Literature DB >> 31536833

Pharmacoinformatics-based identification of potential bioactive compounds against Ebola virus protein VP24.

Samuel K Kwofie1, Emmanuel Broni2, Joshua Teye2, Erasmus Quansah3, Ibrahim Issah2, Michael D Wilson4, Whelton A Miller5, Elvis K Tiburu6, Joseph H K Bonney7.   

Abstract

BACKGROUND: The impact of Ebola virus disease (EVD) is devastating with concomitant high fatalities. Currently, various drugs and vaccines are at different stages of development, corroborating the need to identify new therapeutic molecules. The VP24 protein of the Ebola virus (EBOV) plays a key role in the pathology and replication of the EVD. The VP24 protein interferes with the host immune response to viral infections and promotes nucleocapsid formation, thus making it a viable drug target. This study sought to identify putative lead compounds from the African flora with potential to inhibit the activity of the EBOV VP24 protein using pharmacoinformatics and molecular docking.
METHODS: An integrated library of 7675 natural products originating from Africa obtained from the AfroDB and NANPDB databases, as well as known inhibitors were screened against VP24 (PDB ID: 4M0Q) utilising AutoDock Vina after energy minimization using GROMACS. The top 19 compounds were physicochemically and pharmacologically profiled using ADMET Predictor™, SwissADME and DataWarrior. The mechanisms of binding between the molecules and EBOV VP24 were characterised using LigPlot+. The performance of the molecular docking was evaluated by generating a receiver operating characteristic (ROC) by screening known inhibitors and decoys against EBOV VP24. The prediction of activity spectra for substances (PASS) and machine learning-based Open Bayesian models were used to predict the anti-viral and anti-Ebola activity of the molecules, respectively.
RESULTS: Four natural products, namely, ZINC000095486070, ZINC000003594643, ZINC000095486008 and sarcophine were found to be potential EBOV VP24-inhibitiory molecules. The molecular docking results showed that ZINC000095486070 had high binding affinity of -9.7 kcal/mol with EBOV VP24, which was greater than those of the known VP24-inhibitors used as standards in the study including Ouabain, Nilotinib, Clomiphene, Torimefene, Miglustat and BCX4430. The area under the curve of the generated ROC for evaluating the performance of the molecular docking was 0.77, which was considered acceptable. The predicted promising molecules were also validated using induced-fit docking with the receptor using Schrödinger and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The molecules had better binding mechanisms and were pharmacologically profiled to have plausible efficacies, negligible toxicity as well as suitable for designing anti-Ebola scaffolds. ZINC000095486008 and sarcophine (NANPDB135) were predicted to possess anti-viral activity, while ZINC000095486070 and ZINC000003594643 to be anti-Ebola compounds.
CONCLUSION: The identified compounds are potential inhibitors worthy of further development as EBOV biotherapeutic agents. The scaffolds of the compounds could also serve as building blocks for designing novel Ebola inhibitors.
Copyright © 2019. Published by Elsevier Ltd.

Entities:  

Keywords:  African natural products; Ebola virus inhibitors; Ebola virus protein VP24; Molecular docking; Molecular dynamics; Virtual screening

Year:  2019        PMID: 31536833     DOI: 10.1016/j.compbiomed.2019.103414

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  12 in total

1.  Multi-target potential of Indian phytochemicals against SARS-CoV-2: A docking, molecular dynamics and MM-GBSA approach extended to Omicron B.1.1.529.

Authors:  Jency Roshni; R Vaishali; K S Ganesh; N Dharani; Khalid J Alzahrani; Hamsa Jameel Banjer; Ali H Alghamdi; Abdulrahman Theyab; Shiek Ssj Ahmed; Shankargouda Patil
Journal:  J Infect Public Health       Date:  2022-05-13       Impact factor: 7.537

2.  Computational Identification of Potential Anti-Inflammatory Natural Compounds Targeting the p38 Mitogen-Activated Protein Kinase (MAPK): Implications for COVID-19-Induced Cytokine Storm.

Authors:  Seth O Asiedu; Samuel K Kwofie; Emmanuel Broni; Michael D Wilson
Journal:  Biomolecules       Date:  2021-04-29

3.  Network pharmacology of iridoid glycosides from Eucommia ulmoides Oliver against osteoporosis.

Authors:  Ting Wang; Liming Fan; Shuai Feng; Xinli Ding; Xinxin An; Jiahuan Chen; Minjuan Wang; Xifeng Zhai; Yang Li
Journal:  Sci Rep       Date:  2022-05-06       Impact factor: 4.996

4.  Discovery of the Novel Inhibitor Against New Delhi Metallo-β-Lactamase Based on Virtual Screening and Molecular Modelling.

Authors:  Xiyan Wang; Yanan Yang; Yawen Gao; Xiaodi Niu
Journal:  Int J Mol Sci       Date:  2020-05-18       Impact factor: 5.923

5.  Cheminformatics-Based Identification of Potential Novel Anti-SARS-CoV-2 Natural Compounds of African Origin.

Authors:  Samuel K Kwofie; Emmanuel Broni; Seth O Asiedu; Gabriel B Kwarko; Bismark Dankwa; Kweku S Enninful; Elvis K Tiburu; Michael D Wilson
Journal:  Molecules       Date:  2021-01-14       Impact factor: 4.411

6.  Molecular modelling and de novo fragment-based design of potential inhibitors of beta-tubulin gene of Necator americanus from natural products.

Authors:  Odame Agyapong; Seth O Asiedu; Samuel K Kwofie; Whelton A Miller; Christian S Parry; Robert A Sowah; Michael D Wilson
Journal:  Inform Med Unlocked       Date:  2021-09-15

Review 7.  Antiviral Activity Exerted by Natural Products against Human Viruses.

Authors:  Maria Musarra-Pizzo; Rosamaria Pennisi; Ichrak Ben-Amor; Giuseppina Mandalari; Maria Teresa Sciortino
Journal:  Viruses       Date:  2021-05-04       Impact factor: 5.048

8.  A Molecular Modeling Approach to Identify Potential Antileishmanial Compounds Against the Cell Division Cycle (cdc)-2-Related Kinase 12 (CRK12) Receptor of Leishmania donovani.

Authors:  Emmanuel Broni; Samuel K Kwofie; Seth O Asiedu; Whelton A Miller; Michael D Wilson
Journal:  Biomolecules       Date:  2021-03-18

9.  Computational Study on Potential Novel Anti-Ebola Virus Protein VP35 Natural Compounds.

Authors:  Louis K S Darko; Emmanuel Broni; Dominic S Y Amuzu; Michael D Wilson; Christian S Parry; Samuel K Kwofie
Journal:  Biomedicines       Date:  2021-11-30

10.  Anti-Ebola: an initiative to predict Ebola virus inhibitors through machine learning.

Authors:  Akanksha Rajput; Manoj Kumar
Journal:  Mol Divers       Date:  2021-08-06       Impact factor: 2.943

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