as a result they have potential anti-inflammatory medicinal values. Thus the study puts forth experimental validation for traditional antidote and these phyto-compounds could be further promoted as potential lead molecule.

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Computational analysis by molecular docking of thirty alkaloid compounds from medicinal plants as potent inhibitors of SARS-CoV-2 main protease

SDRP Journal of Computational Chemistry & Molecular Modelling ◽

10.25177/jccmm.4.4.ra.10699 ◽

2021 ◽

Vol 4 (4) ◽

pp. 487-503

Author(s):

Tunga Kuhana A ◽

◽

Jason T. Kilembe ◽

Aristote Matondo ◽

Khamis M. Yussuf ◽

...

Keyword(s):

Molecular Docking ◽

Binding Energy ◽

Medicinal Plants ◽

Computational Analysis ◽

Potential Drug ◽

Lipinski’S Rule ◽

Main Protease ◽

Lipinski’S Rule Of Five ◽

Potential Inhibitors ◽

Therapeutic Profile

Year 2020 has been highly affected by the COVID-19 outbreak. The urgent need for a potent and effective drug for the treatment of this malignancy put pressure on researchers and scientists worldwide to develop a potential drug or a vaccine to resist SARS-CoV-2 virus. We report in this paper the assessment of the efficiency of thirty alkaloid compounds derived from African medicinal plants against the SARS-CoV-2 main protease through molecular docking and bioinformatics approaches. The results revealed four potential inhibitors (ligands 18, 21, 23 and 24) with 12.26 kcal/mol being the highest binding energy. Additionally, in silico drug-likeness and ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) properties for the four ligands showed a good predicted therapeutic profile of druggability, and fully obey the Lipinski's rule of five as well.

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Molecular Docking Studies for Protein-Targeted Drug Development in SARS-CoV-2

Letters in Drug Design & Discovery ◽

10.2174/1570180818666210512021619 ◽

2021 ◽

Vol 18 ◽

Author(s):

Ahmad Dzulfikri Nurhan ◽

Maria Apriliani Gani ◽

Saipul Maulana ◽

Siswandono Siswandono ◽

Chrismawan Ardianto ◽

...

Keyword(s):

Molecular Docking ◽

Binding Energy ◽

Docking Studies ◽

Binding Energies ◽

Spike Glycoprotein ◽

Protein Targets ◽

Lipinski’S Rule ◽

Global Pandemic ◽

Potential Inhibitors ◽

3Cl Protease

Background: The SARS-CoV-2/COVID-19 infection has resulted in a global pandemic and emergency. Currently, there is no therapeutic agent that has been proven to be effective and selective to deal with this pandemic. Objective: In this study, we explored and screened 401 compounds-related viruses that may inhibit one or more of the three protein targets in SARS-CoV-2 (3CL protease, RdRp, and spike glycoprotein) using in-silico approach. Methods: Lipinski's rule of five was used as an initial screening for these compounds. Ligand preparation was carried out using JChem software and Schrödinger's LigPrep module, while protein elucidation used AutoDockTools-1.5.6. Molecular docking was analyzed using AutoDockVina. Results: A total of five compounds-related viruses were obtained from each SARS-CoV-2 protein with ideal and potential binding energy as a candidate for target protein inhibitor on SARS-CoV-2. At the protein 3CL protease imatinib, TAK-981, lopinavir, mefloquine, and sitagliptin were found to be potential inhibitors of this protein. In the protein RdRp tetrandrine, relacatib, AZD7986, imatinib, and TAK-981 revealed potential as an inhibitor of this protein. At the protein spike, glycoprotein AZD7986, selinexor, imatinib, lopinavir, and ciclesonide, were found to have potential as inhibitors of these proteins. All these compounds have better binding energy than the three comparator drugs (remdesivir, chloroquine, and hydroxychloroquine). Conclusion: We have obtained several compounds-related viruses with reliable binding energies to the SARS-CoV-2 proteins and potentially better than the three comparator drugs. Furthermore, this research will pave the way for accelerating the development of Covid-19 drugs.

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Molecular Docking and Dynamics Simulation Analysis of Thymoquinone and Thymol Compounds from Nigella sativa L. that Inhibits P38 Protein: Probable Remedies for Hepatocellular Carcinoma

Medicinal Chemistry ◽

10.2174/1573406415666190416165732 ◽

2020 ◽

Vol 16 (3) ◽

pp. 350-357

Author(s):

Heena Tabassum ◽

Iffat Z. Ahmad

Keyword(s):

Hepatocellular Carcinoma ◽

Molecular Docking ◽

Binding Energy ◽

Simulation Analysis ◽

Nigella Sativa ◽

Pharmacological Action ◽

Dynamics Simulation ◽

Ligand Interaction ◽

Lipinski’S Rule ◽

Discovery Studio

Background: Currently, a novel antagonist against p38 is being designed and applied to inhibit hepatocellular carcinoma. Protein–ligand interaction plays a major role in the identification of the possible mechanism for the pharmacological action. The involvement of p38 remains an important target for anticancer drug development as its activation induces apoptosis in hepatoma cells. Objective: The aim is to identify the best candidate from the plants of N. sativa which binds with the hepatocellular carcinoma (HCC) targets by computational approach. Materials and Methods: The reported phytoconstituents such as thymoquinone and thymol present in the plant, N. sativa were docked with the HCC target such as p38. Structures of phytoconstituents were prepared using ChemDraw Ultra 10 software and converted into its 3D PDB structure and minimized using Discovery Studio client 2.5. The target protein, p38 was retrieved from RCSB PDB. Lipinski’s rule and ADMET toxicity profiling were carried out on the phytoconstituents of the N. sativa, and the compounds were further promoted for molecular docking and MD simulation analysis. Results: The docking results revealed promising inhibitory potential of thymoquinone against p38 with binding energy of -7.67 kcal/mole as compared to its known standard doxorubicin having binding energy of -6.68 kcal/mol respectively. Further, molecular dynamic (MD) simulations for 5ns were conducted for optimization, flexibility prediction, and determination of folded p38 stability. The p38-thymoquinone complex was found to be quite stable with RMSD value of 0.2 nm. Conclusion: Obtained results propose thymoquinone binding energy on the selected targets. Hence, this compound bears outstanding potential against hepatocellular carcinoma and has to be taken up for experimental work against hepatocellular carcinoma.

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Vaccinomics strategy for developing a unique multi-epitope monovalent vaccine against Marburg marburgvirus

10.1101/484923 ◽

2018 ◽

Author(s):

Mahmudul Hasan ◽

Kazi Faizul Azim ◽

Aklima Begum ◽

Noushin Anika Khan ◽

Tasfia Saiyara Shammi ◽

...

Keyword(s):

Matrix Protein ◽

Hemorrhagic Fever ◽

Coli Strain ◽

Marburg Virus ◽

Docking Analysis ◽

E Coli ◽

Monovalent Vaccine ◽

High Degree

Marburg virus causes severe hemorrhagic fever in both humans and non-human primates with high degree of infectivity and lethality. To date no approved treatment is available for Marburg virus infection. A study was employed to design a novel chimeric vaccine against Marburg virus by adopting reverse vaccinology approach. Envelope glycoprotein and matrix protein VP40 were identified as most antigenic viral proteins which generated a plethora of antigenic epitopes. Results showed that vaccine construct V1 was superior in terms of various physicochemical properties and structural stability. Molecular docking analysis of the refined vaccine with different MHCs and human immune TLR8 receptor demonstrated higher binding affinity. Moreover, complexed structure of the modeled vaccine and TLR8 indicated minimal deformability at molecular level. Translational potency and microbial expression of the modeled vaccine within E. coli strain K12 by pET28a(+) vector were also biologically significant. However, further in vitro and in vivo investigation could be implemented for the acceptance and validation of the designed vaccine against Marburg virus.

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